FixGuardian

Dynamic Task Assignment

Harness the power of AI to automatically assign and prioritize maintenance tasks based on historical data and real-time conditions. This feature optimizes workflow by reducing manual scheduling efforts, ensuring that the most critical issues are addressed first, ultimately slashing downtime and streamlining operations.

Requirements

Data Integration Engine

"As a property manager, I want the system to seamlessly integrate various data sources so that I can rely on accurate and timely maintenance task assignments without manual data processing."

Description

This requirement involves the integration of historical maintenance data and real-time sensor inputs to fuel the AI-driven task assignment engine. The system must process and analyze large volumes of property records and sensor-generated data, ensuring that the dynamic task assignment accurately reflects current property conditions and maintenance histories. It enhances system accuracy, enabling proactive and informed task prioritization.

Acceptance Criteria

Historical Data Processing

Given a dataset of historical maintenance records, when the data is ingested, then the system must correctly map and store at least 99% of records accurately.

Real-time Sensor Integration

Given live sensor inputs, when the data is received, then the system must update property conditions within 5 seconds with a reliability of 95% or higher.

Coherent Data Fusion

Given simultaneous historical and real-time inputs, when the data is processed, then the system must merge the data seamlessly to generate prioritized maintenance tasks with less than a 2% error rate.

Scalable Data Analysis

Given a high-volume dataset (e.g., 1 million records), when the data integration engine processes it, then processing time should not exceed 60 seconds.

Fault Tolerance

Given scenarios with missing or corrupted data, when the system processes inputs, then it must gracefully handle errors and continue to process valid data without crashes.

Real-Time Priority Optimization

"As a property manager, I want the system to update task priorities in real time so that critical issues are addressed immediately and potential property damage is prevented."

Description

This requirement focuses on enabling the system to adjust task priorities in real time based on evolving conditions and incoming sensor data. It involves creating algorithms that continuously monitor property conditions and automatically reorder task assignments according to urgency and impact. The optimization should allow the system to respond to sudden issues swiftly and accurately.

Acceptance Criteria

Real-Time Sensor Alert

Given new sensor data indicating a property anomaly, when the sensor triggers, then the system automatically adjusts task priorities in less than 30 seconds.

Automated Reprioritization Logic

Given multiple pending maintenance tasks and dynamic sensor inputs, when conditions change, then the algorithm reevaluates and reassigns tasks based on urgency and impact without manual intervention.

Continuous Monitoring and Adjustment

Given real-time monitoring of property conditions, when sensor readings fluctuate, then the system continuously updates task priorities and reorders tasks accurately.

Immediate Response to Critical Failure

Given detection of a critical property issue via sensor input, when the sensor reading exceeds a predefined threshold, then the system flags the task for immediate attention and moves it to the top of the queue.

Audit Trail of Priority Changes

Given any automated reordering event triggered by sensor data, when a task priority is adjusted, then the system logs the change with a timestamp and sensor details for traceability.

Manual Override and Customization

"As a property manager, I want to be able to manually override task assignments so that I can adjust priorities during unexpected circumstances or based on my expertise."

Description

This requirement ensures that property managers have the ability to manually override, adjust, or customize the automatically assigned and prioritized tasks. The feature will include user-friendly tools to edit task parameters, set custom priorities, and add supplementary notes, ensuring flexibility and control over the maintenance workflow while maintaining an audit trail.

Acceptance Criteria

Manual Override Basic Functionality

Given the property manager is on the maintenance dashboard, when they click the 'Override' button on an individual task, then they must be able to modify task details, including custom priority and supplementary notes, with all changes recorded in an audit trail.

Real-time Audit Trail Logging

Given the manager makes a manual override, when the task modification is confirmed, then the system logs the change with a timestamp, user ID, and details of the modifications in the audit trail.

Custom Task Parameters Update

Given the manager accesses the task details view, when they update parameters like priority or notes and save the changes, then the updated task must reflect the modifications across all relevant system interfaces while retaining historical data for reporting.

User-friendly Override Interface

Given the manager initiates a manual override, when the override interface loads, then all relevant fields such as task details, priority, and notes must be displayed clearly, be editable, and include tooltips for guidance.

Unexpected Input Handling

Given that the manager enters invalid or unsupported data in the override form, when the form is submitted, then the system should display clear error messages, prevent the submission, and guide the manager to correct the input before allowing the override process to complete.

Predictive Prioritization

An AI-driven system that forecasts potential maintenance issues and prioritizes tasks accordingly. By proactively addressing problems before they escalate, this feature helps maintain property value, minimizes disruptions, and provides a clear roadmap for efficient operations.

Requirements

Maintenance Issue Forecasting

"As a property manager, I want the system to forecast maintenance issues ahead of time so that I can proactively schedule repairs and minimize disruptions."

Description

Develop an AI-powered module that processes historical maintenance data and current property conditions to forecast potential maintenance issues before they occur. This module will analyze trends and apply predictive algorithms to generate a prioritized list of tasks to enhance the efficiency of property maintenance and reduce downtime.

Acceptance Criteria

Forecast Generation

Given a set of historical maintenance records and current property conditions, when the system processes the data, then it must return a prioritized list of predicted maintenance issues sorted by urgency with at least 90% accuracy.

Data Integration

Given integrated historical and real-time property data, when the system aggregates the data, then it must achieve at least a 95% data accuracy rate across all sources.

Automated Task Scheduler Update

Given the generated maintenance forecast, when the system updates the task scheduler, then the updated prioritized tasks must be visible and actionable within 1 minute of forecast generation.

AI Prediction Accuracy

Given a controlled dataset with known maintenance issues, when running the forecasting module, then the AI must correctly identify at least 80% of the simulated issues as validated against the test dataset.

User Notification

Given a high-priority maintenance issue forecast, when such an issue is detected by the system, then it must send a notification alert to the property manager with 100% reliability.

Automated Task Scheduling

"As a property manager, I want maintenance tasks to be automatically scheduled based on urgency so that operations are more streamlined and my workload is reduced."

Description

Implement an intelligent scheduling engine that automatically assigns and optimizes maintenance tasks based on the priority generated by predictive algorithms. The engine will integrate with existing property management systems to ensure that task assignments are streamlined and executed efficiently.

Acceptance Criteria

Task Scheduling Trigger

Given a maintenance request with a predictive priority, when a new maintenance trigger occurs, then the intelligent scheduling engine automatically assigns the task based on the forecasted priority.

Integration with PMS

Given an integration with an existing Property Management System, when the scheduling engine receives updated task data, then it should synchronize and reflect the changes without manual intervention.

Optimization of Task Assignments

Given multiple simultaneous maintenance tasks, when the predictive prioritization algorithm evaluates them, then the scheduling engine should optimize the task assignments to minimize downtime and reduce overall costs.

Handling Updates and Rescheduling

Given that task conditions are modified or new high-priority tasks emerge, when the system re-evaluates task priorities, then the scheduling engine must automatically reschedule tasks to adapt to the changes while maintaining efficient operations.

User Notification and Alert System

"As a property manager, I want to receive real-time notifications about predicted maintenance issues so that I can quickly address any problems before they escalate."

Description

Design a comprehensive notification system that alerts property managers via email, SMS, or in-app notifications about upcoming maintenance tasks prioritized by the AI system. This feature will facilitate timely response and ensure that urgent issues receive prompt attention, directly contributing to improved property management.

Acceptance Criteria

Email Notification Trigger

Given a maintenance task is prioritized by the AI system, when the notification generation process runs, then an email containing task details and alert instructions is sent to the property manager's registered email address.

SMS Notification Delivery

Given that a maintenance task is flagged as critical, when the system triggers notifications, then an SMS alert must be dispatched to the property manager's registered mobile number within 2 minutes.

In-App Notification Display

Given that a maintenance task is upcoming, when the property manager logs into the FixGuardian app dashboard, then the notification is prominently displayed with all necessary actionable details.

Notification Preferences Update

Given the property manager accesses their account settings, when they update the notification preferences, then the system immediately reflects these changes and sends notifications only through the selected channels.

Error Handling on Notification Failure

Given there is a failure to deliver a notification via a selected channel, when an alternative channel is available, then the system automatically retries using another channel and escalates the issue if needed.

Dashboard Analytics for Prioritization

"As a property manager, I want a clear dashboard that displays predictive maintenance data and task priorities so that I can easily monitor and manage property maintenance strategies."

Description

Develop an intuitive analytics dashboard that visually represents maintenance priorities, predicted issues, and historical trends. The dashboard will provide actionable insights and performance metrics, enabling property managers to assess the effectiveness of the predictive system and make data-driven decisions.

Acceptance Criteria

Dashboard Data Visualization

Given a logged-in property manager, when they access the dashboard, then an intuitive interface displaying maintenance priorities, predicted issues, and historical trends is visibly rendered.

Real-Time Analytics Updates

Given updated maintenance data, when the dashboard refreshes automatically or via user action, then the analytics and visualizations reflect new predictions and trends in real-time.

Interactive Performance Metrics

Given a property manager interacting with the dashboard, when they click on a specific maintenance issue, then detailed performance metrics and historical trends are displayed promptly for deeper insights.

Adaptive Rescheduling

Experience a fully dynamic scheduling system that adjusts maintenance tasks in real-time based on changing conditions. This feature ensures optimal task timing and resource allocation, allowing property managers to swiftly respond to unforeseen challenges without compromising efficiency.

Requirements

Real-Time Condition Monitoring

"As a property manager, I want to view live property condition data so that I can proactively manage maintenance tasks based on current conditions."

Description

Implement a continuous monitoring module that aggregates and analyzes sensor data, weather updates, and maintenance logs in real time to immediately detect property conditions and emerging issues. This module serves as the foundation for triggering adaptive rescheduling, significantly reducing downtime and unexpected repair costs.

Acceptance Criteria

Real-Time Data Integration

Given live sensor feeds, weather data, and maintenance logs, when the module collects data, then it must aggregate and synchronize all incoming data within 5 seconds.

Adaptive Triggering Mechanism

Given input data indicating abnormal property conditions, when a threshold is exceeded, then the system must trigger an adaptive rescheduling event within one minute.

Robust Error Handling

Given interrupted or faulty data inputs, when errors are detected, then the system must log error details and initiate a fallback protocol without compromising data integrity.

System Performance Under Load

Given high-frequency data input scenarios, when multiple data points are aggregated concurrently, then the module must maintain a response time of under 5 seconds without data loss.

Dynamic Task Adjustment Algorithm

"As a property manager, I want maintenance tasks to automatically adjust based on real-time conditions so that I can optimize scheduling and minimize downtime."

Description

Develop an automation engine that leverages real-time data to dynamically adjust maintenance scheduling. This algorithm will integrate predictive maintenance insights and conditional rules to continuously optimize task timing and resource allocation, ensuring efficient operations without manual intervention.

Acceptance Criteria

Real-time Task Rescheduling

Given that real-time data is received by the system, when a maintenance issue is detected, then the algorithm should automatically adjust scheduling and task priorities accordingly.

Predictive Maintenance Trigger

Given that predictive insights indicate potential system issues, when risk thresholds are exceeded, then the algorithm must preemptively reschedule maintenance tasks and allocate resources.

Conditional Rules Enforcement

Given that multiple tasks are scheduled, when contextual conditions such as occupancy or weather change occur, then the algorithm should enforce conditional rules to optimize task assignments.

Automated Alert Integration

Given that a task has been rescheduled, when the algorithm finalizes the new schedule, then the system must notify the property manager through an automated alert.

Performance Under Load

Given that high volumes of data are processed concurrently, when multiple maintenance instances are triggered, then the algorithm must adjust schedules within 2 seconds for at least 95% of the cases.

Comprehensive Notification & Alert System

"As a property manager, I want to receive prompt notifications about schedule adjustments so that I can stay informed and quickly respond to any challenges."

Description

Create a robust notification framework that delivers timely alerts across multiple channels, such as email, SMS, and in-app notifications, when maintenance schedules are dynamically adjusted. This ensures property managers are immediately informed of changes, fostering prompt decision-making and rapid response to emergent issues.

Acceptance Criteria

Immediate Email Notification

Given a maintenance task reschedule event, when the system processes the event, then an email alert is sent to the property manager within 2 minutes.

SMS Alert for Urgent Changes

Given a critical maintenance schedule adjustment, when the rescheduling is flagged as urgent, then an SMS notification is sent immediately to the property manager.

In-App Notification Synchronization

Given a schedule change event, when the system updates the maintenance schedule, then an in-app alert is displayed synchronously on the property manager's dashboard.

Multi-Channel Consistency

Given a maintenance rescheduling event, when the notifications are triggered, then email, SMS, and in-app notifications must contain consistent and accurate information regarding the change.

Notification Audit Logging

Given any rescheduling notification event, when a notification is sent, then the system records the event details (timestamp, channel, recipient, and message content) in the audit log for future review.

Real-Time Alerts

Stay informed with instant notifications as the system detects schedule deviations or emerging maintenance needs. These alerts enable timely intervention, empowering managers to make informed decisions and keep operations smooth and cost-effective.

Requirements

Automated Deviation Detection

"As a property manager, I want the system to automatically detect deviations in the maintenance schedule so that I can intervene before problems escalate."

Description

Implement a robust algorithm that continuously monitors scheduled maintenance tasks against real-time activity data to identify deviations or emerging issues promptly. Integrate this component with AI-driven predictions to reduce downtime by triggering alerts when discrepancies exceed predefined thresholds.

Acceptance Criteria

Real-Time Deviation Alert Execution

Given a scheduled maintenance task is assigned, when the system detects a deviation beyond the predefined threshold using real-time data, then an instant alert must be generated and dispatched to the relevant property manager.

Pre-emptive Issue Notification

Given an emerging maintenance issue identified by AI-driven predictive analytics, when the system detects potential escalation before the scheduled execution, then it should trigger an alert notifying the property manager with necessary details.

Alert Accuracy Verification

Given simulated maintenance scenarios with known deviations, when the automated deviation detection processes these inputs, then it should accurately flag at least 95% of true deviations while minimizing false positives.

Dashboard Alert Integration

Given the generation of an alert, when the property manager accesses the FixGuardian dashboard, then the alert with contextual information must be clearly displayed in real-time for immediate review.

Alert Response Time Measurement

Given an instance of deviation detection, when the alert is triggered, then the notification delay must not exceed 5 minutes from the time of detection to ensure timely intervention.

Instant Push Notifications

"As a property manager, I want to receive instant push notifications on my devices so that I can quickly address unexpected maintenance issues."

Description

Create an alert delivery module that sends real-time push notifications to managerial devices as soon as the system identifies schedule deviations or maintenance issues. This module should integrate with mobile and web platforms to provide immediate synchronization of alert data, ensuring timely decision making.

Acceptance Criteria

Immediate Real-Time Alert Delivery

Given the maintenance system detects a schedule deviation or maintenance issue, When the alert delivery module processes the incident, Then a push notification must be sent to the managerial device within 2 seconds.

Accurate Notification Content

Given that an alert is triggered, When the push notification is delivered, Then it must display all relevant details including issue type, priority, and location accurately on both mobile and web platforms.

Cross-Platform Synchronization

Given a push notification is sent, When a manager accesses the system on either mobile or web platforms, Then the notification data must be uniformly synchronized and updated across both platforms.

User Interaction with Alert

Given that a push notification is received, When a manager taps on the alert, Then the system must directly navigate to the corresponding maintenance or deviation details screen, allowing immediate actionable insight.

Error Handling in Notification Delivery

Given that network or system disruptions occur, When the push notification delivery fails, Then the module should log the error, initiate an automatic retry mechanism, and notify the manager through an alternate channel if necessary.

Multi-Channel Alert Distribution

"As a property manager, I want alerts to be delivered via multiple communication channels so that I never miss critical notifications even if one channel is unavailable."

Description

Develop a flexible alert distribution system that supports multiple channels including SMS, email, and in-app notifications. This system should allow property managers to choose their preferred communication methods, ensuring that important alerts are received regardless of connectivity or platform limitations.

Acceptance Criteria

Real-time SMS Alerts Notification

Given a maintenance issue is detected, when the system sends an SMS to the selected phone number, then the alert should be received within 5 minutes of detection.

Instant Email Alerts

Given a schedule deviation is identified, when the system triggers an email alert to the configured email address, then the alert must include detailed information and be delivered within one minute.

In-App Notification for Critical Alerts

Given a high-priority maintenance event, when the system dispatches an in-app notification, then the alert must appear within 10 seconds and provide actionable items.

User Preference Configuration for Alert Channels

Given that a property manager accesses the notification settings, when they select their preferred channels (SMS, Email, In-App), then the system must save and apply these selections for all subsequent alerts.

Fallback Mechanism for Connectivity Issues

Given a connectivity issue with the primary notification channel, when the system fails to deliver an alert, then it must automatically switch to an alternate configured channel without user intervention.

Multi-Channel Alert Distribution Logging

Given that multiple channels are used to send an alert, when the system logs the notification details, then it must accurately record the channel, timestamp, and delivery status for each alert sent.

Alert Customization and Threshold Settings

"As a property manager, I want to customize alert settings so that the notifications are tailored to my operational needs and priorities."

Description

Introduce a configuration interface enabling property managers to customize alert thresholds, select preferred notification channels, and set escalation rules. The interface should be user-friendly and seamlessly integrate with the Real-Time Alerts system to offer tailored experiences that meet specific operational requirements.

Acceptance Criteria

Threshold Adjustments

Given a property manager is on the alert customization interface, when they change an alert threshold value, then the system should immediately update and display the new threshold with a confirmation message.

Notification Channel Selection

Given a property manager accesses the notification settings, when they select one or multiple notification channels (email, SMS, push), then the system should save the preferences and utilize them for real-time alerts.

Escalation Rules Setup

Given a property manager sets up an escalation rule, when defined alert conditions are met, then an escalation alert is triggered with appropriate logging and notification escalations executed.

User-Friendly Interface Validation

Given a property manager interacts with the configuration interface, when performing customizations, then the interface should be intuitive, provide real-time feedback, tooltips, and error handling to guide the user.

Integration With Real-Time Alerts

Given a property manager saves their modified alert settings, when an alert condition is triggered, then the system should utilize the updated customization settings to deliver the alert promptly.

Alert Acknowledgment and Escalation

"As a property manager, I want to acknowledge alerts and trigger escalations if necessary so that urgent issues are promptly addressed and managed effectively."

Description

Implement an acknowledgment workflow that allows alerts to be confirmed or deferred by managers. If an alert is not acknowledged within a predefined period, the system should automatically escalate the issue to a higher level, ensuring that urgent maintenance concerns receive immediate attention.

Acceptance Criteria

Immediate Alert Acknowledgment

Given a maintenance alert is generated, when the manager receives the real-time notification, then they must be able to confirm the alert acknowledgment, with the system capturing the acknowledgment timestamp.

Deferred Alert Handling

Given a new alert is received, when the manager opts to defer the alert, then the system should record the deferral along with the scheduled follow-up notification time.

Unacknowledged Alert Escalation

Given an alert remains unacknowledged for the predefined period, when the period elapses, then the system must automatically escalate the alert to the next level and log the escalation event.

Audit Trail for Alert Actions

Given any alert action (acknowledgment, deferral, escalation) is performed, when the action is logged, then the audit trail should include the user ID, timestamp, and type of action for accountability.

Responsive Multi-device Alert Handling

Given that the alert is accessible on multiple devices, when the manager performs an action (acknowledge or defer) on one device, then the system should synchronize the action status across all devices promptly.

Smart Calendar Integration

Seamlessly sync maintenance schedules with popular calendar tools. This integration offers a consolidated view of all tasks, improves coordination across teams, and reduces the risk of oversight, enhancing overall operational efficiency.

Requirements

Seamless Calendar Sync

"As a property manager, I want my maintenance schedule to automatically sync with my calendar so that I can efficiently track and manage tasks without manual intervention."

Description

The system must enable seamless synchronization between maintenance tasks and popular calendar tools such as Google Calendar and Outlook. This integration will automatically update maintenance schedules based on task changes and calendar events, ensuring that all users have the most current view of upcoming maintenance activities and reducing the risk of oversight.

Acceptance Criteria

Task Creation Sync

Given a new maintenance task is created in FixGuardian, when the task is saved, then the event should automatically appear in the user’s connected calendar with correct details such as title, date, and description.

Task Update Sync

Given an existing maintenance task is updated, when the changes are saved, then the linked calendar event must automatically update to reflect the latest information including time and details.

Task Deletion Sync

Given a maintenance task is deleted, when the deletion is confirmed in FixGuardian, then the corresponding event must be automatically removed from the connected calendar.

Calendar Event Change Sync

Given a calendar event is modified in the connected tool (Google Calendar or Outlook), when the change is detected by FixGuardian, then the associated maintenance task must update to reflect the changes in schedule.

Real-time Sync Performance

Given multiple task or calendar changes occur, when the system syncs these updates, then all changes should be processed and reflected in both systems within 60 seconds without data loss.

Two-Way Data Sync

"As a property manager, I want updates made on either my maintenance system or calendar to reflect across both platforms so that I maintain alignment and consistency in scheduling."

Description

Implement a two-way synchronization mechanism that allows changes in FixGuardian or connected calendar applications to be reflected across both platforms. This ensures that any updates made from either end are consistently applied, reducing data discrepancies and manual data entry.

Acceptance Criteria

Calendar Update Propagation

Given a maintenance task is updated in FixGuardian, when the update is saved, then the connected calendar must reflect the change within 5 seconds.

FixGuardian Update Propagation

Given a maintenance schedule is modified in a connected calendar application, when the update is completed, then FixGuardian must automatically sync and display the updated schedule promptly.

Conflict Resolution Handling

Given simultaneous updates occur on both FixGuardian and the connected calendar, when a synchronization conflict is detected, then the system will resolve by prioritizing the most recent update and log the conflict resolution details.

Data Integrity Verification

Given a two-way data sync operation, when the synchronization process completes, then a checksum or equivalent validation must confirm data consistency across both platforms.

Performance and Latency Evaluation

Given a high volume of update events, when the sync mechanism is triggered, then the overall data synchronization latency should not exceed 5 seconds under normal load conditions.

Conflict Detection and Resolution

"As a property manager, I want the system to detect scheduling conflicts in my maintenance calendar so that I can promptly adjust and avoid overlapping tasks."

Description

Develop a conflict detection mechanism that scans for overlapping maintenance tasks and calendar events. The system should alert users to any scheduling conflicts and offer automated or suggested resolutions to ensure clear, non-overlapping schedules and efficient task management.

Acceptance Criteria

Real-Time Overlap Detection

Given that a maintenance task is added or modified, when the system detects an overlapping calendar event, then an instant alert is triggered displaying conflict details and recommended resolution options.

Automated Conflict Resolution Suggestion

Given that a conflict is detected, when a user views the conflict details in the dashboard, then the system automatically suggests alternative task schedules or calendar slots to resolve the conflict.

User Confirmation for Resolution

Given that a resolution suggestion is provided, when the user selects the suggested resolution, then a confirmation dialog is displayed to verify the schedule update, and the update is applied upon confirmation.

Conflict Log and Audit

Given that scheduling conflicts occur, when the system logs the conflict event, then detailed entries including timestamps, affected events, and resolution actions are securely stored for audit purposes.

Integration with Calendar Sync

Given that a maintenance task is synchronized with an external calendar, when an overlapping event is identified on the external calendar, then the conflict detection mechanism synchronizes in real-time and alerts the user to resolve the conflict.

Automated Reminders and Alerts

"As a property manager, I want to receive automated reminders for my scheduled maintenance tasks so that I never miss an important update or deadline."

Description

Provide an automated reminder system that integrates with the calendar to send timely notifications for upcoming tasks, changes, or updates to the maintenance schedule. The alerts should be customizable to suit user preferences, thereby reducing missed entries and ensuring smoother workflows.

Acceptance Criteria

Timely Task Reminder

Given the automated reminder system, when an upcoming maintenance task is within the notification window, then the system sends a customizable alert to the associated calendar event.

Calendar Sync Update

Given the integration with popular calendar tools, when a maintenance schedule update occurs, then the system automatically adjusts the corresponding calendar entries and sends an alert if changes are critical.

Customization of Alerts

Given the settings interface, when users modify alert preferences, then alerts are customized accordingly, and the system confirms the update via a test notification.

Notification Delivery Failure Handling

Given a failed alert attempt, when the system detects a delivery error, then it logs the error and retries up to a defined number of attempts, alerting the user if failure persists.

Multi-Device Synchronization

Given that notifications are sent for critical task updates, when a user accesses their calendar from multiple devices, then all devices reflect the latest schedule changes and alerts consistently.

Instant Repair Signal

Receive instantaneous notifications pinpointing cost-effective repair opportunities through advanced anomaly detection and predictive maintenance analytics. This feature ensures property managers can act swiftly to mitigate repair costs and extend asset life.

Requirements

Instant Alert System

"As a property manager, I want real-time repair alerts so that I can respond swiftly to emerging maintenance issues and minimize downtime."

Description

Develop a robust alert mechanism that delivers immediate notifications to property managers when repair signals are detected through advanced anomaly detection and predictive analytics. This system integrates real-time data processing, push notifications on multiple platforms, and customizable alert criteria to ensure that the relevant stakeholders are informed promptly to mitigate repair downtime and costs.

Acceptance Criteria

Real-Time Notification

Given a detected repair signal, when the real-time processing engine validates the event, then a push notification is sent immediately to the property manager.

Platform-Specific Alerts

Given that alerts are configured for multiple platforms, when an alert is triggered, then notifications must be delivered on Android, iOS, and web interfaces simultaneously.

Customizable Alert Criteria

Given that property managers can define custom alert preferences, when a repair signal occurs that meets these criteria, then the system must only send notifications that match the custom preferences.

Predictive Maintenance Analytics

Given that historical data and predictive analytics are integrated, when an anomaly is detected, then the alert system must provide a detailed analysis of the potential repair cost and urgency.

Cross-Platform Reliability

Given a network failure or offline scenario, when the system recovers connectivity, then undelivered alerts must be re-sent ensuring that no critical notifications are missed.

Predictive Maintenance Analytics

"As a property manager, I want predictive insights on repair needs so that I can proactively schedule maintenance and avoid costly breakdowns."

Description

Implement a predictive analytics module that utilizes historical data and machine learning algorithms to forecast upcoming maintenance needs. This module will process data from various sources to predict potential repair opportunities and schedule maintenance before issues escalate, ultimately reducing costs and extending asset lifespan.

Acceptance Criteria

Real-Time Anomaly Detection

Given historical dataset is available, When the system processes real-time data, Then it should detect anomalies indicating potential repair needs instantly.

Predictive Maintenance Scheduling

Given the generated maintenance forecasts, When the module identifies upcoming issues, Then it automatically schedules maintenance tasks prior to escalation.

Data Integration from Multiple Sources

Given input data from various sensors and logs, When the analytics system aggregates and analyzes the data, Then it must produce accurate and timely predictive maintenance alerts.

Cost-Benefit Analysis and Validation

Given cost-effectiveness metrics and historical benchmarks, When maintenance predictions are validated, Then measurable reductions in repair costs and extended asset lifespan should be demonstrated.

Cost-Effective Estimation Engine

"As a property manager, I want cost analysis for repair options so that I can choose the most economical maintenance strategy."

Description

Create an estimation engine that analyzes historical costs, repair efficacy, and material expenses to assess the cost-effectiveness of various repair options. This tool will enable property managers to compare potential repairs and select financially advantageous solutions, ensuring optimal maintenance spending.

Acceptance Criteria

Historical Costs Analysis

Given historical maintenance and repair cost data, when the estimation engine processes the input, then it should generate cost predictions with an error margin of less than 5%.

Repair Efficacy Assessment

Given performance and durability metrics for past repairs, when evaluating repair options, then the estimation engine shall rank repairs based on a composite index that factors in effectiveness, durability, and cost.

Material Expense Evaluation

Given detailed material cost inputs for various repair options, when calculating overall expenses, then the engine shall identify and highlight options with material costs reduced by at least 10% compared to current benchmarks.

Comparative Financial Analysis

Given multiple repair options and their associated cost data, when generating a comparative analysis report, then the engine shall produce a detailed breakdown including cost, projected savings, and ROI metrics for each option.

Threshold Validations and Alerts

Given a cost threshold set by the property manager, when the estimation engine forecasts repair costs that exceed this threshold, then it must trigger an automatic alert along with actionable recommendations for cost-effective alternatives.

User Dashboard for Repair Signals

"As a property manager, I want a consolidated dashboard to easily view repair signals and management insights so that I can prioritize maintenance tasks efficiently."

Description

Design an intuitive dashboard that consolidates real-time repair alerts, predictive maintenance analytics, and cost analysis into a single visual interface. The dashboard will offer comprehensive insights, historical trends, and customizable views to help property managers monitor and prioritize repair tasks effectively.

Acceptance Criteria

Real-Time Repair Alerts Display

Given a property manager is logged into the dashboard, when a repair signal is generated by the system, then the dashboard must immediately display the alert with key details such as repair cost estimates, priority level, and predictive maintenance analytics.

Historical Trends and Analytics

Given that the dashboard provides historical data, when a property manager selects the historical trends view, then the system must present graphical trends and statistical data for repair signals over a specified period.

Customizable Views and Filters

Given that the dashboard supports custom views, when a property manager applies filters based on repair category, cost threshold, or date range, then the displayed data should update accordingly to reflect the selected criteria.

User Accessibility and Responsiveness

Given that the dashboard is accessed on various devices, when a user interacts with the interface, then all elements must load within two seconds and adapt effectively to different screen sizes, ensuring a seamless user experience.

Seamless Integration with Predictive Maintenance

Given that repair signals are produced by an anomaly detection system, when these signals are integrated into the dashboard, then they must be correlated with predictive maintenance models and displayed in a clear, user-friendly format that allows immediate action.

Mobile Integration for Notifications

"As a property manager, I want mobile access to repair notifications so that I can stay updated on maintenance issues even when I am away from my desk."

Description

Develop mobile integration capabilities to ensure that all repair alerts, maintenance analytics, and dashboard insights are accessible on smartphones and tablets. This integration will facilitate on-the-go access, enabling property managers to receive timely notifications and review repair details no matter where they are.

Acceptance Criteria

Real-Time Alert on Mobile

Given property managers using the mobile app, when a repair alert is triggered, then the alert notification must be delivered instantly on the smartphone with a clear display of repair details.

Predictive Analytics Display

Given a predictive maintenance event, when a user logs in via their mobile device, then the system should display a dashboard widget with analytical insights and repair cost predictions.

Mobile User Interface Consistency

Given various mobile devices with differing screen sizes, when accessing the mobile integration, then the interface should adapt responsively while retaining all functionalities and clear data presentation.

Offline Notification Access

Given a temporary network disruption on a mobile device, when an alert is received, then the app must cache the notification locally and display it once connectivity is restored or remain accessible offline.

Notification Action Integration

Given a notification alert received on the mobile app, when a property manager taps on it, then the app should navigate directly to the detailed repair management screen with all relevant information.

Expense Tracker Notification

Monitor expected repair costs in real-time with detailed notifications that highlight areas for potential savings. This tool empowers property managers to prioritize interventions that yield maximum financial benefits.

Requirements

Real-Time Expense Alert

"As a property manager, I want instant alerts on abnormal repair expense trends so that I can quickly address issues and prevent budget overruns."

Description

Integrate a real-time notification system that alerts property managers when repair costs exceed predefined thresholds. This mechanism leverages predictive analytics to assess potential repair issues and sends timely alerts, enabling immediate intervention and cost control. It seamlessly integrates with the expense tracking module to provide actionable insights, improving budget optimization and operational efficiency.

Acceptance Criteria

Real-Time Notification Trigger

Given that predictive analytics detects repair costs exceeding the predefined threshold, when the system evaluates repair expense data, then a real-time alert notification is generated to inform the property manager.

Alert Threshold Customization

Given that the property manager sets or updates expense thresholds in the system, when repair costs exceed these limits, then an alert must be triggered in accordance with the custom settings.

Integration with Expense Tracker

Given that the expense tracking module is active, when repair-related cost updates occur, then the real-time notification system must integrate seamlessly with the expense tracker to display the alert.

Actionable Insights in Alert

Given that a repair cost alert is triggered, when the property manager reviews the alert details, then the notification must include specific actionable insights and recommended interventions to mitigate costs.

Alert Delivery across Channels

Given that the system identifies threshold breaches, when an alert is generated, then notifications must be dispatched via multiple channels (such as dashboard, email, and SMS) to ensure prompt awareness.

Detailed Notification View

"As a property manager, I want to view detailed breakdowns of each expense notification so that I can analyze and prioritize maintenance tasks effectively."

Description

Implement a detailed notification view that provides a summary of potential repair costs along with contextual data such as historical trends, estimated savings, and risk factors. This view offers clear, actionable insights that help property managers understand financial implications and prioritize repairs to maximize ROI.

Acceptance Criteria

Real-Time Expense Update

Given repair cost predictions are updated in the backend, when the notification view loads, then the UI must display the latest actual and predicted repair costs, ensuring data synchronization with historical trends and risk factors.

Contextual Data Integration

Given a notification is received, when a property manager clicks the notification detail, then the system should provide contextual data including historical trends, estimated savings, and risk factors in a detailed and organized view.

Actionable Notification Alerts

Given the detection of high potential repair costs, when the notification is generated, then the detailed view should prominently highlight actionable insights that inform prioritization and ROI maximization.

User Interface Usability

Given a property manager accesses the detailed notification view, when interacting with the UI, then all key data points such as cost summary, historical trends, and risk factors must be easily readable and intuitively presented to facilitate decision making.

Visual Analysis Dashboard

Given historical expense data is available, when the detailed notification view is opened, then visual representations such as charts or graphs must be rendered to depict trends over time, accompanied by clear labels and legends.

Customizable Alert Thresholds

"As a property manager, I want to customize repair cost thresholds so that the notifications align with my property's budget and risk preferences."

Description

Allow property managers to set and adjust thresholds for repair costs based on property-specific budgets and risk profiles. This customization ensures that notifications are tailored to each property's financial constraints and maintenance history, resulting in a personalized experience that maximizes savings and minimizes unnecessary alerts.

Acceptance Criteria

Setting Alert Threshold

Given a property manager is on the threshold settings page, when they enter a valid threshold value along with property-specific budgeting data, then the system saves the threshold successfully and applies it to subsequent notifications.

Editing Alert Threshold

Given a property manager has an existing threshold, when they modify the threshold value, then the system updates and applies the new threshold to all future notifications.

Alert Threshold Comparison

Given a property manager has set a threshold, when a repair cost is recorded that meets or exceeds the threshold, then the system triggers a detailed notification highlighting the potential savings.

Validation of Threshold Input

Given a property manager enters a threshold value, when the input is invalid or non-numeric, then the system displays an appropriate error message preventing an invalid threshold from being saved.

Threshold Reset Option

Given a property manager needs to revert threshold settings, when they select the reset option, then the system resets the thresholds to the default values pre-configured for the property.

Predictive Expense Forecasting

"As a property manager, I want to receive predictive forecasts of upcoming repair costs so that I can plan and budget for future maintenance effectively."

Description

Develop an AI-driven forecasting engine to predict future repair costs based on historical data and real-time trends. This feature empowers property managers with proactive insights into upcoming maintenance expenses, enabling effective planning and improved financial management across properties.

Acceptance Criteria

Real-Time Forecasting

Given that a property manager accesses the dashboard, when historical repair cost data and current trends are fed into the forecasting engine, then it must generate a predictive expense forecast with an accuracy within 5% of actual costs.

Proactive Notification

Given that the system identifies potential cost anomalies in the incoming data, when a threshold is crossed, then it must immediately send a detailed notification highlighting areas for potential savings.

Data Integration Validation

Given that data from historical records and real-time sources are incorporated, when new data is merged into the forecasting model, then the integration must be validated successfully without error or data loss.

User Interface Reporting

Given that the predictive engine calculates future repair costs, when a manager views the expense tracking module, then the forecast and graphical trends must be displayed clearly along with actionable insights.

In-App Notification Redirection

"As a property manager, I want to click on an alert to directly access a detailed expense analysis so that I can quickly review and act on maintenance priorities."

Description

Enable a feature that allows property managers to click on a notification to be redirected directly to an in-depth expense analysis dashboard. This seamless navigation minimizes response time and enhances workflow efficiency by providing immediate access to detailed data for informed decision-making.

Acceptance Criteria

Immediate Notification Click Redirection

Given a property manager receives an expense tracker notification, when the notification is clicked, then the system must redirect the user directly to the detailed expense analysis dashboard.

Dashboard Load Performance

Given a successful redirection from a notification, when the dashboard loads, then the page must fully display all required expense analysis data within 3 seconds.

Correct Data Association

Given a property manager is redirected by clicking a notification, when the expense analysis dashboard is displayed, then it must show expense details corresponding only to the notification context.

Error Handling on Data Unavailability

Given a redirection is attempted and required expense data is unavailable, when the dashboard fails to load, then an error message must be displayed with guidance for further action.

Budget Guardian Alerts

Shield your operational budget with real-time alerts that flag critical repair scenarios offering cost reductions. Benefit from proactive insights that balance property maintenance needs with financial efficiency.

Requirements

Real-Time Alert Engine

"As a property manager, I want to receive immediate alerts about potential high-cost repair scenarios so that I can quickly address issues and protect my operational budget."

Description

Develop an engine that monitors repair scenarios in real-time, leveraging AI-based predictive analytics to flag critical repair scenarios before they escalate. This engine will continuously process sensor data and maintenance logs to deliver instant notifications and alerts. Its integration will enable property managers to mitigate unexpected repair costs and maintain budget control by facilitating timely interventions. Implementation should focus on reliable and low-latency data processing to ensure alerts are delivered without delay.

Acceptance Criteria

Real-Time Data Processing

Given that sensor data and maintenance logs are continuously ingested, When the AI engine detects anomalies indicative of a potential repair issue, Then an alert is generated within 2 seconds.

Low-Latency Alert Delivery

Given an alert has been triggered, When the system processes the alert, Then the notification should be delivered to the property manager within 2 seconds to facilitate timely intervention.

Integration with Budget Guardian Alerts

Given a critical repair alert is generated, When the alert is classified and processed, Then it should automatically integrate with the Budget Guardian Alerts feature to provide cost reduction insights.

Alert Customization Dashboard

"As a property manager, I want to customize my alert settings so that I only receive notifications that match my operational priorities and budget constraints."

Description

Implement a user-friendly dashboard that allows property managers to customize alert parameters, such as threshold levels and alert frequencies. This feature will empower users to tailor the alert system to their property management style and financial constraints, ensuring alerts are relevant and actionable. The dashboard should integrate seamlessly with the main interface of FixGuardian, providing granular control over notification settings and detailed historical alert data for informed decision-making.

Acceptance Criteria

Dashboard Access and Navigation

Given a property manager logs in, when selecting the Alert Customization Dashboard from the main interface, then the dashboard should load within 3 seconds and display an intuitive navigation menu for customization options.

Alert Parameter Customization

Given the dashboard is active, when the property manager modifies alert thresholds and frequencies, then the system must save the changes immediately, update the displayed settings, and provide a visual confirmation.

Real-Time Preview of Settings

Given the property manager adjusts alert parameters, when previewing these changes, then the dashboard should render a real-time preview of the alert notifications based on the adjusted configurations.

Historical Alert Data Integration

Given the property manager accesses the historical alert data tab, when filtering data by a specified date range, then the system should display the correct historical records and allow export in CSV format.

Main Interface Integration

Given the property manager navigates from the main FixGuardian interface, when accessing the Alert Customization Dashboard, then the dashboard should integrate seamlessly with the main interface, reflecting any updates or changes instantly.

Historical Alert Reporting Module

"As a property manager, I need access to historical alert data and analysis so that I can review past performance and adjust maintenance strategies to improve cost savings and budgeting accuracy."

Description

Develop a reporting module that compiles historical alert data and cost analyses to provide insights into recurring maintenance trends and budget impacts. This module should generate comprehensive reports that detail alert frequency, repair cost savings, and predictive accuracy over time. It will serve as a decision-support tool for optimizing maintenance schedules and budgeting future repairs, and integrate with existing property management analytics for cohesive financial oversight.

Acceptance Criteria

Historical Alerts Report Generation

Given valid historical alert data is available, when the user requests a report, then the module generates a detailed report showing alert frequency, repair cost savings, and maintenance trends over time.

Report Accuracy Validation

Given clean and comprehensive historical data, when the report is generated, then it must accurately reflect alert occurrences, repair cost savings, and include computed predictive accuracy metrics.

Integration with Property Management Analytics

Given integration with existing analytics systems, when a report is generated, then the module must seamlessly consolidate data from both systems to deliver a unified financial oversight report.

Real-Time Data Update in Reports

Given new alert data is periodically ingested, when the reporting cycle is triggered, then the report must reflect the most up-to-date information, ensuring near-real-time accuracy.

User Decision-Support Functionality

Given the need for strategic decision-making, when the report is generated, then the module must include clear summary insights and predictive trends to support maintenance scheduling and budgeting decisions.

Maintenance Cost Optimizer

A dynamic system delivering alerts on repair opportunities strategically aligned with cost-saving measures. Detailed cost breakdowns help managers make informed decisions and optimize budget allocations.

Requirements

Dynamic Cost Alert System

"As a property manager, I want to receive real-time alerts about cost-saving repair opportunities so that I can proactively manage maintenance expenses."

Description

Implement an automated alert system that monitors upcoming maintenance events and identifies repair opportunities that align with cost-saving measures. This feature integrates predictive analytics to provide timely notifications, empowering property managers to take proactive actions to minimize maintenance costs and downtime.

Acceptance Criteria

Proactive Alert Delivery

Given maintenance events are predicted using AI-driven analytics, When a scheduled maintenance event is detected, Then the system automatically sends an alert with a detailed cost breakdown and repair opportunity suggestions.

Cost Breakdown Visibility

Given a repair opportunity is identified, When the property manager accesses the alert, Then the system displays clear and concise cost breakdown details along with recommendations for cost-saving measures.

Timely Notification Response

Given that predictive analytics forecast an imminent high-cost saving opportunity, When the prediction is confirmed, Then the system triggers an urgent alert to the property manager with actionable insights to minimize maintenance downtime and costs.

Detailed Cost Breakdown Module

"As a property manager, I want to see detailed cost breakdowns for each repair opportunity so that I can make informed decisions on budget allocation."

Description

Develop a module that provides comprehensive cost breakdowns for each maintenance activity, detailing component costs, labor fees, and historical expenditure trends. This module will integrate with the main system to offer managers precise financial insights, enhancing their decision-making process and optimizing budget allocations.

Acceptance Criteria

Dynamic Cost Breakdown Display

Given a maintenance activity record, when the Detailed Cost Breakdown Module is invoked, then display comprehensive cost details including component costs, labor fees, and other variable charges.

Historical Expenditure Trends Analysis

Given a set of historical maintenance data, when a user selects a maintenance activity, then display detailed graphs and tables showing expenditure trends and comparisons to facilitate cost analysis.

Real-Time Alert Generation for Cost Anomalies

Given real-time cost input for maintenance activities, when the system detects a significant deviation from expected cost figures, then generate an alert summarizing the anomaly and suggesting review actions.

Budget Allocation Optimization Integration

Given the generated detailed cost breakdown, when a manager reviews the report, then provide an option to export and integrate this data for further budget allocation analysis, ensuring data accuracy and compatibility.

Predictive Maintenance Analysis

"As a property manager, I want to access predictive maintenance insights so that I can plan repairs in advance and avoid unexpected repair costs."

Description

Implement an AI-driven analysis tool that forecasts future repair needs and potential cost escalations. By analyzing historical data and current maintenance workflows, this tool will help managers predict and plan for upcoming issues, thus reducing unexpected expenses and ensuring proactive maintenance scheduling.

Acceptance Criteria

Historical Data Analysis

Given historical maintenance data is available, when the AI-driven analysis tool processes this data, then it should identify recurring issues and predict future repair needs with at least 90% accuracy.

Future Maintenance Prediction

Given current maintenance workflow information, when the system runs its predictive analysis, then it should forecast potential repair needs within a 30-day period and provide cost estimations for each forecasted repair.

Cost Escalation Alert

Given a trend of increasing repair costs, when the tool analyzes cost-related data alongside repair predictions, then it should trigger an alert with a detailed breakdown of cost escalations and recommended preventive actions.

AI-Driven Decision Support

Given integration with property management systems, when the AI analysis is completed, then it should provide actionable maintenance scheduling recommendations to optimize repair timing and budget allocations.

Integration with Work Order System

"As a property manager, I want the maintenance cost optimizer to integrate with my work order system so that cost data is automatically updated and easily accessible."

Description

Develop integration capabilities with the existing work order system to automatically synchronize cost data from repair opportunities. This seamless integration ensures that all maintenance scheduling and expense data remain consistent and up-to-date across platforms, thus streamlining operational workflows.

Acceptance Criteria

Real-Time Data Synchronization

Given a repair opportunity is recorded in the work order system, when cost data is updated, then the integration must automatically sync the updated cost data to FixGuardian within 5 minutes.

Accurate Cost Breakdown Synchronization

Given that a detailed cost breakdown exists in the work order system, when the integration retrieves data, then the synchronized cost breakdown in FixGuardian must exactly match the source values.

Automated Error Handling

Given a failure during synchronization, when an error occurs, then the system must log the error, notify the maintenance manager, and initiate an automatic retry within 10 minutes.

User Notification on Synchronization Status

Given the integration process, when the synchronization completes or fails, then the system must display a clear status notification on the FixGuardian dashboard to inform the user of the sync outcome.

Data Integrity Verification

Given the synchronization of cost data, when the data is merged between the systems, then integrity checks must confirm all numeric values and breakdown details are transferred accurately without loss.

Customizable Alert Settings

"As a property manager, I want customizable alert settings so that I only receive notifications that match my specific cost-saving criteria."

Description

Enable users to configure alert thresholds and notification preferences according to their specific cost-saving criteria. This customization feature will allow property managers to adjust the sensitivity of alerts based on repair cost percentages, frequency, and other criteria, ensuring that they receive only the most relevant notifications.

Acceptance Criteria

Threshold Configuration

Given a property manager is logged in, when they navigate to the alert customization page, then they should be able to set alert thresholds based on repair cost percentages using a slider input and see a confirmation message upon successful save.

Notification Preferences Setup

Given a property manager is on the alert settings page, when they select their preferred notification channels (email, SMS, or in-app), then the system should update these preferences and display a confirmation dialogue.

Filtering Alerts by Frequency

Given the maintenance cost alert system is active, when a user configures alert frequency filters, then the system should only trigger notifications that match the specified frequency and ignore those that do not.

Custom Alert Sensitivity

Given an active alert configuration, when a user adjusts the sensitivity using a cost-saving criteria slider, then the system should dynamically update alert generation based on the new threshold and provide immediate feedback on how the adjustment affects predictions.

Persistent User Settings

Given a property manager has customized alert settings, when they log out and log back in, then their personalized configurations should persist and be automatically applied without requiring reconfiguration.

Smart Savings Notifier

Leverage AI-driven insights to receive timely alerts for repair interventions that maximize savings. This feature offers actionable recommendations, enabling seamless integration of cost efficiencies into maintenance schedules.

Requirements

Real-Time Savings Alerts

"As a property manager, I want to receive timely, AI-driven alerts for cost-effective repairs so that I can minimize maintenance expenses and avoid downtime."

Description

This requirement ensures that the system sends real-time, AI-driven alerts to property managers regarding optimal repair interventions that maximize cost savings. It gathers data from maintenance records and predictive analytics to deliver timely notifications, allowing users to act swiftly on cost-effective repairs. The alerts are designed to integrate seamlessly with FixGuardian's existing processes, reducing downtime and enhancing decision-making.

Acceptance Criteria

Real-Time Alerts Delivery

Given a property manager is actively using FixGuardian, when real-time alert should be sent, then the system must deliver the alert via the chosen notification method within 3 seconds.

AI-Driven Alert Accuracy

Given that the system processes up-to-date maintenance records and predictive analytics, when generating repair intervention alerts, then only recommendations with an estimated savings above a predefined threshold should trigger an alert.

Actionable Alert Details

Given a triggered alert is displayed, when a property manager reviews the alert, then the alert should clearly list repair cost, estimated savings, and step-by-step recommendations.

Seamless Integration

Given the alert generation process, when an alert is issued, then it must update FixGuardian’s task scheduling and maintenance log systems automatically with the relevant details.

High Notification Load

Given a peak period with multiple simultaneous alerts, when the system processes alert data, then all alerts must be delivered within 5 seconds with no loss of detail or accuracy.

Actionable Recommendation Engine

"As a property manager, I want actionable and data-driven repair recommendations so that I can efficiently schedule repairs and optimize maintenance costs."

Description

This requirement focuses on developing an intelligent engine that analyzes historical and real-time maintenance data to generate actionable repair recommendations. By leveraging machine learning algorithms, the engine evaluates trends and predicts the optimal time for interventions, ensuring that each alert provides practical and cost-saving advice. This functionality is a core component of the Smart Savings Notifier and is tightly integrated with the overall FixGuardian system.

Acceptance Criteria

Real-time Data Analysis Trigger

Given incoming real-time maintenance data, when the engine receives data that deviates significantly from historical trends, then it generates an alert with actionable repair recommendations.

Historical Data Trend Analysis

Given historical maintenance records, when the engine processes these records, then it identifies recurring issues and suggests optimal intervention times to maximize cost savings.

Actionable Alert Messaging

Given a generated recommendation, when the notification is sent to the property manager, then it includes clear action steps and estimated benefits in terms of cost savings.

Schedule Integration Efficiency

Given the actionable recommendations, when integrated with the FixGuardian system, then the engine must automatically update the Smart Savings Notifier's schedule with proposed maintenance windows.

Optimization and Feedback Loop

Given responses from maintenance outcomes, when the engine receives performance feedback from executed recommendations, then it adjusts future recommendations to improve accuracy and relevancy.

Seamless Schedule Integration

"As a property manager, I want maintenance alerts to automatically integrate with my existing schedule so that I can streamline operations without manual adjustments."

Description

This requirement entails integrating the Smart Savings Notifier with the existing maintenance scheduling system within FixGuardian. It ensures that alerts from the notifier automatically trigger schedule updates or recommendations, aligning cost-saving interventions with the repair workflow. The integration minimizes manual scheduling efforts and assures a synchronized response to maintenance alerts, ultimately boosting operational efficiency.

Acceptance Criteria

Scheduled Alert Trigger on Repair Detection

Given a repair alert from the Smart Savings Notifier is generated, when the alert is received by the maintenance scheduling system, then the schedule is automatically updated with the recommended task details to reflect the repair intervention.

Verified Schedule Update Integration

Given that FixGuardian’s maintenance schedule is active and up-to-date, when an alert from the Smart Savings Notifier is processed, then the system synchronizes the schedule with updated recommendations while ensuring no duplication or conflict with existing tasks.

Manual Override Testing for Schedule Integration

Given a scenario where a manager manually alters the maintenance schedule, when a new alert from the Smart Savings Notifier is received, then the system confirms the change by appending new recommendations without overriding the user’s manual adjustments.

Smart Sensor Grid

Integrates strategically placed IoT sensors to continuously monitor building systems and structural health, providing early detection of anomalies. Users benefit from real-time insights and proactive alerts, translating into reduced downtime and lower long-term maintenance costs.

Requirements

Automated Sensor Calibration

"As a property manager, I want sensors to self-calibrate automatically so that I can rely on precise, up-to-date data without the need for constant manual adjustments."

Description

Implement an automated calibration module that ensures each IoT sensor within the Smart Sensor Grid is accurately optimized for real-time data collection. This module should continuously monitor sensor performance, adjust calibration parameters in response to environmental changes, and maintain data integrity across the network. The system will use predefined calibration algorithms integrated with AI-driven analytics to ensure sensors remain accurate over time, reducing manual intervention and maintenance effort.

Acceptance Criteria

Real-Time Sensor Calibration

Given a sensor operating under normal conditions, when an environmental change is detected, then the automated calibration module must adjust the sensor parameters to maintain accuracy within predefined thresholds.

Continuous Performance Monitoring

Given a sensor integrated within the Smart Sensor Grid, when the module performs periodic performance assessments, then sensor data integrity must be maintained and any drift auto-corrected using AI-driven analytics.

Fallback Alert Mechanism

Given a scenario where auto-calibration fails due to environmental anomalies, when the failure is detected, then the system must trigger an immediate alert for manual intervention.

Real-Time Data Analytics Dashboard

"As a property manager, I want a real-time dashboard that visually displays sensor data trends and alerts so that I can make informed decisions quickly and address potential issues before they escalate."

Description

Develop a comprehensive real-time dashboard that aggregates, visualizes, and analyzes data from all IoT sensors deployed across properties. The dashboard should present key performance indicators, trend analysis, and anomaly alerts in an easy-to-understand format. Integration with AI algorithms will provide predictive insights, enabling property managers to take proactive measures in maintaining building systems.

Acceptance Criteria

Real-Time KPI Overview

Given the IoT sensor data feed is active, when the property manager logs in, then the dashboard displays up-to-date key performance indicators with a maximum delay of 5 seconds.

Anomaly Detection Alert

Given abnormal sensor readings are identified by the AI algorithms, when an anomaly is detected, then an immediate alert is triggered and displayed on the dashboard.

Trend Analysis Reporting

Given the availability of historical sensor data, when the property manager accesses trend analysis, then the dashboard accurately renders graphs and statistics representing trends over time.

User Interaction with Data Filters

Given multiple types of sensor data, when the property manager applies filter criteria, then the dashboard updates the displayed data dynamically without requiring a full page reload.

Predictive Maintenance Insights

Given the integration with AI-based predictive algorithms, when potential maintenance issues are forecasted, then the dashboard displays predictive insights with a validation accuracy of at least 80% against historical performance.

Predictive Maintenance Alerts

"As a property manager, I want to receive predictive maintenance alerts based on sensor data and AI analysis so that I can address issues proactively, reducing downtime and maintenance expenses."

Description

Design an alerting system that leverages AI-driven predictions to notify property managers of potential system failures or anomalies detected by the sensor grid. The alerts should be customizable, offering tiered notifications based on severity and potential impact. The system should integrate with mobile and desktop platforms, ensuring alerts are delivered promptly to the appropriate stakeholders.

Acceptance Criteria

Alert Prediction and Notification

Given a sensor detects an anomaly and the AI predicts potential system failure, when the system evaluates the risk, then a predictive maintenance alert is sent to the property manager.

Customizable Notification Preferences

Given the property manager accesses the alert settings, when they modify the tiered notification and severity options, then the system immediately updates and applies these customizations across all platforms.

Multi-Platform Alert Delivery

Given an alert is triggered, when the system dispatches the notification, then alerts are delivered simultaneously on both mobile and desktop platforms within 2 minutes.

Alert Severity Tiering

Given a sensor detects a high-severity anomaly, when the system processes the AI prediction, then the alert must clearly indicate the high priority and provide detailed remediation suggestions.

Integration with Building Management Systems

"As a property manager, I want the sensor grid to integrate effortlessly with my current building management systems so that all property monitoring and maintenance activities are centralized for streamlined operations."

Description

Establish robust integration protocols and APIs between the Smart Sensor Grid and existing Building Management Systems (BMS). This integration should facilitate seamless data sharing, enabling unified control and monitoring of property systems. It will allow for centralization of alerts, sensor data logs, and maintenance schedules, thereby enhancing operational efficiency and responsiveness in property management.

Acceptance Criteria

RealTime Data Synchronization

Given the integration is configured, when a sensor detects an anomaly, then the sensor data is transmitted in real-time to the BMS and recorded in the data log.

Unified Alerts Integration

Given the system is operational, when an alert is triggered by the Smart Sensor Grid, then the alert is immediately displayed on the centralized BMS dashboard.

Maintenance Scheduling Automation

Given predefined maintenance thresholds are reached, when sensor data indicates impending issues, then the system automatically updates the maintenance schedule in the BMS.

API Data Exchange Reliability

Given a valid API connection, when requests for sensor logs are made, then the BMS retrieves the data with proper error handling and within defined performance metrics.

Centralized Logging System

Given continuous monitoring, when sensor events and alerts occur, then these events are consolidated in the BMS with accurate timestamps and sensor identifiers accessible via audit logs.

AI Diagnostics

Utilizes advanced AI to analyze sensor data and diagnose emerging issues before they become critical. This feature empowers property managers with actionable insights, enabling timely intervention to prevent costly breakdowns and ensure smoother operations.

Requirements

Real-Time Data Acquisition

"As a property manager, I want the system to continuously collect real-time sensor data so that I can detect emerging issues promptly and reduce downtime."

Description

Implement a sensor data collection module that captures real-time readings from property sensors and ensures a continuous data feed to the AI diagnostics engine. This module is critical for enabling timely detection and analysis of maintenance issues, thereby reducing response time and preventing costly breakdowns.

Acceptance Criteria

Real-Time Sensor Data Capture

Given that the sensor module is active, when a sensor sends data, then the system must capture and transmit the data to the AI diagnostics engine within 1 second.

Continuous Data Feed Verification

Given continuous sensor operation, when the data pipeline is running, then the system must maintain at least a 99% availability of the data feed to the AI diagnostics engine over any given time window.

Fault Tolerance in Data Collection

Given a sensor or connection failure, when an error is detected, then the system must automatically attempt a reconnection or switch to backup sensors within 5 seconds and log the incident on the monitoring dashboard.

Predictive Analytics Engine

"As a property manager, I want the system to analyze sensor data for predictive insights so that I can preemptively address maintenance issues before they become critical."

Description

Develop an AI-driven analytics engine that leverages both historical and real-time sensor data to predict potential maintenance issues before they escalate. This predictive capability supports proactive intervention, minimizes unexpected failures, and helps manage maintenance costs effectively.

Acceptance Criteria

Real-Time Alert Generation

Given that sensor data is being analyzed in real time, when the predictive analytics engine identifies a potential maintenance issue, then the system must immediately alert the property manager.

Historical Trend Analysis

Given historical sensor data is available, when the system analyzes maintenance trends, then it must correctly identify recurring issues with at least 85% accuracy.

Integration with Sensor Data Streams

Given multiple sensor inputs, when data is ingested by the predictive analytics engine, then it must accurately correlate and process data from at least 3 distinct sensor types in real time.

Proactive Maintenance Scheduling

Given a predicted maintenance issue, when the alert is generated, then the system must propose an optimized maintenance schedule based on both historical and real-time analysis.

User Dashboard Reporting

Given predictions are generated, when the system displays this data on the user dashboard, then it must show all active predictions, recommended interventions, and status updates with a refresh rate of no more than 5 minutes.

Automated Alert System

"As a property manager, I want to receive immediate alerts on my device when a potential issue is detected so that I can respond quickly and prevent service interruptions."

Description

Design and implement an automated alert and notification system that dispatches actionable insights directly to property managers as soon as the AI diagnostics engine identifies potential issues. This real-time alert mechanism is vital for ensuring timely responses and minimizing disruption.

Acceptance Criteria

Real-Time Alert Dispatch

Given that the AI diagnostics engine detects a potential issue from sensor data, when the sensor data breaches a predefined threshold, then the system must send an automated alert to the property manager within 30 seconds.

Email and SMS Notifications

Given the property manager's contact information is available, when a diagnostic alert is triggered, then the system must dispatch notifications via both email and SMS channels concurrently within 60 seconds.

Actionable Insight Format

Given an alert is generated, when the property manager views the alert, then it must include a clear description of the diagnosed issue, actionable next steps, and a link to further details on the incident.

Alert Acknowledgment Feature

Given an alert is received by a property manager, when they acknowledge the alert through the system interface, then the system must log the acknowledgment timestamp and update the alert status to 'Acknowledged'.

System Reliability and Downtime Check

Given continuous operation of the automated alert system, when monitored over a 24-hour period, then the system must maintain a 99.9% uptime and ensure no false alerts are sent during routine checks.

Dashboard and Reporting Interface

"As a property manager, I want a clear and interactive dashboard that displays both real-time and historical diagnostic data so that I can make informed decisions about maintenance strategies."

Description

Create an intuitive and interactive dashboard that consolidates diagnostic insights, visualizes sensor data trends over time, and provides historical reporting on maintenance performance. This interface will facilitate data-driven decision-making and streamline property maintenance management.

Acceptance Criteria

Sensor Trends Visualization

Given sensor data exists, when a property manager views the dashboard, then sensor data trends should be accurately visualized using adaptive line charts that update in real-time.

Diagnostic Insights Display

Given AI diagnostic results are available, when the dashboard loads, then a dedicated section should display actionable insights in real-time with clear prioritization of issues.

Historical Maintenance Reporting

Given a selection of a specific date range, when a user attempts to view historical maintenance performance, then the system should retrieve and display accurate historical reports including key metrics and trends.

Interactive Dashboard Navigation

Given an interactive dashboard interface, when a user clicks on any specific data point or trend, then detailed breakdown and diagnostic information should be immediately available for further actions.

System Integration and API Connectivity

"As a property manager, I want the AI diagnostics feature to integrate seamlessly with my existing maintenance tools so that I can consolidate and manage all property data from a single platform."

Description

Enable seamless integration between the AI Diagnostics feature and existing property management systems through robust API connectivity. This integration ensures that diagnostic data is easily accessible and interoperable, improving overall system efficiency and data flow.

Acceptance Criteria

Real-Time Data Synchronization

Given that AI Diagnostics is operational, when sensor data is transmitted via the API, then the data should be received by the property management system in real-time with a maximum delay of 2 seconds.

Error Handling and Data Integrity

Given that data transmission encounters an interruption, when network failures occur, then the system must log the error, attempt automatic retries, and ensure data integrity through verification checks.

Secure API Authentication

Given that an external system requests diagnostic data, when the request is made, then the API must enforce OAuth 2.0 authentication and allow access only when a valid token is provided.

Health Dashboard

Offers a centralized, interactive display that visualizes building health metrics and sensor data trends. This user-friendly dashboard makes it easy for managers to monitor conditions and identify maintenance needs at a glance, facilitating informed decision-making.

Requirements

Real-time Data Feed

"As a property manager, I want to view real-time sensor data on the dashboard so that I can quickly address any emerging maintenance concerns."

Description

Integrate live sensor data feed in the Health Dashboard to provide immediate visualizations of building health metrics and sensor trends. This integration enables property managers to monitor conditions dynamically, facilitating prompt responses to maintenance issues and informed decision-making.

Acceptance Criteria

Real-time Sensor Data Ingestion

Given the Health Dashboard is accessed, when live sensor data is fed into the system, then the dashboard must update visualizations of building health metrics within 5 seconds.

Dynamic Data Visualization Accuracy

Given continuous sensor data input, when the dashboard displays real-time metrics, then all sensor values must reflect the most recent and accurate readings without delay.

User Alert Trigger on Threshold Breach

Given that sensor data breaches predefined safety thresholds, when such an event is detected, then an immediate, detailed alert is triggered on the dashboard for the property manager.

Predictive Maintenance Alerts

"As a property manager, I want to receive predictive maintenance alerts so that I can proactively schedule repairs and avoid unexpected disruptions."

Description

Develop an AI-driven predictive analytics module that leverages historical and real-time sensor data to forecast potential maintenance issues. This module will generate timely alerts to preemptively address failures, reducing downtime and maintenance costs while improving tenant satisfaction.

Acceptance Criteria

Real-Time Alert Detection

Given a sensor reading anomaly, when the system detects a potential failure pattern, then it should generate an alert within one minute.

Historical Data Analysis

Given the historical sensor data, when the AI module processes the dataset, then it should identify recurring issues with at least 90% accuracy.

User Notification on Health Dashboard

Given a generated predictive maintenance alert, when a property manager logs into the Health Dashboard, then the alert should be prominently displayed with details for immediate action.

Multi-Sensor Data Correlation

Given multiple sensor inputs, when the system correlates data from various sources, then it should flag issues that are common across sensors with a confidence threshold of 80%.

Alert Logging and Acknowledgement

Given a maintenance alert is created, when the user acknowledges or dismisses the alert, then the system should log the action with a timestamp for audit purposes.

Interactive Dashboard Filters

"As a property manager, I want to customize my dashboard view with filters so that I can focus on the most critical data pertaining to my properties."

Description

Implement interactive filtering and customization options on the dashboard that allow users to sort and select sensor data based on location, timeframe, and specific performance metrics. This feature ensures that property managers can easily isolate relevant trends and respond to specific maintenance needs.

Acceptance Criteria

Dashboard Filter by Location

Given the dashboard displaying sensor data, when a user selects a specific location filter, then the dashboard should update in real-time to show only sensor data for that location.

Dashboard Filter by Timeframe

Given sensor data available over various time intervals, when a user selects a custom timeframe filter, then the dashboard must display only the data corresponding to the selected period in chronological order.

Dashboard Filter by Performance Metric

Given that multiple performance metrics are presented, when a user selects a specific metric from the filter options, then the dashboard shall update to display only sensor data relevant to that performance metric.

Customization Persistence for Filters

Given that a user applies custom filter settings, when the dashboard is refreshed or re-accessed within the same session, then the previously applied filters should persist to maintain the user's customized view.

Multiple Filters Interaction

Given that a user intends to apply multiple filters simultaneously, when selecting filters for location, timeframe, and performance metrics together, then the dashboard should accurately display the intersected data set without noticeable delay.

Historical Data Analysis

"As a property manager, I want to access historical data trends so that I can analyze long-term performance and plan strategic maintenance schedules."

Description

Enable the dashboard to present historical sensor data alongside current readings, providing a comparative analysis tool. This allows property managers to identify trends over time, assess maintenance reliability, and strategize future preventive measures effectively.

Acceptance Criteria

Historical Trend Visualization

Given a property manager navigates to the Historical Data Analysis section, when the dashboard loads, then the system displays at least 12 months of historical sensor data alongside current readings in a comparative view.

Interactive Timeframe Selection

Given a property manager selects a custom date range, when the timeframe filter is applied, then the dashboard updates dynamically to showcase historical sensor data corresponding to the selected period.

Data Comparison Accuracy

Given sensor data is collected continuously, when historical and current data are displayed side-by-side, then the system ensures the data metrics are accurate within a 2% discrepancy margin.

Alert Management Interface

"As a property manager, I want an intuitive alert management interface so that I can efficiently keep track of and resolve maintenance notifications."

Description

Create a dedicated interface within the Health Dashboard for managing and prioritizing maintenance alerts. This feature allows property managers to review, acknowledge, and address alerts efficiently, ensuring that critical issues are tracked and resolved in a timely manner.

Acceptance Criteria

Alert Review and Acknowledgement

Given that a property manager accesses the Health Dashboard, when the Alert Management Interface loads, then a clear list of maintenance alerts is displayed sorted by priority along with an option to acknowledge each alert.

Prioritize Alerts

Given that multiple alerts exist, when a manager selects an alert and updates its priority, then the system reorders the alert list to reflect the new priority and displays a confirmation message.

Alert Resolution Tracking

Given that an alert has been acknowledged, when the manager marks it as resolved, then its status updates accordingly, a resolution timestamp is recorded, and the alert is moved to a resolved alerts section.

Real-Time Alert Update

Given that sensor data triggers a new alert, when conditions exceed predefined thresholds, then the Alert Management Interface automatically updates in real-time to display the new alert without requiring a page refresh.

Automated Alerts

Delivers instant notifications when sensors suggest potential issues, ensuring that property managers receive timely updates. This feature minimizes unexpected disruptions by prompting preemptive actions, thereby enhancing tenant satisfaction and operational efficiency.

Requirements

Real-Time Sensor Data Processing

"As a property manager, I want the system to process sensor data in real time so that I receive timely alerts on potential maintenance issues."

Description

The system must integrate sensor data feeds with minimal latency to process inputs in real time, analyzing incipient maintenance issues automatically. This capability ensures alerts are generated promptly and accurately, enabling property managers to act quickly to mitigate potential downtime and costs.

Acceptance Criteria

Immediate Sensor Data Capture

Given the sensor data feed is active, when new data is received, then the system must process the data within 1 second to ensure real-time operations.

Accurate Issue Detection

Given the processed sensor data, when the algorithm analyzes the incoming data, then it must detect incipient maintenance issues with a false positive rate below 5%.

Alert Notification Latency

Given an issue is detected through sensor data, when an alert is generated, then the notification must be sent to property managers within 500 milliseconds.

Seamless Integration with Automated Alerts

Given the sensor data stream and automated alert system are active, when the threshold conditions are met, then the system must trigger an alert that integrates seamlessly with the Automated Alerts feature.

Fallback Mechanism Activation

Given a disruption or delay in sensor data feed, when system connectivity issues are detected, then the fallback protocol must automatically activate to maintain essential monitoring functions with a minimal acceptable performance level.

Automated Alert Trigger Engine

"As a property manager, I want maintenance alerts to be triggered automatically based on sensor data so that potential issues are addressed before they cause significant damage."

Description

Implement an AI-driven engine that analyzes incoming sensor data and predictive patterns to automatically trigger maintenance alerts. This ensures that property managers are notified before issues escalate, allowing for proactive actions that reduce unexpected disruptions and enhance operational efficiency.

Acceptance Criteria

Automated Alert on Sensor Trigger

Given sensor readings indicate a potential issue, When the AI engine processes the data, Then an alert must be automatically triggered to the property manager within 2 minutes.

Preemptive Alert with AI Pattern Recognition

Given historical sensor data is available, When the AI engine identifies deviations from normal patterns, Then the system must preemptively alert the property manager before issues escalate.

Alert Accuracy Verification

Given sensor data is available, When the AI predictions are compared against actual maintenance issues, Then the alert accuracy must be at least 95% to ensure minimal false positives.

Network Resilience in Alert Delivery

Given potential network interruptions, When sensor data is delayed or fails to upload in real-time, Then the system must queue the alerts and deliver them once connectivity is restored.

Customizable Alert Thresholds

"As a property manager, I want to customize alert thresholds so that the alerts I receive are tailored to my property's unique conditions."

Description

Allow property managers to customize alert thresholds based on property-specific conditions. By enabling configuration of sensitivity levels for various sensor inputs, the system can reduce false positives and ensure that alerts are relevant and actionable.

Acceptance Criteria

Customized Residential Alert Settings

Given a property manager is logged in, when navigating to alert settings, then they should be able to adjust threshold settings for sensor inputs and verify immediate confirmation.

False Alert Prevention

Given a manager has configured custom alert thresholds, when sensor data is received, then alerts should only be triggered if the readings consistently exceed the set thresholds over a configurable period.

Instant Configuration Update

Given a property manager updates the alert thresholds, when the configuration is saved, then the new settings should be applied immediately to real-time sensor alerts with a confirmation message displayed.

Multi-Channel Notification Delivery

"As a property manager, I want to receive notifications through multiple channels so that I remain informed even if one communication method fails."

Description

Design a notification system that supports multiple delivery channels such as SMS, email, and mobile app push notifications. This redundant delivery approach ensures that alerts reach property managers reliably, even if one communication channel experiences issues.

Acceptance Criteria

Real-Time Sensor Alert Handling

Given a sensor detects a potential issue, When the issue is identified, Then the system must send notifications simultaneously via SMS, email, and push notifications.

Fallback Notification Channel

Given a failure in the primary delivery channel, When the system identifies that SMS/email or push notification has not been delivered within the stipulated time, Then the system must automatically trigger delivery via an alternative channel.

Notification Aggregation under High Frequency Alerts

Given multiple alerts occurring within a short time span, When the system detects several issues in under one minute, Then it must consolidate the alerts into a single multi-channel notification to prevent flooding the user.

User Preference for Notification Channels

Given a property manager's defined notification preferences, When alerts are generated, Then the system must prioritize sending notifications through the preferred channels while maintaining redundancy in backup channels.

Secure Notification Delivery

Given a registered device receives a push notification, When a notification is sent, Then the system must confirm device authentication and use encryption protocols to secure the delivery.

Alert History and Analytics Dashboard

"As a property manager, I want to view historical alert data and analytics so that I can identify recurring maintenance issues and plan effectively for the future."

Description

Develop a comprehensive dashboard that logs historical alerts and provides analytic insights into alert patterns over time. This tool will assist property managers in identifying recurring issues and trends, facilitating long-term maintenance planning and strategic decision-making.

Acceptance Criteria

Initial Dashboard Login and Overview

Given a property manager logs into FixGuardian, when they access the Alert History and Analytics Dashboard, then the dashboard must display a summary of recent alerts with corresponding analytic trends and graphs.

Historical Alert Log Filtering

Given a manager is viewing the alert log, when applying date or sensor type filters, then the dashboard must update the displayed data to reflect the filter conditions accurately.

Data Visualization Accuracy

Given the manager selects a specific time period, when analyzing the chart data, then the dashboard must show accurate visual representations of alert trends and patterns in real-time.

Exporting Analytical Reports

Given a manager wants to export alert data, when selecting the export option, then the dashboard must generate and download a formatted report containing all relevant metrics in CSV or PDF format.

User Interaction and Navigation

Given a property manager navigates across different sections of the dashboard, when interacting with various components, then the dashboard must ensure smooth transitions and immediate feedback with no performance lags.

Predictive Scheduling

Seamlessly integrates AI forecasts with maintenance scheduling, triggering proactive service appointments before issues escalate. Property managers benefit from reduced emergency repairs and improved workflow efficiency, contributing to both cost savings and higher property value.

Requirements

Real-Time Data Integration

"As a property manager, I want access to real-time data updates so that I can rely on accurate maintenance predictions and timely service appointments."

Description

Integrate real-time property data, including sensor inputs and historical logs, into the AI scheduling engine to continuously predict maintenance needs and enhance scheduling precision.

Acceptance Criteria

Real-Time Sensor Data Feed

Given real-time sensor data is available, When the system receives sensor inputs, Then it updates the AI scheduling engine in real-time to adjust maintenance schedules.

Historical Data Integration for Predictions

Given historical property logs are accessible, When the AI engine processes past and present data, Then it refines predictive models to accurately forecast maintenance needs.

Automated Alert and Schedule Adjustment

Given an anomaly is detected in sensor data, When potential maintenance issues are identified, Then the system automatically triggers a schedule adjustment and sends alerts to property managers.

Automated Appointment Triggering

"As a property manager, I want the system to automatically trigger maintenance appointments based on predictive insights so that I can minimize downtime and streamline operations."

Description

Implement an automated system that initiates service appointments based on AI forecasts, reducing manual scheduling efforts and minimizing the risk of emergency repairs.

Acceptance Criteria

AI Trigger Activation

Given the AI forecast indicates a potential maintenance need based on historical data and current sensor inputs, when the forecast meets the predefined threshold criteria, then the system must automatically initiate a service appointment.

Scheduling Confirmation

Given that an appointment has been automatically triggered, when the appointment details are finalized, then a confirmation notification must be sent to the property manager detailing the appointment information.

Manual Appointment Override

Given that an appointment has been automatically scheduled, when the property manager decides to modify or cancel the appointment, then the system must allow for manual intervention without affecting the logging and tracking mechanisms.

Error Handling and Logging

Given an error occurs during the automated appointment triggering process, when any part of the process fails, then the system must log the error details, send an alert to the maintenance team, and retry the operation based on a defined retry policy.

Maintenance Resource Allocation

"As a property manager, I want the system to recommend efficient resource allocations based on forecasted maintenance needs so that I can optimize team deployment and reduce costs."

Description

Develop a functionality that analyzes predictive maintenance data to suggest optimal resource allocation, improving workflow efficiency and reducing overall maintenance costs.

Acceptance Criteria

Real-time Predictive Analysis

Given predictive maintenance data from the AI, when the system processes current property conditions and historical trends, then it should generate optimal resource allocation recommendations for personnel and materials.

Resource Reallocation Notification

Given that potential maintenance issues are identified, when resource allocation suggestions are created, then managers must receive clear notifications detailing prioritized action items and timeframes.

Cost Reduction Validation

Given the generated resource allocation recommendations based on predictive insights, when these allocations are implemented, then the system should report a measurable reduction in maintenance costs within a defined period.

Schedule Conflict Resolution

Given overlapping maintenance tasks triggered by predictive analysis, when resource allocation suggestions are provided, then the system should offer conflict resolution options ensuring optimal distribution of resources.

User Customizable Alert Thresholds

"As a property manager, I want to customize alert thresholds in the predictive scheduling system so that notifications match the specific risk profile and requirements of my properties."

Description

Offer customizable settings that allow property managers to adjust the sensitivity of maintenance alerts, ensuring the predictive system aligns with specific property risks and operational needs.

Acceptance Criteria

Threshold Adjustment via Settings Panel

Given a property manager is logged into FixGuardian, when they navigate to the alert threshold settings panel, then they should see current default thresholds and be allowed to adjust each threshold value with appropriate input constraints.

Real-Time Threshold Update Impact

Given that a property manager modifies the alert thresholds, when the change is saved, then the system should immediately update the predictive scheduling engine with the new threshold values and adjust maintenance notifications accordingly.

Validation and Error Handling for Threshold Inputs

Given that a property manager enters a new threshold value, when the input is invalid (e.g., non-numeric or out-of-bound values), then the system should display an appropriate error message and reject the invalid input.

Guided Walkthrough

An interactive tutorial that leads new users step-by-step through FixGuardian’s key functionalities. This feature helps users understand essential operations, reduces the initial learning curve, and enhances early engagement by showcasing the benefits of the platform.

Requirements

Interactive Onboarding Sequence

"As a new user, I want an interactive onboarding sequence so that I can quickly understand FixGuardian’s key functionalities and begin managing properties efficiently."

Description

The interactive onboarding sequence provides a step-by-step tutorial that immerses new users in FixGuardian’s core functionalities. This requirement integrates an engaging guided walkthrough that highlights essential operations and the benefits of using the platform. It is designed to reduce the learning curve, ensure operational efficiency from the first interaction, and boost overall user engagement by proactively addressing potential queries during the introduction.

Acceptance Criteria

User Onboarding Start

Given a new user accesses the onboarding sequence, when the user chooses to begin the walkthrough, then the first step of the guided tutorial loads within 2 seconds.

Navigating Through Steps

Given the user is engaged in the guided walkthrough, when the user successfully completes a step, then the system automatically highlights the next step without manual intervention.

Interactive Query Assistance

Given the presence of contextual help icons, when a new user hovers or clicks on an icon, then relevant tips or FAQs appear within a modal window.

Completion Feedback

Given a user finishes the interactive onboarding sequence, when the final step is reached, then a summary screen is presented that confirms completion and instructs next actions.

Error Handling in Onboarding

Given that an error occurs during the onboarding process, when a step fails to load, then the system provides a clear error message and an option to retry the step.

Guided Navigation for Key Functions

"As a user, I want a clear guided navigation through the key functions so that I can seamlessly learn and use the platform without confusion."

Description

This requirement focuses on implementing a clear, guided navigation system that directs users through FixGuardian’s most important functions. The system is dynamically integrated with the platform, ensuring that users encounter a logical progression of tasks that mirrors real-world usage. Its primary benefit is to streamline the user's path through the tutorial, thereby reducing friction and improving comprehension.

Acceptance Criteria

Guided Walkthrough for New Users

Given a new user logs in, when they access the Guided Walkthrough feature, then the system must automatically initiate a step-by-step tutorial highlighting key functions with contextual hints.

Contextual Navigation Hints

Given that the tutorial is in progress, when the user interacts with an element, then the system should display contextual navigation hints to guide their navigation through the platform.

Dynamic Task Progression

Given that the user completes a step in the tutorial, when progressing to the next segment, then the system must dynamically update the navigation path with clear visual indicators and progression markers.

Completion Feedback Integration

Given that the guided navigation is complete, when the final step is finished, then the system should provide a summary of completed tasks and suggest next steps for further user engagement.

Error Handling and Re-guidance

Given that a user encounters an error during the guided navigation, when the error is detected, then the system should display corrective instructions and offer an option to restart the affected segment.

Contextual Assistance & Tips

"As a new user, I want context-specific tips available during the walkthrough so that I can immediately understand the benefits of each feature and feel confident in using the platform."

Description

This functionality provides users with real-time, contextual assistance and tips as they navigate the walkthrough. By integrating smart tooltips and help cues, the feature will address common questions and guide users through complex functions, thereby enhancing the learning process. It is designed to deliver targeted educational content in a non-intrusive manner, elevating the overall user support within the tutorial.

Acceptance Criteria

Real Time Tooltip Assistance

Given a user navigates the guided walkthrough, when they hover over or click on a complex function, then a smart tooltip appears displaying concise, context-specific help and step-by-step instructions.

Context-Sensitive Help Cue Activation

Given a user pauses on a walkthrough step for more than 30 seconds, when system detects inactivity, then a relevant help cue is automatically displayed with tips tailored to that step.

User Customizable Assistance Level

Given a new user is interacting with the guided walkthrough, when they access the settings panel, then they are provided with options to select the level of assistance (e.g., basic, intermediate, advanced) that adjusts the detail of contextual tips.

Adaptive Assistance Based on User Progress

Given a user progresses through the walkthrough steps, when the system tracks completion metrics, then the frequency and detail of contextual assistance automatically adjusts to match the user’s familiarity with the application.

Progress Tracking Indicator

"As a user participating in the guided walkthrough, I want to see a progress indicator so that I know how far I have progressed and how many steps remain."

Description

The progress tracking indicator visually represents the user's advancement through the guided walkthrough. This requirement involves creating a dynamic progress bar or step indicator that updates in real-time, offering clear feedback on the completion status of the walkthrough. Its integration ensures that users are aware of their position in the onboarding process, which can enhance user motivation and reduce abandonment rates.

Acceptance Criteria

Onboarding Step Completion

Given a user is navigating the guided walkthrough, when each section is completed, then the progress tracking indicator updates accordingly to reflect the correct progress percentage or step count.

Real-Time Progress Update

Given that a user is interacting with the guided walkthrough, when navigating between different steps, then the progress indicator should update immediately in real-time without requiring a page refresh.

Resume Walkthrough Progress

Given that a user exits the walkthrough before completion, when the user later resumes the session, then the progress tracking indicator must restore and display the last recorded progress state accurately.

Visual Milestone Feedback

Given that a significant progress milestone (e.g., 50% or 100%) is reached during the walkthrough, when the progress indicator updates, then it should display a distinct visual cue (such as a color change or checkmark) to denote milestone achievement.

Feedback Mechanism at End of Walkthrough

"As a user, I want an option to provide feedback at the end of the walkthrough so that my experience can help improve and refine the tutorial for future users."

Description

This requirement introduces a built-in feedback mechanism at the end of the guided walkthrough, enabling users to share their experiences and suggestions directly. The feature is designed to collect actionable insights that inform continuous improvements in the tutorial. Its integration is crucial for iterative development and helps tailor future enhancements based on real user input.

Acceptance Criteria

Walkthrough Completion Feedback Prompt

Given a user completes the guided walkthrough, when they reach the final step, then the system must display a clear and prominent feedback prompt.

Feedback Submission Validation

Given a user submits their feedback, when the submission occurs, then the system must validate the input ensuring it is complete and free of errors.

Storing and Retrieving Feedback Data

Given a feedback response is submitted, when the system processes the input, then the feedback must be stored in the database and be retrievable for later analysis.

User-Friendly Interface for Feedback Mechanism

Given a user accesses the feedback form, when the interface is rendered, then it must be intuitive, following the design guidelines and accessible to the target audience.

Real-Time Feedback Acknowledgement

Given a feedback submission is successfully sent, when the system completes the transaction, then the user must receive an immediate confirmation notification.

Quick Start Wizard

A streamlined setup assistant that gathers initial inputs and configures essential settings automatically. It simplifies the onboarding process, ensuring that new users quickly become productive while enjoying a customized setup that reduces frustration.

Requirements

Introduction Screen

"As a property manager, I want to be greeted with a clear introduction so that I can quickly understand how to use the quick start wizard."

Description

This screen provides a warm welcome and overview, guiding users through the quick start wizard with clear instructions and visuals that simplify their first interactions with FixGuardian.

Acceptance Criteria

Welcome Message Display

Given the user launches FixGuardian for the first time, when the Introduction Screen appears, then it must showcase a warm welcome message along with concise instructions and appropriate visuals.

Navigation to Quick Start

Given the introduction content is displayed, when the user clicks the 'Get Started' or equivalent action button, then the application should navigate the user to the Quick Start Wizard seamlessly.

Visual Branding Consistency

Given the Introduction Screen loads, when the UI elements render, then they must adhere to FixGuardian's established color schemes, fonts, and logos ensuring visual consistency.

Responsive Interface

Given the user accesses the Introduction Screen from various devices, when the screen is rendered, then the layout should dynamically adjust for optimal display on desktop, tablet, and mobile formats.

Instruction Clarity

Given that the Introduction Screen provides onboarding guidance, when a user reads the instructions, then they must be clear, concise, and directly lead to productive use of the Quick Start Wizard.

Input Validation Mechanism

"As a property manager, I want immediate feedback on my inputs so that I can correct errors instantly and proceed without frustration."

Description

This requirement ensures all user inputs during the onboarding process are validated in real-time, preventing errors and guiding users to provide accurate information, thereby reducing setup errors and ensuring seamless configuration.

Acceptance Criteria

Real-Time Field Validation

Given the onboarding form is active, when a user inputs data and shifts focus, then the system must validate the input instantly and display an error message for any invalid entry.

Error Notification Mechanism

Given a user provides invalid data, when the input fails validation, then the system must present a clear error message with guidance on how to correct the input.

Successful Input Confirmation

Given a user enters valid input, when the data is submitted or field loses focus, then the system must visually confirm the validity (e.g., with a green border or check mark).

Empty Input Warning

Given that a mandatory field in the onboarding form is left blank, when the field loses focus or the form is submitted, then the system must flag the empty field with an error message indicating it cannot be blank.

Consistent Data-Type Validation

Given input fields of various types (text, numeric, email), when a user submits input, then the system must validate each field against its required format and constraints accurately.

Auto Configuration Engine

"As a property manager, I want the system to automatically configure my settings so that I can start using FixGuardian quickly without manual adjustments."

Description

Automatically configures essential settings based on provided inputs, leveraging AI to detect property management requirements and tailor the setup to optimize maintenance scheduling and cost reduction.

Acceptance Criteria

Initial User Onboarding

Given a new user has entered property details and management preferences in the Quick Start Wizard, when the Auto Configuration Engine processes the input, then the essential settings are correctly configured to optimize maintenance scheduling and cost reduction.

Error Handling in Input

Given a user has provided incomplete or conflicting property management inputs, when the Auto Configuration Engine validates the input, then appropriate error messages are returned and the configuration process does not proceed until corrections are made.

AI-Driven Setting Adjustment

Given the provided data triggers AI recommendations, when the Auto Configuration Engine applies the AI logic, then the system automatically adjusts configurations to proactively handle maintenance needs and minimize costs.

User Confirmation and Override

Given the Auto Configuration Engine has applied default settings, when the user reviews these settings, then the user is provided with options to confirm, modify, or override the configurations before finalizing the setup.

Customization Options

"As a property manager, I want to adjust the suggested configurations so that the system better reflects my specific property management needs."

Description

Offers users the ability to modify default configurations and personalize the setup, accommodating specific operational needs and preferences while ensuring a balance between automation and user control.

Acceptance Criteria

User Personalizes Setup Options

Given a new user accesses the Quick Start Wizard, when they navigate to the customization phase, then they should see a set of configurable options that allow modification of default settings.

User Saves Customized Configurations

Given a user modifies any configuration option, when they click the 'Save' button, then the system must store the changes and update subsequent operational workflows accordingly.

User Navigates Back to Customization

Given a user completes the initial setup, when they access the settings from the main dashboard, then they should be able to review and modify their chosen configurations without loss of data.

Validation of Input in Customization Options

Given a user enters data in the customization fields, when they attempt to save these entries, then the system should validate the input against predefined formatting and constraint rules, providing clear error messages if necessary.

Default Settings Load Correctly

Given the Quick Start Wizard is initiated, when no modifications are made by the user, then the system should accurately load and apply default configuration settings without errors.

Onboarding Completion Feedback

"As a property manager, I want to receive a concise summary of my configured settings at the end of onboarding so that I can proceed with confidence."

Description

Provides clear feedback upon completion of the onboarding process, including summary details and next steps, ensuring that users understand their configuration and are guided towards full system utilization.

Acceptance Criteria

Onboarding Completion Summary

Given the user has completed the Quick Start Wizard, when the onboarding process finishes then a feedback screen displays a detailed summary including configuration details and clear next steps.

Feedback Detail Verification

Given the onboarding process is complete, when the feedback is presented then all key configuration details and recommended next actions are clearly listed in a structured, easy-to-read format.

Feedback Usability Confirmation

Given that the feedback page loads after onboarding, when the user interacts with it then intuitive navigation cues and highlighted tools guide the user to further actions.

Error Handling During Feedback Generation

Given an unexpected issue occurs during the feedback generation, when the problem arises then the system displays a clear error message with actionable resolution steps for the user.

Responsive Feedback Display

Given that the feedback page is accessed on multiple devices, when being viewed then the layout and content adjust responsively to fully accommodate different screen sizes.

Feature Spotlight

A dynamic onboarding tool that highlights different FixGuardian functionalities at the right moments, using contextual pop-ups and brief descriptions. This feature improves user understanding by illustrating key benefits and guiding exploration of advanced features.

Requirements

Contextual Pop-up Triggers

"As a property manager, I want to receive targeted pop-up notifications that guide me through the system's functionalities so that I can learn and use advanced features effectively."

Description

This requirement ensures that the Feature Spotlight module intelligently displays pop-ups based on user actions or contextual events, guiding users to key functionalities at optimal moments. It integrates with FixGuardian's core property maintenance system to deliver timely insights and facilitate a smoother learning curve for property managers.

Acceptance Criteria

User Login Trigger

Given the property manager successfully logs in, when the system recognizes a first login session, then display the introductory contextual pop-up highlighting major features.

Maintenance Schedule Update

Given a maintenance schedule update occurs, when the system registers the change, then display a targeted pop-up introducing the updated scheduling functionalities.

Property Issue Prediction Alert

Given the AI-driven system detects a potential maintenance issue, when the risk threshold is met, then display an alert pop-up providing proactive recommendations.

Interactive Help Request

Given a property manager hovers over a help icon in a module, when the hover duration exceeds three seconds, then trigger a contextual pop-up to offer feature guidance.

Contextual Navigation Enhancement

Given the property manager accesses a new functionality for the first time, when the module loads, then display a pop-up highlighting key benefits and usage tips.

Onboarding Flow Customization

"As a property management admin, I want to configure the onboarding experience for new users so that the introduction aligns with our operational priorities and focuses on the most relevant features."

Description

This requirement provides an editable onboarding flow configuration that allows administrators to adjust the sequence, appearance, and content of Feature Spotlight pop-ups. It offers customization options to tailor the onboarding experience according to different user roles and experience levels, ensuring a personalized approach to introducing the FixGuardian capabilities.

Acceptance Criteria

Customizable Popup Sequence

Given an administrator is on the onboarding flow configuration screen, when they reorder the feature spotlight pop-ups, then the system should update the display order and persist the new sequence.

Role-Based Customization

Given an administrator selects a specific user role for onboarding customization, when configuring the flow, then only options relevant to that user role are displayed and correctly saved.

Editable Content and Appearance

Given an administrator is editing the content, design, and timing of a Feature Spotlight pop-up, when the changes are submitted, then the onboarding experience should reflect the updated configurations.

Real-Time Preview

Given an administrator customizes a pop-up's settings, when the preview function is activated, then a simulated pop-up should display reflecting all current changes accurately.

Access Control Validation

Given an unauthorized user or an administrator without sufficient privileges attempts to modify the onboarding configuration, when they try to save the changes, then the system should block the modification and display an appropriate error message.

Tooltip Content Management

"As a content manager, I want to easily update and manage the pop-up and tooltip content so that the information communicated to users is always current and engaging."

Description

This requirement mandates the integration of a content management system for tooltip copy and linked media within the Feature Spotlight tool. It facilitates the process of updating, reviewing, and testing informational content related to various FixGuardian functionalities, ensuring that the messaging remains accurate, engaging, and up-to-date.

Acceptance Criteria

Tooltip Content Update

Given an editor logs into the CMS, when they select a tooltip copy to update and modify the content, then the changes must be reflected in a real-time preview with the linked media correctly attached.

Tooltip Review Process

Given a new tooltip content submission, when an admin reviews the content and media, then they must be able to approve or request changes, with an audit history capturing all alterations.

Scheduled Tooltip Update

Given a scheduled update in the CMS, when the update time arrives, then the tooltip content and associated media should update automatically across the user interface without downtime.

Tooltip Rollback Functionality

Given that a newly updated tooltip content is flagged as problematic, when an admin initiates a rollback, then the system must revert the tooltip to its previous approved version and confirm the action.

Tooltip Version Control

Given an update is made to the tooltip content, when the version history is accessed, then a detailed log of updates with timestamps and editor details must be available to ensure content transparency.

User Engagement Analytics Integration

"As a product manager, I want to track user interactions with the onboarding tool so that I can measure its effectiveness and optimize feature delivery for improved user satisfaction."

Description

This requirement focuses on integrating user engagement analytics into the Feature Spotlight to monitor interactions, pop-up effectiveness, and gather user feedback. By tracking key metrics and correlating user actions with specific onboarding steps, it will help evaluate the tool's impact and guide improvements to enhance overall product adoption among property managers.

Acceptance Criteria

User Interaction Tracking

Given Feature Spotlight is active, When any pop-up is displayed, Then log user interaction events including timestamp, click status, and pop-up view duration.

Pop-up Effectiveness Measurement

Given a user sees a pop-up, When the user interacts by clicking 'learn more' or dismissing it, Then track the click-through and dismissal rates along with time spent on the pop-up.

Feedback Correlation with Onboarding Steps

Given a user completes an onboarding step, When the user provides feedback via the integrated form, Then associate that feedback with the corresponding step and log the satisfaction rating and any reported issues.

Analytics Dashboard Data Integration

Given that all user interactions are logged, When data is aggregated, Then the analytics dashboard must display key metrics such as interaction counts, conversion rates, and step-wise breakdown in near real-time.

Interactive Help Hub

A centralized resource center offering on-demand video tutorials, FAQs, and step-by-step guides. This feature provides new users with immediate support and educational content, helping them master the platform with ease and confidence.

Requirements

Video Tutorial Integration

"As a property manager, I want to access high-quality video tutorials so that I can learn how to use FixGuardian efficiently and resolve issues quickly."

Description

This requirement focuses on integrating a centralized video tutorial repository within the Interactive Help Hub. It includes an organized library of on-demand video guides that cover all aspects of FixGuardian functionalities. It enables users to quickly locate and watch relevant tutorials, thereby reducing the time needed for troubleshooting and learning. The integration should support adaptive streaming, high-quality playback, and responsiveness across devices.

Acceptance Criteria

Video Tutorial Search and Filter

Given a user is on the Interactive Help Hub, when they enter keywords in the search bar, then video tutorials matching the keywords must be accurately displayed sorted by relevance and allow applying filters by category, duration, or difficulty.

Adaptive Streaming Playback

Given a user starts a video tutorial on any device, when network conditions fluctuate, then the system should seamlessly adjust the video quality without interruption, ensuring smooth playback and responsive controls.

Cross-Device Responsive Integration

Given a user accesses the Interactive Help Hub from a desktop, tablet, or smartphone, when navigating to the video tutorial repository, then the tutorials must render correctly with optimal layout and functionality across all devices, adapting the playback interface to different screen sizes.

Dynamic FAQ System

"As a new user, I want quick answers to common questions so that I can resolve issues without delay and enhance my overall productivity."

Description

This requirement involves developing a dynamic FAQ platform that delivers immediate, context-aware answers to common user questions. It will feature an intelligent search function that filters FAQs based on keywords and usage patterns, ensuring users receive relevant support. This system will update periodically with new content and integrate seamlessly into the Interactive Help Hub, ultimately reducing downtime and improving user troubleshooting capabilities.

Acceptance Criteria

Intelligent FAQ Search

Given a user enters a keyword search in the FAQ system, when they submit the query, then the system returns relevant FAQ entries based on intelligent keyword matching and contextual relevance.

Context-Aware FAQ Response

Given a logged-in user accesses the FAQ system during an active session, when they request help, then the system filters and displays FAQs relevant to the user's current context and usage patterns.

Periodic FAQ Content Update

Given new FAQ content has been added to the central repository, when the scheduled update cycle is triggered, then the dynamic FAQ system automatically integrates and displays the updated content in the Interactive Help Hub.

Seamless Integration with Help Hub

Given a user navigates to the Interactive Help Hub, when they access the FAQ section, then the dynamic FAQ system loads without interface delays and maintains consistent design and responsiveness across the platform.

Responsive Mobile FAQ Experience

Given a user accesses the Interactive Help Hub from a mobile device, when the FAQ system is loaded, then the system displays all functionalities, including search and filter, in a mobile-optimized and user-friendly layout.

Interactive Step-by-Step Guides

"As a new user, I need interactive walkthroughs so that I can learn the system's features in a hands-on manner and gain confidence quickly."

Description

This requirement is about creating interactive, walkthrough-based guides that assist users in navigating through complex processes on FixGuardian. The guides should combine text, images, and interactive elements to provide step-by-step instructions. They will be integrated into the Help Hub and tailored to various user roles, ensuring that both novices and experienced users can benefit from guided instruction. The implementation is expected to improve the onboarding experience and reduce error rates.

Acceptance Criteria

First-time User Onboarding

Given a new user accesses the Interactive Help Hub, when they select the Interactive Step-by-Step Guides, then the system displays a comprehensive walkthrough with text, images, and interactive prompts.

Experienced User Quick Reference

Given an experienced user logs into FixGuardian, when they invoke the Interactive Step-by-Step Guides, then the system allows them to quickly jump to specific tasks relevant to their role.

Role-based Customization

Given a user’s role is determined upon login, when the Interactive Step-by-Step Guides are accessed, then the content is tailored to display role-specific processes and instructions.

Error Recovery Guidance

Given an error occurs during a process, when the Interactive Step-by-Step Guide is activated, then the system provides clear, actionable steps integrated with visual aids to help recover from the error.

Feedback Integration

Given a user completes a walkthrough session, when the guide concludes, then the system prompts the user to provide feedback on the clarity and usefulness of the guide.

User Success Tracker

An integrated progress monitor that tracks onboarding milestones and celebrates achievements. By providing personalized tips and progress updates, this feature motivates users and ensures a smooth transition toward mastering all aspects of FixGuardian.

Requirements

Milestone Progress Dashboard

"As a property manager, I want to see a visual representation of my onboarding milestones so that I can easily track my progress and stay motivated throughout the onboarding process."

Description

Create a centralized dashboard that visually displays the user's onboarding milestones, progress updates, and overall success trajectory. This dashboard will integrate seamlessly with FixGuardian, offering real-time visual feedback on completed tasks, upcoming milestones, and overall progress indicators to keep users informed and motivated.

Acceptance Criteria

Visual Onboarding Milestones

Given a logged-in property manager on the dashboard, when the onboarding process starts, then the dashboard must clearly display all key milestones with progress bars and icons.

Real-Time Progress Updates

Given the completion of a milestone task, when the user refreshes the dashboard, then the new progress must be immediately reflected across all relevant sections.

Integration with FixGuardian Core

Given the FixGuardian system environment, when the dashboard loads, then it must seamlessly integrate with core functions to display real-time onboarding progress data.

Upcoming Milestones Indicator

Given a set of scheduled upcoming tasks, when the user reviews the dashboard, then upcoming milestones should be prominently indicated with alerts and tooltips.

User Success Celebrations

Given the achievement of a significant milestone, when the milestone is completed, then the dashboard should display a personalized congratulatory message and tips for the next steps.

Personalized Achievement Tips

"As a property manager, I want to receive personalized tips based on my progress so that I can overcome onboarding challenges and fully leverage the platform's capabilities."

Description

Develop a module that provides users with customized tips and actionable insights based on their onboarding progress. This feature will analyze user activity and milestones to generate targeted recommendations, helping users overcome onboarding challenges and maximize their use of FixGuardian.

Acceptance Criteria

Onboarding Milestone Reached

Given the user has completed a key onboarding milestone, when the system processes their progress, then it should generate and display personalized achievement tips that are relevant to the milestone reached.

User Activity Analysis Trigger

Given the system continually analyzes user activities, when a significant activity pattern is detected, then it should automatically generate actionable tips that align with current usage trends.

Feedback-Triggered Recommendations

Given the system collects explicit feedback from the user, when an indication of confusion or difficulty is received, then it should provide targeted tips and recommendations to address the user’s specific challenge.

Engagement with Achievement Tips

Given that personalized achievement tips are displayed, when the user interacts with or clicks on a tip, then the system should record this engagement for further analysis and improvement of recommendation quality.

Data-Driven Tip Accuracy

Given the AI-driven model processes both user onboarding data and historical performance metrics, when a tip is generated, then it should accurately reflect the user’s progress and provide a measurable improvement suggestion.

Automated Celebratory Notifications

"As a user, I want to receive automated celebratory notifications when I complete a milestone so that I feel recognized and motivated to continue progressing."

Description

Implement an automated notification system that celebrates user's achievements by sending congratulatory messages and rewards upon the completion of key onboarding milestones. This system will enhance user engagement, create a positive onboarding experience, and reinforce the value of achieving milestones.

Acceptance Criteria

Milestone Completion Notification

Given a user reaches an onboarding milestone, when the milestone completion is detected, then the system should automatically send a congratulatory notification highlighting the achievement and associated reward details.

Personalized Achievement Messages

Given a user's progress data is available, when the user completes a milestone, then the system must deliver a personalized congratulatory message incorporating the user's name and milestone specifics.

Reward Triggering Verification

Given a user receives a congratulatory notification, when the notification is sent, then the corresponding reward must be added to the user's account and validated by an update in the rewards tracker.

Notification Performance and Timeliness

Given the automated notification system is active, when a milestone is reached, then the notification must be delivered within 5 minutes, and logs should confirm the timely dispatch without delays.

Smart Prediction Engine

Harness advanced machine learning to analyze historical maintenance data and accurately forecast future repair needs. This feature empowers property managers to preemptively address issues, reducing emergency fixes and improving workflow efficiency.

Requirements

Data Integration Preprocessing

"As a property manager, I want my historical maintenance data integrated seamlessly so that the AI can provide precise and actionable repair predictions."

Description

Ensure the Smart Prediction Engine automatically retrieves and standardizes historical maintenance data from various property management systems. This integration facilitates clean and unified data input for the AI engine, streamlining model training and enabling accurate future repair predictions across diverse data sources.

Acceptance Criteria

Historical Data Extraction

Given that the system has access to various historical maintenance data sources, when the integration process is initiated, then it automatically retrieves all available maintenance data from these sources without manual intervention.

Data Standardization

Given the extracted maintenance data, when the preprocessing module runs, then all fields are standardized according to the defined formats and mapping rules to ensure consistency across datasets.

Error Handling and Logging

Given that discrepancies or errors may occur during data retrieval or standardization, when an error is encountered, then the system logs detailed error information and triggers an alert for immediate review.

Performance Benchmarking

Given a large volume of historical maintenance data, when the integration and preprocessing processes execute, then the complete workflow should finish within the acceptable performance benchmark (e.g., under 5 minutes for a typical dataset size).

Data Consistency Verification

Given the standardized data from multiple systems, when the dataset is integrated, then consistency checks must validate that data fields match predefined integrity rules and duplicate entries are flagged for review.

AI Model Training and Tuning

"As a property manager, I want the system to continually learn from past trends so that I can proactively schedule repairs and reduce emergency maintenance costs."

Description

Develop robust machine learning models that are trained on historical and real-time data and periodically tuned to improve prediction accuracy. This requirement focuses on implementing advanced algorithms and iterative refinement processes to ensure the Smart Prediction Engine adapts to evolving trends and provides reliable forecasts for maintenance needs.

Acceptance Criteria

Initial Model Training with Historical Data

Given a dataset with historical maintenance records, when the training algorithm runs, then the model should achieve a minimum accuracy of 80% on the validation set and log relevant performance metrics.

Incorporation of Real-Time Data

Given access to live maintenance updates, when the model ingests new data, then it should update its predictions within a maximum latency of 60 seconds and reflect changes in the prediction dashboard.

Regular Model Tuning Process

Given a scheduled tuning interval, when performance analytics are collected, then the system must automatically tune the model to yield at least a 5% improvement in prediction accuracy compared to the previous version.

Error Handling and Rollback Mechanism

Given a drop in model performance post-tuning, when the system detects errors, then it must automatically rollback to the last stable version within 2 minutes and generate an incident report.

Integration Verification with Smart Prediction Engine

Given a query from the Smart Prediction Engine, when the model processes the request, then responses should be delivered with consistent accuracy and within 2 seconds for at least 95% of requests.

Predictive Notification System

"As a property manager, I want to receive proactive alerts based on predictive analysis so that I can address potential maintenance issues before they become emergencies."

Description

Build a notification system that leverages AI outputs to provide timely alerts and actionable insights. This system will communicate predicted maintenance needs through multiple channels and integrate with scheduling tools, ensuring property managers are promptly informed of potential issues before they escalate into critical problems.

Acceptance Criteria

Timely Notification Delivery

Given an upcoming maintenance need identified by AI, When the system processes the prediction, Then send the notification via the selected channel within 5 minutes.

Multi-Channel Alert Distribution

Given a predicted maintenance event, When the system triggers alerts, Then the notifications must be dispatched via email, SMS, and in-app notifications concurrently.

Integration with Scheduling Tools

Given a maintenance alert, When the property manager receives it, Then the system must provide actionable links that integrate directly with scheduling functionality within the platform.

Actionable Insight Display

Given a maintenance notification, When the property manager views it, Then the alert must display concise insights and recommended next steps to facilitate prompt decision-making.

User Preference Customization

Given multiple communication channels, When a property manager sets their notification preferences, Then the system should deliver alerts only through the preferred channels specified.

User Feedback Loop Integration

"As a property manager, I want to provide feedback on the predictive alerts so that the system can continuously refine its forecasts and better suit my maintenance scheduling needs."

Description

Implement a mechanism to gather and analyze user feedback regarding the accuracy and timeliness of maintenance predictions. This will allow continuous improvement of the AI model by incorporating real-world performance insights and adjusting predictions accordingly, thereby enhancing overall user satisfaction and system effectiveness.

Acceptance Criteria

RealTime User Feedback Capture

Given a property manager is reviewing AI-driven maintenance predictions, when they view the prediction interface, then they should be able to quickly submit feedback on prediction accuracy and timeliness.

Scheduled Feedback Review

Given that feedback entries accumulate over time, when a scheduled review cycle is executed, then the system must automatically compile, analyze, and categorize the feedback for insights.

Feedback-Driven Model Update

Given the system identifies recurring feedback trends, when critical feedback patterns are verified, then the AI prediction model should trigger a parameter adjustment process.

Feedback Notification

Given that user feedback is submitted and assessed, when the analysis identifies high severity issues affecting prediction accuracy, then an immediate notification should be sent to the property manager.

Feedback History Access

Given a property manager is logged into the system, when accessing the feedback module, then they should be presented with a comprehensive history of submitted feedback, including analysis trends.

Forecast Dashboard

Provides an intuitive, real-time visual interface that displays upcoming maintenance trends and predicted repair events. The dashboard helps managers quickly interpret data, making it easier to schedule proactive interventions and optimize resource allocation.

Requirements

Real-Time Data Refresh

"As a property manager, I want to see real-time data updates on maintenance events so that I can proactively address potential issues before they escalate."

Description

The Forecast Dashboard must automatically update and display the latest maintenance trends and predicted repair events without requiring manual refresh. This capability integrates live data streams, ensuring that property managers receive up-to-date information for timely decision-making. It enhances operational efficiency by reducing latency in data presentation and facilitating prompt intervention.

Acceptance Criteria

Initial Dashboard Load

Given the Forecast Dashboard is accessed, when the page loads, then the system should fetch and display the latest maintenance trends and predicted repair events from live data streams without requiring a manual refresh.

Real-Time Data Update Notification

Given the system receives an update from the live data stream, when new maintenance trend data is available, then the dashboard should automatically refresh the data display within 2 seconds.

Error Handling on Data Fetch

Given a failure in fetching live data, when the data stream is interrupted, then the dashboard should display an appropriate error message and initiate an automatic retry within 5 seconds.

Continuous Monitoring

Given that the Forecast Dashboard remains open, when live data updates occur over a period exceeding 10 minutes, then the dashboard should continuously poll for data and update the display seamlessly without user intervention.

Predictive Maintenance AI Integration

"As a property manager, I want AI-powered predictions of upcoming maintenance tasks so that I can prepare and schedule interventions to minimize downtime and unexpected repairs."

Description

This requirement integrates AI-driven predictive analytics within the Forecast Dashboard to analyze historical and real-time data for forecasting repair events. It leverages machine learning models to deliver actionable insights, enabling property managers to anticipate maintenance issues and strategically allocate resources for preventative measures.

Acceptance Criteria

Real-time Prediction Update

Given historical and real-time data inputs, when the AI processes new data, then the Forecast Dashboard shall update maintenance predictions within 10 seconds with at least 90% accuracy.

User-Friendly Visual Alerts

Given a predicted maintenance event, when the AI identifies risk thresholds, then the dashboard must display a clear visual alert detailing predicted time, severity, and potential impact.

Resource Allocation Insight

Given forecasted data trends, when managers review the dashboard, then it should provide actionable recommendations for resource allocation based on predicted repair events.

Historical Data Integration

Given access to historical maintenance records, when the AI integrates this data into the model, then predictions must reflect historical trends in forecasting future repair incidents.

Proactive Intervention Recommendations

Given an upcoming maintenance event prediction, when the AI analysis determines potential risks, then the system should output a set of preventative measures with a confidence score above the defined threshold.

Customizable Dashboard Filters

"As a property manager, I want to customize the dashboard filters so that I can focus on the data that is most pertinent to my operational needs and priorities."

Description

The requirement allows users to personalize the Forecast Dashboard by applying filters based on parameters such as property location, maintenance type, and specific time ranges. By providing tailored views, this feature empowers managers to sift through data efficiently, focusing on the most relevant metrics to improve their decision-making and resource allocation.

Acceptance Criteria

Filter by Property Location

Given a dashboard that displays property maintenance tasks, when a manager selects a specific property location filter, then only tasks associated with that location are displayed.

Filter by Maintenance Type

Given a dashboard with various maintenance types, when a user selects a maintenance type filter, then only tasks related to the chosen maintenance type are shown.

Filter by Time Ranges

Given a time range filter on the dashboard, when a manager inputs a valid start and end date, then the dashboard displays only the tasks scheduled within that period.

Combination Filters

Given multiple filters available (property location, maintenance type, time range), when a user applies them simultaneously, then the dashboard correctly displays tasks that meet all selected criteria.

Reset Filters

Given a reset filter option on the dashboard, when a manager clicks the reset button, then all filters are cleared and the default view is restored.

Proactive Intervention Planner

Leverages prediction insights to generate actionable maintenance plans, allowing property managers to schedule timely repairs before issues escalate. This feature enhances operational planning, minimizes downtime, and protects property value.

Requirements

Predictive Analytics Integration

"As a property manager aged 30-55, I want the system to analyze maintenance data and predict issues before they occur so that I can schedule repairs proactively and minimize operational downtime."

Description

The system shall integrate with the AI predictive analytics engine to analyze property maintenance data and forecast potential issues. It will continuously monitor historical trends and real-time data to predict maintenance requirements, auto-populating the intervention planner and issuing alerts to property managers to schedule timely repairs, thereby reducing reactive fixes and lowering maintenance costs.

Acceptance Criteria

Maintenance Prediction Trigger

Given the system has access to both historical and real-time data, when the predictive analytics engine identifies a potential maintenance issue, then the system must auto-populate the intervention planner with recommended actions and notify the property manager.

Proactive Scheduler Population

Given the integration with the AI predictive analytics engine, when a maintenance issue is forecasted, then the system must automatically update the intervention planner with a detailed schedule, including repair tasks and timelines.

Real-Time Trend Analysis

Given a continuous data feed from property sensors and historical trends, when risk thresholds are exceeded, then the system must issue an alert within 5 minutes and update the maintenance plan accordingly.

Cost Reduction Measure

Given the baseline of reactive repairs, when the proactive intervention system is implemented, then there must be at least a 20% reduction in reactive repair incidents and costs within the first operational quarter.

Automated Maintenance Plan Generation

"As a property manager, I want the system to automatically propose detailed maintenance plans derived from predictive insights so that I can efficiently schedule tasks and minimize the risk of unexpected property issues."

Description

The system shall automatically generate actionable maintenance plans based on AI-driven predictions and maintenance priorities. It will format these plans in an integrated calendar view, detailing recommended repair dates, necessary tasks, and resource allocation to streamline scheduling and protect property value.

Acceptance Criteria

Calendar View Generation

Given valid AI predictions and maintenance priorities, when the system generates a maintenance plan, then the calendar view must display recommended repair dates, necessary tasks, and allocated resources.

Actionable Maintenance Plan Accuracy

Given historical maintenance data and AI-driven insights, when the system generates the maintenance plan, then each plan must accurately reflect predicted repair dates and align with established maintenance priorities.

User Dashboard Integration

Given a generated maintenance plan, when a property manager accesses the dashboard, then the integrated calendar view should display the plan correctly and allow for scheduling modifications.

Proactive Intervention Trigger

Given continuous monitoring of property conditions, when the AI predicts potential issues, then the system should automatically update the maintenance plan with proactive tasks to address issues before escalation.

Interactive Proactive Planning Dashboard

"As a property manager, I want to see an interactive dashboard of predicted maintenance tasks and scheduled interventions so that I can easily manage priorities, oversee progress, and ensure timely repairs."

Description

The system shall offer an interactive dashboard that visualizes predictive insights, upcoming maintenance schedules, and real-time status updates. The dashboard will provide filters, detailed reporting options, and actionable recommendations, enabling property managers to customize views, monitor maintenance tasks, and make informed decisions to enhance operational efficiency.

Acceptance Criteria

Dashboard Initialization

Given a property manager logs into FixGuardian, when the Interactive Proactive Planning Dashboard loads, then the dashboard should display all predictive insights, upcoming maintenance schedules, and real-time status updates accurately.

Filter Customization Functionality

Given the interactive dashboard is active, when the manager applies specific filters such as date ranges, severity levels, or task categories, then the dashboard should update in real-time to show only the relevant maintenance tasks and insights.

Real-Time Updates

Given ongoing maintenance task updates, when changes occur (like task completion or new maintenance schedules), then the dashboard must reflect these updates within 5 seconds of the event.

Interactive Reporting

Given the property manager selects the reporting feature, when generating a maintenance report, then the report should include detailed custom metrics, applied filters, and historical performance data for comprehensive analysis.

Actionable Recommendations Integration

Given predictive insights have been analyzed by the AI, when maintenance tasks are presented on the dashboard, then each task should include actionable recommendations with estimated cost and time savings details.

Historical Trend Reporter

Offers detailed reports on maintenance trends derived from historical and predictive data analysis. By highlighting recurring issues and long-term patterns, this feature enables managers to refine their maintenance strategies, ensuring cost-effective improvements and sustained tenant satisfaction.

Requirements

Historical Data Ingestion

"As a property manager, I want the system to automatically import all historical maintenance records so that I can identify long-term trends without manual data entry."

Description

Implement robust data ingestion pipelines that extract historical maintenance records from various data sources and transform them into a consistent format for analysis. This involves integrating with external databases and property management systems to ensure comprehensive coverage of data, enabling detailed trend analysis. It should efficiently process large datasets while ensuring data quality and integrity.

Acceptance Criteria

Database Connectivity Verification

Given the historical data ingestion pipeline initiates, when the system attempts to connect to external databases, then a successful connection must be established and logged as 'Connected'.

Data Transformation Accuracy

Given historical maintenance data is extracted, when the data transformation process is executed, then the output must conform to the predefined schema with guaranteed consistency and formatting.

Bulk Data Processing Efficiency

Given a large volume of historical data, when the ingestion pipeline processes the data, then it should complete within configured performance thresholds and without causing system bottlenecks.

Data Quality and Integrity Check

Given the data ingestion completes, when the system performs quality checks, then it must detect and report any anomalies, missing records, or corrupt data, ensuring full data integrity.

Integration with Property Management Systems

Given the pipeline interacts with external property management systems, when it retrieves data via API, then it must capture a complete and accurate historical dataset without any data loss.

Trend Analysis Engine

"As a property manager, I want the system to analyze maintenance history and predict future issues so that I can schedule preventative maintenance and reduce costs."

Description

Develop an AI-driven trend analysis engine that processes historical maintenance data to identify recurring issues, seasonal patterns, and long-term trends. This engine should leverage predictive analytics to continuously monitor data streams and generate insights, which will inform proactive maintenance scheduling and cost-reduction strategies. It must be scalable and compatible with the existing infrastructure.

Acceptance Criteria

Identifying Recurring Issues

Given historical maintenance records, when the Trend Analysis Engine processes the data, then it should identify recurring issues with at least 90% accuracy.

Seasonal Patterns Recognition

Given seasonal variations in maintenance data, when the engine processes the records, then it should detect seasonal patterns with a success rate of 85%.

Predictive Analytics Integration

Given a continuous stream of maintenance data, when the engine leverages predictive analytics, then it should generate actionable insights that improve proactive scheduling efficiency by at least 15%.

Scalability and Performance

Given high-volume maintenance data on the existing infrastructure, when the engine performs analysis, then it must maintain response times under 2 seconds without performance degradation.

Trend Report Dashboard

"As a property manager, I want to view customizable reports on historical maintenance trends so that I can make informed decisions to optimize maintenance strategies."

Description

Create a comprehensive dashboard that visualizes historical and predictive maintenance data. The dashboard should offer customizable filters, intuitive graphs, and detailed reports, enabling managers to drill down into specific maintenance issues and time periods. It must integrate seamlessly with the existing property management interface and provide export options for further analysis.

Acceptance Criteria

Interactive Dashboard Visualization

Given a property manager is logged in, When the Trend Report Dashboard loads, Then intuitive graphs visualizing historical and predictive data are displayed, ensuring clear visual representation of maintenance trends.

Customizable Filters for Trend Reports

Given a user accesses the dashboard, When they apply date ranges and issue-specific filters, Then the dashboard updates dynamically to show only the relevant trend data, ensuring accurate filtering.

Data Drill-down Capability

Given a property manager views a specific trend on the dashboard, When they click on a graph or a segment of a report, Then a detailed breakdown of maintenance issues and time periods is presented, facilitating in-depth analysis.

Export Functionality for Report Data

Given a property manager needs offline analysis, When they trigger the export option, Then the system generates a downloadable CSV or PDF file containing the filtered historical and predictive maintenance data, ensuring complete data export.

Maintenance Alert Automation

"As a property manager, I want to receive timely alerts when the trend analysis detects anomalies in maintenance data so that I can promptly address potential issues."

Description

Integrate an alert and notification system that leverages the trend analysis engine to notify property managers of emerging issues or unusual data trends. This system should provide real-time alerts via email and mobile notifications, allowing for timely intervention and scheduling adjustments. It must accurately target alerts based on defined thresholds and historical patterns.

Acceptance Criteria

Real-Time Alert Delivery

Given a property manager is logged into FixGuardian, when a maintenance anomaly is detected by the trend analysis engine, then an email alert with detailed information is automatically sent in real-time.

Mobile Notification Integration

Given the property manager has enabled mobile notifications, when an emerging issue based on historical patterns is identified, then a push notification is triggered on the mobile device with relevant maintenance details.

Threshold-Based Alert Customization

Given the alert thresholds are set by the property manager, when maintenance parameters exceed these predefined limits, then the system sends a customized alert that aligns with the specific trigger values.

Alert Accuracy and Historical Pattern Matching

Given the system processes historical and predictive maintenance data, when an alert is generated, then the alert’s accuracy is validated against historical trend similarities with at least a 90% match to ensure reliable notifications.

Product Details

Vision & Mission

Problem & Solution

Details & Audience

User Personas

Efficient Emily

Background

Needs & Pain Points

Needs

Pain Points

Psychographics

Channels

Predictive Paul

Background

Needs & Pain Points

Needs

Pain Points

Psychographics

Channels

Techie Tanya

Background

Needs & Pain Points

Needs

Pain Points

Psychographics

Channels

Product Features

Dynamic Task Assignment

Requirements

Data Integration Engine

Description

Acceptance Criteria

Real-Time Priority Optimization

Description

Acceptance Criteria

Manual Override and Customization

Description

Acceptance Criteria

Predictive Prioritization

Requirements

Maintenance Issue Forecasting

Description

Acceptance Criteria

Automated Task Scheduling

Description

Acceptance Criteria

User Notification and Alert System

Description

Acceptance Criteria

Dashboard Analytics for Prioritization

Description

Acceptance Criteria

Adaptive Rescheduling

Requirements

Real-Time Condition Monitoring

Description

Acceptance Criteria

Dynamic Task Adjustment Algorithm

Description

Acceptance Criteria

Comprehensive Notification & Alert System

Description

Acceptance Criteria

Real-Time Alerts

Requirements

Automated Deviation Detection

Description

Acceptance Criteria

Instant Push Notifications

Description

Acceptance Criteria

Multi-Channel Alert Distribution

Description

Acceptance Criteria

Alert Customization and Threshold Settings

Description

Acceptance Criteria

Alert Acknowledgment and Escalation

Description