EcoFlow

Surge Sentry

Real-time anomaly detection that monitors waste inflow patterns and triggers immediate alerts. Surge Sentry empowers urban planners to proactively address waste surges, minimizing operational disruptions and enhancing waste management efficiency.

Requirements

Dynamic Anomaly Detection Algorithm

"As a municipal decision-maker, I want an intelligent system to detect anomalies in waste inflows so that I can address potential surges before they escalate into major issues."

Description

Develop an AI-driven algorithm that continuously monitors waste inflow patterns, identifying any deviations from the norm. This capability ensures early detection of waste surges by analyzing historical trends and real-time data. It integrates within EcoFlow’s predictive analytics framework to provide actionable insights that enable proactive management and reduce operational disruptions while supporting the push towards sustainable urban waste management.

Acceptance Criteria

Real-time Anomaly Monitoring

Given continuous waste inflow data, when the algorithm processes the real-time stream, then any deviation from the predicted normal range exceeding 10% triggers an alert.

Historical Data Analysis

Given historical waste inflow data, when the algorithm performs a trend analysis, then it should accurately identify seasonal patterns and outliers exceeding the 95th percentile threshold.

Alert Notification System Integration

Given an anomaly detection event, when the system verifies alert thresholds, then the algorithm must dispatch immediate notifications to designated urban planners with a 95% success rate.

Data Integration with EcoFlow Framework

Given the integration within EcoFlow’s predictive analytics, when the algorithm processes both real-time and historical data, then it should maintain seamless data flow with less than 1-second latency.

Instant Alert Notification System

"As an urban planner, I want to receive instantaneous alerts when anomalies occur so that I can mobilize resources quickly and mitigate potential disruptions."

Description

Implement a real-time alert system that triggers immediate notifications upon detecting anomalies in waste inflow data. This feature should support multi-channel alerts (e.g., SMS, email) and customizable thresholds to ensure that relevant personnel are promptly informed and can take swift corrective action. The integration with Surge Sentry ensures that alerts are precise and actionable, minimizing downtime in waste management operations.

Acceptance Criteria

Real-Time Waste Anomaly Alert

Given waste inflow anomaly is detected by Surge Sentry, when the alert system processes the event, then immediate notifications are sent via SMS and email, ensuring multi-channel delivery within 60 seconds.

Threshold Customization for Waste Management

Given a municipal planner accesses the alert settings, when the threshold is updated, then the new value is saved and applied to all subsequent anomaly detections, ensuring customizable configuration per user preference.

Integration Testing Alert Trigger

Given an anomaly in waste inflow is recorded, when Surge Sentry detects the anomaly, then the alert system receives the event and triggers precise notifications that include all necessary details for swift corrective action, confirming seamless system integration.

Interactive Anomaly Dashboard Interface

"As a municipal decision-maker, I want to visually review waste inflow patterns and anomaly alerts so that I can analyze trends and optimize waste management strategies."

Description

Create an intuitive, user-friendly dashboard that visualizes real-time data on waste inflow and detected anomalies. This interface should provide filtering, drill-down capabilities, and historical data analysis, allowing urban planners to monitor trends, review alert logs, and make informed decisions on waste resource allocation. It seamlessly integrates with EcoFlow’s data analytics backend to ensure consistency and accuracy of displayed information.

Acceptance Criteria

Dashboard Overview Access

Given an authenticated urban planner, when the planner accesses the dashboard, then the dashboard must display real-time waste inflow data along with a summary of detected anomalies.

Data Filtering Functionality

Given a user selects filtering options, when the user applies a filter (by date range, waste type, or anomaly severity), then the dashboard should update to display only the filtered data.

Drill-down Data Analysis

Given a user clicks on a specific anomaly indicator, when the user drills down into the data, then the dashboard should present detailed historical data and contextual information related to that anomaly.

Alert Log Review

Given a waste surge alert is generated, when the user checks the alert log, then the dashboard should list the alert with a timestamp, a brief description, and associated actions in chronological order.

Backend Data Consistency

Given the integration with the EcoFlow analytics backend, when real-time data is received, then the dashboard must accurately reflect backend data with timely updates and consistent information.

Hotspot Mapper

An interactive visualization tool that transforms data into a dynamic map highlighting predicted waste surge zones. Hotspot Mapper enables users to quickly identify problem areas and coordinate targeted interventions for optimized resource allocation.

Requirements

Real-time Data Aggregation

"As an urban planner, I want the map to update in real-time so that I can coordinate timely interventions in high-risk waste zones."

Description

Enable the Hotspot Mapper to aggregate real-time waste data from multiple municipal sources to ensure timely visualization of waste surge trends and accurate hotspot prediction. This integration fortifies data accuracy and provides critical insights for municipal decision-makers.

Acceptance Criteria

Real-time Data Feed Integration

Given a set of municipal data sources, when Hotspot Mapper executes a real-time aggregation, then the system must update the waste surge data within 30 seconds of receiving new input.

Data Accuracy Verification

Given the input from diverse waste data sources, when the data is displayed on Hotspot Mapper, then the aggregated data accuracy must match predefined benchmarks with an error rate below 2%.

Multiple Source Aggregation

Given multiple municipal data feeds, when Hotspot Mapper aggregates the real-time data, then the system must merge and present a unified dataset without conflicts or loss of information.

Scalable Data Throughput

Given high-traffic access scenarios, when real-time data aggregation is performed, then the Hotspot Mapper must maintain a system response time under 1 second for data refresh operations.

Error Handling and Alerts

Given potential interruptions or errors in data feeds, when an error is detected during aggregation, then Hotspot Mapper must log the error, alert the user, and fall back to the most recent correct dataset.

Historical Data Correlation

Given the aggregation of current waste data with historical trends, when differential analysis is performed, then the system should flag anomalies that deviate more than 15% from historical averages.

User Notification on Data Updates

Given significant updates from municipal sources, when the aggregated data reflects a waste surge increase over 20% compared to previous intervals, then Hotspot Mapper must trigger an immediate notification to municipal decision-makers.

AI-Powered Hotspot Prediction

"As a municipal decision-maker, I want AI-driven predictions on waste hotspots so that I can allocate resources efficiently and lower landfill usage."

Description

Implement advanced predictive analytics using AI algorithms on aggregated waste data. The system should forecast potential waste surge hotspots on the interactive map, enabling early detection and efficient resource allocation. This predictive capability enhances proactive urban planning.

Acceptance Criteria

Real-Time Data Ingestion

Given live waste data feeds, when the system receives aggregated data, then it must update the AI prediction model in real-time.

Accurate Hotspot Prediction

Given a set of historical and real-time waste data, when AI algorithms run, then they must predict waste surge hotspots with at least 85% accuracy.

Dynamic Map Visualization Update

Given a new prediction output from the AI model, when the map interface is loaded, then it must display updated hotspot markers indicating potential waste surges.

Proactive Alert Generation

Given identified hotspot areas, when prediction thresholds are exceeded, then the system must trigger alerts to municipal decision-makers within 5 minutes.

User Interaction and Drill-down Analytics

Given an interactive map display, when a user clicks on a hotspot indicator, then the system must provide drill-down analytics and detailed insights for that area.

Interactive Map Interface

"As a city planner, I want an interactive map interface so that I can easily navigate and explore predicted hotspot trends across different regions."

Description

Develop an intuitive and responsive user interface for the Hotspot Mapper, featuring dynamic zoom, pan, and filter functionalities. The interface should allow users to seamlessly explore different geographical areas, view detailed insights, and customize display settings based on data layers, ensuring a user-friendly experience.

Acceptance Criteria

Dynamic Zoom Functionality

Given the user is interacting with the map, when they dynamically zoom in or out, then the map should smoothly transition and update displayed data layers with minimal latency.

Pan Navigation Experience

Given the user is viewing a map area, when they pan the map, then the view should smoothly shift to the new area while maintaining full data synchronization.

Filter Customization

Given the map displays various data layers, when the user applies filters to select specific waste surge zones, then only the selected layers should display with accurate, updated insights.

Responsive Interface Rendering

Given the application is accessed from multiple devices, when it is loaded on mobile, tablet, or desktop, then the interactive map interface should render correctly with the appropriate dynamic UI adjustments.

Detailed Insight Viewing

Given the user selects a data point on the map, when they click on it, then a detailed insight popup should be displayed containing relevant information about the predicted waste surge zone.

Customizable Data Filters

"As a waste management official, I want customizable filters so that I can focus on specific data segments relevant to my city's needs."

Description

Create advanced filtering options that allow users to select and analyze specific waste categories, timeframes, and geographical zones. These filters should provide detailed insights, empowering users to drill down into the data and make informed decisions tailored to specific waste management challenges.

Acceptance Criteria

Filter Initialization Use Case

Given an urban planner accesses the system, when the Customizable Data Filters page loads, then the platform displays all filter options (waste categories, timeframes, geographical zones) accurately and in a user-friendly format.

Advanced Filter Application

Given the filter options on the interface, when a user selects specific waste categories, timeframes, and geographical zones, then the system must correctly filter and display detailed insights relevant to the chosen parameters.

Filter Persistence Across Sessions

Given that a user customizes their filter settings, when they log out and log back in, then the system should recall and reapply the previously selected filters if the user has opted to save their configuration.

Performance Optimization in Filtered Data Visualization

Given the application of multiple filters, when the system processes the filter request, then the response time must be under 3 seconds to ensure a seamless user experience.

Real-Time Data Update in Filtered View

Given that data is continuously updated, when filters are applied, then the visualization must reflect new data within 1 minute to maintain real-time accuracy.

Resource Coordination Module

"As a municipal coordinator, I want a resource coordination module so that I can effectively assign teams to high-risk zones and track the progress of interventions."

Description

Integrate a module that enables coordination among various departments by linking predicted hotspots with available waste management resources. This feature should facilitate the assignment of tasks, track intervention progress, and optimize overall resource allocation, thereby reducing waste overflow.

Acceptance Criteria

Task Assignment Efficiency

Given a predicted hotspot is selected in the Hotspot Mapper, when the Resource Coordination Module is activated, then available resources from various departments must be displayed and task assignment should complete within 2 minutes.

Interdepartmental Collaboration

Given a waste management intervention is required, when the module is used, then it should enable coordination between departments by linking available resources to the hotspot and confirm assignment across all selected departments.

Real-Time Intervention Tracking

Given an assigned intervention task, when progress is updated, then the module must reflect real-time updates and send automated notifications to all relevant departments.

Optimized Resource Allocation

Given multiple available resources, when the module analyzes the predicted hotspot data, then it should suggest the optimal resource allocation based on historical data to minimize waste overflow.

User Feedback Integration

Given user feedback is provided on task effectiveness, when feedback is submitted, then the system should log the input and display aggregated results to inform future resource allocation decisions.

Adaptive Scheduler

Leveraging predictive analytics to automatically adjust collection timings and routing, Adaptive Scheduler ensures efficient waste management during surge events. This feature minimizes fuel consumption and manpower expenses while maximizing operational effectiveness.

Requirements

Dynamic Collection Routing

"As an urban planner, I want the system to automatically optimize waste collection routes so that I can reduce fuel use and improve overall operational efficiency."

Description

This requirement integrates an advanced routing mechanism that leverages AI-driven predictive analytics to dynamically adjust waste collection routes. It optimizes paths and minimizes travel time and fuel consumption during surge events, ensuring that resources are allocated efficiently and urban areas experience timely waste removal.

Acceptance Criteria

Surge Event Adaptive Routing

Given a surge event is detected by AI analytics, when the system recalculates the collection route, then the new route should reduce overall travel time by at least 15% while ensuring all scheduled stops are maintained.

Fuel Consumption Efficiency

Given a dynamically adjusted collection route is calculated, when the system compares fuel usage metrics, then the optimized route should achieve an average fuel reduction of at least 10% compared to the baseline route.

Real-Time Route Adjustment Alerts

Given real-time operational changes, when the system updates the collection route, then notifications must be dispatched to operators within 2 minutes detailing the changes.

Automated Surge Adjustments

"As an operations manager, I want the system to automatically modify collection timings during surge events so that waste is managed effectively without additional cost or delay."

Description

This requirement provides the capability for the scheduler to automatically adjust collection timings during high-demand periods. It uses predictive analytics to detect surge events in real-time and reassigns collection schedules accordingly, reducing manpower expenses and preventing service delays.

Acceptance Criteria

Real-Time Surge Detection Activation

Given the predictive analytics detects a surge event in real-time, when surge event data is received, then the system must trigger an immediate alert within 5 minutes.

Automatic Collection Reassignment

Given a confirmed surge event, when the system processes the event, then it should automatically adjust collection timings and reassign routes to minimize service delays by at least 20%.

Minimized Resource Allocation During Surges

Given a surge event is detected, when the system reassigns collection schedules, then fuel consumption and manpower expenses must decrease by a minimum of 15% compared to normal operations.

User Notification on Schedule Adjustment

Given that a surge event has been processed, when the schedule is adjusted, then municipal decision-makers should receive a notification within 2 minutes detailing the new schedule.

Real-time Monitoring Dashboard

"As a municipal decision-maker, I want to see real-time insights into our waste collection operations so that I can quickly identify issues and ensure optimal performance."

Description

This requirement develops a comprehensive dashboard that displays real-time data on waste collection performance and adaptive scheduler adjustments. The dashboard enables stakeholders to monitor key performance indicators, track efficiency gains, and swiftly respond to any anomalies in collection operations. Integration with AI analytics ensures up-to-date insights for informed decision-making.

Acceptance Criteria

Dashboard Integration and Data Refresh

Given the dashboard is accessed by stakeholders, when real-time data is updated via integration with AI analytics, then all key performance indicators must refresh within 10 seconds with accurate data.

Anomaly Detection Alerting

Given a deviation from standard waste collection performance is detected, when the issue crosses predefined thresholds, then the dashboard must automatically display detailed alerts and suggested corrective actions.

Adaptive Scheduler Display

Given the Adaptive Scheduler updates collection timings and routes based on predictive analytics, when changes occur, then the dashboard must accurately reflect the latest schedule adjustments and related performance metrics.

Trend Analyzer

A robust analytical tool that aggregates historical waste data with predictive insights to reveal long-term trends. Trend Analyzer supports strategic planning by revealing patterns over time, enabling data-driven decisions and policy improvements.

Requirements

Historical Data Aggregation

"As an urban planner, I want aggregated historical data so that I can identify past trends and inform future policy decisions."

Description

Implement a module that gathers and processes historical waste management data, combining raw figures from various sources into a unified dataset. This functionality will create a comprehensive database that supports the Trend Analyzer in uncovering long-term trends and correlating historical waste patterns with municipal changes, thereby enabling strategic insights.

Acceptance Criteria

Data Collection at Import

Given the module is initiated for historical data aggregation, when it connects to all approved source systems, then it should collect and merge data from each source within the expected time window.

Data Normalization Process

Given raw historical data from multiple sources, when processed by the module, then it must be normalized to a unified format that ensures consistency across the dataset.

Data Integrity Verification

Given the complete aggregated dataset, when the aggregation process finishes, then the dataset should be verified to ensure completeness and consistency, with no missing or duplicated records.

Performance Benchmarking

Given a large volume of historical waste data, when the module executes the aggregation process, then it should complete within the specified performance threshold (e.g., processing 5 years of data within 10 minutes).

Error Handling and Logging

Given any retrieval or processing errors during data aggregation, when an error occurs, then the module must log detailed error messages and allow the process to recover gracefully without affecting the overall system.

Predictive Trend Modeling

"As a municipal decision-maker, I want predictive modeling capabilities so that I can plan resource allocation proactively and improve waste management strategies."

Description

Develop and integrate machine learning models that utilize both historical and current data to forecast future waste generation trends. This capability will provide predictive insights that allow municipal decision-makers to anticipate resource needs and adjust policies effectively for sustainable waste management. The solution should seamlessly integrate with existing data systems to provide timely and accurate predictions.

Acceptance Criteria

Real-time Data Integration

Given historical and current waste data is available, When the predictive model ingests the data, Then the system should seamlessly integrate these data sources in real-time.

Accurate Forecasting

Given a dataset with known historical waste trends, When the predictive model generates forecasts for future waste generation, Then the forecast accuracy should meet or exceed 85%.

Performance and Scalability

Given an increase in the volume of data, When the model processes the data for predictions, Then it should deliver results within 2 seconds under peak loads.

Error Handling and Alerts

Given unexpected data anomalies or missing fields, When the predictive model encounters such issues, Then it should trigger an error alert with meaningful diagnostics for user intervention.

Seamless Integration with Existing Systems

Given the existing data systems integrated within EcoFlow, When the predictive modeling module operates, Then it should exchange data without disruptions or data losses.

Interactive Trend Visualization

"As a city policy maker, I want an interactive visualization dashboard so that I can quickly grasp data trends and make informed decisions based on clear and accessible representations."

Description

Create an interactive dashboard that presents both historical and predictive data insights using dynamic charts, graphs, and heat maps. This visualization tool will be integrated into the EcoFlow ecosystem, offering decision-makers an intuitive way to interpret complex data, explore trends over time, and interact with the results for deeper insights. The design should emphasize clarity, responsiveness, and ease of navigation.

Acceptance Criteria

Real-Time Data Update

Given that a user is interacting with the interactive trend visualization dashboard, when new data is available, then the dashboard updates the charts, graphs, and heat maps dynamically within 5 seconds of data changes.

User Navigation Experience

Given the interactive visualization dashboard, when the user clicks on any dynamic element, then the system should provide seamless navigation to detail views, with tooltips and drill-down functionalities responding without performance delays.

Responsive Dashboard Layout

Given that the dashboard is accessed on various devices, when the user accesses the dashboard on different screen sizes (desktop, tablet, mobile), then the layout automatically adjusts to maintain clarity, usability, and intuitive interaction.

Data Accuracy and Clarity

Given that the dashboard displays both historical and predictive data, when the interactive charts and graphs are rendered, then each element must show correct, precise, and up-to-date information without discrepancies.

Interactive Filtering and Customization

Given that the dashboard supports data exploration, when a user applies filters such as date range, region, or waste type, then the interactive elements refresh instantaneously to reflect the selected parameters accurately.

FillWatch

Leverages smart sensor data to continuously monitor waste bin fill levels in real-time, sending instant alerts when bins approach capacity. This feature helps urban planners preemptively address overflow issues, ensuring timely collections and optimized waste management operations.

Requirements

Real-Time Sensor Monitoring

"As an urban planner, I want real-time updates on waste bin statuses so that I can proactively manage collections and avoid overflow."

Description

Provides continuous updates on waste bin fill levels by processing data from smart sensors deployed in bins. Integrates with EcoFlow's central dashboard to visualize real-time metrics and trigger automatic analyses. This real-time data flow enhances the operational efficiency of city waste management by ensuring immediate alerts and informed decision-making.

Acceptance Criteria

Real-Time Dashboard Update

Given sensor updates are received, when data is processed, then the dashboard displays updated metrics with a latency of less than 5 seconds.

Automatic Overflow Alert

Given a bin's fill level exceeds 90%, when the sensor data is received, then an instant alert is triggered on the dashboard notifying the urban planner.

Data Integration Consistency

Given multiple sensor inputs are fed into the system, when data is integrated into EcoFlow's central dashboard, then the displayed information must reflect at least 99% accuracy across all sensor data.

Sensor Communication Reliability

Given sensors operating under varied network conditions, when sensor data is transmitted, then the system consistently receives and processes the data without error.

Real-Time Analytical Trigger

Given live sensor data feeds, when thresholds for analysis are met, then the system automatically triggers analysis and provides actionable insights in real-time.

Instant Overflow Alerts

"As a city waste manager, I want to receive instant alerts when bins are nearly full so that I can swiftly dispatch collection teams."

Description

Implements a robust alert system that sends notifications to urban planners when bins near or exceed fill capacity. The alerts will be delivered in real-time across multiple channels to ensure timely response and effective waste management. This system integrates seamlessly with the EcoFlow platform, enabling immediate action to prevent overflows.

Acceptance Criteria

Real-Time Overflow Alert Notification

Given a waste bin's fill level reaches 90% of its capacity, when the sensor data is received, then the system shall send an immediate alert notification to urban planners via SMS, email, and mobile push notification.

Accurate Threshold Monitoring

Given a waste bin in operation, when sensor reports fill levels, then the system shall monitor and update the fill levels with an accuracy tolerance of ±5%.

Multi-Channel Notification Delivery

Given an overflow event, when the alert is triggered, then notifications must be delivered through at least three channels: email, SMS, and in-app alerts.

Alert Integration with EcoFlow Platform

Given an overflow alert, when the notification is sent, then the alert should be logged on the EcoFlow dashboard with a timestamp, sensor ID, and bin location for traceability.

User Acknowledgement and Response Tracking

Given an alert notification is sent, when an urban planner acknowledges the alert via the EcoFlow interface, then the system shall record the acknowledgement time and update the alert status accordingly.

Historical Data Analytics

"As an urban planner, I want to view historical trends of waste accumulation so that I can optimize collection routes and schedules."

Description

Collects and analyzes historical sensor data to provide trend analysis and predictive insights for future waste accumulation patterns. This requirement integrates with the main EcoFlow platform to help urban planners forecast bin filling rates, optimize collection schedules, and strategically allocate resources for improved sustainability.

Acceptance Criteria

Data Ingestion

Given a dataset of historical sensor data from the past 12 months, when the data is ingested into the system, then all records must be stored and indexed with no data loss.

Data Integrity Validation

Given the migrated historical sensor data, when a data validation process is executed, then the system must verify 100% data integrity with consistency checks against source records.

Trend Analysis Execution

Given a complete dataset of historical sensor data, when trend analysis is conducted, then the system must generate predictive reports with at least 80% accuracy in forecasting waste accumulation patterns.

Predictive Insight Generation

Given processed historical data, when predictive algorithms are applied, then the resulting forecasts of waste accumulation rates should have an error margin of no more than 5% when compared to actual outcomes.

Dashboard Visualization

Given the results from historical data analysis, when the data is displayed on the EcoFlow dashboard, then visualizations must update in near real-time and meet specified UI guidelines.

Sensor Health Management

"As an operations manager, I want the sensor system to self-check and alert me of maintenance needs so that data accuracy is continuously upheld."

Description

Ensures that smart sensors maintain accurate readings by automating regular calibration and maintenance checks. This requirement enhances system reliability by detecting sensor malfunctions early and prompting maintenance activities. It integrates into the EcoFlow platform through automated diagnostics and alerts.

Acceptance Criteria

Regular Calibration Workflow

Given a sensor that has not been calibrated within the scheduled timeframe, when the system initiates the calibration process, then the sensor should complete the calibration automatically and log the event.

Sensor Malfunction Detection

Given sensor data, when readings deviate beyond the acceptable threshold, then the system must flag the sensor as malfunctioning and trigger an automated alert.

Automated Maintenance Notification

Given that sensor diagnostics indicate a potential issue, when the maintenance threshold is met, then the system should notify the maintenance team immediately via automated alerts.

Dashboard Integration Verification

Given sensors pass their calibration and diagnostic tests, when data is transmitted to the EcoFlow dashboard, then the dashboard must display real-time sensor health status and calibration logs.

Data Accuracy Verification

Given calibrated sensor readings, when compared against manual or secondary sensor measurements, then the deviation must not exceed defined acceptable limits.

Dashboards and Analytics Integration

"As a municipal decision-maker, I want to access a dashboard that consolidates real-time and historical sensor data so that I can quickly understand and act upon waste management metrics."

Description

Offers a comprehensive dashboard within EcoFlow that visualizes real-time sensor data, alerts, and historical trends through clear and intuitive interfaces. This feature facilitates decision-making by providing actionable insights at a glance, enabling urban planners and waste management teams to monitor system performance effectively.

Acceptance Criteria

Real-Time Data Visualization

Given the dashboard is loaded, when sensor data is updated, then the dashboard reflects the changes within 5 seconds.

Alert System for Approaching Capacity

Given a bin sensor reading exceeds 80% of capacity, when data is analyzed, then an instant alert is generated and displayed on the dashboard.

Historical Trends Analytics

Given the user selects the historical data view, when querying data, then a graph displaying at least the past 30 days of data in consistent intervals is rendered.

User Interaction with Dashboard Widgets

Given the user interacts with any dashboard widget, when an action (click or hover) is performed, then detailed information related to that widget is displayed within 2 seconds.

Seamless Integration with FillWatch Data

Given FillWatch sends real-time sensor updates, when data is received, then the dashboard automatically reloads the relevant sections without requiring a manual refresh.

Route Optimizer

Automatically integrates bin fill alerts with dynamic route planning, recalculating collection routes in real-time based on sensor data. By minimizing unnecessary pickups and reducing fuel consumption, this feature streamlines waste collection and enhances operational efficiency.

Requirements

Real-time Route Recalculation

"As a municipal planner, I want the system to automatically recalculate routes in real-time based on bin fill alerts, so that I can ensure efficient resource allocation and timely waste pickups."

Description

This requirement involves integrating sensor data to dynamically recalculate waste collection routes in real-time. It prioritizes bins triggering fill alerts by automatically adjusting routes on the fly, ensuring optimal resource utilization and reducing fuel consumption. The implementation will seamlessly adjust navigation based on live data, resulting in more efficient waste management operations.

Acceptance Criteria

Real-Time Route Recalculation Trigger

Given live sensor data indicating a bin fill alert, when the bin reaches the predefined threshold, then the system must automatically recalculate the shortest route within 30 seconds.

Optimal Route Adjustment Verification

Given a recalculation event triggered by sensor data, when the dynamic routing algorithm processes the data, then the new route must minimize fuel consumption and reduce total travel distance by at least 10%.

Handling Concurrent Bin Alerts

Given multiple simultaneous bin fill alerts, when the system processes these alerts, then it must prioritize bins with the highest fill levels and recalculate the route to service them first within a 30-second window.

System Resilience Under Load

Given a surge in bin fill alerts during peak operation times, when the system is under high load, then the route recalculation process must not exceed a delay threshold of 60 seconds and maintain data accuracy.

Fallback Procedure for Sensor Data Failure

Given a scenario of sensor data failure or erroneous readings, when an error is detected, then the system must revert to the most recent valid route and automatically trigger a maintenance alert for investigation.

Bin Fill Alert Integration

"As a waste collection manager, I want to receive instant alerts when bins are full, so that I can promptly schedule precise pickups and improve operational efficiency."

Description

This requirement focuses on integrating bin sensor data to trigger immediate fill alerts. By capturing accurate and live information from waste bins, the system ensures that critical alerts are timely relayed to the route optimizer, facilitating prioritization of pickups and efficient route adjustments.

Acceptance Criteria

Real-Time Sensor Data Processing

Given a bin sensor sends fill alert data, When the system receives this data, Then the alert is immediately forwarded to the route optimizer.

Threshold-Based Alert Triggering

Given a bin's fill level reaches the 90% threshold, When the sensor confirms the reading, Then an alert is triggered and transmitted to the route optimizer without delay.

Alert Accuracy Validation

Given a bin sends multiple sensor readings within one minute, When alerts are generated, Then the system creates only one valid alert to avoid duplicate notifications.

Dynamic Route Adjustment Confirmation

Given a valid bin fill alert is received, When the route optimizer processes the alert, Then it recalculates the collection route to prioritize the pickup point corresponding to the alert.

Fuel Consumption Optimization

"As a city operations director, I want to optimize collection routes to minimize fuel consumption, so that we can reduce costs and lower our environmental footprint."

Description

This requirement adds intelligence to the route planning process by incorporating algorithms that minimize fuel usage. It reduces unnecessary travel by optimizing collection routes to avoid redundant or inefficient loops, thereby lowering operational costs and environmental impact.

Acceptance Criteria

Real-time Route Recalculation

Given sensor data indicating bin fill alerts, when new data is received, then the system must recalculate and update collection routes in real-time to minimize fuel consumption.

Fuel Efficiency Algorithm Integration

Given the deployment of fuel optimization algorithms, when these algorithms process dynamic route data, then the system must reduce fuel usage by a predetermined percentage compared to historical averages.

Redundant Loop Elimination

Given multiple nearby bin fill alerts, when planning routes, then the system must identify and eliminate redundant loops in the route to ensure efficient travel.

Operational Cost Reduction Validation

Given the implementation of fuel consumption optimization, when analyzing operational data, then the system must show a measurable reduction in fuel costs and overall operational expenses.

Environmental Impact Assessment

Given real-time route optimization and historical fuel usage data, when performing environmental impact analysis, then the system must demonstrate a reduction in fuel consumption and associated emissions.

Dynamic Rescheduling and Notifications

"As a driver, I want to receive real-time notifications when my route is updated, so that I can promptly adjust my schedule and maintain efficient collection operations."

Description

This requirement enables dynamic rescheduling of routes with integrated push notifications. It ensures that waste collection teams are immediately updated about any route modifications, facilitating quick adaptation to new conditions and maintaining coordinated operations during dynamic route adjustments.

Acceptance Criteria

Immediate Notification Delivery

Given a route is dynamically rescheduled, when the update is triggered, then a push notification must be sent to the waste collection team’s devices within 5 seconds.

Dynamic Rescheduling Based on Bin Fill Alerts

Given that bin fill alerts exceed the predefined sensor threshold, when the system processes sensor data, then it should recalculate and update the waste collection route accordingly.

Real-time Route Update Display

Given that a new route is generated based on updated sensor data, when the system recalculates the route, then the updated route must be immediately displayed on the dispatcher dashboard.

User Acknowledgment Tracking

Given a push notification for a route update is sent, when the waste collection team receives the notification, then they must acknowledge receipt within the app, and the system should log the acknowledgment time.

Error Handling and Retry Mechanism

Given a push notification fails to deliver due to network issues, when the failure is detected, then the system must automatically retry sending the notification up to two additional times.

Sensor Pulse

Provides continuous monitoring of each waste bin’s sensor health, detecting malfunctions or irregularities. Sensor Pulse not only ensures reliable data collection but also triggers maintenance alerts to preserve system integrity and prevent service disruptions.

Requirements

Sensor Health Monitoring

"As a municipal waste operations manager, I want to continuously monitor sensor performance so that I can detect and address malfunctions before they impact our waste management data."

Description

Implement continuous sensor monitoring to assess operational performance and detect any deviations from standard behavior. This ensures that every sensor's health is consistently evaluated, providing early detection of malfunctions to prevent data inaccuracies and service interruptions. The integration with the EcoFlow system enhances real-time analytics and supports a proactive maintenance strategy.

Acceptance Criteria

Real-time Sensor Health Alert

Given sensor monitoring is active, when a sensor deviates from its standard operational parameters, then the system must trigger an alert within 30 seconds.

Continuous Data Stream Validation

Given sensors are transmitting data continuously, when data packets are received, then each packet must be validated for integrity and completeness.

Maintenance Alert Activation

Given a sensor malfunction is detected, when sensor readings remain abnormal for more than two consecutive cycles, then the system must automatically generate a maintenance ticket.

System Integration and Communication

Given the sensor monitoring system is integrated with EcoFlow’s real-time analytics, when sensor health data is updated, then the integrated system should reflect the new data within 1 minute.

Manual Override for Sensor Alerts

Given an alert has been triggered, when a maintenance operator reviews the alert dashboard, then they must have the option to acknowledge and manually override the alert if determined as a false alarm.

Real-Time Maintenance Alerts

"As a maintenance technician, I want to receive instant alerts about sensor issues so that I can quickly address them and maintain continuous service reliability."

Description

Develop an alert mechanism that triggers notifications immediately when a sensor reports irregularities or failures. This helps in prompt maintenance actions, reducing downtime and maintaining the integrity of the data being collected. The alerts will be integrated into the EcoFlow system, ensuring that maintenance teams receive actionable insights in real time.

Acceptance Criteria

Immediate Sensor Failure Alert

Given a sensor reports an irregularity, When the system detects the failure, Then an alert notification is triggered in real-time displaying sensor ID and error details.

Unresponsive Sensor Alert

Given a sensor stops sending data for a predefined duration, When no data is received for 5 minutes, Then the system automatically generates and sends a maintenance alert to the designated team.

Real-Time Notification Integration

Given that an alert is triggered by a sensor failure or irregularity, When the alert is generated, Then it integrates seamlessly into the EcoFlow dashboard with clear actionable details.

Data Integration and Dashboard Updates

"As an urban planner, I want to access up-to-date sensor health data on a central dashboard so that I can make informed decisions regarding urban waste management strategies."

Description

Incorporate live sensor status and alert information into the EcoFlow dashboard to provide a centralized view of sensor health. This integration aids urban planners in visualizing current sensor performance and operational issues, supporting informed decision-making and proactive planning for waste management improvements.

Acceptance Criteria

Live Sensor Health Monitoring

Given an urban planner accesses the EcoFlow dashboard, when live sensor data is received, then the dashboard must display the current sensor health status in real time with updated values.

Maintenance Alert Notification

Given a sensor malfunction is detected, when sensor health data falls below the defined threshold, then the dashboard must trigger a maintenance alert with precise sensor ID, location, and error details.

Data Refresh Interval Verification

Given the sensor data integration is active, when the sensor status updates are scheduled at a 30-second interval, then the dashboard must refresh the sensor data accordingly and accurately.

Real-time Data Updates Under Load

Given a high volume of sensor data coming from multiple waste bins, when real-time updates are performed, then the EcoFlow dashboard must remain responsive and update all sensor data without lag.

Consistent Data Visualization

Given the integration of sensor and alert data, when an urban planner views the dashboard, then all data elements must be presented in a consistent, user-friendly interface adhering to defined UI standards.

Historical Sensor Data Logging

"As a data analyst, I want to review historical sensor data so that I can identify patterns and help forecast future maintenance needs."

Description

Create a logging system to store historical sensor performance data for trend analysis and predictive maintenance planning. By maintaining comprehensive logs, the system will enable retrospective analysis and continuous improvements, helping to identify recurring issues and optimize maintenance schedules.

Acceptance Criteria

Initial Data Logging

Given sensor data is received, when the data is processed, then it should be logged with a timestamp and sensor ID in the historical data store.

Data Integrity Verification

Given log records exist, when they are queried, then they should accurately reflect sensor readings with no missing or corrupted data.

Trend Analysis Readiness

Given one month of sensor data logs, when the system performs trend analysis, then it should generate accurate maintenance predictions based on identified recurring issues.

System Scalability

Given an increased volume of sensor data logs, when the logging system is stressed, then it must continue to log, store, and retrieve data efficiently without performance degradation.

Logging Reliability

Given a sensor anomaly detected by Sensor Pulse, when the anomaly is logged, then the system must archive the data reliably and trigger a maintenance alert within 5 minutes.

Data Bridge

Consolidates real-time sensor data into an interactive dashboard, presenting actionable insights and historical trends. Urban planners and decision-makers can use this feature to analyze waste generation patterns, forecast peak fill times, and optimize resource allocation effectively.

Requirements

Real-time Sensor Data Integration

"As an urban planner, I want to view live sensor data on a single dashboard so that I can quickly assess waste accumulation and intervene before potential issues arise."

Description

Provide functionality that consolidates real-time sensor data into EcoFlow's interactive dashboard, enabling urban planners to monitor waste generation patterns effectively. Ensure the system seamlessly integrates with existing sensor networks, offering reliable, live data feeds that are essential for timely decision-making and proactive resource management.

Acceptance Criteria

Live Sensor Feed Display

Given the sensor network is configured and active, when real-time data is received, then the dashboard updates every 5 seconds or less with current sensor metrics.

Data Integration with Existing Sensors

Given a legacy sensor network setup, when the integration module is activated, then the dashboard integrates data seamlessly without data loss and presents both historical and real-time data.

System Performance Under Load

Given high-frequency sensor data streams, when the system processes concurrent data inputs, then the dashboard maintains a response time below 2 seconds and displays consistent live updates.

Interactive Analytics Dashboard

"As a municipal decision-maker, I want an interactive dashboard that visualizes complex data into digestible insights so that I can expedite and improve waste management decisions."

Description

Develop an interactive dashboard that provides urban planners with actionable insights by visualizing real-time data and historical trends. The dashboard should offer robust filtering, drill-down capabilities, and customizable views to support informed decision-making, ensuring safe and effective waste management.

Acceptance Criteria

Real-Time Data Integration

Given the dashboard is active, when new sensor data is received, then the dashboard must update in real-time (within 5 seconds) to reflect the latest information.

Historical Data Visualization

Given the availability of historical waste management data, when a user selects a specific time range, then the dashboard must accurately display historical trends and numerical summaries.

Filtering and Drill-down Capabilities

Given a dataset of waste generation, when a user applies filters and drills down into data points, then the dashboard must return precise, contextual results with correct aggregations.

Customizable Dashboard Views

Given a user accessing the dashboard, when the user customizes widget layouts and view settings, then these customizations must be saved and applied in future sessions.

Interactive Data Query Response

Given the user submits an interactive data query, when the query is processed, then the system must deliver relevant insights with a response time not exceeding 2 seconds.

Historical Trend Analysis

"As a city planner, I want to analyze historical data trends so that I can predict future waste patterns and plan resource allocation accordingly."

Description

Implement capability to retrieve and analyze historical sensor data, enabling urban planners to identify waste generation trends over time. This function should allow for forecasting and prediction of peak waste fill times, thus optimizing resource allocation while ensuring the system captures and renders historical data effectively.

Acceptance Criteria

Historical Data Retrieval

Given the urban planner is logged into EcoFlow and navigates to the Historical Trend Analysis module, when they request historical sensor data, then the system displays the data in chronological order with no missing records.

Trend Identification

Given that historical sensor data is loaded, when the system processes the data, then it accurately identifies waste generation trends with a minimum threshold accuracy of 95%.

Peak Fill Time Forecasting

Given the historical trends are established, when forecasting algorithms are applied, then the system predicts peak waste fill times in alignment with past trends and displays the forecast on the dashboard.

Dashboard Data Visualization

Given that the trend analysis is complete, when the data is rendered on the interactive dashboard, then the visualization refreshes spontaneously with real-time updates at intervals of no longer than 5 minutes.

Data Integrity and Quality Check

Given that historical sensor data is retrieved, when processing and analysis are finalized, then the system performs automated data quality checks ensuring consistency, completeness, and accuracy of the data.

Smart Alert

Delivers immediate push notifications to municipal teams and urban planners based on preset fill-level thresholds. This proactive alert system ensures rapid responses to critical waste management issues, enhancing overall system responsiveness and reducing the risk of overflow.

Requirements

Push Notification Trigger

"As a municipal team member, I want to receive instant push notifications when waste fill-levels reach critical thresholds so that I can respond quickly and prevent overflow."

Description

This requirement ensures that the system automatically sends immediate push notifications to municipal teams and urban planners when waste fill-level thresholds are met or exceeded. It integrates seamlessly with the existing data analytics platform, enabling real-time alerting to improve rapid response and minimize risk of overflow. The function performs continuous monitoring and instant trigger execution, enhancing overall system effectiveness and coordination among teams.

Acceptance Criteria

Standard Threshold Exceeded Alert

Given that the system continuously monitors waste fill-level data, when the fill-level reaches or exceeds the preset threshold, then an immediate push notification is triggered to the designated municipal teams and urban planners.

Alert Notification Accuracy

Given that threshold criteria are predefined, when the fill-level threshold is met, then the push notification must include accurate alert details such as location, current fill-level, and timestamp.

Data Platform Integration

Given the integration with the existing data analytics platform, when the threshold is reached, then the system retrieves real-time data from the platform and ensures that the notification reflects accurate current conditions.

Multiple Threshold Alerts

Given multiple waste fill-level thresholds distributed across different zones, when any threshold is surpassed concurrently, then the system sends timely notifications to the respective municipal teams with proper priority handling.

Threshold Management Interface

"As an urban planner, I want a user-friendly interface to set and adjust alert thresholds so that I can customize alerts to meet the specific needs of different areas."

Description

This requirement involves developing an intuitive interface that allows users to configure and adjust fill-level thresholds for triggering alerts. It provides flexibility for urban planners to set customized parameters for different waste collection zones, ensuring that the alert system is tailored to the unique operational needs of various areas within the city. The interface integrates with the backend analytics system for dynamic adjustments and real-time updates.

Acceptance Criteria

Threshold Configuration by Zone

Given a municipal decision-maker accessing the interface, when they select a specific waste collection zone, then they should be able to set, adjust, and save a fill-level threshold value within defined acceptable ranges.

Real-time Threshold Update Reflects on Dashboard

Given that a threshold value has been updated, when the backend analytics system processes the change, then the new threshold should immediately reflect on the real-time system dashboard.

User Permission Control for Threshold Adjustments

Given a user with restricted access attempting to adjust threshold settings, when the user submits a change, then the system should block the action and display an appropriate error message.

Integration with Smart Alert System

Given that a threshold has been configured on a specific zone, when the waste level exceeds the set threshold, then the Smart Alert system should trigger an immediate push notification to the appropriate municipal teams.

Alert Acknowledgment and Tracking

"As a municipal team member, I want to acknowledge and log the alerts I receive so that there is a clear record of the actions taken to manage waste issues."

Description

This requirement focuses on enabling users to acknowledge received notifications and track the response actions taken. It adds a layer of accountability and coordination by logging each alert and the subsequent handling steps. This logging mechanism supports subsequent review and optimization of response protocols while ensuring that critical incidents are managed with proper follow-up.

Acceptance Criteria

User Acknowledges Alert

Given a push notification received by a municipal team member, when the user taps the 'Acknowledge' button, then a timestamp and user identity are logged and the alert status is updated to 'Acknowledged'.

Response Action Tracking

Given an acknowledged alert, when a response action is initiated, then the system records details including the start time, assigned personnel, and action type in the alert log.

Real-Time Log Update

Given that an alert has been acknowledged and a response action is in progress, when any changes occur to the response status, then the system immediately updates the log and notifies the responsible team member.

Alert Escalation for Unacknowledged Notifications

Given a notification requiring acknowledgment, when the alert remains unacknowledged after a predetermined time interval, then the system escalates the alert to higher-level management and logs the escalation event.

Audit Trail Verification

Given that an alert has been processed, when an administrator reviews the alert log, then all events, including acknowledgments, response actions, and escalations, are displayed accurately with corresponding timestamps and user details.

Live Metrics

Delivers real-time analytics summarizing waste collection trends, sensor inputs, and route efficiencies. Live Metrics empowers urban planners to instantly monitor and act upon operational insights, ensuring timely, data-driven decisions that enhance performance and sustainability.

Requirements

Real-Time Data Aggregation

"As an urban planner, I want to view aggregated real-time data in a single dashboard so that I can promptly monitor and adjust waste management operations."

Description

The system should continuously collect sensor data, waste collection trends, and route efficiency metrics from various sources, integrating them in a centralized real-time dashboard. This seamless aggregation facilitates monitoring and rapid response to operational irregularities, ensuring that urban planners have consistent, up-to-date information to make proactive decisions in waste management.

Acceptance Criteria

Sensor Data Aggregation

Given sensor data is available from various sources, when the system collects the data, then it must display aggregated sensor metrics on the real-time dashboard within 2 seconds.

Waste Collection Trends Update

Given waste collection events are reported, when new data is received, then the dashboard should update waste collection trends dynamically and accurately.

Route Efficiency Metrics Integration

Given vehicle route data is transmitted, when the system processes the data, then it must integrate and display route efficiency metrics in real time with a minimal latency of 2 seconds.

Dashboard Real-Time Refresh

Given a continuous data stream, when the system aggregates data, then the dashboard is refreshed instantaneously to reflect the latest metrics without manual intervention.

Dynamic Alert System

"As a municipal decision-maker, I want to receive immediate alerts when key metrics deviate from the norm so that I can take swift action to resolve any emerging issues."

Description

The system must incorporate a dynamic alert mechanism that triggers notifications when real-time metrics exceed predefined thresholds or exhibit unusual trends. This feature is essential for ensuring that critical issues are promptly addressed, thereby minimizing potential disruptions and contributing to the overall efficiency and sustainability of municipal waste management.

Acceptance Criteria

Threshold Exceeded Notification

Given real-time metrics are being monitored, When any metric value exceeds its predefined threshold, Then a dynamic alert notification must be triggered immediately via multiple channels (e.g., email, SMS, dashboard alert).

Unusual Trend Detection Alert

Given historical data trends and real-time sensor inputs, When an unusual trend or anomaly is detected in waste collection patterns, Then the system must generate an alert indicating potential disruption or issue.

Alert Response and Acknowledgment

Given that an alert has been triggered, When a municipal operator acknowledges or dismisses the alert, Then the system must log the response time and update the alert status accordingly for follow-up actions.

Advanced Trend Analytics

"As an urban planner, I want advanced trend analysis tools to forecast future waste management needs so that I can strategically allocate resources and plan for sustainable growth."

Description

This requirement involves integrating predictive analytics to identify and visualize emerging trends in waste collection efficiency and sensor data over time. By leveraging historical data, the feature will deliver actionable insights and forecasts, empowering urban planners to optimize resource allocation and strategize for future growth in a sustainable manner.

Acceptance Criteria

Real-Time Data Visualization

Given the Live Metrics dashboard is accessed and real-time sensor data is streamed, when new data is received, then the system updates and displays evolving waste collection trends accurately in under 2 seconds.

Historical Data Analysis

Given that historical waste collection data and sensor inputs are available, when a user selects a specific date range, then the system must generate trend forecasts and visual graphs with a minimum accuracy of 90%.

Trend Forecast Trigger

Given that analysis of historical data indicates emerging trends, when the threshold parameters for deviation are met, then the system triggers predictive forecasts providing actionable insights with a lead time of at least 24 hours.

Actionable Insights Alerts

Given that predictive analytics identify a significant decline in waste collection efficiency, when these trends cross predefined alert thresholds, then the system sends real-time notifications to urban planners for timely intervention.

Analytics Performance Metrics

Given the backend predictive engine is operational, when system performance is stress-tested, then it must respond within 2 seconds and deliver trend predictions with an accuracy rate of at least 95%.

Interactive Dashboard Customization

"As an urban planner, I want to customize my dashboard view so that I can focus on the specific metrics most relevant to my city's waste management challenges."

Description

Enable user-customizable dashboard interfaces that allow urban planners to filter, sort, and visualize live metrics according to their specific operational requirements. This enhanced flexibility ensures that each user can tailor the interface to highlight the most relevant data for their strategic decision-making, ultimately leading to more effective and nuanced waste management practices.

Acceptance Criteria

Filter Selection Customization

Given a user on the Interactive Dashboard, when they apply specific filter options (e.g., waste type, collection date, sensor input), then the dashboard dynamically refreshes the live metrics view to display only the filtered data.

Data Sorting Efficiency

Given a user on the dashboard, when they sort waste collection data by different parameters (e.g., route efficiency, collection volume), then the system should update and display sorted datasets within two seconds.

Visualization Customization

Given a user selecting preferred chart types or data visualization formats, when they customize the dashboard visual layouts, then the changes are instantly applied while maintaining data accuracy and clarity.

Dashboard Layout Persistence

Given a user has customized their dashboard layout, when they save their configuration, then the system consistently loads the stored layout on future logins without data loss.

Real-Time Data Integration

Given a user is monitoring live metrics, when sensor inputs or waste collection events occur, then the dashboard updates automatically in real-time without the need for a manual refresh.

Resource Visualizer

Transforms raw data into actionable, interactive visualizations including charts and maps. This feature allows users to immediately grasp resource allocation patterns and waste surge trends, facilitating fast, informed resource optimization and urban decision-making.

Requirements

Dynamic Charts Generation

"As a municipal decision-maker, I want to view dynamic charts that update in real time so that I can quickly understand resource allocation patterns and respond to urgent waste management needs."

Description

This requirement enables the system to transform raw waste management data into dynamic, interactive charts. It seamlessly integrates with incoming data streams, updating visualizations in real time to highlight resource allocation trends and waste surge patterns. The functionality supports decision-makers with immediate insights for swift resource optimization, allowing urban planners to analyze and quickly respond to fluctuations in waste management metrics.

Acceptance Criteria

Real-Time Data Update

Given the system is integrated with a continuous data stream, when new waste management data is received, then the dynamic charts must update within 30 seconds to reflect the latest information.

Interactive Charts Filtering

Given the dynamic charts are displayed, when a decision-maker applies a filter based on date, waste type, or resource allocation, then the chart should immediately update to display only the relevant data subset.

Interactive Chart Zoom and Pan

Given that the dynamic charts are rendered, when a user performs zooming or panning actions, then the interface must smoothly transition to the new view within 2 seconds without compromising data accuracy.

Data Accuracy Verification

Given the raw data input from waste management streams, when the dynamic chart is generated, then it must accurately represent the data values and trends as verified against a validated sample dataset.

Seamless Integration with Map Visualizations

Given the integration between dynamic charts and map visualizations, when resource allocation and waste surge patterns are updated, then both visualizations should synchronize and reflect changes simultaneously.

Interactive Map Visualization

"As an urban planner, I want an interactive map displaying waste management hotspots and resource distribution so that I can make data-driven adjustments to operational strategies."

Description

This requirement involves converting geographic resource data into interactive map visualizations. It supports layer toggling, zoom functionalities, and spatial data overlays, offering clear, visual insight into regional waste management performance and resource distribution. The interactive maps empower users by providing location-based actionable intelligence, facilitating precise urban planning and resource deployment.

Acceptance Criteria

Layer Toggling Functionality

Given a user is viewing the interactive map, when they select the layer toggle option, then the corresponding map layer is displayed or hidden immediately without requiring a page reload.

Zoom and Pan Navigation

Given the interactive map is loaded, when a user uses the zoom controls or mouse scroll, then the map smoothly zooms in or out and supports panning without visual glitches or delays.

Spatial Data Overlays

Given a user selects a spatial data overlay, when the overlay is activated, then the map displays accurate and integrated data layers over the base map, highlighting regional resource distribution and waste trends.

Real-time Data Updates

"As a city manager, I want real-time updates in our data visualizations so that I can promptly address and mitigate sudden waste surges and resource discrepancies."

Description

This requirement ensures that all visualizations within the Resource Visualizer feature are updated in real time with data from integrated sensors and data sources. Real-time feedback is crucial for capturing transient trends and anomalies in waste management activities, allowing stakeholders to receive immediate notifications and thereby optimize resource allocation more efficiently.

Acceptance Criteria

Instant Sensor Data Feed

Given sensor data is continuously streamed, when a new data point is received from any integrated sensor, then the visualization updates within 2 seconds to display the new data.

Real-Time Map Refresh

Given that the system aggregates multiple data sources, when any data point is updated, then map visualizations are refreshed instantly to reflect accurate resource allocation information.

Live Data Anomaly Alert

Given that the system monitors and analyzes data patterns, when an anomaly or transient trend is detected, then an immediate notification is sent to stakeholders for prompt action.

Predictive Pulse

Utilizes historical data and machine learning algorithms to forecast waste collection demands and surge events. With predictive pulse, urban planners gain foresight into upcoming challenges, enabling preemptive actions that streamline operations and reduce environmental impact.

Requirements

Historical Data Ingestion

"As an urban planner, I want to reliably ingest and preprocess historical waste data so that I can trust the forecasting outputs and optimize resource allocation."

Description

Integrate and preprocess diverse historical waste management data streams to ensure robust input for the Predictive Pulse analytics engine. This feature cleanses and standardizes data, handles missing or inconsistent entries, and optimizes the data flow for machine learning operations.

Acceptance Criteria

Data Source Validation

Given a set of input historical data sources, when data is ingested, then the system verifies and authenticates each source.

Data Standardization

Given raw heterogeneous data, when processed, then the system transforms it into a unified format compliant with the predictive analytics engine.

Missing Data Handling

Given datasets with incomplete entries, when the data preprocessing step is executed, then missing values are either imputed or flagged for further review.

Data Cleansing and Preprocessing

Given raw input data containing anomalies, when the ingestion pipeline operates, then the system removes outliers and normalizes data for consistent downstream analysis.

Performance Optimization

Given high-volume historical data streams, when the ingestion process is executed, then the system processes and optimizes data flow within acceptable performance thresholds.

Machine Learning Forecasting Engine

"As an urban planner, I want an accurate forecasting tool that uses ML to predict waste surges so that I can proactively manage and allocate resources."

Description

Develop and embed a comprehensive machine learning engine that analyzes historical data to forecast waste collection demands and predict surge events. This module leverages advanced algorithms to identify trends, adjust for anomalies, and provide precise future demand estimates.

Acceptance Criteria

Historical Data Analysis Integration

Given the system has access to historical waste management data, when the Machine Learning Forecasting Engine processes this data, then it must accurately identify baseline trends, seasonal variations, and recurring patterns.

Real-Time Surge Event Detection

Given real-time input from waste collection sensors and data streams, when a surge in waste collection demand occurs, then the system should detect and alert the urban planner within 1 minute of the event.

Demand Forecast Visualization

Given processed historical and real-time data, when the forecasting output is generated, then it must be represented in a user-friendly visualization (charts, graphs) with clear metrics for future demand estimates.

Anomaly Adjustment Validation

Given input data that includes outlier values, when the Machine Learning Forecasting Engine runs its analysis, then it must adjust forecasts to filter anomalies and maintain prediction accuracy.

Performance and Accuracy Benchmarking

Given a benchmark test dataset, when predictions are generated, then the forecasting engine should achieve an accuracy of at least 85% with processing times within predefined performance thresholds.

Real-time Alert Integration

"As a municipal decision-maker, I want to receive real-time alerts about potential waste surges so that I can promptly intervene and adjust operational strategies."

Description

Implement a real-time alert system that leverages predictive insights to notify urban planners of upcoming waste collection surge events. This component ensures timely and automated communication of critical events to support preemptive operations.

Acceptance Criteria

Surge Event Notification

Given that predictive analytics identify an upcoming surge event, when the event threshold is met, then the system must generate and dispatch a real-time alert to designated urban planners within 2 minutes.

Automated Alert Scheduling

Given continuous predictive data streams, when imminent waste collection surge events are detected, then the system should automatically schedule and deliver alerts to both the urban planning dashboard and mobile application simultaneously.

Alert Acknowledgement Confirmation

Given an alert has been dispatched, when the urban planner acknowledges receipt through the system interface, then the system must log the confirmation and update the alert status in real-time.

Alert Missed Follow-up Escalation

Given that an alert is sent and receives no acknowledgment within 5 minutes, when the system detects the lack of response, then an escalation message must be automatically sent to the municipal emergency manager.

System Performance Under High Load

Given high user traffic during peak waste surge events, when multiple alerts are triggered concurrently, then the system must deliver all alerts without performance degradation, maintaining a response time under 5 seconds per alert.

Dashboard Visualization Integration

"As an urban planner, I want an integrated dashboard that visually presents predictive insights so that I can easily interpret data and take informed actions."

Description

Integrate predictive analytics outputs into an intuitive dashboard with clear visualizations, representing forecast trends, surge probabilities, and alert statuses. This feature offers urban planners an accessible, real-time view of analytics to facilitate proactive decision-making.

Acceptance Criteria

Real-Time Visualization Loading

Given an urban planner accesses the dashboard, when predictive analytics outputs are updated, then the dashboard must refresh within 3 seconds and display forecast trends, surge probabilities, and alert statuses.

Interactive Trend Analysis

Given an urban planner interacts with the dashboard, when selecting any forecast trend, then detailed historical trends along with associated predictions must be displayed in an interactive graph.

Alert Status Notifications

Given surge events are predicted, when the system detects an anomaly, then a clear visual alert with color-coded indicators must appear on the dashboard along with a concise description of the event.

User Customizable Dashboard Views

Given the urban planner wishes to personalize the dashboard, when they adjust the visualization settings, then the system must allow toggling between different views and threshold settings for surge events and trends.

Actionable Alerts

Integrates live notifications into the EcoFlow DashDrive dashboard to flag deviations, anomalies, or emergent waste management issues. By receiving instant, actionable alerts, users can rapidly respond to critical situations, minimizing disruptions and inefficiencies.

Requirements

Real-Time Alert Notification

"As a municipal decision-maker, I want to receive instant real-time notifications for waste management anomalies so that I can promptly address and mitigate emergent issues."

Description

Provide a system that continuously monitors waste management data and triggers live notifications when deviations, anomalies, or emergent issues are detected. This real-time alert functionality integrates into the EcoFlow DashDrive dashboard, ensuring that municipal decision-makers can rapidly respond to critical situations, thereby minimizing disruptions and inefficiencies in city operations.

Acceptance Criteria

Data Monitoring and Alert Trigger

Given waste management data is being continuously monitored, when the system detects a deviation from predefined thresholds, then a real-time alert is immediately triggered on the EcoFlow DashDrive dashboard.

Alert Accuracy and Relevance

Given data inputs from various sensors, when anomalies occur, then only accurate and relevant alerts are displayed, ensuring minimal false positives and a response time of under 2 seconds.

User Interaction with Alerts

Given that municipal decision-makers are monitoring the dashboard, when an alert is received, then users can acknowledge and dismiss the alert via a dashboard confirmation button.

System Performance Under Load

Given high volumes of waste management data during peak periods, when real-time alerts are triggered, then all notifications must be delivered within 3 seconds without system degradation or crashes.

Alert Customization

"As an urban planner, I want to customize alert parameters so that I only receive notifications that are pertinent to my city’s unique waste management challenges."

Description

Enable users to tailor alert notifications by setting custom thresholds, specifying particular anomaly types, and refining regional parameters. This customizable approach ensures that alerts are relevant to specific urban environments and waste management priorities, helping officials focus on the most critical issues.

Acceptance Criteria

Threshold Configuration

Given a municipal urban planner is logged into EcoFlow DashDrive, when they navigate to the Alert Customization section, then they must be able to set custom alert threshold levels for various waste management indicators.

Anomaly Type Selection

Given the user is in the alert customization interface, when they select specific anomaly types from a provided list, then the system should only trigger alerts corresponding to the selected anomalies.

Regional Alert Refinement

Given an urban planner managing alerts for multiple regions, when they define or modify regional parameters, then only alerts corresponding to those selected regions should appear on the dashboard.

Real-time Notification Testing

Given the alert customization settings have been configured, when a deviation is detected in real-time waste management data, then the system should issue the custom alert within a predefined short duration (e.g., 60 seconds).

Alert Filter Verification

Given custom alert settings are applied, when events occur that do not meet the defined thresholds or parameters, then the system should suppress unnecessary alerts to maintain dashboard clarity.

Historical Alert Analytics

"As a city planning official, I want to access historical alert data and analytics so that I can identify trends and make informed decisions to enhance waste management practices."

Description

Develop an analytics module that archives alert data and provides comprehensive insights, including trend analysis, frequency patterns, and performance metrics. By reviewing historical alert data, users can detect recurring issues and refine predictive models, leading to smarter resource allocation and long-term improvements in waste management strategies.

Acceptance Criteria

Historical Data Archival

Given that alert data is generated from the actionable alerts feature, when the analytics module processes it, then the data must be archived with accurate timestamps and necessary metadata for future analysis.

Trend Analysis Computation

Given the archived alert data, when a user initiates a trend analysis, then the system must compute frequency patterns, performance metrics, and recurring issue indicators with an accuracy of at least 95%.

User Interface Analytics Display

Given the processed historical data, when the user accesses the analytics dashboard, then the system must display clear and interactive visualizations (charts and graphs) representing trends and anomalies.

Data Export Functionality

Given that a comprehensive analysis has been completed, when the user selects to export the data, then a downloadable report in CSV or PDF format must be generated containing all computed metrics and trend analyses.

Collaboration Hub

A centralized communication platform within the dashboard that fosters real-time teamwork among municipal decision-makers. The Collaboration Hub supports interactive discussion, shared data review, and coordinated task management, ensuring cohesive and agile responses to emerging waste management needs.

Requirements

Real-Time Messaging

"As a municipal planner, I want to exchange real-time messages with my team so that we can quickly discuss and resolve waste management issues as they arise."

Description

Implement a robust messaging system that supports instant text, voice, and video communications among municipal decision-makers. This system will enable group chats, direct messages, and cross-channel notifications to ensure seamless, synchronous collaboration, facilitating prompt feedback and decision-making.

Acceptance Criteria

Group Chat Functionality

Given municipal decision-makers are logged into EcoFlow, when they initiate a group chat and send a message, then the message must be delivered and visible to all chat participants within 1 second.

Direct Messaging Functionality

Given a user selects a direct messaging conversation, when they send a text or media message, then the recipient must receive the message instantly with a confirmation of delivery and read receipt enabled.

Voice/Video Communication Reliability

Given a decision-maker initiates a voice or video call, when the recipient accepts, then the call should connect within 2 seconds and maintain a defined quality threshold throughout the conversation.

Cross-Channel Notification Workflow

Given a new message is posted on any messaging channel, when that event occurs, then all relevant users across channels should receive an immediate notification on their devices irrespective of platform used.

Load Performance for Messaging System

Given peak usage with multiple concurrent messaging threads, when the system processes high volumes of messages, then the platform must maintain a response latency of less than 2 seconds and ensure no service downtime.

Data Collaboration Workspace

"As a municipal decision-maker, I want a shared workspace to review and discuss data insights so that our team can collectively interpret trends and make informed decisions."

Description

Develop a collaborative workspace that allows users to collectively review, annotate, and comment on real-time data dashboards and reports. The workspace will integrate interactive visualizations and maintain version histories to support asynchronous collaboration, ensuring that municipal decision-makers are well-informed to interpret waste management trends.

Acceptance Criteria

Real-Time Data Annotation

Given a live data dashboard, when a user selects a data point, then they can add annotations that are instantly visible to all authorized users.

Collaborative Commenting

Given a shared report, when a user submits a comment, then the comment appears in real-time for all users with appropriate metadata such as timestamp and user ID.

Version History Audit

Given a modified dashboard, when a user accesses version history, then the system displays a complete log of changes with timestamps and author details, and allows users to revert to any previous version.

Coordinated Task Management

"As a municipal decision-maker, I want to assign and track tasks within the collaboration hub so that my team can efficiently manage project responsibilities and deadlines."

Description

Introduce a task management feature that enables users to create, assign, track, and update tasks in real time. This system will support prioritization, deadline notifications, and progress tracking, ensuring that all tasks related to waste management initiatives are handled efficiently and in a coordinated manner.

Acceptance Criteria

Task Creation and Assignment

Given a user with appropriate permissions, when the user creates a new task by entering all required fields and assigning it to a specific team member, then the task is successfully created, visible in both the creator's and assignee's task lists with accurate details.

Task Prioritization and Deadline Notifications

Given a task in the system, when a user prioritizes the task and sets a deadline, then the system automatically sends a notification to the assigned user(s) at configurable intervals before the deadline.

Real-Time Task Updates

Given multiple users in the Collaboration Hub, when one user updates the status or details of a task, then all other users see the updated task information in real time without needing to refresh the platform.

Task Filtering and Sorting

Given a list of tasks, when a user applies filters or sorts tasks by criteria such as status, priority, or deadlines, then the system correctly displays the filtered or sorted tasks based on the selected parameters.

Task Progress Tracking

Given a task with multiple defined progress stages, when a user marks one or more stages as complete, then the overall progress of the task is updated automatically, reflecting the percentage of completion accurately.

Integrated Scheduler

"As a municipal planner, I want to schedule meetings and align team availability easily within the platform so that we can coordinate discussions effectively and minimize scheduling conflicts."

Description

Implement an integrated calendar and meeting scheduler that synchronizes with users’ existing calendars to plan and organize discussions and review sessions. This tool will provide real-time availability, automated reminders, and facilitate booking of virtual meetings, aiding municipal decision-makers to coordinate their schedules efficiently.

Acceptance Criteria

Real-Time Calendar Sync

Given a user’s existing calendar is connected, When a meeting is scheduled in the integrated scheduler, Then the meeting details should automatically sync in the user’s calendar with up-to-date availability information.

Automated Meeting Reminders

Given the integrated scheduler is set up, When a meeting is scheduled, Then users must receive automated reminders via email and within the dashboard at preset intervals.

Virtual Meeting Booking

Given a user selects the option to book a meeting, When the booking is confirmed, Then the system should automatically generate a virtual meeting link and update both the integrated scheduler and the user's connected calendar.

Conflict Detection

Given a meeting is being scheduled, When the system detects a scheduling conflict with another event, Then the system should alert the user and offer alternative time slots for the meeting.

Product Details

Vision & Mission

Problem & Solution

Details & Audience

User Personas

Innovative Ingrid

Background

Needs & Pain Points

Needs

Pain Points

Psychographics

Channels

Efficient Ethan

Background

Needs & Pain Points

Needs

Pain Points

Psychographics

Channels

Green Guardian Grace

Background

Needs & Pain Points

Needs

Pain Points

Psychographics

Channels

Product Features

Surge Sentry

Requirements

Dynamic Anomaly Detection Algorithm

Description

Acceptance Criteria

Instant Alert Notification System

Description

Acceptance Criteria

Interactive Anomaly Dashboard Interface

Description

Acceptance Criteria

Hotspot Mapper

Requirements

Real-time Data Aggregation

Description

Acceptance Criteria

AI-Powered Hotspot Prediction

Description

Acceptance Criteria

Interactive Map Interface

Description

Acceptance Criteria

Customizable Data Filters

Description

Acceptance Criteria

Resource Coordination Module

Description

Acceptance Criteria

Adaptive Scheduler

Requirements

Dynamic Collection Routing

Description

Acceptance Criteria

Automated Surge Adjustments

Description

Acceptance Criteria

Real-time Monitoring Dashboard

Description

Acceptance Criteria

Trend Analyzer

Requirements

Historical Data Aggregation

Description

Acceptance Criteria

Predictive Trend Modeling

Description

Acceptance Criteria

Interactive Trend Visualization

Description

Acceptance Criteria

FillWatch

Requirements