Build a dashboard with alert statistics

[abhayprabhakar]

Display analytics like total alerts, alerts per location, and category-wise graphs using Flask + Chart.js.

[aaditiiiii1]

@abhayprabhakar Hi, Can you assign me this issue, I would like to work on this, and create a dashboard with alert statistics as described by you.

[biswas2200]

#ieeesoc - Dashboard with Alert Statistics Implementation Assignment

Title

Build a comprehensive analytics dashboard for SafeVision alert statistics using Flask and Chart.js

Overview

I'll develop an interactive analytics dashboard that visualizes total alerts, location-based distributions, and category-wise graphs using Flask backend and Chart.js for frontend visualization.

Motivation

This dashboard is crucial for monitoring the effectiveness of our SafeVision system by providing stakeholders with real-time insights into alert patterns, hotspots, and trends, enabling data-driven decision-making for improved security monitoring.

Deliverables

• Backend Flask API routes to retrieve and aggregate alert statistics
• Frontend templates with responsive Chart.js visualizations for:
  • Total alerts overview (daily/weekly/monthly)
  • Geographic heat map of alerts by location
  • Category distribution charts (pie/bar graphs)
  • Trend analysis over customizable time periods
• Data filtering capabilities by date range, location, and alert category
• CSV export functionality for further analysis
• Comprehensive documentation and testing

Dependencies

• Flask: https://flask.palletsprojects.com/
• Chart.js: https://www.chartjs.org/
• Flask-SQLAlchemy: https://flask-sqlalchemy.palletsprojects.com/
• pandas: https://pandas.pydata.org/ (for data manipulation)
• Repository: https://github.com/UmashankarGouda/SafeVision

Approach

1. Data Layer:

   • Create models for alerts with appropriate relationships
   • Implement aggregation queries for statistics
   • Design efficient data retrieval methods to minimize response time

2. Backend:

   • Develop Flask routes for each dashboard component
   • Implement data formatting for Chart.js consumption
   • Add caching for improved performance

3. Frontend:

   • Design responsive dashboard layout
   • Create modular Chart.js components
   • Implement interactive filters and controls
   • Ensure cross-browser compatibility

4. Testing & Optimization:

   • Unit tests for backend functionality
   • Visual testing for chart accuracy
   • Performance optimization for large datasets

I'll start with setting up the data models and Flask routes, then move to the Chart.js integration. Please assign this task to me.

[Jojohere05]

@abhayprabhakar I would like to work on this issue if active and someone is working could i join them?