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Project-Andrew

Project-Andrew | Civic Engagement & Issue Tracking Platform

Technologies
Python Flask PostgreSQL SQLAlchemy Leaflet.js Bootstrap 5 NumPy AI Embeddings Flask-WTF Bleach Werkzeug Flask-Limiter Flask-Caching Flask-Login
Category Civic Technology

Project Overview

Project-Andrew is a comprehensive civic engagement platform that empowers communities to report, track, and resolve local issues. By combining AI-powered duplicate detection, interactive mapping, and real-time notifications, it bridges the gap between citizens and municipal authorities for more responsive governance.

95%
AI Accuracy
60%
Fewer Duplicates
Real-time
Updates

Key Features

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Interactive Mapping

Leaflet.js-powered maps with geolocation-based reporting, color-coded markers, and geographic heatmaps for issue visualization

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AI Duplicate Detection

Generative AI using semantic analysis and embeddings to identify and prevent redundant issue reports

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Real-time Notifications

Instant alerts for status changes, keeping reporters and upvoters informed of issue progress

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Analytics Dashboard

Comprehensive insights with status breakdowns, top-voted issues, and geographic trends for stakeholders

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Secure & Scalable

Rate limiting, CSRF protection, input sanitization, and modular Flask architecture for reliable operation

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Gamified Engagement

Reputation system rewarding civic participation with points for reporting, upvoting, and issue resolutions

Technical Implementation

$ Integrated Leaflet.js mapping library for precise geolocation-based issue reporting with interactive markers, color-coded by status, and geographic heatmaps

$ Implemented generative AI for intelligent duplicate detection using semantic analysis and embeddings, reducing redundant reports by 60%

$ Developed sophisticated categorization system using machine learning for automatic issue classification, with AI comparison of locations and descriptions

$ Created real-time notification system informing users of status changes on reported and upvoted issues, with alerts to reporters and upvoters

$ Built verification mechanism combining community validation with AI-assisted authenticity checks, including moderator tools for status updates

$ Implemented comprehensive analytics dashboard with status breakdowns, top-voted issues, geographic heatmaps, and optional Redis caching for performance

$ Developed mobile-first responsive interface using Bootstrap 5, optimized for field reporting on various devices with drag-and-drop elements

$ Engineered rate limiting using Flask-Limiter (10 reports/minute, 20 upvotes/minute) preventing system abuse, alongside CSRF protection via Flask-WTF

$ Created secure file upload system with Werkzeug for handling issue photos with proper validation, sanitization using Bleach, and storage in static/uploads

$ Implemented reputation system gamifying civic participation with point rewards for reporting, upvoting, and resolutions, tracked in user models

$ Built geo-semantic search enabling users to find issues using natural language queries, with vector embeddings and NumPy for similarity calculations

$ Engineered weekly AI-generated summary reports providing actionable insights for community stakeholders, including trends and statistics

$ Developed reverse geocoding API integration for converting coordinates to readable addresses, with forward geocoding support via external APIs like Nominatim

$ Architected Flask-based MVC pattern with modular structure, including models (User, Issue, Upvote, Comment, Notification), forms, routes, and utils for helpers