CivicLens: AI-Powered Civic Problem Analyzer & Issue Tracker
AI Vision-powered public infrastructure diagnostic platform: automated damage classification, structural hazard estimation, and geospatial citizen issue tracking.
Role-Isolated Ecosystem Previews
AI-driven civic reporting console: image upload with EXIF metadata parsing, multimodal Gemini diagnostic outputs, municipal escalation workflows, and civic impact documentation.
Project Architecture & Overview
CivicLens accelerates municipal infrastructure maintenance using artificial intelligence. Citizens simply snap photos of public hazards such as potholes, damaged sidewalks, or illegal dumping sites. The system analyzes the imagery in real time using the Google Gemini Vision API to quantify structural risk, validate GPS coordinates on interactive maps, and compile standardized escalation reports for public works authorities.
Case Study & Retrospective
AI Vision Classification Accuracy Under Low-Light Conditions
Nighttime photos of road defects taken under dim streetlighting frequently yielded classification noise and false positives.
Applied client-side CLAHE image preprocessing to enhance contrast and edge definition prior to sending frames to the Gemini Vision API.
Duplicate Issue Report De-duplication Near Identical Coordinates
Multiple citizens submitting photos of the exact same street pothole within a 10-meter radius caused database clutter.
Engineered PostGIS spatial queries with ST_DWithin clustering to merge incoming alerts into existing active municipal tickets.



