How We Built an AI Littering Detection System in 4 Days — and Won 2nd Place

We had 4 days, one laptop with an RTX 2050, and a problem nobody on our team had fully solved before. This is the story of building TRACE — and everything that broke along the way. What Is TRACE? TRACE (Trash Recognition and Automated Civic Enforcement) is a real-time AI surveillance pipeline that: Detects littering events across multiple live camera feeds Confirms offender identity using a 5-state behaviour machine Reads license plates via OCR for vehicle offenders Routes WhatsApp alerts with evidence snapshots to the nearest municipality ward office using GPS distance Streams live annotated video to a real-time analytics dashboard Stack: Python · YOLOv8 · ByteTrack · EasyOCR · FastAPI · SQLite · Twilio · OpenCV · HTML/CSS/JS We won 🥈 2nd place at NextGenHack 2026 . This was my first ever hackathon, first semester of college, competing against seniors. Here's what actually happened during those 4 days. Problem 1: Detecting Behaviour , Not Just Objects The obvious approach — detect tra