Project
CleanClik
ML-assisted waste sorting experience with verified disposal workflows, participation incentives, and measurable cleanup outcomes.
Project Details
CleanClik delivers a structured cleanup flow: identify waste through on-device vision, route users to the correct disposal stream, verify completion through QR confirmation, and maintain engagement through points and leaderboard mechanics.
The implementation combines a Flutter mobile client with Supabase-backed identity and profile services, while Google ML Kit powers real-time classification within the camera experience.
Recognition confidence thresholds are used to improve routing accuracy before disposal guidance is shown, helping reduce incorrect sorting and improve disposal quality across repeat usage.
The user journey is optimized for field conditions: users can move from capture to confirmation in a short, continuous sequence without context switching or interface overhead.
Operationally, participation events and category-level disposal trends provide actionable visibility into waste patterns, allowing targeted interventions and localized awareness campaigns.