Virtual Booth

Project RECLAIM presents an advanced, scalable smart community infrastructure engineered to bridge the critical gap in automated, data-driven waste management. Operating under a robust dual-brain architecture integrating a Raspberry Pi 3 and an Arduino Uno, the prototype replaces traditional, high-friction manual sorting methods with an instantaneous, automated mechanical segregation framework driven by customized YOLOv11 machine learning computer vision. The system achieves real-time classification and physical separation of municipal waste across four major recyclable categories: aluminum, plastic, paper, and glass with zero operational latency.

To achieve continuous field monitoring and preventive logistics, RECLAIM integrates a high-precision VL53L0X Time-of-Flight laser sensor, streaming continuous capacity metrics directly to an administrative Django-powered web dashboard via automated web and email notification triggers. For institutional asset protection and optimal vehicle routing, the smart infrastructure incorporates an ATGM336H GPS module ensuring synchronized live location tracking and foolproof anti-theft security. Furthermore, a natural language processing AI chatbot assistant is embedded within the interface to instantly handle daily public recycling queries, fostering proactive green communities.

Validated through comprehensive technical and behavioral evaluations on campus, RECLAIM converts passive disposal habits into an engaging, interactive automated ecosystem. The project directly aligns with four United Nations Sustainable Development Goals: Goal 3 (Good Health), Goal 9 (Innovation and Infrastructure), Goal 11 (Sustainable Cities), and Goal 12 (Responsible Consumption and Production). By showcasing substantial manpower cost reductions and reliable asset durability, RECLAIM delivers a highly marketable, deployment-ready IoT solution capable of driving sustainable paradigm shifts and embedding systemic green habits within modern smart city framework.