TrashTrade is our thesis project.
It is an innovative waste disposal system developed as our undergraduate thesis project. It combines machine learning, gamification, and mobile technology to tackle the pressing issue of improper waste disposal. With TrashTrade, users can properly dispose of waste, earn points based on the type and amount of trash they classify, and redeem rewards such as vouchers and discounts through a user-friendly mobile application.
The system features a smart trash platform powered by a Raspberry Pi and a Residual Neural Network (ResNet) model for waste classification. It also includes a mobile application for tracking points and rewards, as well as a web-based administrator dashboard for system management. This comprehensive solution demonstrates how technology can make waste management more efficient and engaging while promoting sustainable behavior.
We are proud to share that TrashTrade was selected as one of the 11 Finalists nationwide for the prestigious 2024 BPI-DOST Innovation Awards. After pitching our project at the culminating event held in Makati City, Philippines, on December 11, 2024, we were honored to receive the Best Project of the Year Award, a recognition of our dedication to innovation and environmental impact.
This project represents our commitment to leveraging technology for meaningful solutions, and it stands as a milestone achievement in our academic journey.
Video Demonstration
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