Campus waste facilities process nearly 7,850 tons of material each year but achieve low diversion rates (19% in 2025), falling short of the Illinois Climate Action Plan (iCAP) Zero Waste goals. To address this challenge, our team installed cameras at the Waste Transfer Station and developed an initial AI model for 
real-time waste classification. While the prototype delivered promising results, it was trained on a limited dataset and constrained by single-camera coverage. Building on this foundation, the proposed project will expand the dataset (~2,000 to >10,000 labeled images) and integrate multiple cameras and weight sensors for real-time accuracy. In parallel, a robotics feasibility study will establish the foundation for future automation in waste sorting, contributing towards achieving iCAP goals.

This proposal directly funds the following. See approved budget for details.|

1. Robot
2. Hourly material testing
3. Publication costs
4. Graduate and undergraduate wages
5. F&S wages for support of conveyor belt operations