Project status: Active
We are building a waste bin that automatically sorts between recycling and trash/contaminated recycling. Confusion on what items can be recycled leads to recyclable items being thrown into trash bins and increases unnecessary waste. For example, nonrecyclable items thought to be recycled like plastic bags and bins with leftover food are thrown in recycling bins, contaminating entire bags of recycling. Rubicon reports that the average U.S. recycling contamination rate is 25%, and The Environmental Protection Agency estimates that 75% of waste is recyclable, yet only close to 34% of it is recycled. This contamination, whether it be food waste or nonrecyclable items, clogs single stream recycling at Material Recovery Facilities (MRFs), demands more manual sorting from MRF employees, and hinders the number of items able to be recycled. Our product will reduce contamination and increase the recycling rate by using machine learning to sort between trash and recycling and more effectively sort than people. This will allow for more recycling, which is better for the environment, and will enable users to save money on their recycling service as recycling plants will pay for better-sorted recycling.
Michael Tobin, Founder/Product Management, Trinity, 2025
Sam Hiner, UNC-Chapel Hill, 2025