Grantee Research Project Results
AI-Driven Recycling Centers for Disadvantaged Communities: Improving Recovery, Safety, and Costs
EPA Contract Number: 68HERC24C0023Title: AI-Driven Recycling Centers for Disadvantaged Communities: Improving Recovery, Safety, and Costs
Investigators: Lamuraglia, Jack
Small Business: KLAW Industries LLC
EPA Contact: Richards, April
Phase: I
Project Period: December 1, 2023 through May 30, 2024
Project Amount: $100,000
RFA: Small Business Innovation Research (SBIR) - Phase I (2024) RFA Text | Recipients Lists
Research Category: Small Business Innovation Research (SBIR)
Description:
Creating the Foundation for Modern Recycling Facilities
The processing technology used in the recycling industry has remained unchanged since the 1980s, relying on manual labor and rudimentary machinery to solve our waste crisis. For the past 40 years, municipalities have shelled out egregious tipping fees for ineffective and dangerous sorting practices. Cities across the U.S. need a new recycling processing system to enter the waste industry and correct the backward economic model plaguing the sector.
This project will create a proof of concept of a rapidly deployable, autonomous robotic sorting system to build the foundation for the next era of recycling facilities. Rather than relying on slow-moving waste haulers, KLAW Industries will develop, deploy, and operate this technology to reduce municipal tipping fees by 31%. With an autonomous sorting system to match the modern waste stream, we can reduce product contamination to 0.5%, lower capital costs by 65%, and decrease excess hauling by 94%.
Technical Feasibility & Comparative Performance
With backing from the City of Binghamton, KLAW Industries' researchers have made a breakthrough innovation in feature extraction and convolutional neural networks to make rapidly deployable autonomous sorting possible at a local level, resulting in higher recovery rates and a significant savings potential for City residents. This project will develop a prototype to demonstrate this technology can be used in an industrial setting to process regular volumes of recyclables from citizens of the disadvantaged community of the East Side of Binghamton.
Our target market is cities and commissioners of public works who face the unpleasant dilemma between paying more for recycling or saving money, time, and headaches by dropping the program entirely, as many low-income towns and villages already have.
Market Size & Performance Benefits & Environmental Benefits
With a total available market (TAM) of $37.8B in the U.S., the achievements in computer science present an opportunity to rectify one of the most extensive economic calamities in history. With drastic reductions in capital costs, we can shuffle diesel-powered hauling enterprises out and usher in technology companies focused on long-term material recovery.
The recycling sector injury rate is 3.2 per 100 full-time-equivalent workers. Autonomous sorting protects critical workers by moving away from conveyor belts and toward computer terminals. With an increased sorting accuracy of 90% and a 31% lower tipping fee, this project will begin sorting, classifying, and reusing waste locally to achieve a recycling rate of 50% by 2030.
Progress and Final Reports:
SBIR Phase II:
AI-Driven Recycling Centers for Disadvantaged Communities: Improving Recovery, Safety, and CostsThe perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.