Abstract
Singapore produced more than 982,000 tonnes of plastic waste in 2021. Plastic waste is among the top 4 generated wastes in volume. Astonishingly, plastic waste has one of the lowest recycling rates of just 6% compared to the other 3 highly generated wastes (99% for ferrous metal, 39% for paper, 99% for construction waste). Critically, the lack of effective plastic waste sorting technologies is one key factor that inhibits recycling rate.
Existing plastic sorting relies on manual checking of the printed RIC on plastic wastes. As the printed RIC codes could be small in size, printed at different locations on the plastic objects, and potentially contaminated with dirt, mud, filth, etc., manual plastic sorting is slow, labour intensive, error-prone and poses health risks to facility workers. Overall, existing plastic sorting is ineffective and is a critical barrier in plastic recycling.
In this presentation, we report our work on the development of novel AI/ML-assisted multispectral and hyperspectral imaging technologies and integrate that into a robotic platform for automatic plastic waste sorting and recycling. The outcome is a noticeable increase in plastic waste recycling rate.