Abstract Scope |
Effective management of medical waste is crucial for environmental sustainability and public health. This study presents an innovative approach that integrates computer vision and near-infrared (NIR) spectroscopy to improve the sorting and recycling of medical waste. By leveraging advanced vision algorithms and NIR spectral analysis, this method accurately identifies and classifies various types of medical waste materials, including plastics, metals, and hazardous substances. Specifically, this system can detect and sort different plastic types such as PET (polyethylene terephthalate), HDPE (high-density polyethylene), PVC (polyvinyl chloride), LDPE (low-density polyethylene), PP (polypropylene), and PS (polystyrene). At UHV Technologies, we have previously utilized AI and XRF for various metal and material sorting, demonstrating the potential of these technologies in different applications. This new system enhances the precision of waste sorting, reduces contamination, and promotes efficient recycling processes. The technology offers a sustainable solution to medical waste management, contributing to resource conservation and environmental protection. |