IoT-Enabled Medical Waste Segregation Bin with Dynamic Sectioning and Automated Classification

In today’s era, waste classification, segregation, and management remain pressing issues across various sectors, including households, hospitals, and agriculture. Proper waste segregation offers numerous benefits, such as environmental protection, resource conservation, and operational cost savings. However, many people neglect to dispose of waste correctly, complicating waste management efforts. There is a pressing need to develop a smart bin with an automated waste segregation system that classifies and directs waste into the appropriate sections. This paper proposes an IoT-enabled smart bin utilizing a Raspberry Pi 5 as its microcontroller to automatically segregate waste through deep learning applied to captured images. The bin’s design allows for adaptability in the number of sections and types of waste categories, making it suitable for various sectors, including households, medical facilities, and industrial applications. The focus of this paper is on medical waste, categorized into three types: general, infectious, and sharps. Additionally, a Flutter application was developed to monitor the fill levels of each bin section, with IoT technology used for the wireless transmission of bin data to the app. The system achieves high classification accuracy and completes the segregation process within a few seconds. Overall, the proposed smart bin is compact, user-friendly, and adaptable to any sector with appropriate configuration adjustments and program logic.