Environmentally responsible innovative technologies for biomedical waste management: Implementing machine learning classifiers and IoT tracking

Biomedical waste management (BMWM) is necessary to control the spread of infectious debris. The health care organizations must disinfect, dispose and segregate waste properly. Therefore, new technologies must be implemented to dispose of biomedical waste (BMW) properly. The current study aimed to implement innovative methods to treat bio-medical waste using waste treatment technologies. A qualitative method was used to determine the existing practices in the disposal of BMW and to check hospital workers' knowledge of the biomedical waste recycling process. The images of COVID waste that were collected waste were classified and sorted to be recycled. A support vector machine (SVM) classifier and fuzzy-based system were used for categorizing the waste, and an IoT server was used to track it. The IoT-based monitoring system observes indoor, outdoor, and hazardous materials. RFID technology was used to monitor indoor waste, and GPS was used to collect outdoor waste. The study results showed that the recycling process is necessary in hospitals to treat BMW. Findings also show that the SVM classifier achieved specificity, sensitivity, and accuracy of about 95.9 %, 95.3 %, and 96.5 %, respectively. The medical waste is documented, tracked, located, scanned, and labeled using an IoT tracking device. Implementing these technologies in BMWM helps minimize waste and ensure proper waste disposal. Locating and monitoring more types of waste and separating them using IoT service systems ensures adequate segregation.