Adoption of artificial intelligence and the internet of things in dental biomedical waste management

Abstract

The production of waste is an ongoing activity that must be managed efficiently to protect both the environment and the health of the general population. Therefore, proper management of waste from dental care is essential in protecting the environment's health, and it should become an inherent part of dental services.  This study’s primary objective was to use artificial intelligence in dental biomedical waste management. The goal of this project was to develop an automated technique for categorizing dental trash to enhance the process of managing biological waste. In the proposed research, the Support Vector Machine classifier has been regarded as the most effective method of classification for a dataset of Euclidean size. The most effective classifier used in the model is a support vector machine (with an accuracy of 96.5%, 95.9% specificity, and 95.3% sensitivity) when classifying the different types of garbage. The categorization is accomplished through machine learning techniques, to accurately separate waste into recycling categories, precisely four categories for dental biomedical waste. Based on the findings of these trials, This method has the potential to be used for garbage sorting and classification on different scales, which might aid in the scientific disposal of biological waste.