An Efficient Smart Waste Management System Using Machine Learning

Introducing a smart waste management system using Machine Learning (ML) on waste management is a novel idea in waste management. This particular system employs the Internet of Things (IoT), sensors, and ML algorithms to form an evaluation of the data that are collected. The system is intended to view the waste collection and disposal process. The waste bins are outfitted with sensors that allow the monitoring of aspects such as fill level, the weight and position of the bin. After going through the data, the algorithms tell the quantity of waste produced, how often it should be collected, and how to dispose of it. In general, incorporating ML into SWM can be considered the solution for improvement and unburdening of the traditional system, and, thereby, contribute to a more sustainable future. It assists in the identification and consequent segregation of the types of waste by the use of sensors and storage. The proposed system has reduced the number of paths by 36.8% and cost by 13.35% through the implementation of cycle route optimization. For instance, dynamic scheduling as well as changing the routes on the basis of the real time information helps to decrease the distance to be traveled by the collection trucks, and, therefore, helps to decrease fuel costs, as well as labor costs. This efficiency can be supported by simulation models indicating possible declines in operating costs. ML can identify and separate waste with an accuracy of 72.8 to 99.95%.