Machine Learning Application in Solid Waste Management

Abstract

In this paper, we present a comprehensive review of research dedicated to applications of machine learning in Solid waste management. The works analyzed were categorized in classes of three generic categories; namely, prediction of waste generation model, waste detection models, optimization of collection and disposal models. The paper reviewed studies from 2008 that focusing the three domain and the different machine learning models used to solve waste management challenge. The analysis prioritized domain in prediction of generation, detection and finally optimization of collection solid waste, the findings indicated GIS-based optimized using ArcGIS Network Analyst tool applied on variables such as cost, route distance and number of trucks, gives the best results. Further research will be carried out in future to realize and validate the tool.