Impact of artificial intelligence for the recycling of organic waste

Abstract

Traditional methods for treating and recycling Organic Solid Waste (OSW) have inherent limitations, such as low efficiency, restricted accuracy, high costs, and potential environmental risks. In recent years, there has been a significant increase in the use of artificial intelligence (AI) techniques to address challenges in Organic Waste Management (OWM). AI has proven effective in solving complex problems, learning from experience, and managing uncertainty and incomplete data. This chapter provides a comprehensive review of various types of OSWs and their recycling for agriculture, biofuel, and biomass production. Moreover, the applications of AI in OWM and recycling processes are reviewed, especially in forecasting waste characteristics, predicting process parameters, and OWM planning. Information about various AI models, including the software platforms employed for implementing such models is compiled. Finally, challenges and insights associated with the application of AI techniques in OWM are highlighted.