Artificial Intelligence and Machine Learning Techniques for Next-Generation Waste Management System: An Overview

This article presents an overview of artificial intelligence and machine learning techniques for next-generation waste management systems. Due to the rapidly increasing energy demand, waste management has gained popularity among energy sector professionals. Reutilizing waste resources is essential for achieving highly efficient energy use and improving human living standards. Waste management plays a critical role in developing resource-efficient lifestyles. This article also highlights several case studies that address energy convergence and the generation of smart energy from waste. Moreover, it provides an overview of emerging techniques involving artificial intelligence, machine learning, and internet of things for waste utilization, ensuring optimal resource use in waste management systems. Finally, through the examples and insights presented, the article demonstrates that waste management is central to advancing next-generation recycling energy systems and fostering sustainable development.

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Publication Details

Journal
Cureus Journal of Computer Science.
Published
2025-08-12
DOI
https://doi.org/10.7759/s44389-025-04880-y
Primary Topic
Municipal Solid Waste Management
Type
article
Field-Weighted Citation Impact
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article

Artificial Intelligence and Machine Learning Techniques for Next-Generation Waste Management System: An Overview

Nayan Kumar, Prabhansu Shrivastav
Cureus Journal of Computer Science.
Municipal Solid Waste Management
article

Artificial Intelligence and Machine Learning Techniques for Next-Generation Waste Management System: An Overview

Nayan Kumar, Prabhansu Shrivastav
article en

Abstract

This article presents an overview of artificial intelligence and machine learning techniques for next-generation waste management systems. Due to the rapidly increasing energy demand, waste management has gained popularity among energy sector professionals. Reutilizing waste resources is essential for achieving highly efficient energy use and improving human living standards. Waste management plays a critical role in developing resource-efficient lifestyles. This article also highlights several case studies that address energy convergence and the generation of smart energy from waste. Moreover, it provides an overview of emerging techniques involving artificial intelligence, machine learning, and internet of things for waste utilization, ensuring optimal resource use in waste management systems. Finally, through the examples and insights presented, the article demonstrates that waste management is central to advancing next-generation recycling energy systems and fostering sustainable development.

Cureus Journal of Computer Science.
Responsible consumption and production
Openalex Percentile: Top 75%
Municipal Solid Waste Management
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Artificial Intelligence and Machine Learning Techniques for Next-Generation Waste Management System: An Overview — Nayan Kumar, Prabhansu Shrivastav · Cureus Journal of Computer Science. (2025) | TGRS Research Map | TGRS