A comprehensive review of the role of soft computing techniques in municipal solid waste management

ABSTRACT

In today's world, Municipal Solid Waste (MSW) management is considered the primary issue for protecting the surrounding environment, individuals, and natural resources. To effectively protect it, various strategies have been developed. Among various strategies, many attempts have been made from the perspective of soft computing, especially through Artificial Intelligence (AI) techniques aimed at achieving better results. Although much research has been conducted in this field, few efforts have focused on using AI to solve MSW problems. This article systematically reviews soft computing techniques related to waste management (for example, MSW generation, collection, treatment, and disposal). This review comprehensively analyses the contribution of different AI technologies to various evolutionary algorithms, such as Artificial Neural Networks (ANN), fuzzy-based methods, Genetic Algorithms (GA), Ant Colony Optimization (ACO), etc., and machine learning algorithms such as Support Vector Machines (SVM), Multiple Linear Regression (MLR), etc., that are used to solve MSW problems. It is observed from the literature that 53% of researchers use evolutionary algorithms and 47% of researchers use machine learning algorithms to solve MSW problems.

GRAPHICAL ABSTRACT

KEYWORDS:

• Artificial intelligence
• artificial neural network
• deep learning
• municipal solid waste management
• machine learning

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

T. Raja Sree

T Raja Sree received her B.Tech. degree from the Department of Information Technology, Anna University, Chennai, India in 2008, and M.Tech. degree from the Department of Information Technology, Anna University, Coimbatore in 2010. She received her Ph.D. degree at the Department of Computer Science and Engineering at the National Institute of Technology, Tiruchirappalli, India in 2018. She is currently working as an Assistant Professor Senior in the Department of Computer Science and Engineering at the Vellore Institute of Technology Chennai. She worked as an Ad-hoc Faculty in the Department of Computer Science and Engineering at the National Institute of Technology, Calicut, India. She has more than 10 years of teaching experience at undergraduate and postgraduate levels. Her research interests include Cloud computing, Cloud security, Cloud Forensics, and Fog Computing.

S. Kanmani

S Kanmani received her B.E. degree from the Department of Civil Engineering, Anna University, Chennai, India in 2008, and M.E. degree from the Department of Environmental Engineering, Anna University, Coimbatore in 2010. She received her Ph.D. degree at the Department of Civil Engineering at the National Institute of Technology, Tiruchirappalli, India in 2014. She is currently working as an Associate Professor in the Department of Civil Engineering at the KPR Institute of Engineering and Technology Coimbatore. She has more than 10 years of teaching experience at undergraduate and postgraduate levels. Her research interests include Waste management, Wastewater treatment, and Water Treatment.