Solid waste management techniques powered by in-silico approaches with a special focus on municipal solid waste management: Research trends and challenges

Shaili Vyas; Kusum Dhakar; Sunita Varjani; Reeta Rani Singhania; Preeti Chaturvedi Bhargava; Raveendran Sindhu; Parameswaran Binod; Jonathan W C Wong; Xuan-Thanh Bui

doi:10.1016/j.scitotenv.2023.164344

Solid waste management techniques powered by in-silico approaches with a special focus on municipal solid waste management: Research trends and challenges

Sci Total Environ. 2023 Sep 15:891:164344. doi: 10.1016/j.scitotenv.2023.164344. Epub 2023 May 25.

Authors

Shaili Vyas¹, Kusum Dhakar², Sunita Varjani³, Reeta Rani Singhania⁴, Preeti Chaturvedi Bhargava⁵, Raveendran Sindhu⁶, Parameswaran Binod⁷, Jonathan W C Wong⁸, Xuan-Thanh Bui⁹

Affiliations

¹ Swinburne University of Technology, Hawthorn, Melbourne, Victoria 3122, Australia.
² Department of Biochemistry and Biotechnology, University of Thessaly, 41500, Greece.
³ School of Energy and Environment, City University of Hong Kong, Tat Chee Avenue, Kowloon 999077, Hong Kong; Sustainability Cluster, School of Engineering, University of Petroleum and Energy Studies, Dehradun 248 007, Uttarakhand, India. Electronic address: drsvs18@gmail.com.
⁴ Department of Marine Environmental Engineering, National Kaohsiung University of Science and Technology, Kaohsiung City 81157, Taiwan.
⁵ Aquatic Toxicology Laboratory, Environmental Toxicology Group, Council of Scientific and Industrial Research-Indian Institute of Toxicology Research (CSIR-IITR), Vishvigyan Bhawan, 31, M.G. Marg, Lucknow 226001, Uttar Pradesh, India.
⁶ Department of Food Technology, T K M Institute of Technology, Kollam 691 505, Kerala, India.
⁷ CSIR-National Institute for Interdisciplinary Science and Technology (NIIST), Trivandrum 695 019, Kerala, India.
⁸ Institute of Bioresource and Agriculture, Hong Kong Baptist University, Hong Kong.
⁹ Faculty of Environment and Natural Resources, Ho Chi Minh City University of Technology (HCMUT), Ho Chi Minh City 700000, Viet Nam; Key Laboratory of Advanced Waste Treatment Technology, Vietnam National University Ho Chi Minh (VNU-HCM), Linh Trung ward, Thu Duc district, Ho Chi Minh City 700000, Viet Nam.

PMID: 37244611
DOI: 10.1016/j.scitotenv.2023.164344

Abstract

Many technical, climatic, environmental, biological, financial, educational, and regulatory factors are typically involved in solid waste management (SWM). Artificial Intelligence (AI) techniques have lately gained attraction in providing alternative computational methods for resolving problems of solid waste management. The purpose of this review is to direct solid waste management researchers taking an interest in the use of artificial intelligence in their area of study through main research elements such as AI models, their own benefits and drawbacks, effectiveness, and applications. The major AI technologies recognized are discussed in the subsections of the review, which contains a specific fusion of AI models. It also covers research that equated AI technologies to other non-AI methodologies. The section that follows contains a brief debate of the numerous SWM disciplines where AI was consciously applied. The article concludes with progress, challenges and perspectives in implementing AI-based solid waste management.

Keywords: Artificial intelligence; Artificial neural networks; Genetic algorithm; Municipal solid waste; Support vector machine.

Publication types

Review