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

Sree, T. Raja; Kanmani, S.

doi:10.1080/21622515.2023.2293679

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2024

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Cited by 3 publications

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A Proposed Framework of Integrating Artificial Intelligence in Green Computing for Business Sustainability

Bahaaudeen

2024

Studies in Systems, Decision and Control

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A Proposed Framework of Integrating Artificial Intelligence in Green Computing for Business Sustainability

Bahaaudeen

2024

Studies in Systems, Decision and Control

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ITS-AI Integration: Enhanced Strategies for Mitigating Urban Traffic Congestion

Santhiya,

Jebadurai,

Paulraj

et al. 2024

2024 5th International Conference on Recent Trends in Computer Science and Technology (ICRTCST)

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Featuring Machine Learning in Municipal Solid Waste Management

Singh,

Kaunert,

Malviya

2024

Practice, Progress, and Proficiency in Sustainability

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Due to the expansion of urban areas and the steady growth of the global population, the management of municipal solid waste has become increasingly complex in recent times. Inadequate handling of waste poses risks to the environment, public health, and exacerbates greenhouse gas emissions. There are various approaches such as the principle of reduce, reuse, recycle, and recover have been introduced to tackle these challenges. However, effectively implementing these strategies remains intricate and challenging. Machine learning stands out as a promising technology with the potential to revolutionize municipal solid waste management. ML can play a pivotal role in streamlining waste sorting and segregation processes, thereby enhancing the efficiency and cost-effectiveness of waste management operations. This chapter explores the machine learning enables route optimization, waste categorization, and prediction of waste characteristics, aiming to enhance efficiency, reduce costs, and minimize environmental impact solid waste management.

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

Cited by 3 publications

References 55 publications

A Proposed Framework of Integrating Artificial Intelligence in Green Computing for Business Sustainability

A Proposed Framework of Integrating Artificial Intelligence in Green Computing for Business Sustainability

ITS-AI Integration: Enhanced Strategies for Mitigating Urban Traffic Congestion

Featuring Machine Learning in Municipal Solid Waste Management

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