Artificial intelligence applications in solid waste management: A systematic research review.
By M. Abdallah, Manar Abu Talib, Sainab Feroz, Qassim Nasir, Hadeer Abdalla, Bayan Mahfood. Waste Management, 2020
398 citations recorded by the source corpus.
The waste management processes typically involve numerous technical, climatic, environmental, demographic, socio-economic, and legislative parameters. Such complex nonlinear processes are challenging to model, predict and optimize using conventional methods. Recently, artificial intelligence (AI) techniques have gained momentum in offering alternative computational approaches to solve solid waste management (SWM) problems. AI has been efficient at tackling ill-defined problems, learning from experience, and handling uncertainty and incomplete data. Although significant research was carried out in this domain, very few review studies have assessed the potential of AI in solving the diverse SWM problems. This systematic literature review compiled 85 research studies, published between 2004 and 2019, analyzing the application of AI in various SWM fields, including forecasting of waste characteristics, waste bin level detection, process parameters prediction, vehicle routing, and SWM planning. This review provides comprehensive analysis of the different AI models and techniques applied in SWM, application domains and reported performance parameters, as well as the software platforms used to implement such models. The challenges and insights of applying AI techniques in SWM are also discussed.
Subfields: Environmental Engineering, Industrial and Manufacturing Engineering, Public Health, Environmental and Occupational Health
View Paper: https://www.semanticscholar.org/paper/8098ee5d7236138d43d930fb1631677ec3fa62a0
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Citations in the corpus
- Artificial intelligence for waste management in smart cities: a review (2023, background): “Artificial intelligence is a rapidly advancing technology that is gaining popularity in various industries, particularly waste management (Abdallah et al. 2020).”