Abstract
As robust tools for different purposes, including prediction and clustering, data-centric (DC) and artificial intelligence (AI) techniques have been widely employed in land pollution studies. Considering this point, this chapter investigates a number of the recent studies utilizing DC and AI in the land pollution area, while also providing brief explanations about the main concepts in the field of land and soil pollution. After discussing the importance of the topic, the application of DC and AI learning methods in flow modeling of landfill leachate is investigated. Then, the discussion moves to the application of deep learning and machine learning methods in soil quality assessment and remediation, and next, establishing a nexus between nonbiodegradable waste and DC systems is explained. Case studies of evaluations and analyse of solid waste management techniques by DC and AI methods is included in the final part of the chapter.
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