Applications of Artificial Intelligence (AI) Technology and Tools in the Monitoring and Management of Environmental Pollution and Pollution Controlling Aspects: A Review

Aluvihara S, Hamdi MS, Alqasi NJK, Pestano-Gupta F, Omar MH and Khalifa ZA

Published on: 2026-02-28

Abstract

Environmental pollution poses an existential threat to biodiversity, human health, and ecosystem stability. Traditional methods of monitoring and managing pollution are often resource-intensive, time-consuming, and limited in scope, struggling to keep pace with the scale and complexity of modern environmental challenges. This review paper comprehensively explores the transformative role of Artificial Intelligence (AI) technologies and tools in revolutionizing environmental pollution monitoring, management, and control. We delve into specific applications across various pollution types, including air, water, soil, noise, and waste, highlighting how machine learning, deep learning, computer vision, natural language processing, fuzzy logic, and expert systems are employed. The paper elaborates on AI's contributions to real-time data acquisition and analysis, predictive modeling, anomaly detection, optimization of pollution control processes, development of early warning systems, and informed decision-making for policy formulation and remediation strategies. Furthermore, we discuss the current challenges in AI adoption, such as data quality, model interpretability, computational demands, and ethical considerations. Finally, the paper outlines future directions and emerging trends, including federated learning, digital twins, and explainable AI (XAI), emphasizing the need for interdisciplinary collaboration and robust ethical frameworks to fully harness AI's potential in creating a sustainable and pollution-free future. This extensive review synthesizes findings from over 50 academic articles, providing a holistic perspective on the current state and future prospects of AI in environmental stewardship.