Paper Details

The increasing demand of clean water globally has been a major problem confronting water experts saddled with the responsibility of meeting the daily global water demand. Environmental challenges also poses danger in sustainability of water quality, making it necessary to develop strategies and innovative approaches to combat such. Artificial Intelligence (AI) is increasingly being recognized as a powerful tool in the field of sustainable water quality management, presenting significant progress in monitoring, forecasting, and decision-making procedures. This research explores the diverse use of Artificial Intelligence in improving water quality management and its sustainability. It examined the fusion of AI with real-time monitoring systems and remote sensing technologies, which furnish continuous and extensive data on a variety of water quality characteristics. The predictive models provide insights into future water quality scenarios, supporting proactive management strategies and risk assessment. Decision support systems, rooted in AI, enabled efficient and cost-efficient management strategies, while simultaneously involving the public through interactive platforms that raise awareness and encourage engagement. Despite the promising advantages, challenges such as data quality, technical complexity, high implementation costs, and ethical issues, need to be addressed to fully harness AI's potential. This review emphasized the importance of interdisciplinary collaboration, capacity building, and the establishment of ethical frameworks for a responsible and fair application of AI in water quality management. Critically assessing current advancements, restrictions, and future pathways, this analysis underscores the capability of AI to transform sustainable water quality management, ensuring the protection and endurance of crucial water resources for forthcoming generations. KEYWORDS:Sustainability, Artificial Intelligence, Predictive, Risk, Transform