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Optimizing Water Resource Management and Environmental Conservation
Abstract
This paper investigates the optimization of water resource management and environmental conservation through AI-driven engineering solutions. Through case studies and research insights, it examines how artificial intelligence is revolutionizing traditional approaches to water management, including water quality monitoring, flood prediction, and drought mitigation. The study highlights the application of AI techniques such as machine learning, remote sensing, and hydroinformatics in analyzing large-scale water data, improving decision-making, and enhancing resilience to water-related challenges. Additionally, it discusses the integration of AI with IoT sensors, satellite imagery, and hydraulic models to enable real-time monitoring and adaptive management of water resources. The paper also addresses challenges such as data scarcity, interoperability, and stakeholder engagement in the adoption of AI-driven engineering solutions in water management. It emphasizes the need for interdisciplinary collaboration, policy support, and public participation to harness AI's potential in achieving sustainable and equitable water resource management for present and future generations.
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References
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