AI-Powered Smart Water Distribution System: An Intelligent Approach for Resource Optimization
Keywords:
Smart Water Distribution,, Artificial Intelligence, Machine Learning, Internet of Things,, Leak Detection, Demand Forecasting, Resource Optimization, Deep Learning, Reinforcement LearningAbstract
Water distribution systems face critical challenges
including leakage detection, demand prediction, and
optimization of resource allocation. This research
presents a novel AI-powered smart water distribution
system that integrates machine learning algorithms,
IoT sensors, and cloud computing to revolutionize
water management. The proposed system employs a
hybrid approach combining deep learning for demand
forecasting, reinforcement learning for valve control
optimization, and anomaly detection algorithms for
leak identification. Experimental results demonstrate
significant improvements in water conservation
(28%), operational cost reduction (32%), and leak
detection accuracy (94.7%) compared to conventional
systems. The framework's scalable architecture allows
for seamless implementation across various urban
water infrastructures, offering a sustainable solution
to global water management challenges.
