An Autonomous Smart Water Grid Integrating IoT Sensors, Edge AI, Self-Healing Mechanisms, Fair Distribution Algorithms, and Predictive Water Management
Keywords:
Edge AI, IoT, Predictive analytics, Self-healing system, Smart cities, Smart water grid, Water distributionAbstract
This paper presents an advanced Autonomous Smart Water Grid that integrates Internet of Things (IoT) sensors with artificial intelligence (AI)-based decision systems to enhance water management efficiency, sustainability, and reliability. The proposed system enables real-time monitoring of critical parameters such as water level, flow rate, pressure, and water quality using a network of distributed IoT sensors. Edge AI techniques are employed for localized decision-making, significantly reducing latency and minimizing dependence on continuous network connectivity. Key features of the system include a self-healing mechanism for automatic fault detection, isolation, and rerouting of the water supply, ensuring uninterrupted service delivery. A fair distribution algorithm is incorporated to guarantee equitable water allocation among users, while a water credit system regulates consumption and promotes responsible usage. Additionally, predictive demand mapping and pipe health monitoring modules support proactive planning and preventive maintenance, reducing infrastructure failures. The system effectively minimizes water wastage, detects leakages in real time, prevents unauthorized usage, and optimizes resource allocation. Experimental analysis demonstrates improved operational efficiency, reduced water losses, enhanced scalability, and adaptability, making the proposed solution suitable for both urban smart cities and rural water management applications.
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