A comprehensive IoT and blockchain-integrated framework for autonomous water management in sustainable urban ecosystems

Abstract

Different approaches to urbanization, decaying infrastructure, and climate change may blend into multiple pressures on the urban water management system. It would turn the limelight towards the intrinsic weaknesses of the systems in terms of traditional, centralized-inherently reactive, opaque, and unreliable-public systems. This proposed research brings a new decentralized paradigm synergistically utilizing IoT, blockchain technology, and machine learning in mutual respect and strength for resilient urban ecosystems. The architecture consists of IoT sensors for real-time monitoring and data collection, with water quality sensors and flow meters sending data through edge devices to a blockchain network, thereby ensuring integrity, security, and resistance to tampering. Respectively, machine learning algorithms embedded in the system will use historical and real-time data to perform predictive analytics to forecast future water demand and detect water-quality anomalies. This multi-layer architecture allows for real-time monitoring, transparency, automated decision-making, and intelligent resource reallocation. The results show significant improvements: predictive analytics for water demand forecasting achieved an F1-score of 91 %; the blockchain achieved 95 % fault tolerance; and energy efficiency improved by as much as 75 % at low-load conditions. Furthermore, the system provided low-latency communication and high transactions throughput, proving its scalability and applicability in different urban settings.