Intelligent Systems Lab

Author(s): Evangelos Syrmos, Vasileios Sidiropoulos, Dimitrios Bechtsis, Fotis Stergiopoulos, Eirini Aivazidou, Dimitris Vrakas, Prodromos Vezinias and Ioannis Vlahavas

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Appeared In: Accepted for Publication in Sustainability, Special Issue on Water Management and Environmental Engineering

Keywords: Smart Cities; IoT; LoRaWAN; LoRa; Smart meters; Water Quality Monitoring; Machine Learning

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Abstract: This work proposes a modular water monitoring IoT system that enables quantitative and qual-itative measuring of water in terms of an upgraded version of the water infrastructure to sustain operational reliability. The proposed method could be used in urban and rural areas for con-sumption and quality monitoring, or eventually scaled up to a contemporary water infrastructure enabling water providers and/or decision-makers (government, global water organization etc.) to supervise and drive optimal decisions in troubling times. The inherent resilience and agility that the presented system presents along with the maturity of IoT communications and infra-structure can lay the foundation for a robust smart water metering solution. Introducing a mod-ular system can also allow for optimal consumer profiling while alleviating the upfront adoption cost by providers, environmental stewardship and an optimal response to emergencies. The pro-vided system addresses the urbanization and technological gap in the smart water metering do-main by presenting a modular IoT architecture with consumption and quality meters along with Machine Learning capabilities to facilitate smart billing and user profiling, all the while enabling the development of new business models and monetization strategies on a finite commodity.