Advancing Water Data Ecosystems: Identifying and Optimizing Connectivity and Beyond-Connectivity Requirements with 5G/6G Technologies

This paper examines the connectivity and beyond-connectivity requirements essential for water data ecosystems, highlighting the critical role of advanced communication technologies, such as 5G/6G, in enabling rapid, reliable data transmission for real-time monitoring and decision-making. Optimizing communication protocols supports robust infrastructure, interoperability among diverse sources, including environmental sensors, weather data, and utility-provided information, and seamless data integration and utilization, while promoting innovation, efficiency, and sustainability in water management.

The study is structured in two main parts. First, it identifies specific connectivity and beyond-connectivity requirements, focusing on the integration of various water data sources and evaluating the efficacy of communication protocols to support dynamic data integration, including capabilities like artificial intelligence, sensing, and sustainability. This forms the foundation for subsequent analysis. Second, it analyzes and optimizes connectivity services offered by 5G/6G and beyond technologies to meet these requirements, considering factors such as energy efficiency, reliability, scalability, and integrated services like sensing, AI, and computation.

The study aims to demonstrate that addressing these requirements enhances the integration and utilization of diverse water data, facilitating access to information, development of new solutions, improved understanding of water management challenges, and innovation in water supply through enhanced prediction models and more efficient, sustainable solutions. It identifies and optimizes key performance indicators (KPIs) as well as services derived from standardization bodies, tailored to water-related use cases such as leak detection, wastewater monitoring, and resource efficiency. These include ultra-low latency for critical alerts, high reliability for infrastructure control, energy efficiency in sensor networks, scalability for IoT-dense environments, and integrated AI for dynamic data processing. Anticipated insights reveal how water data ecosystems can overcome challenges like demand-supply gaps through efficient data collection, sharing, and utilization, while addressing barriers such as limited data availability and regulatory constraints. This necessitates clear visions, effective data-sharing mechanisms, and scalable architectures to drive innovation and reduce water loss.

The proposed framework facilitates informed strategies and new opportunities for stakeholders in water utilities and related sectors. This study advances the understanding of digitalization in critical infrastructure, demonstrating how optimized connectivity can promote efficiency and sustainability in water management.