Detecting NRW using Internet of Things and Artificial Intelligence
Smart data-driven methods for detecting water losses in public networks are becoming very popular. Such solutions are based on the application of the Internet of Things and Artificial Intelligence (AI) techniques, whereby “AI” algorithms are trained with large real-time flow and pressure datasets collected through smart meters. “AI” is then used to extract information, validate hydraulic models, detect patterns and highlight anomalies. This helps service providers narrow the search area for losses within large public networks and make evidence-based and timely decisions for corrective actions, thus saving time and resources invested in reducing Non-Revenue Water (NRW).
Accelerator Lab Experiment
The UNDP/PAPP’s Accelerator Lab partnered with a promising start-up company, FlowLess, to test a locally developed and cost-efficient smart system for detecting water losses using IoT and AI, supported with a customized web-platform. The start-up team brings together four talented young innovators and experts in water engineering, mechatronics and software development. This locally developed solution is envisioned to assist water service providers to accurately collect data and provide rigorous analysis on the status, sources and location of leakage or losses in public water networks. This solution also helps service providers monitor water networks remotely during times of crises when movement is restricted. The experiment was conducted in selected areas in Tammun and Ras Al Far’a in Tubas governorate in the West Bank. The Accelerator Lab and FlowLess collaborated with the Tubas Joint Service Council for Water and Wastewater (JSCWW), who showed a high sense of ownership and support for this experiment, which is key for the uptake and sustainability of the solution.
The Accelerator Lab acknowledges that similar solutions are provided by global companies specialized in water management; however, the challenge resides in affordability, especially that integrated smart water management systems are very expensive, and in many cases, service providers purchase or install part of the system. Experts in this field also explained how these solutions require large investments in updating the existing water infrastructure to comply with the smart system requirements, not to mention the costly maintenance, web-platform subscription, update fees, difficulty in accessing on-the ground technical support, and following-up post installation.
The experiment with FlowLess was designed to test whether this locally developed solution can address these challenges and provide an alternative sustainable, affordable and flexible smart water management system that can be adapted to water networks’ infrastructure, whose technology and complexity vary across Palestinian communities. Most importantly, The Accelerator Lab wanted to showcase through a field demonstration how a local private enterprise that is committed to social impact can assist and collaborate with local government units and joint service councils in addressing NRW. The water sector is crippled with complex challenges, and efficient management is key to maintain quality service delivery to citizens, and such unusual partnerships could foster solutions that would have otherwise been unattainable.