A genetic algorithm‐based intelligent solution for water pipeline monitoring system in a transient state.

Summary: Water pipeline monitoring system becomes a relevant solution to cope with various pipeline hydraulic failures in order to save the environment from water losses. In this respect, cognitive water distribution system (WDS) combines Internet of Things (IoT) technology with Big Data generated by various connected objects and devices for reliable structural health monitoring of pipelines. Accordingly, designing a scalable WDS with smart leak detection and localization requires a serious study and an adequate planning. In this paper, we suggest a cognitive IoT‐based architecture with adequate data collection based on the Apache Spark framework. Furthermore, our objective is to elaborate a hybrid mechanism that defines and performs accurate leakage identification and localization by taking into account both the steady‐state and transient behavior of water. The bio‐inspired sensitivity analysis of the water pressure profile based on the genetic algorithm ensures the effectiveness and the accuracy of the proposed monitoring solution. [ABSTRACT FROM AUTHOR]