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

Abstract

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.

A systematic review of municipal smart water for climate adaptation and mitigation

“…Candelieri et al (2013) analyze flow and pressure data measured at crucial network points to improve efficiency of leak localization. Abdelhafidh et al (2020) develop a cognitive IoT-based architecture using a genetic algorithm for smart leak detection and localization. Sun et al, (2020) combine linear discriminant analysis, a neural network, and Bayes temporal reasoning for leak detection and localization in a District Metered Area.…”

“…Two studies specifically focus on measuring and managing pressures (Pan et al, 2015; Pérez-Padillo et al, 2020). Many studies focus on detecting and localizing pipe leaks (Abdelhafidh et al, 2020; Al-Bayari et al, 2020; Candelieri et al, 2013; Fabbiano et al, 2020; Farah and Shahrour, 2017; Hsia et al, 2020; Karray et al, 2016; Luciani et al, 2019; Mounce et al, 2015; Pointl and Fuchs-Hanusch, 2021; Rojek and Studzinski, 2019; Stephens et al, 2020; Sun et al, 2020; Wang., et al, 2020; Zhang., et al, 2020). One study focuses on helping water operators identify leaks with a web-based tool (Meseguer et al, 2014).…”

A cloud‐based service for emergency evacuation of mine water inrush accidents

“…As the levels of underground mining increase continuously in terms of intensity and depth, undesired phenomena such as high karst water pressure, high geostress, and strong mining disturbances contribute to the rising danger of underground mine flooding 1 . Nowadays, to our best knowledge, with the wide application of the Internet Of Things (IOT) technology and the deepening development of the coal mine enterprise information construction, 2 more and more the mining enterprises have equipped with various advanced monitoring systems to monitor the personnel location and underground environmental data such as water height and breathing gas composition. Data exchange and transmission between system servers and sensors can be carried out at any place as long as under the coverage of the industrial ring network.…”