A Mining Approach for Water Pipe line Leakage Detection and Localization

Abstract

A test based smart water meter distribution network is a water grid that provides reliable and capable to self protected and   trustworthy twenty four hours throughout the week  water distribution service. The main of this experiment is that the water pipe line leakage identification and localization. The research based experiment main objective is that the identifying unexpected damages to the water pipelines and find out exact leakage location by using prime factor like longitude and latitude. Providers and Consumers are turning to the Internet of Thing, machine learning and deep learning algorithmic techniques to meet requirement. This is very wearisome task that the continuously look at the system and taking manually requirements. The Smart water meter nodes with hall sensors provide continuous measurements and warehoused in databasecaptured from the smart city water meter distribution grid. Thisresearch journal handlessmart water meter water distribution pipe line leakage detection and localization of faults. In order to find out leakage intensity estimation and exact leakage localization in water distribution pipelines the proposed frameworkuses the pulse rate, flow rate and quantity as prime factors with help of longitude and latitude.The various machine learning and deep learning algorithms are exhibits significantly better result in leakage detection and localization.