Mobile sensor networks for optimal leak and backflow detection and localization in municipal water networks. (June 2016)

• Record Type: Journal Article
• Authors: Gong, Weijiao; Suresh, Mahima Agumbe; Smith, Lidia; Ostfeld, Avi; Stoleru, Radu; Rasekh, Amin; Banks, M. Katherine
• Is Part Of: Environmental modelling & software. Volume 80(2016:Jun.)
• Page Start: 306
• Page End: 321
• Publication Date: 2016-06
• Subjects: Mobile wireless sensor network -- Leak detection -- Backflow detection -- Source identification -- Localization -- Water distribution systems -- Municipal water networks; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2016.02.001
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Leak and backflow detections are essential aspects of Water Distribution Systems (WDSs) monitoring and are commonly fulfilled using approaches that are based on static sensor networks and point measurements. Alternatively, we propose a mobile, wireless sensor network solution composed of mobile sensor nodes that travel freely inside the pipes with the water flow, collect and transmit measurements in near-realtime (called sensors) and static access points (called beacons). This study complements the tremendous progress in mobile sensor technology. We formulate the sensor and beacon optimal placement task as a Mixed Integer Nonlinear Programming (MINLP) problem to maximize localization accuracy with budget constraint. Given the high time complexity of MINLP formulation, we propose a disjoint scheme that follows the strategy of splitting the sensor and beacon placement problems and determining the respective number of sensors and beacons by exhaustive search in linear time. Highlights: We present a mathematical model for the joint optimization of sensor and beacon placement to minimize localization error. We propose a computationally less expensive disjoint formulation for sensor and beacon placement. We demonstrate the advantage of our solution on a sample WDS from EPANET and a virtual model city called Micropolis.