Monitoring water consumption using machine learning

Malek Almobarek, Abdalla Alrashdan

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

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Abstract

This paper concerns one of the most important elements in economic life, which is water. Normally, the user, who is responsible to manage water services, is not aware about the consumption situation prior to issuing the bill, so, this research proposes innovative managerial techniques to monitor water consumption across the network. Machine learning is used through clustering techniques to achieve the monitoring goal, which contributes towards decision making, fault prediction, and data management processes.in facility management. Artificial Neural Network is the specific part of the chosen technique and Python is used as a tool to implement the method. A case study is applied in one of the universities and a network including six locations is studied at a specific time. The method shows a
significant result where the consumption at three locations were found high and accordingly, the user made further inspection and continuous monitoring about the network in discussion.
Original languageEnglish
Title of host publicationProceedings of the 11th Annual International Conference on Industrial Engineering and Operations Management Singapore, March 7-11, 2021
Pages3493-3499
Number of pages7
Publication statusPublished - 31 May 2017
Event11th Annual International Conference on Industrial Engineering and Operations Management 2021 - Singapore, Singapore
Duration: 7 Mar 202111 Mar 2021

Conference

Conference11th Annual International Conference on Industrial Engineering and Operations Management 2021
Country/TerritorySingapore
CitySingapore
Period7/03/2111/03/21

Keywords

  • water consumption
  • machine learning
  • artificial neural network
  • monitoring and clustering

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