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.
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 language | English |
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Title of host publication | Proceedings of the 11th Annual International Conference on Industrial Engineering and Operations Management Singapore, March 7-11, 2021 |
Pages | 3493-3499 |
Number of pages | 7 |
Publication status | Published - 31 May 2017 |
Event | 11th Annual International Conference on Industrial Engineering and Operations Management 2021 - Singapore, Singapore Duration: 7 Mar 2021 → 11 Mar 2021 |
Conference
Conference | 11th Annual International Conference on Industrial Engineering and Operations Management 2021 |
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Country/Territory | Singapore |
City | Singapore |
Period | 7/03/21 → 11/03/21 |
Keywords
- water consumption
- machine learning
- artificial neural network
- monitoring and clustering