Implement the detection of leaks and breaks - analytics

Project Member(s): Wang, Y., Chen, F., Verma, S., Liang, B.

Funding or Partner Organisation: Sydney Water Corporation
Sydney Water Corporation

Start year: 2020

Summary: Predictive analytics to detect leaks and breaks to minimise impact to customers in Sydney Water

Publications:

Ding, Y, Wang, L, Liang, B, Liang, S, Wang, Y & Chen, F 2023, 'Domain Generalization by Learning and Removing Domain-specific Features'.
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Nikoloska, R, Bykerk, L, Vitanage, D, Valls Miro, J, Chen, F, Wang, Y & Liang, B 2020, 'Enhancing Sydney Water’s leak prevention through acoustic monitoring', Water e-Journal, vol. 5, no. 2, pp. 1-15.
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Liang, B, Verma, S, Xu, J, Liang, S, Li, Z, Wang, Y & Chen, F 1970, 'A Data Driven Approach for Leak Detection with Smart Sensors', 2020 16th International Conference on Control, Automation, Robotics and Vision (ICARCV), 2020 16th International Conference on Control, Automation, Robotics and Vision (ICARCV), IEEE, Shenzhen, China, pp. 1311-1316.
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FOR Codes: Pattern Recognition and Data Mining, Water Services and Utilities, Data mining and knowledge discovery

Acknowledgement of Country

UTS acknowledges the Gadigal people of the Eora Nation, the Boorooberongal people of the Dharug Nation, the Bidiagal people and the Gamaygal people, upon whose ancestral lands our university stands. We would also like to pay respect to the Elders both past and present, acknowledging them as the traditional custodians of knowledge for these lands.