Smart sewer monitoring system

Project Member(s): Kodagoda, S., Ranasinghe, R., Dissanayake, G.

Funding or Partner Organisation: South Australian Water Corporation

Start year: 2015

Summary: Sewer corrosion is a significant problem to all wastewater managing utilities around the globe. Australia is not an exception. The work proposes here investigates the state of the art sewer monitoring systems and making innovations in enhanced sewer monitoring capability. With current understanding, the factors that affect sulphide induced sewer corrosion are: the amount of gas phase H2S, surface wall temperature, surface moisture content and acidophilic bacterial activity. There are commercially available gas phase H2S monitors in the market. To our understanding, there is no technology available to measure the other important above factors in sewer conditions. Therefore development of innovative sensing and processing strategies will enhance the current capabilities of sewer monitoring. It is also aimed at prototyping a robust deployable unit which can provide three dimensional maps of the sewers with overlaid other measurements of interest. These measurements will enhance the water utility's (Sydney Water¿s) current sewer monitoring capabilities and provide valuable information to the NICTA¿s data analytic models and UoN analysis.

Publications:

Thiyagarajan, K, Kodagoda, S, Ranasinghe, R, Vitanage, D & Iori, G 2020, 'Robust Sensor Suite Combined With Predictive Analytics Enabled Anomaly Detection Model for Smart Monitoring of Concrete Sewer Pipe Surface Moisture Conditions', IEEE Sensors Journal, vol. 20, no. 15, pp. 8232-8243.
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Thiyagarajan, K, Kodagoda, S, Ulapane, N & Prasad, M 1970, 'A Temporal Forecasting Driven Approach Using Facebook’s Prophet Method for Anomaly Detection in Sewer Air Temperature Sensor System', 2020 15th IEEE Conference on Industrial Electronics and Applications (ICIEA), 2020 15th IEEE Conference on Industrial Electronics and Applications (ICIEA), IEEE, Kristiansand, Norway, pp. 25-30.
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Thiyagarajan, K, Kodagoda, S, Ranasinghe, R, Vitanage, D & Iori, G 2018, 'Robust sensing suite for measuring temporal dynamics of surface temperature in sewers', Scientific Reports, vol. 8, no. 1.
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Thiyagarajan, K, Kodagoda, S, Van Nguyen, L & Ranasinghe, R 2018, 'Sensor Failure Detection and Faulty Data Accommodation Approach for Instrumented Wastewater Infrastructures', IEEE Access, vol. 6, no. 1, pp. 56562-56574.
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Li, B, Fan, X, Zhang, J, Wang, Y, Chen, F, Kodagoda, S, Wells, T, Vorreiter, L, Vitanage, D, Iori, G, Cunningham, D & Chen, T 1970, 'Predictive Analytics Toolkit for H2S Estimation and Sewer Corrosion', OZWater, OZWater, Australian Water Association, Sydney.

Thiyagarajan, K, Kodagoda, S & Van Nguyen, L 1970, 'Predictive analytics for detecting sensor failure using autoregressive integrated moving average model', 2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA), 2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA), IEEE, Siem Reap, Cambodia, pp. 1926-1931.
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Ranasinghe, R & Kodagoda, S 1970, 'Spatial prediction in mobile robotic wireless sensor networks with network constraints', 2016 14th International Conference on Control, Automation, Robotics and Vision (ICARCV), 2016 14th International Conference on Control, Automation, Robotics and Vision (ICARCV), IEEE, Phuket, Thailand.
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Thiyagarajan, K & Kodagoda, S 1970, 'Analytical Model and Data-driven Approach for Concrete Moisture Prediction', Proceedings of the International Symposium on Automation and Robotics in Construction (IAARC), 33th International Symposium on Automation and Robotics in Construction, International Association for Automation and Robotics in Construction (IAARC), Auburn, Alabama, USA., pp. 298-306.
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Thiyagarajan, K, Kodagoda, S & Alvarez, JK 1970, 'An instrumentation system for smart monitoring of surface temperature', 2016 14th International Conference on Control, Automation, Robotics and Vision (ICARCV), 2016 14th International Conference on Control, Automation, Robotics and Vision (ICARCV), IEEE, Phuket, Thailand.
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Thiyagarajan, K, Kodagoda, S, Ulapane, N & IEEE 1970, 'Data-driven Machine Learning Approach for Predicting Volumetric Moisture Content of Concrete Using Resistance Sensor Measurements', PROCEEDINGS OF THE 2016 IEEE 11TH CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA), IEEE Conference on Industrial Electronics and Applications, IEEE, Hefei, China, pp. 1288-1293.
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Thiyagarajan, K, Kodagoda, S & IEEE 1970, 'SMART Monitoring of Surface Temperature and Moisture Content Using Multisensory Data Fusion', PROCEEDINGS OF THE 2015 7TH IEEE INTERNATIONAL CONFERENCE ON CYBERNETICS AND INTELLIGENT SYSTEMS (CIS) AND ROBOTICS, AUTOMATION AND MECHATRONICS (RAM), IEEE International Conference on Cybernetics and Intelligent Systems, IEEE, Siem Reap, Cambodia.
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Keywords: Sensing, data interpretation, sewer monitoring

FOR Codes: Control Systems, Robotics and Automation, Environmental Technologies, Water and Waste Services not elsewhere classified, Control engineering, mechatronics and robotics, Environmentally sustainable engineering

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.