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Real-time embedded system for valve detection in water pipelines

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Abstract

Condition assessment is an essential process to comprehend the condition of the water pipelines and facilitate the maintenance as well as the renewal plans. Nowadays, varied in-pipe inspection platforms equipped with closed-circuit cameras are employed to capture the internal condition of the water pipelines. However, the automated platform often faces the challenge to negotiate with the installed valves during the inspection. To ensure continuous inspection, the platform needs identify the valve automatically and activate the control mechanism to pass through it. Thus, the valves need to be detected to facilitate the negotiation and ensure that the control mechanism can take an action in time. This paper focuses on real-time valve detection using Jetson TX2™ and a lightweight algorithm, namely YOLOv3-tiny. The performance of the implementation is compared with state-of-the-art real-time detection models. The experimental results demonstrate that YOLOv3-tiny has a high detection speed in frame per second for valve detection and outperforms the state-of-the-art real-time algorithms. Hence, the deployment YOLOv3-tiny into the embedded system will aid the automated platform to accomplish the uninterrupted inspection and enhance the capability for the condition assessment of the water pipelines.

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Acknowledgements

Natural Sciences and Engineering Research Council of Canada (NSERC) is acknowledged for its support through the “Collaborative Research and Development Grants” (CRDPJ523761-18). The authors would also like to express the gratitude towards Pure Water-Xylem, Mississauga, Ontario, Canada for their kind support to this research.

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Authors and Affiliations

  1. School of Engineering, University of British Columbia, Kelowna, Canada

    Rakiba Rayhana, Yutong Jiao & Zheng Liu

  2. Pure Water-Xylem, Mississauga, ON, Canada

    Angie Wu & Xiangjie Kong

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  1. Rakiba Rayhana
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Correspondence to Zheng Liu.

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Rayhana, R., Jiao, Y., Liu, Z. et al. Real-time embedded system for valve detection in water pipelines. J Real-Time Image Proc 19, 247–259 (2022). https://doi.org/10.1007/s11554-021-01178-9

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