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Meter Location System Base on Jetson NX

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Smart Computing and Communication (SmartCom 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13828))

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Abstract

Analog meter is still widely used due to their mechanical stability and electromagnetic impedance. Relying on humans to read mechanical meters in some industrial scenarios is time-consuming or dangerous, it is difficult for current meter reading robots to operate quickly and maintain high accuracy in edge computing devices. Computer vision-based meter reading systems can solve such dilemmas. We designed an SSD network-based meter image acquisition system that can run in real time in an NVIDIA Jetson NX development board. Moreover, the model can quickly classify meter types and locate meter coordinates in the presence of light changes, complex backgrounds, and camera angle deflection. Tested on NVIDIA Jetson NX using TensorRT acceleration, the inference speed and accuracy reached 9.238 FPS and 53.95 mAP, respectively.

Supported by Hechi University.

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Acknowledgements

This work was supported in part by the Natural Science Research Project in Hechi University (NO. 2022YLXK003). And Project to improve the basic research ability of young teachers in Guangxi universities (NO. 2022KY0602).

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Authors and Affiliations

  1. Hechi University, Hechi, Guangxi, China

    Chengjun Yang & Ling zhou

  2. School of Computer Science and Engineering, Hunan University of Science and Technology, Xiangtan, Hunan, China

    Ce Yang

  3. Hunan Key Laboratory for Service computing and Novel Software Technology, Xiangtan, China

    Ce Yang

Authors
  1. Chengjun Yang
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  2. Ling zhou
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  3. Ce Yang
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Corresponding author

Correspondence to Ce Yang .

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Editors and Affiliations

  1. Dakota State University, Madison, SD, USA

    Meikang Qiu

  2. Fudan University, Shanghai, China

    Zhihui Lu

  3. Ibaraki University, Ibaraki, Japan

    Cheng Zhang

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Yang, C., zhou, L., Yang, C. (2023). Meter Location System Base on Jetson NX. In: Qiu, M., Lu, Z., Zhang, C. (eds) Smart Computing and Communication. SmartCom 2022. Lecture Notes in Computer Science, vol 13828. Springer, Cham. https://doi.org/10.1007/978-3-031-28124-2_4

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  • DOI: https://doi.org/10.1007/978-3-031-28124-2_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-28123-5

  • Online ISBN: 978-3-031-28124-2

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