Real-time reading system for pointer meter based on YolactEdge

Abstract

Despite the extensive deployment of digital instruments in modern times, their stability is challenging to maintain in adverse environmental conditions such as extreme temperatures, pressure, or powerful electromagnetic radiation. Analog meters, owing to their mechanical resilience and electromagnetic impedance, persistently find usage across nuclear power plants, petroleum, and chemical industries. However, under these harsh conditions, manual reading of the instruments may prove to be difficult and dangerous while failing to meet the requirements of real-time monitoring. In recent years, several machine vision-based meter reading systems have been proposed, however, achieving high accuracy through camera-based methods under varying angles and lighting conditions poses significant challenges. Cloud deployment may compromise plant privacy, while edge computing faces limitations in real-time meter reading due to limited computing power. To address these issues, we propose a real-time reading system based on the YolactEdge instance segmentation framework for single-point analog meters. Our system is more accurate than previous studies and is implemented and deployed on the Jetson Xavier NX edge computing device. Our performance evaluation shows that our model outperforms other baselines, with low reference values and relative errors of 0.0237% and 0.0300%, respectively, and an average inference speed of 10.26 FPS with INIT 8 linear acceleration on Nvidia Jetson NX.

Keywords:

• Real-time monitoring
• deep-vision
• edge computing
• instance segmentation
• Jetson Xavier NX

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was partially supported by the National Natural Science Foundation of China under Grants 62072170, the Key Research and Development Program of Hunan Province under Grant 2022GK2015, and the Hunan Provincial Natural Science Foundation of China under Grant 2021JJ30141, the Natural Science Research Project in Hechi University under Grant 2022YLXK003, and the Research Project of Improve the Basic Research Ability of Young Teachers in Guangxi Universities under Grant 2022KY0602.