Abstract
Recently, the governments promote the employment of persons with physical, intellectual, mental or other disabilities and employers must ensure safety in the workplace. However, technical training for the person with disabilities requires explanation of detailed work procedures and the burden on the trainer is increased by monitoring to prevent accidents. In this paper, in order to solve these problems, we presents the analysis of soldering motion for dozing state and attention posture detection based on object detection and posture estimation. Also, we show the experimental results for dozing state and attention posture detection during soldering iron. The experimental results show that the proposed system can detect the dozing state with high accuracy.
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This work was supported by JSPS KAKENHI Grant Number JP20K19793.
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Toyoshima, K. et al. (2023). Analysis of a Soldering Motion for Dozing State and Attention Posture Detection. In: Barolli, L. (eds) Advances on P2P, Parallel, Grid, Cloud and Internet Computing. 3PGCIC 2022. Lecture Notes in Networks and Systems, vol 571. Springer, Cham. https://doi.org/10.1007/978-3-031-19945-5_14
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DOI: https://doi.org/10.1007/978-3-031-19945-5_14
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