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Intelligent Service Robot for High-Speed Railway Passengers

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Data Science (ICPCSEE 2021)

Abstract

With the rapid development of road traffic, the number of high-speed rail passengers is huge, and the flow of people is dense. In epidemic situation, it is prone to intensive infection in high-speed rail carriages, which is not conducive to national prevention and control work. Based on face recognition technology, the intelligent service robot for high-speed rail passengers walks in accordance with the set route and detects the face mask of high-speed rail passengers. The face database of high-speed rail passengers is compared in real time. The passengers who do not wear masks are reminded in time to reduce the risk of infection. Moreover, the robot can accurately remind the passengers of leaving the station in time, and has the functions of automatic selling and student ticket checking. The experimental result is shown to promote the further development of high-speed rail services.

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Acknowledgement

This article is supported by the 2020 Innovation and Entrepreneurship Training Program for College Students in Jiangsu Province (Project name: high-speed railway passenger behavior management system, No. 202011460091T).

This article is supported by the National Natural Science Foundation of China Youth Science Foundation project (Project name: research on Deep Discriminant Spares Representation Learning Method for Feature Extraction, No. 61806098).

This article is supported by Scientific Research Project of Nanjing Xiaozhuang University (Project name: multi-robot collaborative system, No. 2017NXY16).

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Sheng, R., Wang, Y., Huang, L. (2021). Intelligent Service Robot for High-Speed Railway Passengers. In: Zeng, J., Qin, P., Jing, W., Song, X., Lu, Z. (eds) Data Science. ICPCSEE 2021. Communications in Computer and Information Science, vol 1452. Springer, Singapore. https://doi.org/10.1007/978-981-16-5943-0_21

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  • DOI: https://doi.org/10.1007/978-981-16-5943-0_21

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-5942-3

  • Online ISBN: 978-981-16-5943-0

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