Train location detection plays a crucial role in maintaining the railway transportation system. Train crew can use train location information to perform daily tasks such as adding passengers, train coupling and routine inspection. As train operation conditions become increasingly complex, achieving convenient and relatively accurate positioning can facilitate crew members in performing their daily tasks. This paper proposes a new method that uses smartphones as a sensing platform to collect train vibration data and combines neural network technology for position monitoring, providing a new reference method for train position monitoring. In the first stage, data is collected through mobile phone sensors and fused to achieve preliminary positioning. In the second stage, a neural network model is trained to detect targets at key locations. Finally, the above methods are further integrated and compared on the actual route to verify the accuracy of the method proposed in this paper.


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    Title :

    Research on the monitoring method of train moving location based on smartphones


    Contributors:
    Feng, Zhengang (editor) / Mikusova, Miroslava (editor) / Li, Peigang (author) / Sun, Hongjie (author) / Yang, Kang (author) / Sun, Xiaojie (author) / Liu, Zexuan (author)

    Conference:

    International Conference on Smart Transportation and City Engineering (STCE 2024) ; 2024 ; Chongqing, China


    Published in:

    Proc. SPIE ; 13575


    Publication date :

    2025-04-28





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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