Highway tunnels are one of the important infrastructures in urban highway and play an important role in ensuring safe and smooth traffic flow. In order to keep the tunnel in good operating condition during the use of the tunnel, as well as to ensure the travelling experience of users, the regular inspection and maintenance of highway tunnels is crucial. Aiming at the traditional manual inspection of highway tunnels with low efficiency, high time and manpower costs, and the difficulty of controlling highway tunnels, a highway tunnel inspection system based on inspection drones is designed. The system uses a UAV equipped with 3D lidar technology inside the tunnel to implement a comprehensive scan through a preset flight path and carries an optical camera, aiming to efficiently and accurately collect information inside the tunnel. The resulting data is processed by deep learning algorithms to accurately identify problems such as wall damage, dusty lighting fixtures and faded reflective strips, thereby improving the effectiveness and accuracy of tunnel inspections.


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    Titel :

    Highway tunnel detection system based on inspection UAV


    Beteiligte:
    Falcone, Francisco (Herausgeber:in) / Yao, Xinwei (Herausgeber:in) / Shen, Yangjie (Autor:in)

    Kongress:

    4th International Conference on Internet of Things and Smart City (IoTSC 2024) ; 2024 ; Hangzhou, China


    Erschienen in:

    Proc. SPIE ; 13224


    Erscheinungsdatum :

    07.08.2024





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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