To reduce the extra work, the operation cost, and the risk of cargo delay induced by the unloading of wrong containers, this study first develops a container color detection model to predict the color of the container being unloaded. The prediction results are then used to develop two crane operator alarm methods. Method 1 alerts the crane operator if the detected color of a container is not in compliance with the correct container color. Method 2 constructs a decision problem to decide whether to alert the operator. The results of numerical experiments show that methods 1 and 2 are better than the benchmark. Specifically, method 1 can save the expected annual total cost by about 82% while method 2 can save the expected annual total cost by about 85%. Extensive sensitivity analysis is also conducted to verify the methods performance and robustness.


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    Titel :

    Development of computer vision informed container crane operator alarm methods


    Beteiligte:
    Yan, Ran (Autor:in) / Tian, Xuecheng (Autor:in) / Wang, Shuaian (Autor:in) / Peng, Chuansheng (Autor:in)


    Erscheinungsdatum :

    2024-05-03




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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