The essence of object detection in Computer Vision is to identify and precisely locate an object in a scene. In transportation management, it detects traffic signs for application in autonomous vehicles and other road users. Traffic objects and the scene must also be documented and monitored for efficient traffic management. The signs are prone to damage and occlusion, which may compromise road safety, thus the need to detect, document, and monitor traffic signs. This paper proposed a traffic signs detection and recognition model using the state-of-the-art YOLOv8 model and an inventory management system for keeping traffic records. We also proposed a monitoring technique by viewing traffic scenes uploaded on customized Google My Map and Google Map, made possible by geolocation information of traffic signs. Our trained model achieved 87.1% mAP50 and 61.2% mAP50-95 on our dataset. We compared the performance of our model to other versions of YOLOv8.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Viewing on Google Maps Using Yolov8 for Damaged Traffic Signs Detection


    Additional title:

    Communic.Comp.Inf.Science


    Contributors:

    Conference:

    International Conference on Technologies and Applications of Artificial Intelligence ; 2023 ; Yunlin, Taiwan December 01, 2023 - December 02, 2023



    Publication date :

    2024-03-28


    Size :

    11 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




    Real-time Detection of Diverse Bangladeshi Traffic Signs Using YOLOv8

    Ehsanu Hoque, Md. Habib / Mahbub, Mrittika / Bin Md Tomari, Mohd Razali et al. | IEEE | 2024


    Traffic Sign Detection Using YOLOv8

    Kumar, Rahul / Gupta, Aniket / D, Rajeswari | IEEE | 2024


    Design & Implementation of a Vehicle Detection and Tracking System Utilizing YOLOv8 and Google Maps API

    Mhatre, Shreeraj / Deshpande, Vaijayanti / Subhedar, Jahida | IEEE | 2024


    Real-time traffic accident detection using yolov8

    Huy Minh, Quang Nguyen / Dinh, Nen Nguyen / Ho, Long Viet et al. | Elsevier | 2025

    Free access

    Dynamic Traffic Light Controlling System Using Google Maps and IoT

    Mahima, K.T.Y. / Abeygunawardana, R.A.B. / Ginige, T.N.D.S. | IEEE | 2020