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@article{168252,
        author = {KASHVI V and MANOJ GOWDA R and PRAMODA S R and FARDEEN S KHADRI and Dr. KAVITHA DEVI CS},
        title = {VISNAV-Visor Integrated System for Navigation},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {5},
        pages = {624-627},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=168252},
        abstract = {The VISNAV Helmet project aims to revolutionize motorcycle safety by integrating cutting-edge technology into a traditional helmet. This smart helmet features real-time navigation aids, crash detection, and a heavy vehicle detection system using YOLO v10 object detection. A matrix display on the side of the helmet provides visual alerts with directional arrow marks to enhance rider awareness of nearby heavy vehicles. These features collectively aim to reduce accidents and improve safety for both everyday riders and delivery agents. The crash detection feature uses gyroscopes and accelerometers to detect impacts, automatically triggering emergency alerts to designated contacts, thereby expediting rescue efforts. The heavy vehicle detection system, powered by YOLO v10, continuously scans the area behind the rider, providing immediate alerts via the side-mounted matrix display, which uses intuitive arrow marks to indicate the position of detected vehicles. This comprehensive approach not only enhances situational awareness but also helps riders make quick, informed decisions improving overall road safety.},
        keywords = {Crash detection, Heavy vehicle detection, Matrix display, Real-time navigations, Road safety Smart helmet, YOLO v10},
        month = {October},
        }