Neamah, Osamah N.Almohamad, Tarik AdnanBayir, Raif2024-09-292024-09-292024979-8-3503-4915-3979-8-3503-4916-0https://doi.org/10.1109/ZINC61849.2024.10579437https://hdl.handle.net/20.500.14619/6186Zooming Innovation in Consumer Technologies Conference (ZINC) -- MAY 22-23, 2024 -- Novi Sad, SERBIAThis study introduces an innovative approach that combines cutting-edge technology and advanced models for real-time applications. Leveraging the performance of the Nvidia Jetson Nano, alongside an integrated camera and GSM/GPS module, our innovative system demonstrates both its practicality and versatility. Specifically, by employing the YOLOv8 classification model for handling State Farm Distracted Driver Detection data which underscores its adaptability and effectiveness in this critical domain. Additionally, our research thoroughly assesses computational efficiency, exploring both hardware and software-based analysis methods. This work is a cornerstone in harnessing technology for real-world impact, merging innovation with practicality and comprehensive evaluation.eninfo:eu-repo/semantics/closedAccessDeep LearningYOLOv8Distracted Driver DetectionDriver BehaviorVehicle to EverythingConference Object10.1109/ZINC61849.2024.105794372-s2.0-85199213789198N/A194WOS:001266171500044N/A