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@article{199133,
        author = {Dr.J.Sampathkumar and S.SHEHAJATH AALAM and P.SRIDHARAN and VISHNU RAJA A and S. THIRUMOORTHY},
        title = {An AI-Driven Unified Model for Traffic Sign and Lane Detection in Dynamic Road Environments},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {12204-12209},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=199133},
        abstract = {This system is designed to enhance road safety by providing real-time driver assistance through the integration of lane detection, seat safety monitoring, and traffic sign recognition technologies. A camera mounted on the vehicle continuously captures road images, which are processed using advanced computer vision and deep learning techniques. The lane detection module identifies road lane boundaries and alerts the driver in case of unintentional lane departure, helping to prevent accidents caused by driver distraction. The seat safety module monitors seat belt usage and driver seating position using sensors, generating warnings when unsafe conditions are detected. Additionally, the system incorporates traffic sign recognition using Convolutional Neural Networks (CNNs), enabling the detection and classification of important road signs such as speed limits, stop signs, and warning indicators. Once a traffic sign is recognized, the system provides real-time visual and audio alerts to assist the driver in making timely decisions. By integrating these functionalities, the proposed system significantly reduces the risk of accidents caused by inattention, improper safety measures, and missed traffic signs. The system is cost-effective, scalable, and highly suitable for deployment in Intelligent Transportation Systems (ITS) and Advanced Driver Assistance Systems (ADAS).},
        keywords = {Autonomous Vehicles, Traffic Sign Recognition, Lane Detection, Deep Learning, Convolutional Neural Networks (CNN), Computer Vision, Advanced Driver Assistance Systems (ADAS), Intelligent Transportation Systems (ITS), Real-Time Image Processing, Driver Safety Monitoring.},
        month = {April},
        }