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@article{192992,
        author = {Vinothini P and Hemamalini M},
        title = {An AI-Based Smart Traffic Signal Recognition System for Real-Time Road Safety Applications},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {9},
        pages = {3492-3495},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=192992},
        abstract = {The rapid growth of urbanization and vehicular density has increased the demand for intelligent transportation systems that enhance road safety and traffic efficiency. This paper presents a Smart Traffic Signal Recognition System using Artificial Intelligence (AI) designed to detect, classify, and interpret traffic signals in real time. The proposed system utilizes computer vision techniques combined with deep learning algorithms, particularly Convolutional Neural Networks (CNNs), to accurately identify traffic lights and signals under varying environmental conditions such as low light, rain, fog, and occlusions. The system processes live video input from vehicle-mounted cameras, performs image preprocessing, feature extraction, and classification, and then provides actionable outputs to assist drivers or autonomous vehicles. The model is trained on diverse traffic signal datasets to improve robustness and generalization. Experimental results demonstrate high accuracy, reduced latency, and improved reliability compared to traditional image processing methods. This AI-based traffic signal recognition system contributes to the development of advanced driver-assistance systems (ADAS) and autonomous driving technologies, ultimately aiming to reduce accidents and improve road safety.},
        keywords = {Artificial Intelligence (AI), Traffic Signal Recognition, Computer Vision, Deep Learning, Convolutional Neural Network (CNN), Intelligent Transportation Systems, Autonomous Vehicles, Advanced Driver-Assistance Systems (ADAS), Real-Time Detection},
        month = {February},
        }