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@article{195899,
        author = {Ananthi B and Saranya P and Shalini S and Thivya N},
        title = {Real Time AI Based Assistive System for Visually Impaired Individuals},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {2099-2102},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=195899},
        abstract = {Visually impaired individuals face significant challenges in navigating their surroundings safely and independently. Real-time assistance systems play a crucial role in improving accessibility and reducing dependency on others. This project proposes a Real-Time AI-Based Assistive System designed to support visually impaired individuals using computer vision and audio feedback. The system utilizes a camera to capture live images, which are processed using AI-based object detection models such as YOLOv5 to identify objects, obstacles, and pathways. Additionally, obstacle detection sensors are integrated to enhance safety by detecting nearby objects and preventing collisions. A speech processing module, including speech recognition and Text-to-Speech (TTS), enables effective interaction and provides real-time voice feedback to the user. The system is designed to be portable, cost-effective, and efficient for real-world applications. By combining Artificial Intelligence, computer vision, and audio processing, the system enhances navigation, improves independence, and ensures safety for visually impaired individuals},
        keywords = {AI-Based Assistive System, Visually Impaired Assistance, Object Detection, YOLOv5, Computer Vision, Speech Recognition, Text-to-Speech, Obstacle Detection, Real-Time Monitoring, Audio Feedback System},
        month = {April},
        }