R Parvadhavardhni.,Pankhuri Santoshi,A. Mary Posonia
标识
DOI:10.1109/icaaic56838.2023.10140484
摘要
Visually impaired encounter several challenges in their daily lives to impact their independence, safety, and overall quality of life. Visual impairment can be caused by a range of conditions, such as age-related macular degeneration, glaucoma, cataracts, or genetic disorders. A blind navigation system with object detection is designed to assist visually impaired individuals in navigating their environment safely and independently. This system uses a combination of TensorFlow (YOLO), OpenCV, Noir camera, ultrasonic sensor, and Raspberry Pi to achieve real-time object detection and provide audio feedback to the user about the type of detected objects. The use of TensorFlow (YOLO), OpenCV, Noir Camera, Ultrasonic sensors, and Raspberry Pi, in particular, has made it possible to develop a highly effective and accurate system for visually impaired individuals by providing real-time feedback about the user's environment, this system can help improve the user's confidence and independence while navigating through their environment, and can greatly improve their quality of life.