Empowering the Visually Impaired with Real-Time Audio Feedback on Objects and Environment

Abstract: The object recognition is achieved through OpenCV.YOLO uses a similar phase while training, to match the appropriate anchor box with the bounding boxes of each ground truth object within an image. Essentially, the anchor box with the highest degree of flap with an object is responsible for predicting that object\'s class and its location. It has microcontroller which has wi-fi inbuilt module. This guide is convenient and offers data to the client to move around in new condition, regardless of whether indoor or open air, through an ease to use interface. Vision is one of the very essential human senses and it plays the most important role in human perception of our environment, unfortunately there are many people who are visually impaired. Blind people today rely on sighted guides, seeing-eye dogs and canes even a century after these came into existence. The present work aims to aid the blind through a wrist wearable. The wearable is designed to capture the user's environment through a camera and recognize the objects present in image. These identified objects are informed to user through an audio output. In addition to object detection, the device can adapt to different environments and user preferences, offering personalized feedback. The system’s accuracy and reliability are bolstered by extensive use of diverse datasets and real-time processing capabilities, ensuring the wearable remains effective in a wide range of real-world scenarios. This innovation has the potential to enhance the independence of visually impaired individuals, providing them with more autonomy and a greater sense of security while navigating unfamiliar spaces.