Visually impaired people usually have difficulty in doing daily activities. Imagine a future where visually impaired people can seamlessly and independently identify objects and people in their environment. The aim of this research is to increase the independence and mobility of visually impaired people by developing a real-time object and person recognition system. This system uses the power of machine learning and uses computer vision techniques to accurately identify and classify objects and people in the user's environment. Through the integration of speakers or headphones, the system provides auditory feedback to the user and conveys important information about the detected object or person. By combining advanced image processing algorithms with audio output, this solution serves as a valuable tool for visually impaired people, allowing them to effectively perceive and understand their surroundings. This innovative approach demonstrates the potential of technology to bridge access gaps and empower people with visual impairments in their daily lives.

Computer Vision Optical Character Recognition (OCR) Object Recognition Facial Recognition Text to Speech Raspberry Pi