One of the essential aspects of our life as humans is vision, the ability to see and describe the world with our eyes. Therefore, blinds, even visually impaired people, have plenty of hardships in their daily life activities. They may find it difficult to recognize objects or people in front of them. This paper presents an emphasis on developing a real-time system to aid these people using a Raspberry Pi to process pieces of information provided via camera and ultrasonic sensors with a simple feedback mechanism to inform the user through a headphone. Using this system, the blind could walk without the white cane, and most importantly, it reduces the blind's dependence on other people, thus increasing their quality of life. The proposed system works in different scenarios at both indoor or outdoor environment and has multiple modes of operation to help the blind in different situations with minimum hardware to get an affordable device with a satisfactory offline real-time performance. The system mainly utilizes the technology of deep learning with computer vision to efficiently solve common difficulties such as object recognition, face recognition, and reading text in real-time feedback responses. it sends an audio signal for the user informing him about objects with their count and relative position, familiar faces, or text recognized in the captured frame.