• Faiz Aman
• Rakshitha C A
• Sindhu C S
• Upadhya Kshama B
• Vidya S U

Blindness is one of the most frequent and debilitating of the various disabilities. There are million visually impaired people in the globe, according to the World Health Organization (WHO). The proposed system is designed to aid visually impaired persons with real-time obstacle detection, avoidance, indoors and out navigation, and actual position tracking. The gadget proposed is a camera-visual detection hybrid that performs well in low light as part of the recommended technique, this method is utilized to detect and avoid impediments, as well as to aid visually impaired persons in identifying the environment around them. A simple and effective method for people with visual impairments to identify things in their environment and convert them into speech for improved comprehension and navigation. Along with these, the depth estimation, which calculates the safe distance between the object and the person, allowing them to be more self-sufficient and less reliant on others. This were able to achieve this model with the help of TensorFlow and pre-trained models. The approach suggested is dependable, inexpensive, practical, and practicable.

Yolo algorithm, obstacle detection, navigation, Real time object detection

"BLIND ASSIST SYSTEM USING MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 6, page no.h597-h607, June-2024, Available :http://www.jetir.org/papers/JETIR2406763.pdf

"BLIND ASSIST SYSTEM USING MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 6, page no. pph597-h607, June-2024, Available at : http://www.jetir.org/papers/JETIR2406763.pdf