Smart_Eye: A Navigation and Obstacle Detection for Visually Impaired People through Smart App

Abstract

Vision is extremely important in our lives. The loss of sight is a serious issue for anyone. According to the WHO, one-sixth of the world's population suffers from vision impairment. According to World Health Organization (WHO) statistics published in December 2021, more than 283 million people worldwide suffer from sight problems, including 39 million blind people and 228 million people with low vision. Navigation in unfamiliar environments is a significant challenge for the partially sighted and visually impaired. Improving visual information on object location and content can aid navigation in unfamiliar environments. Many efforts have been made over the years to develop various devices to assist the visually impaired and improve their quality of life. Numerous efforts have been made over the decades to develop gadgets to support the visually impaired as well as enhance the quality of their lives by trying to make them skilled. There are many existing navigation alternatives that can aid these people. However, in practice, navigation alternatives are infrequently adopted and implemented. For universal use, many of these gadgets are either too heavy or too expensive. While emphasizing related strengths and limitations, it is necessary to produce a minimally expensive assistive device for people with visual disabilities. The proposed model provides an efficient solution for VIPs to roam from place to place by themselves through smart applications with AI and sensor technology. The smart application captures and classifies the images. The obstacles are detected through ultrasonic sensors. The user can get a sense of the obstacles in the path through voice command. The proposed model is very helpful for the VIPs in terms of qualitative and quantitative performance measures. This enables a ranking of the evaluated systems according to their potential influence on Visually Impaired people's lives.

Keywords

• Visually impaired, Objects, Detection, Recognition, Artificial Intelligence, sensors.