The Deep Learning based Smart Navigational Stick for Blind People

Blind and visually impaired people find difficulty in detecting obstacles and recognizing people in their way, which makes it dangerous for them to walk, to work, or to go in a crowded area/place. They have to be cautious all the time to move, while avoiding any solid obstacles in their way. Typically, they use different aid devices to reach their destination or to accomplish their daily task. The normal stick is useless for blind and visually impaired people since it cannot detect barriers or people's faces. Visually impaired individuals are unable to distinguish between different types of objects in front of them. They are unable to gauge the size of an object or its distance from them. Several works have been done by public individuals and scientific investigators but their work is dearth in technological aspect. This technological aspect need to be addressed by adding artificial intelligence (AI). This prototype aims to help blind and visually impaired individuals in several aspects to simply obtain/perform everyday tasks and help these individuals to live with the same confidence as sighted people live.Therefore, this study inclined deep learning Mobile-Net Single Shot MultiBox detection (SSD) algorithm for object recognition and Dlib library for face recognition. Subsequently, the proposed solution is using an Open CV and Python. Additionally, Ultrasonic sensors are used for distance measurement, which can be a great help for visually impaired people. These components are grouped together to work effectively and efficiently for the development of visually impaired people. The recognition procedure was revealed through headphones, which notifies the visually impaired when face or any object get recognized. Inclusively, the innovative solution would be a great aid for the blind and visually impaired individuals. As a result, to test and validate the accuracy of the smart navigational stick, several experiments have been conducted on a range of objects and faces. Hence, this study’s modified navigational system was adequate and valid for visually impaired people.