The Methods of Visually Impaired Navigating and Obstacle Avoidance

Blindness is a widespread problem that affects people all around the globe. People with this condition have a very difficult time navigating on their own and seeing impediments. Thus, an integrated implementation of the Web of Things & predictive analytics is necessary for properly recognizing impediments. For the blind and visually handicapped to be able to move about freely, they need to be able to sense obstacles and be warned of their presence. First, data on the location and kind of barrier has to be collected, and only then can it be sent to those with visual impairments through other means of communication, such as speech. Using the tensor flow object identification model and the Google voice model, we demonstrate a solution to assist the visually handicapped. The idea has two main parts: environment data and an analytical representation. Using a tensor flow object detection model, it first attempts to analyze the surroundings for obstacles that visually impaired individuals are likely to encounter, and then it tries to relay that knowledge to those persons in the form of spoken words.