Open-Source Sidewalk Navigation Software for Visually-Impaired Individuals using Multithreaded CNN’s

The Indoor and outdoor Navigation Assistance System aims to provide blind or visually impaired individuals with comprehensive navigation support in indoor and outdoor environments

We propose an AI-based computer vision hardware/software implementation to solve the problem of the individual street navigation for visually impaired/blind individuals. With the aid of the current achievements of semantic segmentation and depth estimation, we could integrate those great computer vision algorithms in our solution to provide a street-scene perception. The recent semantic segmentation methods which are trained on the popular segmentation dataset “ADE20K” provide a detailed indoor and outdoor scenes understanding via segmentation. This model can be easily integrated in an AI neural inference unit with camera like OAK-D or raspberry pi. Another tool is integrated in our application which is the GPS which receive the desired location by the user, this GPS service is implemented using mobile application which receive the voice command get it on Google maps, then the smart phone provide the directions to the user through a custom mobile application, during the GPS navigation the OAK-D board is visualizing the street and provide the specific street pavement positioning, obstacle avoidance command until user reach to his destination.

An outdoor navigation for the blind.

This is an outdoor navigation mobile application to help blind people to walk outdoor smoothly

No description available

Special Navigation cane for supporting blind people in outdoor usage

The References about Survey and Analysis of Outdoor Navigation for the Blind

Navigation Assistance using Outdoor Object Detections and Recognitions for People Who are Blind and Visually Impaired using Deep Learning.

An android application which allows blind or visually impaired users to seek assistance for navigation in an outdoor environment by broadcasting the assistance request to the volunteers based on the closest GPS coordinates.

One of the major challenges the blind community face today is navigating from one place to another and most of the time they are dependent on some other person for that. Tools have been made which allow them to ease outdoor navigation through the use of GPS [1, 2, and 3]. Since GPS does not work accurately in indoors as compared to outdoors therefore its credibility in guiding the user towards his destination cannot be trusted upon. VPAN system is an effort to overcome this limitation of GPS systems and assist visually impaired and blind people in navigating indoors. At the backend it relies on google cloud platform for doing its computations and in the front-end there would be a smartphone for processing the generated results required to guide the user to its destination. Location Approximation is done by creating a structural map (vertex labelled graph) of the whole building using images of the various points inside the buildings used as reference points[4] and in order to approximate the location of user we use the user’s field of vision with those already stored images inside our cloud. Although the results are still not enough to provide strong conclusions, they indicate that the system is suitable to guide visually impaired people through an unknown built environment and as the accuracy is concerned we can confidently say it’s up to 2.5 meters (approx.) based on the various trail runs.