A student at St. Petersburg State University of Aerospace Instrumentation has designed a unique wearable navigation system for blind and visually impaired people.
The project is implemented at the junction of advanced end-to-end technologies and is focused on the concept of Edge AI (local artificial intelligence). The device is capable of recognizing objects completely autonomously and orienting the user in space without an Internet connection or cloud servers.
Today, the integration of people with visual impairments into the urban environment remains an acute social problem. Classical rehabilitation tools have critical vulnerabilities. A white cane provides safety only at a distance of one step, and the usual GPS navigators on smartphones are not able to notice dynamic obstacles, such as electric scooters left on the sidewalk, scaffolding or low-hanging road signs. In addition, mobile applications become useless in areas with unstable cellular coverage. The complex developed at SUAI solves these problems by acting as a smart personal assistant that scans the environment in real time and warns of obstacles.
The hardware basis of the device is a compact microcomputer with a portable camera, which is mounted on the user. The software part is divided into two independent computing circuits. The first is macro navigation: a local geoinformation module with support for offline maps. It recognizes the user’s voice commands, finds the desired address, and plots the optimal walking route. The second is micronavigation: a computer vision system based on a lightweight neural network. It continuously analyzes the video stream from the camera, instantly recognizes infrastructure objects (poles, bins, benches, parked cars) and calculates the exact distance to them.
