Simple Smartphone-Based Guiding System for Visually Impaired People

Abstract

Visually impaired people are often unaware of dangers in front of them, even in familiar environments. Furthermore, in unfamiliar environments, such people require guidance to reduce the risk of colliding with obstacles. This study proposes a simple smartphone-based guiding system for solving the navigation problems for visually impaired people and achieving obstacle avoidance to enable visually impaired people to travel smoothly from a beginning point to a destination with greater awareness of their surroundings. In this study, a computer image recognition system and smartphone application were integrated to form a simple assisted guiding system. Two operating modes, online mode and offline mode, can be chosen depending on network availability. When the system begins to operate, the smartphone captures the scene in front of the user and sends the captured images to the backend server to be processed. The backend server uses the faster region convolutional neural network algorithm or the you only look once algorithm to recognize multiple obstacles in every image, and it subsequently sends the results back to the smartphone. The results of obstacle recognition in this study reached 60%, which is sufficient for assisting visually impaired people in realizing the types and locations of obstacles around them.

Tools and Technologies for Blind and Visually Impaired Navigation Support: A Review

“…People who are blind or visually impaired started using conventional navigation aids such as white canes 2 , guide dogs 3,4 , assistance by a trained guide or volunteer [4,5] since long time back. Research shows that people who become blind in their early life often learn to use their acoustic skills such as echolocation in an efficient way for navigation [6][7][8].…”

An Overview of Assistive Devices for Blind and Visually Impaired People

“…This robotic dog had been successfully tested on the flat ground and slope. Lin et al [131] directly used a built-in RGB camera of smartphone to detect and recognize obstacles. However, the recognition accuracy of obstacle in their study was only 60%.…”

Noise Source Visualization Using a Digital Voice Recorder and Low-Cost Sensors

“…The performance of smartphones has improved very rapidly, and they have practically become small computers since apps can be developed and executed on them. As a result, diverse efforts to implement smartphones as portable measurement devices have been made [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 ]. This includes application as low-cost noise measurement devices [ 16 , 17 , 18 , 19 , 20 , 21 , 22 ].…”