An Artificial Intelligence Edge Computing-Based Assistive System for Visually Impaired Pedestrian Safety at Zebra Crossings
Wan‐Jung Chang, Liang-Bi Chen, Cheng-You Sie, Ching-Hsiang Yang
Abstract
This article proposes a wearable assistive system based on artificial intelligence (AI) edge computing techniques to help visually impaired consumers safely use marked crosswalks, or zebra crossings. The proposed wearable assistive system consists of a pair of smart sunglasses, a waist-mounted intelligent device, and an intelligent walking cane (stick). A deep learning technique is adopted for zebra crossing image recognition in real time. Visually impaired consumers need to wear the proposed smart sunglasses and waist-mounted intelligent device and hold the proposed intelligent walking cane when they approach a zebra crossing. When a visually impaired pedestrian reaches a zebra crossing, they will immediately receive a message about the current situation at the crossing and the traffic light signal. Experimental results show that the accuracy of real-time zebra crossing recognition of the proposed system can reach up to 90%.