An Artificial Intelligence Edge Computing-Based Assistive System for Visually Impaired Pedestrian Safety at Zebra Crossings

• Published in: IEEE transactions on consumer electronics 2021-02, Vol.67 (1), p.3-11
• Main Authors: Chang, Wan-Jung, Chen, Liang-Bi, Sie, Cheng-You, Yang, Ching-Hsiang
• Format: Article
• Language: English
• Subjects: Artificial intelligence; Artificial intelligence of the Internet of Things (AIoT); Collision avoidance; Consumers; Dogs; Edge computing; Global Positioning System; Legged locomotion; Object recognition; Pedestrian crossings; Pedestrian safety; pedestrian walking safety; Pedestrians; Real time; Safety; Smart glasses; Sunglasses; Traffic safety; Traffic signals; Visual impairment; visually impaired; Walking; walking cane; wearable assistive devices; Wearable technology; zebra crossing
• ISSN: 0098-3063; 1558-4127
• DOI: 10.1109/TCE.2020.3037065

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%.