Name
Title | ||
|---|---|---|
An Artificial Intelligence Edge Computing-Based Assistive System for Visually Impaired Pedestrian Safety at Zebra Crossings |
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%. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TCE.2020.3037065 | IEEE Transactions on Consumer Electronics |
Keywords | DocType | Volume |
Artificial intelligence of the Internet of Things (AIoT),smart glasses,visually impaired,walking cane,pedestrian walking safety,wearable assistive devices,zebra crossing | Journal | 67 |
Issue | ISSN | Citations |
1 | 0098-3063 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wan-Jung Chang | 1 | 13 | 12.53 |
| Liang-Bi Chen | 2 | 26 | 18.40 |
| Cheng-You Sie | 3 | 0 | 0.34 |
| Ching-Hsiang Yang | 4 | 0 | 0.34 |