Visible Light Positioning Based on Collaborative LEDs and Edge Computing
Bibliographic Data
| ID | 22108637 |
|---|---|
| Authors | Xiangyu Liu (0000-0002-8819-2216, Southern University of Science and Technology), Lei Guo (0000-0003-0537-7280, Chongqing University of Posts and Telecommunications), Helin Yang (0000-0001-9697-7470, Northeastern University), Xuetao Wei (0000-0002-4450-2251, Southern University of Science and Technology) |
| Year | 2022 |
| Volume | 9 |
| Issue | 1 |
| Pages | 324-335 |
| Publication date | 2022-02-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | IEEE Transactions on Computational Social Systems (JOURNAL) |
| Journal identifiers | ISSN: 2329-924X • E-ISSN: 2373-7476 |
| Publisher | Institute of Electrical and Electronics Engineers (IEEE) (PUBLISHER) |
| DOI | 10.1109/tcss.2021.3109631 |
| OpenAlex | W3199322015 |
| Language | EN |
| References cited | 47 |
The proliferation of the Internet of Things pushes the visible light positioning (VLP) system research. However, the existing positioning systems still have the following problems: 1) when the smartphone (receiver) is rotated or tilted during the positioning, existing collaborative LEDs’ positioning algorithms fail and 2) for different smartphone application scenarios, there is not an effective resource management solution between the server and the client. Therefore, in this article, we design and implement a robust and flexible indoor VLP system based on collaborative LEDs and edge computing. First, we propose the enhanced collaborative LEDs’ positioning algorithm, which uses the indoor hidden location information to obtain the rotation angle and tilt angle of the receiver, to achieve the robust system positioning. Then, we use the edge computing solution to balance between bandwidth resources and computing resources and propose a flexible functional segmentation scheme for different smartphone application scenarios. Finally, we conduct experimental tests to evaluate the positioning system performance by landmark decoding rate, positioning accuracy, and segmentation analysis. Test results show that the designed positioning system can achieve centimeter-level positioning. Meanwhile, the smartphone can exchange the least bandwidth resources for the most computing resources under Scheme-3
Computer network · Computer vision · Edge computing · Embedded system · Enhanced Data Rates for GSM Evolution · Hybrid positioning system · Indoor positioning system · Light-emitting diode · Positioning system · Positioning technology · Real-time computing · Visible light communication · Computer Science · Engineering · Indoor and Outdoor Localization Technologies · Optical Wireless Communication Technologies · Smart Parking Systems Research · Artificial Intelligence
| Highly cited | No |
|---|