Title
Centimeter-Level Indoor Visible Light Positioning
Author
Zhu, R. (TU Delft Embedded Systems)
Van Den Abeele, Maxim (Katholieke Universiteit Leuven)
Beysens, Jona (CSEM SA)
Yang, J. (TU Delft Web Information Systems) 
Wang, Q. (TU Delft Embedded Systems)
Date
2024
Abstract
Visible light positioning (VLP) based on the received signal strength (RSS) can leverage a dense deployment of LEDs in future lighting infrastructure to provide accurate and energy-efficient indoor positioning. However, its positioning accuracy heavily depends on the density of collected fingerprints, which is labor-intensive. In this work, we propose a data pre-processing method, including data cleaning and data augmentation, to construct reliable and dense fingerprint samples, thereby alleviating the impact of noisy samples as well as reducing labor intensity. Extensive experiments demonstrate that our proposed method achieves an average positioning error of 1.7 cm, utilizing a sparse dataset that reduces the fingerprint collection effort by 98 percent. Running a tinyML-based model for VLP on the Arduino Nano microcontroller, we also show the possibilities for deploying RSS fingerprint-based VLP systems on resource-constrained embedded devices for real-world applications.
To reference this document use:
http://resolver.tudelft.nl/uuid:a4085c4b-de19-4894-8c45-ea6b684bfe3c
DOI
https://doi.org/10.1109/MCOM.002.2300296
Embargo date
2024-09-30
ISSN
0163-6804
Source
IEEE Communications Magazine, 62 (3), 48-53
Part of collection
Institutional Repository
Document type
journal article
Rights
© 2024 R. Zhu, Maxim Van Den Abeele, Jona Beysens, J. Yang, Q. Wang