LED-based optical wireless power transmission through deep learning-enabled infrared spot recognition

Mingzhi Zhao; Tomoyuki Miyamoto

doi:10.1117/12.2692270

13 March 2024 LED-based optical wireless power transmission through deep learning-enabled infrared spot recognition

Mingzhi Zhao, Tomoyuki Miyamoto

Proceedings Volume 12906, Light-Emitting Devices, Materials, and Applications XXVIII; 129060M (2024) https://doi.org/10.1117/12.2692270
Event: SPIE OPTO, 2024, San Francisco, California, United States

Conference Poster

Abstract

Optical wireless power transmission (OWPT) has emerged as a promising technology for remote power applications due to its long-distance transmission, high directionality, and lack of electromagnetic interference. In practical applications, light-emitting diode (LED) based OWPT systems have advantages over Laser Diode in terms of easy commercialization and reduced safety issues. In this research, we propose a deep learning-based approach to optimize the irradiation spot for improving the LED-OWPT transmission distance. A novel configuration consisting of three-layer lenses and a depth camera minimizes the spot size by real-time detecting the transmission distance. The system achieves an auto-focus performance, resulting in an 8-times improvement of the effective surface irradiation at 3m on a 5×5cm² receiver.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Mingzhi Zhao and Tomoyuki Miyamoto "LED-based optical wireless power transmission through deep learning-enabled infrared spot recognition", Proc. SPIE 12906, Light-Emitting Devices, Materials, and Applications XXVIII, 129060M (13 March 2024); https://doi.org/10.1117/12.2692270

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