Document Type
Article
Version Deposited
Published Version
Publication Date
10-19-2021
Publication Title
Electronics
DOI
10.3390/electronics10202557
Abstract
Ultraviolet disinfection has been proven to be effective for surface sanitation. Traditional ultraviolet disinfection systems generate omnidirectional radiation, which introduces safety concerns regarding human exposure. Large scale disinfection must be performed without humans present, which limits the time efficiency of disinfection. We propose and experimentally demonstrate a targeted ultraviolet disinfection system using a combination of robotics, lasers, and deep learning. The system uses a laser-galvo and a camera mounted on a two-axis gimbal running a custom deep learning algorithm. This allows ultraviolet radiation to be applied to any surface in the room where it is mounted, and the algorithm ensures that the laser targets the desired surfaces avoids others such as humans. Both the laser-galvo and the deep learning algorithm were tested for targeted disinfection.
Recommended Citation
Zierdt, B.; Shi, T.; DeGroat, T.; Furman, S.; Papas, N.; Smoot, Z.; Zhang, H.; Wu, B. Selective Disinfection Based on Directional Ultraviolet Irradiation and Artificial Intelligence. Electronics 2021, 10, 2557. https://doi.org/10.3390/electronics10202557
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Comments
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.