Selective Disinfection Based on Directional Ultraviolet Irradiation and Artificial Intelligence

Electronics

Ben Zierdt¹  Taichu Shi¹  Ben Wu¹  Thomas DeGroat¹  Zachary Smoot¹  Sam Furman¹  Nicholas Papas¹  Hong Zhang² 

[1] Department of Electrical and Computer Engineering, Rowan University, 201 Mullica Hill Rd., Glassboro, NJ 08028, USA;Department of Mechanical Engineering, Rowan University, 201 Mullica Hill Rd., Glassboro, NJ 08028, USA;

关键词: ultraviolet disinfection;    laser-galvo system;    COVID-19;    automatic control;   

DOI  :  10.3390/electronics10202557

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown