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1.
Am J Infect Control ; 50(8): 947-953, 2022 08.
Article in English | MEDLINE | ID: covidwho-2000206

ABSTRACT

BACKGROUND: Ultraviolet germicidal irradiation (UVGI) technologies have emerged as a promising adjunct to manual cleaning, however, their potential to shorten cleaning times remains unexplored. METHODS: A <10-minute disinfection procedure was developed using a robotic UVGI platform. The efficacy and time to perform the UVGI procedure in a CT scan treatment room was compared with current protocols involving manual disinfection using biocides. For each intervention, environmental samples were taken at 12 locations in the room before and after disinfection on seven distinct occasions. RESULTS: The mean UVC dose at each sample location was found to be 13.01 ± 4.36 mJ/cm2, which exceeded published UVC thresholds for achieving log reductions of many common pathogens. Significant reductions in microbial burden were measured after both UVGI (P≤.001) and manual cleaning (P≤.05) conditions, with the UVGI procedure revealing the largest effect size (r = 0.603). DISCUSSION: These results support the hypothesis that automated deployments of UVGI technology can lead to germicidal performance that is comparable with, and potentially better than, current manual cleaning practices. CONCLUSIONS: Our findings provide early evidence that the incorporation of automated UVGI procedures into cleaning workflow could reduce turnaround times in radiology, and potentially other hospital settings.


Subject(s)
Radiology , Robotics , Disinfection/methods , Hospitals , Humans , Ultraviolet Rays
2.
Autonomous Systems: Sensors, Processing and Security for Ground, Air, Sea and Space Vehicles and Infrastructure 2022 ; 12115, 2022.
Article in English | Scopus | ID: covidwho-1949889

ABSTRACT

With the global coronavirus pandemic still persisting, the repeated disinfection of large spaces and small rooms has become a priority and matter of focus for researchers and developers. The use of ultraviolet light (UV) for disinfection is not new;however, there are new efforts to make the methods safer, more thorough, and automated. Indeed, continuous very low dose-rate far-UVC light in indoor public locations is a promising, safe and inexpensive tool to reduce the spread of airborne-mediated microbial diseases. This paper investigates the problem of disinfecting surfaces using autonomous mobile robots equipped with UV light towers. In order to demonstrate the feasibility of our autonomous disinfection framework, we also present a teleoperated robotic prototype. It consists of a robotic rover unit base, on which two separate UV light towers carrying 254 nm UVC and 222 nm far-UVC lights are mounted. It also includes a live-feed camera for remote operation, as well as power and communication electronics for the remote operation of the UV lamps. The 222 nm far-UVC light has been recently shown to be non-inammatory and non-photo carcinogenic when radiated on mammalian skin, while still sterilizing the coronavirus on irradiated surfaces. With far-UVC light, disinfection robots may no longer require the evacuation of spaces to be disinfected. The robot demonstrates promising disinfection performance and potential for future autonomous applications. © 2022 SPIE. All rights reserved.

3.
Build Environ ; 184: 107226, 2020 Oct 15.
Article in English | MEDLINE | ID: covidwho-733924

ABSTRACT

Mass-gathering built environments such as hospitals, schools, and airports can become hot spots for pathogen transmission and exposure. Disinfection is critical for reducing infection risks and preventing outbreaks of infectious diseases. However, cleaning and disinfection are labor-intensive, time-consuming, and health-undermining, particularly during the pandemic of the coronavirus disease in 2019. To address the challenge, a novel framework is proposed in this study to enable robotic disinfection in built environments to reduce pathogen transmission and exposure. First, a simultaneous localization and mapping technique is exploited for robot navigation in built environments. Second, a deep-learning method is developed to segment and map areas of potential contamination in three dimensions based on the object affordance concept. Third, with short-wavelength ultraviolet light, the trajectories of robotic disinfection are generated to adapt to the geometries of areas of potential contamination to ensure complete and safe disinfection. Both simulations and physical experiments were conducted to validate the proposed methods, which demonstrated the feasibility of intelligent robotic disinfection and highlighted the applicability in mass-gathering built environments.

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