Selective Disinfection Based on Directional Ultraviolet Irradiation and Artificial Intelligence

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.

Limited impact of an ultraviolet disinfection intervention on hygienic behaviors of nursing staff in a military hospital

Ultraviolet disinfection (UV-C), though effective, has not been thoroughly evaluated at the level of the clinical end user. We assessed behavioral outcomes related to environmental hygiene among 60 nursing staff in a medical-surgical section after introduction of a UV-C tool aimed at disinfecting 4 high-touch surfaces, and we noted limited changes.

Ultraviolet disinfection robots to improve hospital cleaning: Real promise or just a gimmick?

The global COVID-19 pandemic due to the novel coronavirus SARS-CoV-2 has challenged the availability of traditional surface disinfectants. It has also stimulated the production of ultraviolet-disinfection robots by companies and institutions. These robots are increasingly advocated as a simple solution for the immediate disinfection of rooms and spaces of all surfaces in one process and as such they seem attractive to hospital management, also because of automation and apparent cost savings by reducing cleaning staff. Yet, there true potential in the hospital setting needs to be carefully evaluated. Presently, disinfection robots do not replace routine (manual) cleaning but may complement it. Further design adjustments of hospitals and devices are needed to overcome the issue of shadowing and free the movement of robots in the hospital environment. They might in the future provide validated, reproducible and documented disinfection processes. Further technical developments and clinical trials in a variety of hospitals are warranted to overcome the current limitations and to find ways to integrate this novel technology in to the hospitals of to-day and the future.

Evaluation of the efficiency of a gray water treatment system based on aeration and filtration

Gray water is a great resource for replacing fresh water to be used in standardized usages. The use of treated gray water reduces water consumption and the entry of pollutants into the environment. However, if left untreated, it can be dangerous. The present study examines the efficiency of a gray water treatment system consisting of primary filter, aeration, secondary filter and ultraviolet disinfection unit. After examining the characteristics of gray water, the efficiency of this system was analyzed to remove the pH, TSS, BOD, COD, ABS and total coliform parameters. Then, the gray water treated through this system was compared with the environmental standard of Iran. The pH of the treated gray water was 7.5–7.6. The efficiency of this system for removing the BOD and COD parameters was 98–100 and 76–100%, respectively. This system had an efficiency of 96–97% to eliminate the ABS parameter. Also, this system was able to eliminate total coliform with 100% efficiency. Results showed that in the three series of experiments performed on this system, according to the Iranian standard, the treated wastewater is suitable for irrigation and agricultural uses. However, this system could not be licensed for the COD parameter regarding the discharge to surface water and absorbent wells.