For the first time in Canada, a disinfection robot is using AI (artificial intelligence) technology to sanitize a healthcare facility and a York University nursing professor is overseeing the project.
Irfan Aslam, an assistant professor in the Faculty of Health’s School of Nursing, is the infection control lead at Toronto’s Mon Sheong Home for the Aged, a facility that confirmed its first COVID-19 case April 4 and by April 23 had declared an outbreak.
Aslam, who answered a call-to-action from Ontario Health seeking healthcare workers to assist in ‘COVID facilities,’ stepped into the role on April 30 to implement rigour into infection control measures at the long-term care home.
Since April 5, Aslam says 56 residents have tested positive for COVID-19, resulting in 33 COVID-19-related deaths. Within the staff, there have been 16 positive tests and no deaths.
“As soon as there is a decrease in staff, compliance with infection control goes down,” explains Aslam. “One of my jobs is to make sure there is compliance to ensure staff and residents' safety and to facilitate that compliance.”
After surveying the facility and its operations, he implemented several strategies and procedures to help minimize the risk of transmission, including: removing communal furniture from hallways, creating protocols for social distancing for staff in common areas and elevators, training housekeeping staff on terminal cleaning (intense disinfecting procedures), removing points of cross-contamination for things like obtaining and disposing of PPE, training staff on the proper use of PPE, ensuring staff is assinged only one unit of the facility and more.
“We know that one of the most common ways for the virus to spread is through humans. It’s the staff members who are moving around the facility – not the residents – so if we can contain the staff to one unit we can lower the risk of transmission,” he said.
As of June 5, the facility has been declared COVID-19-free; on June 4, the AI robot arrived to join its cleaning crew.
Manufactured by a company called Global DWS, the robot has been designed to use UV light and disinfectant to sanitize and clean the facility. This in itself is not new – hospitals have been using robot and machine technology as disinfecting tools for some time, says Aslam; however, this is the first time a disinfectant robot has been powered by AI and machine learning to operate.
It works like this: the robot will spend half a day “learning” or mapping the facility through cognitive capabilities (such as custom vision, voice interaction and autonomous navigation). When it is deployed to clean, it will use a combination of 360-degree UV-C light and disinfectant spray (using a liquid under a high pressure atomizer) to clean all surfaces, and deactivate any viral microbes.
The robot can be scheduled to a routine, generate daily reports and send alert notifications.
“UV light can only work in areas where the light can reach, so they have included the disinfectant sprayer to reach more difficult areas,” said Aslam, adding that it’s important to note that it doesn’t replace staff, but improves infection control by limiting human exposure to areas that may present with a high risk of transmission.
The benefits to using this type of technology also includes:
- maintaining disinfection procedures during times when staff it short;
- disinfection of areas that are normally impossible to clean with chemical disinfectants, such as patient charts;
- enabling staff who are working to be deployed to other tasks (such as disinfecting areas the robot cannot or focusing on cleaning of low-traffic areas); and
- reducing costs for deep cleaning, which have risen exponentially for facilities when having to call in external cleaning companies.
To investigate the efficacy of the robot, Aslam will conduct swab tests before and after the cleaning procedures and use of the UV-C dosimeter to determine how effective the disinfectant process was, and will look to publish his results.
Based on the dosimeter results on June 4, Aslam says the surfaces were exposed to UV-C light with the wavelength between 200 to 280 nanometers (nm).
"This is enough intensity to make the virus incapable of infection or reproducing," he said. "I am particularly happy because we were able to disinfect areas and items that are generally impossible to disinfect, for example, resident's charts, fabric couches, rugs, etc. This has decreased the microbe load in the environment and reduced the risk of surface transmission for residents as well as staff."
By Ashley Goodfellow Craig, deputy editor, YFile
Originally published in YFile.