Professor Albert Cheng developed an app helping reduce risk of COVID-19 among crowds. | Courtesy of Albert Cheng
A new application is being developed at UH aiming to provide information on how crowded locations are at specific times so users can evaluate the risk of transmitting COVID-19.
The app, known as RT-CIRAM, is being developed in the lab of professor of computer science, electrical and computer engineering Albert Cheng.
“The system aims to keep the user at a safe distance from others and avoid crowds,” Cheng said. “When the app is given information about where the user wants to go and how they’re traveling, it outputs the route that would reduce the chance of infection.”
The app would use public-domain data on COVID-19 in conjunction with data on the user’s phone to provide information on which places are least likely to put the user at risk for contracting the virus.
Cheng also said he was inspired to create the app after observing how AI-based models had been used to help policymakers create strategies to fight the coronavirus.
“These models help balance the need to contain the pandemic and minimize the economic impact,” Cheng said. “However, they do not advise individual citizens on how to accomplish daily tasks while minimizing the chance of infection.”
Student researchers are currently working on prototype models of the system in Professor Cheng’s lab, and they’ve currently rolled out a bare-bones version of the app in Seattle, which can be viewed here.
Cheng hopes the make the app available in Houston by next month.
While the app has a lot of potential, Cheng noted a few challenges he has been facing over the course of development, including the difficulty of providing accurate data without infringing on privacy.
“The challenge is how to implement the system without information about the precise location of individuals provided by mobile phone data,” Cheng said. “Much of this data is not available unless allowed by phone users.”
