UW researchers developed a project that scans the streets every few weeks to document how Seattle has reacted to the pandemic and what recovery looks like. The team is developing algorithms to help identify things such as cars, people and whether they are physically distancing in each frame. University of Washington
As the city of Seattle shut down in March 2020 to try to slow the spread of COVID-19, a group of University of Washington researchers got to work.
The team captured this series of photos from outside Harborview Medical Center between June and August 2020. The June photo shows very few people in the area. In July, there are people waiting at the bus stop. By August, there are more people at the bus stop and the surrounding areas. Credit: University of Washington
The team’s route takes between eight and 11 hours to drive each time.
"We wanted the route to capture different aspects of the city - such as restaurants, hospitals, schools, parks and museums - and also make sure we had an equal representation across a variety of neighborhoods,” said co-lead researcher Scott Miles , a senior principal research scientist in the human centered design and engineering department.
The researchers try to start the drive at 8 a.m. on Friday, every few weeks, to maintain a consistent schedule, but it depends on weather, specifically the camera doesn’t work in the rain. They also drive on some Sundays to try to capture any variation between weekdays and weekends.
The Street-View-like camera creates huge datasets - each drive is turned into tens of thousands of images that make up an almost 2-terabyte file. So the researchers are developing algorithms to help them identify things such as cars, people and whether they are physically distancing in each frame. Identities - such as human faces and vehicle license plates - will be blurred.
"When people study disaster recovery, they often look at location data from smartphones or transaction data from debit or credit cards,” said co-lead researcher Youngjun Choe , an assistant professor of industrial and systems engineering. "But these data points do not necessarily capture everyone in a community. By looking at our images, I hope we are creating a dataset that better represents all people who live and work in Seattle.”
Any insights gained from this project, such as how people respond to mask recommendations or which populations might need more resources, can help other cities better understand their own recovery trends the researchers said.
"People talk about this as a 100-year pandemic, because the last major pandemic was in 1918,” Errett said. "Now conditions are much different - we have increased population density, climate change and more. I don’t think we’re going to be waiting another hundred years. So whatever we can do to learn from this experience will help us develop better policies and plans for the future.”
Jaqueline Peltier, an operations specialist in civil and environmental engineering; Matthew Martell , a doctoral candidate in industrial and systems engineering; Christopher Salazar, a master’s student in industrial and systems engineering; and Vanessa Yang, an undergraduate student in statistics and informatics, are also part of this project.
For more information, contact Errett at email@example.com , Wartman at firstname.lastname@example.org , Miles at email@example.com and Choe at firstname.lastname@example.org.
Grant number: CMMI-2031119
Tag(s): College of Engineering o COVID-19 o COVID-19 studies o Department of Civil & Environmental Engineering o Department of Environmental & Occupational Health Sciences o Department of Human Centered Design & Engineering o Department of Industrial & Systems Engineering o Joseph Wartman o Nicole Errett o School of Public Health o Scott Miles o Youngjun Choe