Data Science and Food Safety
Computer scientists and cognitive scientists at the University of Rochester are using data science to help make the world a better, more connected, and healthier place.
By “listening” to tweets from patrons of a particular restaurant, a University-developed system could tell you how likely you are to become ill if you ate at that restaurant. University researchers say their system, nEmesis, can help people make more informed decisions, and it also has the potential to complement traditional public health methods for monitoring food safety, such as restaurant inspections. For example, it could enable “adaptive inspections,” which are inspections that are guided, in part, by real-time information that nEmesis provides.
“The Twitter reports are not an exact indicator—any individual case could well be due to factors unrelated to the restaurant meal—but in aggregate the numbers are revealing,” says Henry Kautz, the Robin and Tim Wentworth Director of the Goergen Institute for Data Science and the lead researcher on this project.
In other words, according to Kautz, a “seemingly random collection of online rants becomes an actionable alert” that can help detect cases of foodborne illness in a timely manner. The University recently completed a trial with the Las Vegas Department of Public Health and concluded that its tracking approach led to restaurants that were more prone to violations than others.