Data-driven transit advocacy, with a side of cloud

With a grant from NSF and additional support from CloudBank, another NSF-funded initiative, Vanessa Frias-Martinez, an associate professor at the University of Maryland, is working to put data collection in the hands of residents to enable self-advocacy.

In response to longtime complaints about late buses and other transportation problems, Frias-Martinez “proposed to … build a toolkit, which is basically a mobile app and a dashboard,” she said. “The mobile app will allow residents to collect data about their door-to-door mobility patterns, so it’s kind of a digital diary.”

When residents leave home to use public transit, they start collecting data about their trip on the phone. During the journey, the app asks about their perception of the quality of the service they’re receiving. At the same time, Frias-Martinez’s team collects real-time information from the Maryland Transit Administration (MTA) and data on how long the trip took. Using artificial intelligence algorithms, all the data is analyzed and presented on a dashboard.