By Tracy Chen ’22, Industrial and Management Engineering/Mathematics, and Mia Mayerhofer ’23, Mathematics/Economics
Have you ever been to your student union or library to work on a group project, only to find no tables available? Since the pandemic began, have you gone to get tested for COVID-19, only to leave because your schedule could not accommodate a long line? These inconveniences inspired a group of Rensselaer Polytechnic Institute students in the Institute for Data Exploration and Applications (IDEA), a platform that enables data-driven research projects, to develop a solution for finding locations to study, meet up with friends, and schedule other gatherings.
The StudySafe web application is designed to identify congestion and population density around the Rensselaer campus. The project was supervised under the direction of Kristin Bennett, associate director of IDEA, and John Erickson, director of IDEA research operations, and is part of IDEA’s Data INCITE program, which encourages undergraduate students to apply data science research to real-world problems.
Supported by the United Health Foundation, the application predicts how many people are in a selected building during specified hours by monitoring near-real-time, fully anonymized Wi-Fi access data. The Wi-Fi data used in the application’s visualizations is collected twice hourly from over 1,300 wireless access points on campus.
By providing an assortment of geographical and graphical representations displayed through a user-friendly interface, StudySafe helps to identify patterns and trends in how the community interacts on the campus. StudySafe adopts a simplistic layout that can be accessed on both computers and mobile devices. Users can explore the data and customize the visualizations in several ways by selecting specific days, times, and locations, and interacting with markers on the campus maps.
Although StudySafe is currently only deployed at Rensselaer, the campus-specific data structures may be easily replicated at other institutions and organizations to create similar monitoring tools using Wi-Fi data. The applications can also be integrated with other preventive measures to redesign processes as we all adapt to a post-pandemic world.
Share your feedback on StudySafe by accessing the feedback form linked in the sidebar menu of the application. If you are interested in accessing the code and specific data structures used, please visit the research team’s Github.
