Work In-progress: Mining the Student Data for Fitness

Data mining-driven agents are often used in applications such as waiting times estimation or traffic flow prediction. Such approaches often require large amounts of data from multiple sources, which may be difficult to obtain and lead to incomplete or noisy datasets. University ID card data, in contrast, is easy to access with very low noise. However, little attention has been paid to the availability of these datasets and few applications have been developed to improve student services on campus. This work uses data from CougCard, the Washington State University official ID card, used daily by most students. Our goal is to build an intelligent agent to improve student service quality by predicting the crowdedness at different campus facilities. This work in-progress focuses on the University Recreation Center, one of the most popular facilities on campus, to optimize students’ workout experiences.