Students turn transit data into route improvements
A group of Data Analytics students has completed a major applied research project that maps transit usage across the City of Wrenford, producing recommendations that could make the local transit network more efficient.
The project, supervised by faculty in the School of Computing & Academic Studies, analysed ridership patterns from the past academic year. The team examined which routes carry the most passengers, where transfer points experience the highest demand, and how usage shifts between the Benchlands Campus and the Mercer Street Campus.
Using the skills learned in their program, the students built visual dashboards that highlight peak usage times and underutilized routes. Their analysis suggests several adjustments that could reduce wait times and improve connectivity for students and residents.
"The goal was to take raw data and turn it into something the transit planners can actually use," said Priya, Data Analytics. "We wanted to show where the gaps are and how small changes could make a big difference for daily commuters."
The project was conducted under the guidance of the Research & Innovation office, which supports student-led applied research that benefits the local community. The office provides mentorship and helps students connect their academic work with real-world problems.
The findings have been shared with the City of Wrenford transit department. While the city operates the routes and sets fares, the polytechnic's U-Pass discount is managed separately by the college. The recommendations focus on scheduling and routing based on actual usage data.
Students in the Data Analytics program, offered at both the Benchlands and Mercer Street campuses, work on projects that prepare them for careers in data science, business intelligence, and public sector analytics. The program is available in full-time and hybrid formats, with intakes in September and January.
The project is one example of how the polytechnic connects classroom learning with community needs. Students apply technical skills in data cleaning, statistical analysis, and visualization to solve problems for local organizations.
For more information about student research opportunities, visit the Research & Innovation page. To explore the Data Analytics program, see Data Analytics.