This fall, the campus at Princeton University has not only teemed with returning students but also extensive construction, such as work for the new homes for the School of Engineering and Applied Science and the Princeton University Art Museum.
This has made commute planning difficult for students due to blocked roads and changed bus routes, said Kenny Huang, a senior in the Department of Operations Research and Financial Engineering (ORFE) and a student enrolled in the undergraduate certificate program at the Center for Statistics and Machine Learning (CSML).
To map pedestrian traffic on campus and get students involved with data science tools, Princeton Data Science (PDS), a club sponsored by CSML, is organizing a group project that is focused on finding out where people go every day on campus and elucidating efficient routes to buildings. Last month, PDS put a call out for students to participate in the semester-long group project and now has a core team of eight students, said Huang, a PDS member in the club’s DataDev division and main organizer of the project.
The idea for the group project came about from Huang and others contemplating the best route to get to class.
“I've spent a lot of time on campus and there are a lot of options to get from point A to point B. As an ORFE major, I have taken optimization classes, so I have been pondering how to optimize my commute. It's always been a daily question, but this semester has had more construction than usual,” said Huang. “There are a lot of issues with construction impacting traffic; for example, how do you get from Whitman College to Prospect Avenue.”
The project also came out of a proposal that Huang said he brought to the club.
“I started out my analytics journey doing sports analytics, and I found it a little bit isolating because I didn't know a lot of people who did the same thing,” Huang said.
To address that sense of isolation, Huang proposed a community-oriented, collaborative initiative where students would come together on a common interest. This has resulted in the pedestrian traffic study, which should impact every student and give underclassmen needed experience with data science projects.
The core team has five freshman and three sophomore students. Students will conduct surveys, starting on November 10th. (See note after article about survey participation and opportunities to win a prize). And then students will learn to clean, manipulate and store data. Participants will then code and perform analysis mostly in Python or R. At the end of the semester, the group will then present their findings with the further possibility of an app.
Questions that students will examine during the project include finding pressure points on campus where many people congregate, and how construction is impacting traffic. Are some people taking super long detours due to the construction?
A data point in the project would be a path from point A to point B, said Huang. One path would be from Whitman College to Olden Avenue with notes on the main intersections along this journey. All the paths or data points would result in an overall model of the campus.
Huang hopes that students will come away with not just a greater understanding of the campus and student behavior but also added skills.
“The main goal for this project is to give underclassmen more hands-on experience working on these kinds of projects,” he said. “It would be helpful for everyone who is interested in doing data science or data analytics to have a gateway to learn how to access data, learn how to encode data, and how to enact actionable policies based on data. Our goal is to give underclassmen that opportunity and hopefully make it as interesting and as painless as possible for them along the way.”
How to participate in the survey or data collection of the pedestrian study and learn about opportunities to win a prize:
Data collection will take place from November 10th to the 22nd.
First 30 people to submit 14 walks get a guaranteed prize. There's a raffle for Airpod Pros Generation 2 where each walk gets one entry, max two walks per day count towards the 14 counts.
Instructions link: https://drive.google.com/file/d/1qgfqgOQz_POjT35Fnpl5Op67ni-7PvVR/view