UROP Project

public transportation, bus occupancy, data collection, data analysis, machine learning, deep learning, Wi-Fi probe requests, internet of things

Research Mentor: Dr. Qianwen Guo, she/her
Department, College, Affiliation: FAMU-FSU College of Engineering, FAMU-FSU College of Engineering
Contact Email: qguo@eng.famu.fsu.edu
Research Assistant Supervisor (if different from mentor): Mr. Ziyue Li he/his
Research Assistant Supervisor Email: lzy@eng.famu.fsu.edu
Faculty Collaborators: Mr. Jiaqing Lu
Faculty Collaborators Email: jl23br@fsu.edu

Looking for Research Assistants: No
Number of Research Assistants: 6
Relevant Majors: Open to all majors.
Project Location: On FSU Main Campus
Research Assistant Transportation Required: The data collection will be done on FSU campus shuttle buses
Remote or In-person: Partially Remote
Approximate Weekly Hours: 5,
Roundtable Times and Zoom Link: Not participating in the Roundtable

Project Description

This study proposes leveraging IoT-enabled devices, particularly smartphones, using Wi-Fi technology for transit data collection and analysis. It aims to develop a monitoring system that detects smartphones in real-time, capturing data like MAC addresses and GPS coordinates to infer transit patterns. Challenges include Wi-Fi signal range and device detection inconsistencies. Pilot studies in Florida will validate the system's efficacy across diverse transit systems. Implementing this system enables transit agencies to optimize vehicle dispatching and scheduling while enhancing the overall user experience by providing valuable insights into transit travel flow patterns.

Research Tasks: The primary objective is to collect Wi-Fi data from FSU campus shuttle buses and manually count the bus occupancy for each station.
Students interested in analyzing Wi-Fi data and developing machine learning or deep learning models can pursue additional opportunities.

Skills that research assistant(s) may need: Complete the task diligently and ensure accurate counting.