Exploring Urban Dynamics from Bluetooth Tracking Data: A Case Study of Austin, Texas
In recent decades, the growing availability of location-aware devices, such as Global Positioning System (GPS) receivers and smart phones, has provided new challenges and opportunities for policy makers to analyze, model, and predict human mobility patterns. However, previous studies on Bluetooth technologies have mainly focused on applying Bluetooth data to analyzing traffic and optimizing transportation networks or deploying new Bluetooth devices in civil engineering. The use of such datasets in understanding urban dynamics and real-time land use patterns is rather limited. This study develops an extendable workflow to explore urban dynamics from Bluetooth data based on a case study in Austin, Texas. We identified similar mobility patterns in different areas of Austin during various study periods, including the Memorial Day long weekend in 2016 and a national musical festival (South by Southwest). Our main goal is to prove the efficacy of this specific workflow and methodology to understand urban dynamics based on real-time Bluetooth data. The hypothesis is that Bluetooth data is sensitive to the daily patterns of human interactions and movements on the individual level, therefore it can capture detailed dynamic patterns. The proposed research also validates new concepts such as “human sensing” and “social sensing” in the field of geography and spatial sciences, which introduces new opportunities to monitor the human aspects of social life.