Demographics: 37 participants, undergraduates from a single class in the Social Sciences

Size: over 36 million raw data records

Duration: 4 weeks

Purpose: Investigate the utility of combining indoor localization systems and data provided by smartphones. Demonstrate that low quality data can be cleaned and used to provide meaningful and accurate movement tracing through post-processing. Demonstrate that tracking data can reveal insights that cannot be revealed by traditional tools, such as surveys and sketch maps.

Data Collected 

  • Base Duty Cycle: 2 minutes
    • Accelerometer: 30 seconds
    • Bluetooth: 30 seconds
    • WiFi: 30 seconds 
    • Magnetometer: 30 seconds
    • Battery: 10 records
  • On-phone contextual surveys: approximately 3 per day
  • Demographic survey
  • Sketch maps of frequent paths on campus
  • Campus space use survey

Outcomes: Developed a method to provide accurate indoor localization information by combining the logger, SaskEPS, and Walkable CentreLINE. Spaces frequented by individuals that were not reported in surveys and sketch maps were identified, e.g., bus terminal and skywalks between buildings.

Papers Employing SHED3 Data:

  1. Petrenko, A., Bell, S., Stanley, K., Qian, W., Sizo, A., & Knowles, D. (2013). Human Spatial Behavior, Sensor Informatics, and Disaggregate Data. In Spatial Information Theory (pp. 224-242). Springer International Publishing.
  2. Petrenko, A., Sizo, A., Winchel, Q., Knowles, D., Tavassolian, A., Stanley, K., Bell, S., Exploring Mobility Indoors: an Application of Sensor-based and GIS Systems, Transactions on GIS, in press. 
© Kevin Stanley 2014