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It always seems like an impossible task to find an open table to work or a quick line for food across the WashU campus. BusyBear's goal is to create a database that is accessible to WashU students that will show the population and busyness trends of popular locations on campus, beginning with Lopata Gallery. By using the Wifi receiver located on the Raspberry Pi, we will receive an approximate measurement of busyness based on wifi signals. Our end goal is to gather information to allow the WashU community to create more educated decisions regarding where to go and when to go there.


[View Project Log] [View Project Presentation]

Team Members

Thomas Emerson
Tom Goon
Allison Todd
David Tekien, TA
Jim Feher, Instructor


  • Setup a Raspberry Pi and be able to control it through a virtual machine and/or Putty
  • Learn and be able to code in Python as related to the Pi
  • Implement detection of devices through WiFi (MAC Addresses)
  • Be able to monitor busyness fairly accurately by filtering detected devices
  • Compare busyness at different times of day and between buildings
  • Host a website displaying useful and relevant data through Amazon Web Services (AWS)
  • Create a database to store data and use through AWS


  • Limited experience with working with WiFi receivers or anything to do with MAC Addresses
  • Limited knowledge of Python and Raspberry Pi
  • Connecting our data with a database, AWS, and a website
  • Privacy Concerns

Gantt Chart



Item Description Cost Link
AWS Website Hosting Depends https://aws.amazon.com/pricing/?nc2=h_ql_pr
2 x TL-WN722N Network Adapter $13.46 x 2 https://www.amazon.com/TP-Link-TL-WN722N-Wireless-network-Adapter/dp/B002SZEOLG
Total Cost $26.92


Past Projects: