Difference between revisions of "BusyBear"

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=Design and Solutions=
=Next Steps=
==Tentative Website Layout==
==Tentative Website Layout==
[[File:WebsiteFlowchart.png|600px|thumb|left|Website Design Flowchart]] <br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br>
[[File:WebsiteFlowchart.png|600px|thumb|left|Website Design Flowchart]] <br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br>
Past Projects:
Past Projects:
* [[https://www.crc.id.au/tracking-people-via-wifi-even-when-not-connected/ Tracking People/MAC]]
* [[https://www.crc.id.au/tracking-people-via-wifi-even-when-not-connected/ Tracking People/MAC]]

Revision as of 17:53, 25 March 2019

Project Proposal


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 Bear's Den. By using a network adapter connected to the Raspberry Pi, we will receive an approximate measurement of busyness based on the number of found MAC addresses for a specific region. By looking at pictures taken simultaneously with the MAC address collection, a historic trend between the number of found MAC addresses and relative busyness can be determined. We hope to be able to store this information in a database hosted by AWS and display this data on a website. 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.

Team Members

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


[View Project Log]
[View Project Presentation]
[GitHub Repository]


  • Learn and be able to code in Python as related to the Pi
  • Investigate ping oriented tracking method
  • Investigate sniffing/MAC tracking method
  • Investigate the use of the camera in the analysis of busyness
  • Be able to monitor busyness fairly accurately by filtering detected devices
  • Compare busyness at different times of day and between buildings
  • Design a GUI for an aesthetically pleasing and useful website
  • 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

GanttChart 1.png


Item Description Cost Link
AWS Website Hosting $5 / month https://aws.amazon.com/pricing/?nc2=h_ql_pr
2 x TL-WN722N Network Adapter returned: $7.21 https://www.amazon.com/TP-Link-TL-WN722N-Wireless-network-Adapter/dp/B002SZEOLG
1 x 5dBi Long Range WiFi for Raspberry Pi Network Adapter returned: $5.00 https://www.amazon.com/5dBi-Long-Range-WiFi-Raspberry/dp/B00YI0AIRS/ref=lp_9026119011_1_1?srs=9026119011&ie=UTF8&qid=1550447401&sr=8-1
1 x Alfa AWUSO36NH High Gain USB Wireless G/N Long-Range WiFi Network Adapter Network Adapter $31.99 https://www.amazon.com/Alfa-AWUSO36NH-Wireless-Long-Rang-Network/dp/B0035APGP6/ref=sr_1_1_sspa?keywords=alfa+network+adapter&qid=1553045771&s=gateway&sr=8-1-spons&psc=1
Total Cost $59.20

Design and Solutions


Next Steps

Tentative Website Layout

Website Design Flowchart


Past Projects:

Pi Camera:

Pi Blinking LED:




kismet & monitoring mode: