This Instructable teaches you how to build a system to track indoor positioning of cats. The purpose of this project is to get insight into pet positioning and see their interactions.
The system incorporates RSSI (Received Signal Strength Indicator) to estimate cat position. A bluetooth device is put on the cat, and other bluetooth devices are used as device scanners ("beacons"). These beacons scan the area for the Bluetooth device attached on the cat. The scanning process results in a RSSI for the discovered device. The stronger the RSSI, the closer the cat is to the beacon. In order for the localization to work, we collected "fingerprints" of the RSSIs to multiple beacons to be used as training data for a classifier to predict the location of the cat. After collecting fingerprint data, we ran the live system with the cats to collect test data. We used Machine Learning on the actual test data to predict the location of the cats using the fingerprint data.
The system is based on http://www.kptang.com/pubs/gsmlocalization-hotmob...
List of Materials
- One or more cat to track.
- An apartment or space for cats (preferably a natural environment the cats are comfortable in)
- At least three Bluetooth-enabled devices to use as beacons. We used Android phones with an RSSI reporting app (explained in steps 3-5)
- Any Bluetooth-enabled device to attach to the cat. We used Samsung Galaxy Gear.
- A web server with a database (explained in step 1)
- A visualization for the data (explained in step 9)
This instructable was made as part of the CS graduate course "Tangible Interactive Computing" at the University of Maryland, College Park taught by Professor Jon Froehlich. Please see http://cmsc838f-s14.wikispaces.com/ for more details. This project was done by Hitesh Maidasani and Sana Malik.