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Places like retail stores, museums, libraries are gradually moving towards a more automated experinece for customers. Amazon Go serves as an example where customers can do automated checkout of their items. Towards this end, tracking the activity of the customers in such spaces becomes an important problem that needs to be solved with high accuracy.
Finding by counting is a system which can currently localize moving customers with decimeter level accuracy.
Finding by counting supports the localization of moving customers with the following features:
- Finding by Counting can find physical co-ordinates of moving customers at regular intervals with an average accuracy of 0.4 meters.
- Unlike other state-of-the-art techniques which use Wi-Fi as a medium and use location of Wi-Fi APs, Finding by Counting works on BLE beacons than can be attached with items like products in retail stores.
- Most techniques use RSS or strength values of signals from fixed devices like WiFi APs and then map that to distance either through fingerprinting or by deriving a mathamatical model of signal strength decay with distance. Finding by Couting ignores RSS value altogether due to its high variance and unreliability in indoor settings.
Our first version of Finding by Counting is out. Check it now!
IN PRESS Finding by Counting: A Probabilistic Packet Count Model for Indoor Localization in BLE Environments
Subham De, Shreyans Chowdhary, Aniket Shirke, Yat Long Lo, Robin Kravets and Hari Sundaram, WiNTECH, Mobicom'17, Snowbird, UT, USA. October 2017
Finding by Counting is being developed by a team of undergraduate and graduate students headed by Prof. Hari Sundaram along with Prof. Robin Kravets. The list of contributors includes: Subham De, Shreyans Chowdhary, Aniket Shirke, Yat Long Lo.
Please reach out to the lead PhD student, Subham De ([email protected]) if you'd like to either contribute, or be a tester of Finding by Counting!