Conference Proceeding Article
This paper presents AudioSense, the system to monitor user-item interactions inside a store hence enabling precisely customized promotions. A shopper's smartwatch emits sound every time the shopper picks up or touches an item inside a store. This sound is then localized, in 2D space, by calculating the angles of arrival captured by multiple microphones deployed on the racks. Lastly, the 2D location is mapped to specific items on the rack based on the rack layout information. In our initial experiments conducted with a single rack with 16 compartments, we could localize the shopper's smartwatch with a median estimation error of 15.9 cm in 2-dimensional space.
AoA, Audio sensing, Sound localization, TDoA, Trajectory tracking, Audio acoustics, Time difference of arrival, Wearable computers, Wearable technology, Angles of arrival, Audio sensing, Behavior analysis, Estimation errors, Layout information, Multiple microphones, Sound localization, Trajectory tracking, Ubiquitous computing
Computer and Systems Architecture | Software Engineering
Proceedings of the ACM International Joint Conference on Pervasive and Ubiquitous Computing and ACM International Symposium on Wearable Computers, Maui, United States, 2017 September 11-15
Association for Computing Machinery, Inc
City or Country
Maui; United States
SHARMA, Amit and LEE, Youngki.
AudioSense: Sound-based shopper behavior analysis system. (2017). Proceedings of the ACM International Joint Conference on Pervasive and Ubiquitous Computing and ACM International Symposium on Wearable Computers, Maui, United States, 2017 September 11-15. 488-493. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/3839
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