Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
6-2016
Abstract
In the current retail segment, the retail store owners are keen to understand the browsing behavior and purchase pattern of the shoppers inside the physical stores. Profiling the behavior of the shopper is key to success for any marketing strategies that can optimize or personalize shopping-related services in real-time. We envision that exploiting the knowledge of real-time behavior of shopper’s in-store activities enables novel applications such as: (a) targeted advertising or recommendations: based on longer term shopper profiles, (b) proactive retail help to assist the shoppers who are confused in choosing between two items, (c) smart reminders that can remind the shoppers to pickup an item in the shopping list that they might have missed. Our work is motivated by the fact that a significant fraction of in-store shopping activities involve gestural interactions with objects of interest (such as picking up an item and putting the item in the shopping cart in a grocery store or retrieving and trying out a dress in a clothing store). In our recent works, we showed the design and initial prototype of frameworks for reliably inferring shopper’s in-store interactions and behavior by just observing their hand and foot movement inside a store. The hand gestures and locomotive pattern of the shopper inside a store is identified by appropriately mining the sensor data from shopper's personal smartphone and wearable devices (smartwatch).
Keywords
Location analytics, retail trade, shopper behavior
Discipline
Software Engineering | Technology and Innovation
Research Areas
Software and Cyber-Physical Systems
Publication
MobiSys 2016 Companion: Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services: Singapore, June 25-30
First Page
115
Last Page
115
ISBN
9781450344166
Identifier
10.1145/2938559.2938572
Publisher
ACM
City or Country
New York
Citation
RADHAKRISHNAN, Meeralakshmi; ESWARAN, Sharanya; SEN, Sougata; SUBBARAJU, Vigneshwaran; MISRA, Archan; and BALAN, Rajesh Krishna.
Demo: Smartwatch based shopping gesture recognition. (2016). MobiSys 2016 Companion: Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services: Singapore, June 25-30. 115-115.
Available at: https://ink.library.smu.edu.sg/sis_research/3589
Copyright Owner and License
Publisher
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1145/2938559.2938572