I4S: capturing shopper's in-store interactions
Authors: 
Sougata Sen, Archan Misra, Vigneshwaran Subbaraju, Karan Grover, Meera Radhakrishnan, 
Rajesh K. Balan, Youngki LeeAuthors Info & Claims
Pages 156 - 159
Abstract
In this paper, we present I4S, a system that identifies item interactions of customers in a retail store through sensor data fusion from smartwatches, smartphones and distributed BLE beacons. To identify these interactions, I4S builds a gesture-triggered pipeline that (a) detects the occurrence of "item picks", and (b) performs fine-grained localization of such pickup gestures. By analyzing data collected from 31 shoppers visiting a midsized stationary store, we show that we can identify person-independent picking gestures with a precision of over 88%, and identify the rack from where the pick occurred with 91%+ precision (for popular racks).
References
[1]
P. Bahl and V. N. Padmanabhan. RADAR: An in-building RF-based user location and tracking system. In INFOCOM 2000. IEEE.
[2]
J. Krockel and F. Bodendorf. Intelligent processing of video streams for visual customer behavior analysis. In Proceedings of ICONS 2012, Vol. 1.
[3]
S. Lee, C. Min, C. Yoo, and J. Song. Understanding Customer Malling Behavior in an Urban Shopping Mall Using Smartphones. In ACM Conference on Pervasive and Ubiquitous Computing (UbiComp '13 Adjunct).
[4]
M. Radhakrishnan et al. Iris: Tapping wearable sensing to capture in-store retail insights on shoppers. In International Conference on Pervasive Computing and Communications (PerCom'16). IEEE.
[5]
S. Rallapalli et al. Enabling Physical Analytics in Retail Stores Using Smart Glasses. In 20th Annual International Conference on Mobile Computing and Networking. 2014 (MobiCom'14).
[6]
S. Sen et al. Accommodating user diversity for in-store shopping behavior recognition. In ACM 18th International Symposium on Wearable Computers (ISWC'14).
[7]
L. Shangguan et al. ShopMiner: Mining Customer Shopping Behavior in Physical Clothing Stores with COTS RFID Devices. In 13th ACM Conference on Embedded Networked Sensor Systems. 2015 (SenSys '15).
[8]
C. You, C. Wei, Y. Chen, H. Chu, and M. Chen. 2011. Using phones to monitor shopping time at physical stores. IEEE Pervasive Computing 10, 2 (2011).
[9]
Y. Zeng, P. H. Pathak, and P. Mohapatra. Analyzing shopper's behavior through wifi signals. In 2nd workshop on Workshop on Physical Analytics (WPA'15).
Recommendations
Shopping Behavior and Consumer Preference for Store Price Format: Why "Large Basket" Shoppers Prefer EDLP
<P>In recent years, the supermarket industry has become increasingly competitive. One outcome has been the proliferation of a variety of pricing formats, and considerable debate among academics and practitioners about how these formats affect consumers' ...
Shopping Behavior and Consumer Preference for Store Price Format: Why "Large Basket" Shoppers Prefer EDLP
In recent years, the supermarket industry has become increasingly competitive. One outcome has been the proliferation of a variety of pricing formats, and considerable debate among academics and practitioners about how these formats affect consumers' ...
Effect of Brand Loyalty on Advertising and Trade Promotions: A Game Theoretic Analysis with Empirical Evidence
In this paper we examine the issue of balancing media advertising pull strategy and trade promotions push strategy for manufacturers of consumer packaged goods utilizing a three-stage game theoretic analysis and test model's implications with scanner ...
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
October 2018
307 pages
ISBN:9781450359672
DOI:10.1145/3267242
- General Chairs:
- Kai Kunze,
- Rajesh K. Balan,
- Youngki Lee,
- Program Chairs:
- Michael Beigl,
- Roshan Peiris
Copyright © 2018 ACM.
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]
Sponsors
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 08 October 2018
Check for updates
Qualifiers
- Short-paper
Funding Sources
- National Science Foundation
- Singapore Ministry of Education Academic Research Fund Tier2
- National Research Foundation, Prime Minister?s Office, Singapore
Conference
UbiComp '18: The 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing
October 8 - 12, 2018
Singapore, Singapore
Acceptance Rates
Overall Acceptance Rate 38 of 196 submissions, 19%
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 344Total Downloads
- Downloads (Last 12 months)46
- Downloads (Last 6 weeks)4
Reflects downloads up to 21 Nov 2024
Other Metrics
Citations
Cited By
View allView Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in