Real-time reassurance monitoring shopping basket in retail store: poster abstract
Pages 713 - 714
Abstract
In this study, we propose a sensor network to estimate service reassurance in a store by estimating customer stress level based on a pulse wave. We developed a basket that can calculate an RR interval (RRI) with sufficient accuracy to estimate customer reassurance from the measured pulse wave under in-store conditions. Two processes were applied to the measurement values based on the assumption that certain circumstances may interfere with measuring pulse waves. Furthermore, the authors conducted pulse wave measurement experiments under simulated store conditions. The results showed RRIs' values with an error rate of 4.9% compared to the true value.
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Subbalakshmi Narsajana Krishnadasa, Basha Ahamed, and Ramesh Bhat. 2009. Impact of acute respiratory stress on cardiac autonomic control in young healthy subjects explored by time and frequency domain methods. Chinese Journal of Physiology 52, 5 (2009), 299--305.
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Yuji Suda, Taiga Arai, Takahiro Yoshizawa, Yuki Fujita, Keiichi Zempo, and Yukihiko Okada. 2019. Shopping Baskets for On-line Beacon Sensor Network in Retail Store. In 2019 16th IEEE Annual Consumer Communications & Networking Conference (CCNC). IEEE, 1--2.
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- Real-time reassurance monitoring shopping basket in retail store: poster abstract
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Published In
November 2020
852 pages
ISBN:9781450375900
DOI:10.1145/3384419
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Published: 16 November 2020
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SenSys '20: The 18th ACM Conference on Embedded Networked Sensor Systems
November 16 - 19, 2020
Virtual Event, Japan
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Overall Acceptance Rate 198 of 990 submissions, 20%
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