IRIS: Tapping wearable sensing to capture in-store retail insights on shoppers

• Main Authors: RADHAKRISHNAN, Meera, ESWARAN, Sharanya, MISRA, Archan, CHANDER, Deepthi, DASGUPTA, Koustuv
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2016
• Subjects: IRIS; variable-order HMM-based sequence prediction; change point detection; feature-based landmarking combination; atomic item-level interactions; retail store; smartwatch; smartphone; Sales and Merchandising; Software Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/3238; https://ink.library.smu.edu.sg/context/sis_research/article/4240/viewcontent/1476359.pdf
• Institution: Singapore Management University

We investigate the possibility of using a combination of a smartphone and a smartwatch, carried by a shopper, to get insights into the shopper’s behavior inside a retail store. The proposed IRIS framework uses standard locomotive and gestural micro-activities as building blocks to define novel compos...