Customer behavior analytics using an autonomous robotics-based system

Alexander Petrovsky, Ivan Kalinov, Pavel Karpyshev, Mikhail Kurenkov, Vladimir Ramzhaev, Valery Ilin, Dzmitry Tsetserukou

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Citations (Scopus)

Abstract

This paper suggests a novel method for customer behavior analytics and demand distribution based on Radio Frequency Identification (RFID) stocktaking. Existing solutions lack applicability to real-life situations in retailing, which may result in unobservable loss of sales. The proposed solution provides new parameters of demand distribution to the retailer using a mobile robot for autonomous stocktaking of RFID-equipped shopping rooms. Built models depict location-related demand dependencies, the most and the least purchasable areas in a store, and precise localization of lost and moved items. Our research differs from the related works by the sheer size of the underlying data set collected in a real-world environment for more than ten months.

Original languageEnglish
Title of host publication16th IEEE International Conference on Control, Automation, Robotics and Vision, ICARCV 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages327-332
Number of pages6
ISBN (Electronic)9781728177090
DOIs
Publication statusPublished - 13 Dec 2020
Event16th IEEE International Conference on Control, Automation, Robotics and Vision, ICARCV 2020 - Virtual, Shenzhen, China
Duration: 13 Dec 202015 Dec 2020

Publication series

Name16th IEEE International Conference on Control, Automation, Robotics and Vision, ICARCV 2020

Conference

Conference16th IEEE International Conference on Control, Automation, Robotics and Vision, ICARCV 2020
Country/TerritoryChina
CityVirtual, Shenzhen
Period13/12/2015/12/20

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