Leveraging RFID Data Analytics for the Design of an Automated Checkout System

Faculty/Professorship: Information Systems and Energy Efficient Systems  
Author(s): Hauser, Matthias; Günther, Sebastian  ; Flath, Christoph; Thiesse, Frédéric
Title of the compilation: Tagungsband der Wirtschaftsinformatik
Corporate Body: 13 th International Conference on Wirtschaftsinformatik, February 12 - 15, 2017, St. Gallen, Switzerland
Publisher Information: AIS Electronic Library (AISeL)
Year of publication: 2017
Pages: 1201-1204
Language(s): English
URL: https://aisel.aisnet.org/wi2017/track12/paper/12/
Traditional checkout systems are labor-intensive and can be a great source of frustration for customers when having to wait in line. In contrast, automated checkout systems scan, total and charge a customer’s purchase to a registered payments account while they are simply leaving the store. We focus on the main challenge of automatically detecting customer purchases. To this end, we develop a checkout system that leverages data mining techniques to (i) reliably and timely detect items leaving the shopping floor area and (ii) assign them to individual customers. We demonstrate the system’s feasibility using a large data set collected in the laboratory under real-world conditions.
Keywords: Data Analytics, RFID, Internet of Things, Automated Checkout
Peer Reviewed: Ja
International Distribution: Ja
Type: Conferenceobject
URI: https://fis.uni-bamberg.de/handle/uniba/44378
Year of publication: 31. August 2018