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 ![]() |
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/ |
Abstract: | 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 |

originated at the
University of Bamberg
University of Bamberg