RFID-based Article-to-Fixture Predictions in Real-World Fashion Stores

TL;DR

This paper explores RFID-based methods to accurately localize articles in fashion stores, enabling practical applications like sales heat maps, by analyzing RFID read events with clustering and distance measures.

Contribution

The paper introduces novel RFID-based article-to-fixture prediction approaches using DTW and DBSCAN, achieving over 90% accuracy in real-world retail environments.

Findings

Read events can assign articles to fixtures with >90% accuracy.

Clustering and distance-based methods are effective for RFID localization.

Practical challenges of integrating RFID localization in daily retail operations are identified.

Abstract

In recent years, Radio Frequency Identification (RFID) technology has been applied to improve numerous processes, such as inventory management in retail stores. However, automatic localization of RFID-tagged goods in stores is still a challenging problem. To address this issue, we equip fixtures (e.g., shelves) with reference tags and use data we collect during RFID-based stocktakes to map articles to fixtures. Knowing the location of goods enables the implementation of several practical applications, such as automated Money Mapping (i.e., a heat map of sales across fixtures). Specifically, we conduct controlled lab experiments and a case-study in two fashion retail stores to evaluate our article-to-fixture prediction approaches. The approaches are based on calculating distances between read event time series using DTW, and clustering of read events using DBSCAN. We find that, read events collected during RFID-based stocktakes can be used to assign articles to fixtures with an accuracy of more than 90%. Additionally, we conduct a pilot to investigate the challenges related to the integration of such a localization system in the day-to-day business of retail stores. Hence, in this paper we present an exploratory venture into novel and practical RFID-based applications in fashion retails stores, beyond the scope of stock management.