A Large Scale Trajectory Dataset for Shopper Behaviour Understanding

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Abstract

In intelligent retail environment, Ultra Wideband (UWB) is suitable for applications where the positioning accuracy is a critical parameter. This technology provides the use of several UWB antennas properly positioned inside a predetermined area and powered battery tags free to move inside the area. This has been used to deploy a Real Time Locating System (RTLS), which gives complete oversight of the customers and employees in the store and improves the customer experience. In this paper, it is described a tracking system based on UWB technology. The installation, in stores in Germany and Indonesia became the basis for a trajectory dataset and results presented in this paper based on a two-year experience that measured 10.4 million shoppers. Through the analysis of the collected tracking data, it allows to derive several information on the shoppers behaviour inside a store. Behaviours that concern flows of walking, most visited areas inside the space dedicated to the shopping and average travel times. The collection of this great quantity of data is very important for future marketing research that have the aim to attract people to purchase.

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APA

Gabellini, P., D’Aloisio, M., Fabiani, M., & Placidi, V. (2019). A Large Scale Trajectory Dataset for Shopper Behaviour Understanding. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11808 LNCS, pp. 285–295). Springer Verlag. https://doi.org/10.1007/978-3-030-30754-7_29

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