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2019 | OriginalPaper | Chapter

A Large Scale Trajectory Dataset for Shopper Behaviour Understanding

Authors : Patrizia Gabellini, Mauro D’Aloisio, Matteo Fabiani, Valerio Placidi

Published in: New Trends in Image Analysis and Processing – ICIAP 2019

Publisher: Springer International Publishing

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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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Footnotes
1
www.​nist.​gov, last accessed: March 7, 2016.
 
Literature
1.
Cheng, Q.J., Ng, J.K.Y., et al.: A wireless LAN location estimation system using center of gravity as an algorithm selector for enhancing location estimation. In: 2012 IEEE 26th International Conference on Advanced Information Networking and Applications (AINA), pp. 261–268. IEEE (2012)
2.
Contigiani, M., Pietrini, R., Mancini, A., Zingaretti, P.: Implementation of a tracking system based on UWB technology in a retail environment. In: 2016 12th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications (MESA), pp. 1–6. IEEE (2016)
3.
Farid, Z., Nordin, R., Ismail, M.: Recent advances in wireless indoor localization techniques and system. J. Comput. Netw. Commun. 2013 (2013)
4.
Ferracuti, N., Norscini, C., Frontoni, E., Gabellini, P., Paolanti, M., Placidi, V.: A business application of rtls technology in intelligent retail environment: defining the shopper’s preferred path and its segmentation. J. Retail. Consum. Serv. 47, 184–194 (2019) CrossRef
5.
Frontoni, E., Mancini, A., Zingaretti, P.: Embedded vision sensor network for planogram maintenance in retail environments. Sensors 15(9), 21114–21133 (2015)CrossRef
6.
7.
Fuchs, C., Aschenbruck, N., Martini, P., Wieneke, M.: Indoor tracking for mission critical scenarios: a survey. Pervasive Mob. Comput. 7(1), 1–15 (2011)CrossRef
8.
Gezici, S., et al.: Localization via ultra-wideband radios: a look at positioning aspects for future sensor networks. IEEE Signal Process. Mag. 22(4), 70–84 (2005)CrossRef
9.
Koyuncu, H., Yang, S.H.: A survey of indoor positioning and object locating systems. IJCSNS Int. J. Comput. Sci. Netw. Secur. 10(5), 121–128 (2010)
10.
Lam, K.Y., Ng, J.K.Y., Wang, J., Ho Chuen Kam, C., Wai-Hung Tsang, N.: A pervasive promotion model for personalized promotion systems on using WLAN localization and NFC techniques. Mob. Inf. Syst. 2015 (2015)
11.
12.
Liciotti, D., Paolanti, M., Frontoni, E., Zingaretti, P.: People detection and tracking from an RGB-D camera in top-view configuration: review of challenges and applications. In: Battiato, S., Farinella, G.M., Leo, M., Gallo, G. (eds.) ICIAP 2017. LNCS, vol. 10590, pp. 207–218. Springer, Cham (2017). https://​doi.​org/​10.​1007/​978-3-319-70742-6_​20CrossRef
13.
Liciotti, D., Paolanti, M., Pietrini, R., Frontoni, E., Zingaretti, P.: Convolutional networks for semantic heads segmentation using top-view depth data in crowded environment. In: 2018 24th International Conference on Pattern Recognition (ICPR), pp. 1384–1389. IEEE (2018)
14.
Liu, H., Darabi, H., Banerjee, P., Liu, J.: Survey of wireless indoor positioning techniques and systems. IEEE Trans. Syst. Man Cybern. Part C Appl. Rev. 37(6), 1067–1080 (2007)CrossRef
15.
Mancini, A., Frontoni, E., Zingaretti, P., Placidi, V.: Smart vision system for shelf analysis in intelligent retail environments. In: ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, pp. V004T08A045–V004T08A045. American Society of Mechanical Engineers (2013)
16.
Marin-Hernandez, A., de Jesús Hoyos-Rivera, G., Garcia-Arroyo, M., Marin-Urias, L.F.: Conception and implementation of a supermarket shopping assistant system. In: 2012 11th Mexican International Conference on Artificial Intelligence (MICAI), pp. 26–31. IEEE (2012)
17.
Newman, A.J., Foxall, G.R.: In-store customer behaviour in the fashion sector: some emerging methodological and theoretical directions. Int. J. Retail. Distrib. Manag. 31(11), 591–600 (2003)CrossRef
18.
Paolanti, M., Liciotti, D., Pietrini, R., Mancini, A., Frontoni, E.: Modelling and forecasting customer navigation in intelligent retail environments. J. Intell. Robot. Syst. 91(2), 165–180 (2018)CrossRef
19.
Paolanti, M., Romeo, L., Martini, M., Mancini, A., Frontoni, E., Zingaretti, P.: Robotic retail surveying by deep learning visual and textual data. Robot. Auton. Syst. 118, 179–188 (2019)CrossRef
20.
Paolanti, M., Sturari, M., Mancini, A., Zingaretti, P., Frontoni, E.: Mobile robot for retail surveying and inventory using visual and textual analysis of monocular pictures based on deep learning. In: 2017 European Conference on Mobile Robots (ECMR), pp. 1–6. IEEE (2017)
21.
Yamabe, T., Lehdonvirta, V., Ito, H., Soma, H., Kimura, H., Nakajima, T.: Applying pervasive technologies to create economic incentives that alter consumer behavior. In: Proceedings of the 11th International Conference on Ubiquitous Computing, pp. 175–184. ACM (2009)
22.
You, C.W., Wei, C.C., Chen, Y.L., Chu, H.H., Chen, M.S.: Using mobile phones to monitor shopping time at physical stores. IEEE Pervasive Comput. 2, 37–43 (2011)
23.
Zeimpekis, V., Giaglis, G.M., Lekakos, G.: A taxonomy of indoor and outdoor positioning techniques for mobile location services. ACM SIGecom Exch. 3(4), 19–27 (2002)CrossRef
Metadata
Title
A Large Scale Trajectory Dataset for Shopper Behaviour Understanding
Authors
Patrizia Gabellini
Mauro D’Aloisio
Matteo Fabiani
Valerio Placidi
Copyright Year
2019
Book
New Trends in Image Analysis and Processing – ICIAP 2019

Print ISBN: 978-3-030-30753-0

Electronic ISBN: 978-3-030-30754-7

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-030-30754-7_29

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