Abstract
Nowadays, retailers are embracing the Internet of Things as the latest technology to drive superior customer experience. Leverage data sources from sensors, beacons and mobile devices to identify and analyze in-store customer shopping behavior. With this motivation, this study implemented an in-store customer traffic and path monitoring system for supermarket using image processing and object detection. the system utilized the ultra-wideband indoor positioning technique to monitor the customer shopping path and the single shot multibox detection technique to monitor the real-time customer traffic. The customer monitoring system was implemented and evaluated in an actual small-scale supermarket. Results showed that the detection model prediction score and the traffic counting both obtained an accuracy score of 99%. In addition, the localization system achieved the minimum error difference of 9.73% for x coordinate and 3.86% for y coordinate between pre-determined positions and the actual anchor position readings. Furthermore, the system successfully generated the most frequent path and the total customer traffic of the day. In the future, this work can aid retail owners make better choices, run businesses more efficiently, and deliver improved customer service.
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References
Alfawares D (2018) Ssd: Single shot multibox detector in tensorflow. https://github.com/SolsticeConsulting/koko-ssd-tensorflow. Accessed 10 Dec 2018
Asghari P, Rahmani AM, Javadi HHS (2019) Internet of things applications: a systematic review. Comput Netw 148:241–261. https://doi.org/10.1016/j.comnet.2018.12.008
Caro F, Sadr R (2019) The internet of things (iot) in retail: Bridging supply and demand. Bus Horiz 62(1):47–54. https://doi.org/10.1016/j.bushor.2018.08.002
Chen L, Zhang Z, Peng L (2018) Fast single shot multibox detector and its application on vehicle counting system. IET Intel Transport Syst 12(10):1406–1413. https://doi.org/10.1049/iet-its.2018.5005
Chen R, Peng L, Qin Y (2010) Supermarket shopping guide system based on internet of things. In: IET international conference on wireless sensor network 2010 (IET-WSN 2010), pp 17–20. https://doi.org/10.1049/cp.2010.1020
Contigiani M, Pietrini R, Mancini A, Zingaretti P (2016) Implementation of a tracking system based on uwb technology in a retail environment. Mechatronic and Embedded Systems and Applications (MESA), 2016 12th IEEE/ASME International Conference on. IEEE, IEEE, pp 1–6
Dabove P, Di Pietra V, Piras M, Jabbar AA, Kazim SA (2018) Indoor positioning using ultra-wide band (uwb) technologies: Positioning accuracies and sensors’ performances. In: 2018 IEEE/ION position, location and navigation symposium (PLANS), pp 175–184. https://doi.org/10.1109/PLANS.2018.8373379
Dwiyasa F, Lim M (2016) A survey of problems and approaches in wireless-based indoor positioning. In: 2016 International conference on indoor positioning and indoor navigation (IPIN), pp 1–7. https://doi.org/10.1109/IPIN.2016.7743591
Eldib M, Deboeverie F, Philips W, Aghajan H (2018) Discovering activity patterns in office environment using a network of low-resolution visual sensors. J Ambient Intell Hum Comput 9(2):381–411. https://doi.org/10.1007/s12652-017-0511-7
Hamie J, Denis B, D’Errico R, Richard C (2015) On-body toa-based ranging error model for motion capture applications within wearable uwb networks. J Ambient Intell Hum Comput 6(5):603–612. https://doi.org/10.1007/s12652-013-0215-6
Hui J (2018) Ssd object detection: Single shot multibox detector for real-time processing. https://medium.com/. Accessed 10 Dec 2018
Kim H (2019) Multiple vehicle tracking and classification system with a convolutional neural network. J Ambient Intell Hum Comput. https://doi.org/10.1007/s12652-019-01429-5
Liu W, Anguelov D, Erhan D, Szegedy C, Reed S, Fu CY, Berg AC (2016) SSD: Single shot multibox detector. In: ECCV
Liu L, Zhou B, Zou Z, Yeh S, Zheng L (2018) A smart unstaffed retail shop based on artificial intelligence and iot. In: 2018 IEEE 23rd international workshop on computer aided modeling and design of communication links and networks (CAMAD), pp 1–4. https://doi.org/10.1109/CAMAD.2018.8514988
MathWorks (2018) Matlab visualization app. https://www.mathworks.com/help/thingspeak/matlab-visualizations-app.html. Accessed 10 Dec 2018
Mehmood F, Ullah I, Ahmad S, Kim D (2019) Object detection mechanism based on deep learning algorithm using embedded iot devices for smart home appliances control in cot. J Ambient Intell Hum Comput. https://doi.org/10.1007/s12652-019-01272-8
of Encyclopaedia Britannica TE (2019) Uncertainty principle. https://www.britannica.com/science/uncertainty-principle. Accessed 10 Dec 2018
Orciuoli F, Parente M (2017) An ontology-driven context-aware recommender system for indoor shopping based on cellular automata. J Ambient Intell Hum Comput 8(6):937–955. https://doi.org/10.1007/s12652-016-0411-2
Patil K (2016) Retail adoption of internet of things: applying tam model. In: 2016 International conference on computing, analytics and security trends (CAST), pp 404–409. https://doi.org/10.1109/CAST.2016.7915003
Pei Z, Li Y, Xu S (2012) An anchor-free localization algorithm for shopping carts on supermarket internet of things. In: Proceedings of 2012 2nd international conference on computer science and network technology, pp 1401–1404. https://doi.org/10.1109/ICCSNT.2012.6526182
Perakis H, Gikas V (2018) Evaluation of range error calibration models for indoor uwb positioning applications. In: 2018 International conference on indoor positioning and indoor navigation (IPIN), pp 206–212. https://doi.org/10.1109/IPIN.2018.8533755
Silvia Z, Martina C, Fabio S, Alessandro P (2018) Ultra wide band indoor positioning system: analysis and testing of an ips technology. IFAC-PapersOnLine 51(11):1488–1492. https://doi.org/10.1016/j.ifacol.2018.08.292, 16th IFAC Symposium on Information Control Problems in Manufacturing INCOM 2018
Simonyan K, Zisserman A (2014) Very deep convolutional networks for large-scale image recognition. 1409.1556
Streitz N (2019) Beyond ’smart-only’cities: redefining the ’smart-everything’ paradigm. J Ambient Intell Hum Comput 10(2):791–812. https://doi.org/10.1007/s12652-018-0824-16
Sui W, Wang K (2015) An accurate indoor localization approach using cellphone camera. In: 2015 11th international conference on natural computation (ICNC), pp 949–953. https://doi.org/10.1109/ICNC.2015.7378119
Sun Y, Zhao K, Wang J, Li W, Bai G, Zhang N (2016) Device-free human localization using panoramic camera and indoor map. In: 2016 IEEE International conference on consumer electronics-China (ICCE-China), pp 1–5. https://doi.org/10.1109/ICCE-China.2016.7849743
Tharwat A (2018) Classification assessment methods. Appl Comput Informat. https://doi.org/10.1016/j.aci.2018.08.003
VanderPlas J (2016) Python data science handbook: essential tools for working with data, 1st edn. O’Reilly Media Inc, Newton
Wang Y, Yang C (2016) 3s-cart: A lightweight, interactive sensor-based cart for smart shopping in supermarkets. IEEE Sens J 16(17):6774–6781. https://doi.org/10.1109/JSEN.2016.2586101
Acknowledgements
M. I. Alipio would like to acknowledge the support of Electronics and Communications Engineering Department of the Gokongwei College of Engineering of the De La Salle University, Manila, Philippines.
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Alipio, M.I., Peñalosa, K.M.T. & Unida, J.R.C. In-store customer traffic and path monitoring in small-scale supermarket using UWB-based localization and SSD-based detection. J Ambient Intell Human Comput 14, 4955–4969 (2023). https://doi.org/10.1007/s12652-020-02236-z
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DOI: https://doi.org/10.1007/s12652-020-02236-z