{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,4]],"date-time":"2026-10-04T04:37:08Z","timestamp":1791088628189,"version":"4.1.0"},"reference-count":25,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2024,1,8]],"date-time":"2024-01-08T00:00:00Z","timestamp":1704672000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"De La Salle University","award":["21 IR S 3TAY20-3TAY21"],"award-info":[{"award-number":["21 IR S 3TAY20-3TAY21"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Transactional data from point-of-sales systems may not consider customer behavior before purchasing decisions are finalized. A smart shelf system would be able to provide additional data for retail analytics. In previous works, the conventional approach has involved customers standing directly in front of products on a shelf. Data from instances where customers deviated from this convention, referred to as \u201ccross-location\u201d, were typically omitted. However, recognizing instances of cross-location is crucial when contextualizing multi-person and multi-product tracking for real-world scenarios. The monitoring of product association with customer keypoints through RANSAC modeling and particle filtering (PACK-RMPF) is a system that addresses cross-location, consisting of twelve load cell pairs for product tracking and a single camera for customer tracking. In this study, the time series vision data underwent further processing with R-CNN and StrongSORT. An NTP server enabled the synchronization of timestamps between the weight and vision subsystems. Multiple particle filtering predicted the trajectory of each customer\u2019s centroid and wrist keypoints relative to the location of each product. RANSAC modeling was implemented on the particles to associate a customer with each event. Comparing system-generated customer\u2013product interaction history with the shopping lists given to each participant, the system had a general average recall rate of 76.33% and 79% for cross-location instances over five runs.<\/jats:p>","DOI":"10.3390\/s24020367","type":"journal-article","created":{"date-parts":[[2024,1,8]],"date-time":"2024-01-08T06:12:58Z","timestamp":1704694378000},"page":"367","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["Smart Shelf System for Customer Behavior Tracking in Supermarkets"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5876-8018","authenticated-orcid":false,"given":"John Anthony C.","family":"Jose","sequence":"first","affiliation":[{"name":"Department of Electronics and Computer Engineering, Gokongwei College of Engineering, De La Salle University, 2401 Taft Avenue, Malate, Manila 1004, Metro Manila, Philippines"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christopher John B.","family":"Bertumen","sequence":"additional","affiliation":[{"name":"Department of Electronics and Computer Engineering, Gokongwei College of Engineering, De La Salle University, 2401 Taft Avenue, Malate, Manila 1004, Metro Manila, Philippines"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marianne Therese C.","family":"Roque","sequence":"additional","affiliation":[{"name":"Department of Electronics and Computer Engineering, Gokongwei College of Engineering, De La Salle University, 2401 Taft Avenue, Malate, Manila 1004, Metro Manila, Philippines"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Allan Emmanuel B.","family":"Umali","sequence":"additional","affiliation":[{"name":"Department of Electronics and Computer Engineering, Gokongwei College of Engineering, De La Salle University, 2401 Taft Avenue, Malate, Manila 1004, Metro Manila, Philippines"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jillian Clara T.","family":"Villanueva","sequence":"additional","affiliation":[{"name":"Department of Electronics and Computer Engineering, Gokongwei College of Engineering, De La Salle University, 2401 Taft Avenue, Malate, Manila 1004, Metro Manila, Philippines"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2585-1912","authenticated-orcid":false,"given":"Richard Josiah","family":"TanAi","sequence":"additional","affiliation":[{"name":"Department of Manufacturing Engineering and Management, Gokongwei College of Engineering, De La Salle University, 2401 Taft Avenue, Malate, Manila 1004, Metro Manila, Philippines"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1296-3616","authenticated-orcid":false,"given":"Edwin","family":"Sybingco","sequence":"additional","affiliation":[{"name":"Department of Electronics and Computer Engineering, Gokongwei College of Engineering, De La Salle University, 2401 Taft Avenue, Malate, Manila 1004, Metro Manila, Philippines"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3534-8010","authenticated-orcid":false,"given":"Jayne","family":"San Juan","sequence":"additional","affiliation":[{"name":"Department of Industrial and Systems Engineering, Gokongwei College of Engineering, De La Salle University, 2401 Taft Avenue, Malate, Manila 1004, Metro Manila, Philippines"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Erwin Carlo","family":"Gonzales","sequence":"additional","affiliation":[{"name":"Management and Organization Department, Ramon V. del Rosario College of Business, De La Salle University, 2401 Taft Avenue, Malate, Manila 1004, Metro Manila, Philippines"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,1,8]]},"reference":[{"key":"ref_1","first-page":"159","article-title":"Retail Analytics: Driving Success in Retail Industry with Business Analytics","volume":"7","author":"Chandramana","year":"2017","journal-title":"Res. J. Soc. Sci. Manag."},{"key":"ref_2","unstructured":"Hickins, M. (2023, September 17). What Is Retail Analytics? The Ultimate Guide. Oracle. Available online: https:\/\/www.oracle.com\/in\/retail\/what-is-retail-analytics\/."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1016\/j.ijpe.2010.04.026","article-title":"An empirical analysis of inventory turnover behaviour in Greek retail sector: 2000\u20132005","volume":"133","author":"Kolias","year":"2011","journal-title":"Int. J. Prod. Econ."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"102880","DOI":"10.1016\/j.jretconser.2021.102880","article-title":"Combining sell-out data with shopper behaviour data for category performance measurement: The role of category conversion power","volume":"65","author":"Pascucci","year":"2022","journal-title":"J. Retail. Consum. Serv."},{"key":"ref_5","first-page":"3","article-title":"Financial Management of Micro, Small, and Medium Enterprises in Cebu, Philippines","volume":"8","author":"Anoos","year":"2020","journal-title":"Int. J. Small Bus. Entrep. Res."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1590","DOI":"10.1108\/ITP-12-2020-0867","article-title":"Why do people shop online? A comprehensive framework of consumers\u2019 online shopping intentions and behaviors","volume":"35","author":"Venkatesh","year":"2022","journal-title":"Inf. Technol. People"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Xiao, Z., Yang, J., Wraith, K., and Mosca, P. (2019, January 24\u201326). A Hybrid Solution for Smart Supermarkets Based on Actuator Networks. Proceedings of the 2019 7th International Conference on Information, Communication and Networks (ICICN), Macao, China.","DOI":"10.1109\/ICICN.2019.8834962"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Ruiz, C., Falcao, J., Pan, S., Noh, H.Y., and Zhang, P. (2019, January 13\u201314). AIM3S: Autonomous Inventory Monitoring through Multi-Modal Sensing for Cashier-Less Convenience Stores. Proceedings of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation, New York, NY, USA.","DOI":"10.1145\/3360322.3360834"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Xu, R., Nikouei, S.Y., Chen, Y., Polunchenko, A., Song, S., Deng, C., and Faughnan, T.R. (2018, January 20\u201324). Real-Time Human Objects Tracking for Smart Surveillance at the Edge. Proceedings of the 2018 IEEE International Conference on Communications (ICC), Kansas City, MO, USA.","DOI":"10.1109\/ICC.2018.8422970"},{"key":"ref_10","unstructured":"(2023, November 18). \u201cAiFi\u201d. AiFi. Available online: https:\/\/aifi.com\/platform\/."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3478086","article-title":"ISACS: In-Store Autonomous Checkout System for Retail","volume":"5","author":"Falcao","year":"2021","journal-title":"Proc. ACM Interact. Mob. Wearable Ubiquitous Technol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"278","DOI":"10.26421\/JDI3.2-5","article-title":"Expert Opinions on Smart Retailing Technologies and Their Impacts","volume":"3","author":"Hafner","year":"2022","journal-title":"J. Data Intell."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Higa, K., and Iwamoto, K. (2019). Robust Shelf Monitoring Using Supervised Learning for Improving On-Shelf Availability in Retail Stores. Sensors, 19.","DOI":"10.3390\/s19122722"},{"key":"ref_14","first-page":"47","article-title":"On-Shelf Availability in Retailing","volume":"115","author":"Moorthy","year":"2015","journal-title":"Int. J. Comput. Appl."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"3455","DOI":"10.1109\/JSEN.2022.3140356","article-title":"On-Shelf Load Cell Calibration for Positioning and Weighing Assisted by Activity Detection: Smart Store Scenario","volume":"22","author":"Lin","year":"2022","journal-title":"IEEE Sens. J."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"331","DOI":"10.1016\/j.ins.2020.10.022","article-title":"Compressed Monte Carlo with application in particle filtering","volume":"553","author":"Martino","year":"2021","journal-title":"Inf. Sci."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"2233","DOI":"10.1109\/ACCESS.2019.2961740","article-title":"A Localization Based on Unscented Kalman Filter and Particle Filter Localization Algorithms","volume":"8","author":"Ullah","year":"2020","journal-title":"IEEE Access"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"8725","DOI":"10.1109\/TMM.2023.3240881","article-title":"StrongSORT: Make DeepSORT great again","volume":"25","author":"Du","year":"2023","journal-title":"IEEE Trans. Multimed."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"386","DOI":"10.1109\/TPAMI.2018.2844175","article-title":"Mask R-CNN","volume":"42","author":"He","year":"2020","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., and Sun, J. (2016, January 27\u201330). Deep Residual Learning for Image Recognition. Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, NV, USA.","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Lin, T.-Y., Doll\u00e1r, P., Girshick, R., He, K., Hariharan, B., and Belongie, S. (2017, January 21\u201326). Feature Pyramid Networks for Object Detection. Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, HI, USA.","DOI":"10.1109\/CVPR.2017.106"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Lin, T.-Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., and Doll\u00e1r, P. (2014, January 6\u201312). Microsoft COCO: Common Objects in Context. Proceedings of the Computer Vision\u2014ECCV 2014: 13th European Conference, Zurich, Switzerland.","DOI":"10.1007\/978-3-319-10602-1_48"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"012002","DOI":"10.1088\/1742-6596\/930\/1\/012002","article-title":"Forecasting Error Calculation with Mean Absolute Deviation and Mean Absolute Percentage Error","volume":"930","author":"Khair","year":"2017","journal-title":"J. Phys. Conf. Ser."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"6962","DOI":"10.1016\/j.matpr.2021.12.360","article-title":"Artificial Intelligence Framework for MSME Sectors with Focus on Design and Manufacturing Industries","volume":"62","author":"Sharma","year":"2022","journal-title":"Mater. Today Proc."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"108502","DOI":"10.1016\/j.cie.2022.108502","article-title":"Predicting Cost of Defects for Segmented Products and Customers Using Ensemble Learning","volume":"171","author":"Sariyer","year":"2022","journal-title":"Comput. Ind. Eng."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/24\/2\/367\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T13:41:57Z","timestamp":1760103717000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/24\/2\/367"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1,8]]},"references-count":25,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2024,1]]}},"alternative-id":["s24020367"],"URL":"https:\/\/doi.org\/10.3390\/s24020367","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,1,8]]}}}