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King Saud Univ. Comput. Inf. Sci."],"published-print":{"date-parts":[[2025,8]]},"abstract":"<jats:title>Abstract<\/jats:title>\n          <jats:p>Traditional supermarkets often encounter challenges such as inefficient shopping guidance, long checkout lines, and poor customer experience. To address these issues, this study proposes a fully self-service smart shopping system, comprising three key modules: a smart shopping cart, a client app, and a back-end management platform, with full-chain encryption using TLS (Transport Layer Security) and RSA (Rivest Shamir Adleman) to ensure secure data transmission. The smart shopping system utilizes a KNN (K Nearest Neighbor) collaborative filtering recommendation algorithm to improve the relevance and accuracy of product suggestions. By integrating Mask R-CNN and UWB (Ultra Wide Band) into SLAM (Simultaneous Localization and Mapping) framework, we construct MU-SLAM (Mask R-CNN UWB SLAM), which enables precise localization and robust obstacle avoidance in unknown supermarket environments. Additionally, integrating a distributed DIMP (Discriminative Model Prediction) visual-tracking algorithm and infrared range sensors ensures that the smart shopping cart always follows the customer at a safe distance. Comparative experiments show that the MU-SLAM algorithm\u2019s positioning accuracy increased by 92%, while the distributed DIMP algorithm\u2019s tracking persistence improved by 107%. Furthermore, validation of the real supermarket environment demonstrated that the smart shopping system respectively reduces average shopping time and average checkout time by 33.15% and 90.17%, significantly improving both operational efficiency and the overall customer experience.<\/jats:p>","DOI":"10.1007\/s44443-025-00182-4","type":"journal-article","created":{"date-parts":[[2025,8,5]],"date-time":"2025-08-05T15:17:14Z","timestamp":1754407034000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Design and development of full self-service smart shopping system for unmanned supermarket"],"prefix":"10.1007","volume":"37","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5162-1240","authenticated-orcid":false,"given":"Xiao","family":"Liang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu","family":"Qi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuo","family":"Xi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guanglei","family":"Meng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhujun","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,8,5]]},"reference":[{"key":"182_CR1","doi-asserted-by":"publisher","unstructured":"Astri R, Kamal A, Sura SB (2022) Coffee shop recommendation system using an item-based collaborative filtering approach. 2022 International symposium on information technology and digital innovation (ISITDI), IEEE. https:\/\/doi.org\/10.1109\/ISITDI54883.2022.00019","DOI":"10.1109\/ISITDI54883.2022.00019"},{"issue":"3","key":"182_CR2","doi-asserted-by":"publisher","first-page":"162","DOI":"10.3390\/drones9030162","volume":"9","author":"S Bu","year":"2025","unstructured":"Bu S, Zhang J, Li X et al (2025) IVU-AutoNav: Integrated visual and UWB framework for autonomous navigation. 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