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Optimization of Warehouse Management Using Drones, Artificial Intelligence and RFID

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dc.contributor.authorStasa, Pavel-
dc.contributor.authorBenes, Filip-
dc.contributor.authorSvub, Jiri-
dc.contributor.authorHolusa, Veroslav-
dc.contributor.authorObrusnikova, Miroslava-
dc.contributor.authorDulovec, Jan-
dc.contributor.authorHollesch, Lukas-
dc.contributor.authorUnucka, Jakub-
dc.contributor.authorRhee, Jongtae-
dc.contributor.authorJung, Jin-Woo-
dc.date.accessioned2026-01-12T03:30:13Z-
dc.date.available2026-01-12T03:30:13Z-
dc.date.issued2025-
dc.identifier.issn2155-6806-
dc.identifier.issn2155-6814-
dc.identifier.urihttps://scholarworks.dongguk.edu/handle/sw.dongguk/62722-
dc.description.abstractThis poster presents a novel system for inventory automation in large outdoor warehouses using a lightweight drone-mounted UHF RFID reader. The system leverages autonomous aerial platforms equipped with custom-developed RFID readers operating in the 865-868 MHz band, combined with intelligent software modules for tag readability evaluation. The proposed solution addresses major limitations of traditional stationary or handheld readers by enabling efficient scanning from a distance, including hard-to-reach areas. Two prototypes of RFID readers were developed, tested and optimized for use on commercial drones, and validated in real-world environments in both Czech and Korean warehouse facilities. The results confirm the reader’s ability to reliably detect tags at distances up to 28 meters and demonstrate its applicability for regular inventory processes. In addition to the hardware, two supporting methodologies and a software tool were developed for integration into existing information systems. The project was carried out within an international research consortium, where the Korean partners focused on AI-based image processing for drone navigation and risk avoidance. The presented solution contributes to the development of autonomous inventory systems, improves safety, and significantly reduces human effort and inventory time in logistics operations. © 2025 IEEE.-
dc.format.extent2-
dc.language영어-
dc.language.isoENG-
dc.publisherIEEE-
dc.titleOptimization of Warehouse Management Using Drones, Artificial Intelligence and RFID-
dc.typeArticle-
dc.publisher.location미국-
dc.identifier.doi10.1109/MASS66014.2025.00077-
dc.identifier.scopusid2-s2.0-105026334405-
dc.identifier.bibliographicCitation2025 IEEE 22nd International Conference on Mobile Ad-Hoc and Smart Systems (MASS), pp 502 - 503-
dc.citation.title2025 IEEE 22nd International Conference on Mobile Ad-Hoc and Smart Systems (MASS)-
dc.citation.startPage502-
dc.citation.endPage503-
dc.type.docTypeConference paper-
dc.description.isOpenAccessY-
dc.description.journalRegisteredClassforeign-
dc.subject.keywordAuthorAI integration-
dc.subject.keywordAuthorautonomous logistics-
dc.subject.keywordAuthordrone inventory-
dc.subject.keywordAuthorRFID-
dc.subject.keywordAuthorUHF reader-
dc.subject.keywordAuthorwarehouse automation-
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