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      Reliable Identification Schemes for Asset and Production Tracking in Industry 4.0

      research-article
      1 , * , 1 , 2
      Sensors (Basel, Switzerland)
      MDPI
      asset tracking, IoT, Industry 4.0, low-cost tracking

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          Abstract

          Revolutionizing logistics and supply chain management in smart manufacturing is one of the main goals of the Industry 4.0 movement. Emerging technologies such as autonomous vehicles, Cyber-Physical Systems and digital twins enable highly automated and optimized solutions in these fields to achieve full traceability of individual products. Tracking various assets within shop-floors and the warehouse is a focal point of asset management; its aim is to enhance the efficiency of logistical tasks. Global players implement their own solutions based on the state of the art technologies. Small and medium companies, however, are still skeptic toward identification based tracking methods, because of the lack of low-cost and reliable solutions. This paper presents a novel, working, reliable, low-cost, scalable solution for asset tracking, supporting global asset management for Industry4.0. The solution uses high accuracy indoor positioning—based on Ultra-Wideband (UWB) radio technology—combined with RFID-based tracking features. Identifying assets is one of the most challenging parts of this work, so this paper focuses on how different identification approaches can be combined to facilitate an efficient and reliable identification scheme.

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          Most cited references63

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          An Introduction to RFID Technology

          R. Want (2006)
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            A Survey of Indoor Localization Systems and Technologies

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              Industry 4.0 implications in logistics: an overview

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                Author and article information

                Journal
                Sensors (Basel)
                Sensors (Basel)
                sensors
                Sensors (Basel, Switzerland)
                MDPI
                1424-8220
                02 July 2020
                July 2020
                : 20
                : 13
                : 3709
                Affiliations
                [1 ]Industrial IoT Division, AITIA International Inc., 48–50, Czetz János u., 1039 Budapest, Hungary; gvida@ 123456aitia.ai
                [2 ]Department of Telecommunications and Media Informatics, Budapest University of Technology and Economics, 2, Magyar Tudósok krt., 1117 Budapest, Hungary; pvarga@ 123456tmit.bme.hu
                Author notes
                [* ]Correspondence: afranko@ 123456aitia.ai
                Author information
                https://orcid.org/0000-0002-1076-777X
                https://orcid.org/0000-0002-8475-3610
                Article
                sensors-20-03709
                10.3390/s20133709
                7374395
                32630771
                1c1ecc08-b8be-4781-b55f-8d305efc4dbe
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 25 May 2020
                : 28 June 2020
                Categories
                Article

                Biomedical engineering
                asset tracking,iot,industry 4.0,low-cost tracking
                Biomedical engineering
                asset tracking, iot, industry 4.0, low-cost tracking

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