IDEAS home Printed from https://ideas.repec.org/h/spr/sptchp/978-3-031-60290-0_6.html
   My bibliography  Save this book chapter

Data Collection Technologies in Logistics

In: Logistics Information Systems

Author

Listed:
  • Batuhan Kocaoglu

    (Istanbul Topkapi University)

Abstract

This chapter is a comprehensive exploration of the various technologies that play a pivotal role in gathering data, thereby transforming and optimizing logistics operations. It begins by emphasizing the importance of automatic data collection and subsequently delves into the world of barcodes, including traditional 1D barcodes, GTIN, EAN, UPC, and 2D barcodes like QR codes. Radio Frequency Identification (RFID) technology is extensively discussed, covering passive and active RFID tags, EPC, GTAG, and system components. The chapter proceeds to explore digital scales, handheld terminals, touchscreens, kiosks, wearable systems, and advanced technologies like voice picking, augmented reality (AR), drones, IoT, sensors, cameras, and AI, showcasing how they enhance data collection in logistics. GPS and the role of RFID in combating counterfeiting conclude the chapter, offering a holistic view of how data collection technologies revolutionize the logistics landscape.

Suggested Citation

  • Batuhan Kocaoglu, 2024. "Data Collection Technologies in Logistics," Springer Texts in Business and Economics, in: Logistics Information Systems, chapter 0, pages 181-217, Springer.
    • Handle: RePEc:spr:sptchp:978-3-031-60290-0_6
    DOI: 10.1007/978-3-031-60290-0_6
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    More about this item

    Keywords

    Barcode; EAN13; QR; RFID; EPC; Voice picking; Pick by light; AR; Drone; Sensor; IoT; M2M; GPS;
    All these keywords.

    JEL classification:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:sptchp:978-3-031-60290-0_6. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.