• DocumentCode
    2922082
  • Title

    Big data analytics for logistics and transportation

  • Author

    Ben Ayed, Abdelkarim ; Ben Halima, Mohamed ; Alimi, Adel M.

  • Author_Institution
    REGIM-Lab., Univ. of Sfax, Sfax, Tunisia
  • fYear
    2015
  • fDate
    20-22 May 2015
  • Firstpage
    311
  • Lastpage
    316
  • Abstract
    Nowadays, there are many challenges for the logistics industry mainly with the integration of E-commerce and new sources of data such as smartphones, sensors, GPS and other devices. Those new data sources generate daily a huge quantity of unstructured data, to deal with such complex data, the use of big data analytic tools becomes an obligation. In this context, many works have been done recently in the integration of big data analytics in the logistics industry. In this paper, we propose to give a review of the latest applications of big data analytics in the field of logistics and transportation industry and to propose a novel approach to detect and recognize containers code based on a Hadoop big data analytics system.
  • Keywords
    Big Data; Global Positioning System; data analysis; distributed processing; goods distribution; logistics; production engineering computing; smart phones; GPS; Hadoop big data analytics system; big data analytic tools; containers code; e-commerce; logistics industry; sensors; smartphones; transportation industry; unstructured data; Aggregates; Cities and towns; Computer architecture; Global Positioning System; Industries; Maintenance engineering; XML; big data analytics; logistic; transportation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Logistics and Transport (ICALT), 2015 4th International Conference on
  • Conference_Location
    Valenciennes
  • Type

    conf

  • DOI
    10.1109/ICAdLT.2015.7136630
  • Filename
    7136630