Big Data for Operational Efficiency of Transport and Logistics : A Review

被引:0
|
作者
Borgi, Tawfik [1 ]
Zoghlami, Nesrine [1 ]
Abed, Mourad [2 ]
Naceur, Mohamed Saber [1 ]
机构
[1] Univ Tunis El Manar, Ecole Natl Ingenieurs Tunis, LTSIRS Lab, Tunis 1002, Tunisia
[2] Univ Valenciennes & Hainaut Cambresis, LAMIH, F-59313 Valenciennes 9, France
来源
2017 6TH IEEE INTERNATIONAL CONFERENCE ON ADVANCED LOGISTICS AND TRANSPORT (ICALT) | 2017年
关键词
Big Data; Transport; Logistics;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In the new information and communication era, digital transformation and adoption of recent technological advances have become a must for all transport and logistics providers who aim to significantly improve their activities. Consequently, this digitalization is inevitably giving birth to voluminous and rapidly growing sets of large-scale data generated from heterogeneous data sources, also known as Big Data. With particular management infrastructures and advanced data analysis methodologies, these huge amounts of data can be efficiently harvested to optimize the logistics and transport operations and provide a higher quality of service. This paper provides a review of the application of Big Data technologies in improving the operational efficiency of transport and logistics, exposes the main use cases and identifies some future research challenges.
引用
收藏
页码:113 / 120
页数:8
相关论文
共 50 条
  • [21] A Review of Big Data in Road Freight Transport Modeling: Gaps and Potentials
    Wasim Shoman
    Sonia Yeh
    Frances Sprei
    Jonathan Köhler
    Patrick Plötz
    Yancho Todorov
    Seppo Rantala
    Daniel Speth
    Data Science for Transportation, 2023, 5 (1):
  • [22] Big data applications in intelligent transport systems: a bibliometric analysis and review
    Mahbub Hassan
    Hridoy Deb Mahin
    Abdullah Al Nafees
    Arpita Paul
    Saikat Sarkar Shraban
    Discover Civil Engineering, 2 (1):
  • [23] The Influence of Big Data on Production and Logistics A Theoretical Discussion
    Altendorfer-Kaiser, Susanne
    ADVANCES IN PRODUCTION MANAGEMENT SYSTEMS: THE PATH TO INTELLIGENT, COLLABORATIVE AND SUSTAINABLE MANUFACTURING, 2017, 513 : 221 - 227
  • [24] Using big data to deliver insights into proppant logistics
    Thompson, Carl
    Hart's E and P, 2019, (June):
  • [25] CRM Reform of Logistics Enterprises in Big Data Environment
    Wang, Hui
    Yu, Yang
    PROCEEDINGS OF THE 2016 INTERNATIONAL CONFERENCE ON EDUCATION, MANAGEMENT AND COMPUTER SCIENCE (ICEMC 2016), 2016, 129 : 131 - 135
  • [26] HOSPITAL MEDICAL BEHAVIOUR SUPERVISION AND OPERATIONAL EFFICIENCY EVALUATION METHOD BASED BASED ON BIG DATA PLATFORM
    Liu, Yi
    Zhang, Yi
    SCALABLE COMPUTING-PRACTICE AND EXPERIENCE, 2024, 25 (03): : 1852 - 1862
  • [27] SELIS BDA: Big Data Analytics for the Logistics Domain
    Provatas, Nikodimos
    Kassela, Evdokia
    Chalvantzis, Nikolaos
    Bakogiannis, Anastasios
    Giannakopoulos, Ioannis
    Koziris, Nectarios
    Konstantinou, Ioannis
    2020 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA), 2020, : 2416 - 2425
  • [28] HOSPITAL MEDICAL BEHAVIOUR SUPERVISION AND OPERATIONAL EFFICIENCY EVALUATION METHOD BASED BASED ON BIG DATA PLATFORM
    LIU Y.I.
    ZHANG Y.I.
    Scalable Computing, 2024, 25 (03): : 1852 - 1862
  • [29] Big Data Based Logistics Data Mining Platform: Architecture and Implementation
    Gao, Fei
    Zhao, Qilan
    INTERNATIONAL JOURNAL OF INTERDISCIPLINARY TELECOMMUNICATIONS AND NETWORKING, 2014, 6 (04) : 24 - 34
  • [30] Big Data: A Review
    Sagiroglu, Seref
    Sinanc, Duygu
    PROCEEDINGS OF THE 2013 INTERNATIONAL CONFERENCE ON COLLABORATION TECHNOLOGIES AND SYSTEMS (CTS), 2013, : 42 - 47