Shipping and Logistics Analytics using Big Data : Automatic Identification System Data
Book Details
Format
Hardback or Cased Book
ISBN-10
1032505346
ISBN-13
9781032505343
Publisher
Taylor & Francis Ltd
Imprint
Routledge
Country of Manufacture
GB
Country of Publication
GB
Publication Date
Nov 13th, 2026
Print length
488 Pages
Weight
453 grams
Product Classification:
Product designProduction & quality control managementProduction and quality control managementOperational researchTransport industriesShipping industriesInternational law, transport and commerce: maritime lawInternational maritime lawEngineering: generalCivil engineering, surveying & buildingCivil engineering, surveying and buildingTransport technology & tradesTransport technology and tradesNetwork managementComputer science
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With the advancement of information and communication technology, a data-driven approach applying the tools and methodologies of big data analytics has become quite common across industry.
With the advancement of information and communication technology, a data-driven approach applying the tools and methodologies of big data analytics has become quite common across industry. In maritime shipping, automatic identification system (AIS) vessel movement data is reliable and improving and has been used for the detection of suspicious vessels and to support vessel navigation. However, since detailed cargo items and loading/unloading conditions cannot be directly obtained from AIS data, research using this data in the fields of logistics, shipping, and shipbuilding is still limited. This book introduces the state of the art on the worldwide use of AIS and other maritime big data for shipping and logistics analysis, with data-oriented case studies, for the maritime and related industries and for university use in maritime economics, industrial engineering, and transport engineering.
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