Analysis of Vessel Behaviors in Costal Waterways Using Big AIS Data
| Autor: | Qiankai Cao, Xiang Li, Guolei Tang |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Automatic Identification System
Computer science law 0502 economics and business 05 social sciences Traffic simulation 010501 environmental sciences 01 natural sciences Port (computer networking) 050203 business & management 0105 earth and related environmental sciences Marine engineering law.invention |
| Zdroj: | 2019 IEEE 4th International Conference on Cloud Computing and Big Data Analysis (ICCCBDA). |
| DOI: | 10.1109/icccbda.2019.8725712 |
| Popis: | Enhancing traffic safety and obtaining vessel messages in complicated and varied marine environment has become the focus of attention. Therefore, Automatic Identification System (AIS) is utilized to get the vessel behaviors. In this article, we develop the vessel behavior analysis framework based on JPPF parallel processing framework to get spatial-temporal characteristics of vessel behavior in costal waterways. At last, 1 billion AIS data from Tianjin port in China are input into the proposed framework and vessel behaviors can be obtained, which can serve for vessel traffic simulation, safe navigation of vessel, supervision of the maritime sector and macroscopic dispatch of the country. |
| Databáze: | OpenAIRE |
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