Ten, Ki Hong and Kang, Hooi Siang and Siow, Chee Loon and Goh, Pei Sean and Lee, Kee Quen and Huspi, Sharin Hazlin and Soares, Guedes (2023) Automatic identification system in accelerating decarbonization of maritime transportation: the state-of-the-art and opportunities. Ocean Engineering, 289 (NA). NA. ISSN 0029-8018
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Official URL: http://dx.doi.org/10.1016/j.oceaneng.2023.116232
Abstract
This paper presents a review of the state-of-the-art Automatic Identification System (AIS) data-driven studies and applications in effort to control the carbon footprint from maritime transportation, followed by the prospects of decarbonization measures that demand AIS complement. Pertaining critical impact from global anthropogenic emissions, AIS data serves as the primary source of information for the assessment of the ships emission inventories to study their environmental impact against ambient air quality and evoke awareness from the maritime sector. Wide range of information types, transmission coverage and frequency made AIS data outshines other maritime information services in the provision of consistent serial information of ship activities that offer tedious studies of correlations between parameters. As such, it can potentially be further exploited into various approaches of analytical applications, such as Estimated Time of Arrival (ETA) predictions, emission projections, and decision supporting system for ships. Furthermore, AIS data features are flexible for integration with other data sources to achieve a flawless system, such as weather routing and smart inland shipping. Ultimately, the outcomes of these studies aim to contribute piecewise to the fulfilment of ideal concepts – ‘green’ and ‘smart’ in maritime sector, by efficient processes and minimum waste of energy.
Item Type: | Article |
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Uncontrolled Keywords: | AIS data, decarbonization, emission estimation, maritime traffic efficiency, ship emissions |
Subjects: | T Technology > TJ Mechanical engineering and machinery |
Divisions: | Mechanical Engineering |
ID Code: | 106059 |
Deposited By: | Yanti Mohd Shah |
Deposited On: | 31 May 2024 03:05 |
Last Modified: | 31 May 2024 03:05 |
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