Automatic identification system in accelerating decarbonization of maritime transportation: The state-of-the-art and opportunities

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.

Automated summary

This paper provides an overview of the latest developments and applications of data-driven studies using Automatic Identification System (AIS) in order to control carbon emissions from maritime transportation. The paper emphasizes the importance of AIS data in assessing ship emissions and their environmental impact. AIS data's wide range of information types, coverage, and frequency make it superior to other maritime information services, allowing for in-depth correlation studies. The paper suggests that AIS data can be further utilized in various analytical applications such as Estimated Time of Arrival predictions, emission projections, and decision support systems for ships. Additionally, AIS data's flexibility for integration with other data sources, such as weather routing and smart inland shipping, can contribute to a seamless system. The ultimate goal of these studies is to contribute to a "green" and "smart" maritime sector through efficient processes and minimal energy waste.