Smart and Low Carbon Emission-Oriented Maritime Traffic Management and Controlling
A special issue of Journal of Marine Science and Engineering (ISSN 2077-1312). This special issue belongs to the section "Ocean Engineering".
Deadline for manuscript submissions: 30 June 2025 | Viewed by 27625
Special Issue Editors
Interests: video data-driven intelligent transportation environment perception and understanding; large-scale transportation data analysis (traffic flow data, AIS, etc.); smart ship/autonomous port
Special Issues, Collections and Topics in MDPI journals
Interests: offshore civil engineering; coastal engineering; data mining; intelligent transportation system
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
It is reported that over 50% of people live in urban areas, a figure on track to increase to more than 65% in the future. More foods and varied living products are needed to meet the needs of peoples’ daily lives. Maritime transportation is considered to be a cost-effective manner used to transfer goods around the world. In that way, the maritime community has paid significant attention to enhancing maritime traffic efficiency as well as energy consumption. It is noted that approximately 3% of global carbon emissions come from the shipping industry; thus, there is a significant focus on reducing the carbon emissions of the shipping industry. Many countries encourage ships to sail with low-sulfur oil, whilst for ships sailing in inland waterways, it is mandatory to use low-sulfur oil to reduce carbon emissions.
The focus of many researchers is on employing artificial intelligence (AI), big data, and computer-vision-related techniques to enhance maritime traffic efficiency. To help ships sail in a safer and faster manner, varied advanced techniques are integrated to determine ship maneuvering operations from multiple maritime data sources (e.g., radar, automatic identification system (AIS), maritime videos). It has been found that there are many challenges in the automatous shipping era, along with carbon peaking and carbon neutrality. For instance, it is not easy to automatically find an optimal ship trajectory with low economic cost and fuel consumption for a given voyage. In attempt to reach this aim, we welcome the submission of novel studies to promote cost-effective yet high-efficiency maritime traffic with feasible and transferable solutions. We welcome the submission of manuscripts which align with our Special Issue topic of “Smart and Low Carbon Emission-Oriented Maritime Traffic Management and Controlling Analysis”. We anticipate receiving submissions from a variety of research topics relevant to smart shipping and reductions in ship carbon emissions. The sample topics of interest include, but are not limited to, the following:
- Ship carbon emissions and emission control area analysis;
- Traffic knowledge mining from large-scale maritime data;
- Maritime traffic situation awareness via varied sensory data (maritime surveillance video, AIS, radar, etc.);
- Ship travelling path optimization under influence from varied uncertainty factors;
- Energy consumption reduction analysis for the autonomous ship and port era;
- Ship kinematic information exploitation and analysis via multiple maritime data sources.
Dr. Xinqiang Chen
Dr. Salvatore Antonio Biancardo
Guest Editors
Manuscript Submission Information
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Keywords
- smart shipping
- maritime carbon emissions reduction
- artificial intelligence
- multiple maritime data source
- maritime traffic safety
- ship maneuvering operation
- intelligent traffic situation awareness
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