S. Mouzakitis, C. Kontzinos, Panagiotis Kapsalis, Ioanna Kanellou, Georgios Kormpakis, Giannis Tsapelas, D. Askounis
{"title":"通过人工智能优化海事流程:VesselAI概念和用例","authors":"S. Mouzakitis, C. Kontzinos, Panagiotis Kapsalis, Ioanna Kanellou, Georgios Kormpakis, Giannis Tsapelas, D. Askounis","doi":"10.1109/IISA56318.2022.9904345","DOIUrl":null,"url":null,"abstract":"The beginning of this decade finds artificial intelligence, high performance computing (HPC), and big data analytics in the forefront of digital transformation that is projected to heavily impact various industries and domains. Specifically, the maritime industry, which is already a relatively advanced area concerned to others could stand to gain great benefits from the combination and application of innovative technologies in its practices. This fact, combined with the amount of data generated from naval vessels and sensors points to the direction of AI and big data, two technologies that have the ability to absorb large amounts of data, process them and provide automated and optimised solutions for all maritime stakeholders. Integrating these technologies and tools in a unified system poses various challenges. Under this context, the current publication presents the concept and pilot use cases of VesselAI, an EU-funded project that aims to develop, validate and demonstrate a novel holistic framework based on a combination of the state-of-the-art HPC, Big Data and AI technologies, capable of performing extreme-scale and distributed analytics for fuelling the next-generation digital twins in maritime applications and beyond, including vessel motion and behaviour modelling, analysis and prediction, ship energy system design and optimisation, unmanned vessels, route optimisation and fleet intelligence. The present publication compliments the presentation of the VesselAI project with comprehensive bibliographic research of similar approaches and initiatives that validate the VesselAI concept and prove that there is an unprecedented interest from the research community in applying AI solutions in the maritime industry.","PeriodicalId":217519,"journal":{"name":"2022 13th International Conference on Information, Intelligence, Systems & Applications (IISA)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Optimising Maritime Processes Via Artificial Intelligence: The VesselAI Concept And Use Cases\",\"authors\":\"S. Mouzakitis, C. Kontzinos, Panagiotis Kapsalis, Ioanna Kanellou, Georgios Kormpakis, Giannis Tsapelas, D. Askounis\",\"doi\":\"10.1109/IISA56318.2022.9904345\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The beginning of this decade finds artificial intelligence, high performance computing (HPC), and big data analytics in the forefront of digital transformation that is projected to heavily impact various industries and domains. Specifically, the maritime industry, which is already a relatively advanced area concerned to others could stand to gain great benefits from the combination and application of innovative technologies in its practices. This fact, combined with the amount of data generated from naval vessels and sensors points to the direction of AI and big data, two technologies that have the ability to absorb large amounts of data, process them and provide automated and optimised solutions for all maritime stakeholders. Integrating these technologies and tools in a unified system poses various challenges. Under this context, the current publication presents the concept and pilot use cases of VesselAI, an EU-funded project that aims to develop, validate and demonstrate a novel holistic framework based on a combination of the state-of-the-art HPC, Big Data and AI technologies, capable of performing extreme-scale and distributed analytics for fuelling the next-generation digital twins in maritime applications and beyond, including vessel motion and behaviour modelling, analysis and prediction, ship energy system design and optimisation, unmanned vessels, route optimisation and fleet intelligence. The present publication compliments the presentation of the VesselAI project with comprehensive bibliographic research of similar approaches and initiatives that validate the VesselAI concept and prove that there is an unprecedented interest from the research community in applying AI solutions in the maritime industry.\",\"PeriodicalId\":217519,\"journal\":{\"name\":\"2022 13th International Conference on Information, Intelligence, Systems & Applications (IISA)\",\"volume\":\"38 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-07-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 13th International Conference on Information, Intelligence, Systems & Applications (IISA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IISA56318.2022.9904345\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 13th International Conference on Information, Intelligence, Systems & Applications (IISA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IISA56318.2022.9904345","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimising Maritime Processes Via Artificial Intelligence: The VesselAI Concept And Use Cases
The beginning of this decade finds artificial intelligence, high performance computing (HPC), and big data analytics in the forefront of digital transformation that is projected to heavily impact various industries and domains. Specifically, the maritime industry, which is already a relatively advanced area concerned to others could stand to gain great benefits from the combination and application of innovative technologies in its practices. This fact, combined with the amount of data generated from naval vessels and sensors points to the direction of AI and big data, two technologies that have the ability to absorb large amounts of data, process them and provide automated and optimised solutions for all maritime stakeholders. Integrating these technologies and tools in a unified system poses various challenges. Under this context, the current publication presents the concept and pilot use cases of VesselAI, an EU-funded project that aims to develop, validate and demonstrate a novel holistic framework based on a combination of the state-of-the-art HPC, Big Data and AI technologies, capable of performing extreme-scale and distributed analytics for fuelling the next-generation digital twins in maritime applications and beyond, including vessel motion and behaviour modelling, analysis and prediction, ship energy system design and optimisation, unmanned vessels, route optimisation and fleet intelligence. The present publication compliments the presentation of the VesselAI project with comprehensive bibliographic research of similar approaches and initiatives that validate the VesselAI concept and prove that there is an unprecedented interest from the research community in applying AI solutions in the maritime industry.