i4sea: a big data platform for sea area monitoring and analysis of fishing vessels activity
The i4sea research project provides effective and efficient big data integration, processing, and analysis technologies to deliver both real-time and historical operational snapshots of fishing vessels activity in national sea areas. This paper presents the architecture of the i4sea big data platfor...
Main Authors: | , , , , , , , , |
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Format: | Article |
Language: | English |
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Taylor & Francis Group
2021-10-01
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Series: | Geo-spatial Information Science |
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Online Access: | http://dx.doi.org/10.1080/10095020.2021.1971055 |
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author | Panagiotis Tampakis Eva Chondrodima Andreas Tritsarolis Aggelos Pikrakis Yannis Theodoridis Kostis Pristouris Harry Nakos Panagiotis Kalampokis Theodore Dalamagas |
author_facet | Panagiotis Tampakis Eva Chondrodima Andreas Tritsarolis Aggelos Pikrakis Yannis Theodoridis Kostis Pristouris Harry Nakos Panagiotis Kalampokis Theodore Dalamagas |
author_sort | Panagiotis Tampakis |
collection | DOAJ |
description | The i4sea research project provides effective and efficient big data integration, processing, and analysis technologies to deliver both real-time and historical operational snapshots of fishing vessels activity in national sea areas. This paper presents the architecture of the i4sea big data platform for sea area monitoring and analysis of fishing vessels activity and demonstrates the operation of some use-case pilot scenarios. |
first_indexed | 2024-12-18T23:02:45Z |
format | Article |
id | doaj.art-3f2cb1cfb384407795ae9f136ab0fc32 |
institution | Directory Open Access Journal |
issn | 1009-5020 1993-5153 |
language | English |
last_indexed | 2024-12-18T23:02:45Z |
publishDate | 2021-10-01 |
publisher | Taylor & Francis Group |
record_format | Article |
series | Geo-spatial Information Science |
spelling | doaj.art-3f2cb1cfb384407795ae9f136ab0fc322022-12-21T20:48:31ZengTaylor & Francis GroupGeo-spatial Information Science1009-50201993-51532021-10-010012310.1080/10095020.2021.19710551971055i4sea: a big data platform for sea area monitoring and analysis of fishing vessels activityPanagiotis Tampakis0Eva Chondrodima1Andreas Tritsarolis2Aggelos Pikrakis3Yannis Theodoridis4Kostis Pristouris5Harry Nakos6Panagiotis Kalampokis7Theodore Dalamagas8University of PiraeusUniversity of PiraeusUniversity of PiraeusUniversity of PiraeusUniversity of PiraeusInformation Management Systems InstituteInformation Management Systems InstituteInformation Management Systems InstituteInformation Management Systems InstituteThe i4sea research project provides effective and efficient big data integration, processing, and analysis technologies to deliver both real-time and historical operational snapshots of fishing vessels activity in national sea areas. This paper presents the architecture of the i4sea big data platform for sea area monitoring and analysis of fishing vessels activity and demonstrates the operation of some use-case pilot scenarios.http://dx.doi.org/10.1080/10095020.2021.1971055big datafishingvessel activitymachine learning |
spellingShingle | Panagiotis Tampakis Eva Chondrodima Andreas Tritsarolis Aggelos Pikrakis Yannis Theodoridis Kostis Pristouris Harry Nakos Panagiotis Kalampokis Theodore Dalamagas i4sea: a big data platform for sea area monitoring and analysis of fishing vessels activity Geo-spatial Information Science big data fishing vessel activity machine learning |
title | i4sea: a big data platform for sea area monitoring and analysis of fishing vessels activity |
title_full | i4sea: a big data platform for sea area monitoring and analysis of fishing vessels activity |
title_fullStr | i4sea: a big data platform for sea area monitoring and analysis of fishing vessels activity |
title_full_unstemmed | i4sea: a big data platform for sea area monitoring and analysis of fishing vessels activity |
title_short | i4sea: a big data platform for sea area monitoring and analysis of fishing vessels activity |
title_sort | i4sea a big data platform for sea area monitoring and analysis of fishing vessels activity |
topic | big data fishing vessel activity machine learning |
url | http://dx.doi.org/10.1080/10095020.2021.1971055 |
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