Pregled bibliografske jedinice broj: 1003925
AIS data usage for vessel movement analysis
AIS data usage for vessel movement analysis // My First Conference 2018 - Book of Abstracts / Jardas, Mladen ; Glujić, Darko ; Vukelić, Goran ; Čanađija, Marko ; Travaš, Vanja (ur.).
Rijeka: Pomorski fakultet Sveučilišta u Rijeci ; Tehnički fakultet Sveučilišta u Rijeci ; Građevinski fakultet Sveučilišta u Rijeci, 2018. str. 29-29 (predavanje, domaća recenzija, sažetak, znanstveni)
CROSBI ID: 1003925 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
AIS data usage for vessel movement analysis
Autori
Šakan, Davor ; Rudan, Igor ; Žuškin, Srđan ; Brčić, David
Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, znanstveni
Izvornik
My First Conference 2018 - Book of Abstracts
/ Jardas, Mladen ; Glujić, Darko ; Vukelić, Goran ; Čanađija, Marko ; Travaš, Vanja - Rijeka : Pomorski fakultet Sveučilišta u Rijeci ; Tehnički fakultet Sveučilišta u Rijeci ; Građevinski fakultet Sveučilišta u Rijeci, 2018, 29-29
ISBN
978-953-165-128-8
Skup
2nd edition of annual conference for doctoral students of engineering and technology „MY FIRST CONFERENCE“
Mjesto i datum
Rijeka, Hrvatska, 27.09.2018
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Domaća recenzija
Ključne riječi
Automatic Identification System, AIS, vessel movement, route extraction
Sažetak
Automatic Identification System (AIS) is an automatic data exchange system, mandatory under requirements of International Convention for the Safety of Life at Sea (SOLAS). Since implementation in early 2000s it has significantly improved safe and efficient navigation of ships, environmental protection, traffic and coastal monitoring. It is also used by non-mandatory vessels, coastal stations or as an element of other systems or devices. AIS data, which includes vessel’s static, dynamic and voyage information, has been used in various areas of economic, environmental and transportation research such as vessel exhaust emission estimations, maritime traffic density and trade pattern analysis, vessel route extraction and movement anomalies detection. The ever-increasing availability of data has improved possibilities for extensive research, analysis and prediction, but not without challenges regarding management and interpretation of such big data volumes. Methods of data collection, processing and analysis are presented for vessel movement and route extraction.
Izvorni jezik
Engleski
Znanstvena područja
Tehnologija prometa i transport
POVEZANOST RADA
Ustanove:
Pomorski fakultet, Rijeka