Search
Abstract
Due to safety reasons, the movement of ships on the sea, especially near the coast should be tracked, recorded and stored. However, the amount of vessels which trajectories should be tracked by authorized institutions, often in real time, is usually huge. What is more, many sources of vessels position data (radars, AIS) produces thousands of records describing route of each tracked object, but lots of that records are correlated due to limited dynamic of motion of ships which cannot change their speed and direction very quickly. In this situation it must be considered how many points of recorded trajectories really have to be remembered to recall the path of particular object. In this paper, authors propose three different methods for ship movement prediction, which explicitly decrease the amount of stored data. They also propose procedures which enable to reduce the number of transmitted data from observatory points to database, what may significantly reduce required bandwidth of radio communication in case of mobile observatory points, for example onboard radars.
Citations
-
7
CrossRef
-
0
Web of Science
-
0
Scopus
Authors (2)
Cite as
Full text
- Publication version
- Accepted or Published Version
- DOI:
- Digital Object Identifier (open in new tab) 10.12716/1001.09.01.09
- License
-
open in new tab
Keywords
Details
- Category:
- Articles
- Type:
- artykuły w czasopismach recenzowanych i innych wydawnictwach ciągłych
- Published in:
-
TransNav - The International Journal on Marine Navigation and Safety of Sea Transportation
no. 9,
pages 77 - 83,
ISSN: 2083-6473 - Language:
- English
- Publication year:
- 2015
- Bibliographic description:
- Czapiewska A., Sadowski J.: Algorithms for Ship Movement Prediction for Location Data Compression// TransNav - The International Journal on Marine Navigation and Safety of Sea Transportation. -Vol. 9., nr. 1 (2015), s.77-83
- DOI:
- Digital Object Identifier (open in new tab) 10.12716/1001.09.01.09
- Verified by:
- Gdańsk University of Technology
seen 110 times
Recommended for you
Know your safety indicator – A determination of merchant vessels Bow Crossing Range based on big data analytics
- M. Gil,
- P. Kozioł,
- K. Wróbel
- + 1 authors