Name
Abstract | ||
|---|---|---|
This paper presents recent findings in maritime trajectory pattern and anomaly detection using long-term data collected via a shore-based network of Automatic Identification System (AIS). Since the establishment of the AIS network around Taiwan in 2009, the accumulated massive vessel trajectories have been extensively explored under a series of government research projects. The project themes include safety and efficiency in marine transportation, as well as environment issues. Algorithms and software tools are developed to discover patterns of vessel traffic, routes, and delays, detect various near-miss events, investigate marine casualties, and assist in ship emission inventories. When the massive AIS data are investigated in different aspects and ways, anomalies with security implications emerged. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/CCST.2015.7389720 | 2015 International Carnahan Conference on Security Technology (ICCST) |
Keywords | Field | DocType |
Automatic Identification System,trajectory mining,near miss,anomaly detection | Anomaly detection,Computer science,Computer security,Marine transportation,Shore,Software,Security pattern,Automatic Identification System,Trajectory,Government | Conference |
ISSN | ISBN | Citations |
1071-6572 | 978-1-4799-8690-3 | 0 |
PageRank | References | Authors |
0.34 | 2 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shwu-Jing Chang | 1 | 7 | 2.34 |
| Kuan-Hung Yeh | 2 | 0 | 0.34 |
| Guan-Dun Peng | 3 | 0 | 0.34 |
| Shih-Ming Chang | 4 | 58 | 7.05 |
| Chung-Hao Huang | 5 | 85 | 7.55 |