Data mining analysis on Ships collision risk and marine traffic characteristic of Port Klang Malaysia waterways from automatic identification system (AIS) / Masnawi Mustaffa ... [et al.]

Mustaffa, Masnawi and Ahmad, Shaharudin and Ali, Ab Malik Marwan and Ahmad, Nadim and Mohd Jais, Mohd Hamidi (2019) Data mining analysis on Ships collision risk and marine traffic characteristic of Port Klang Malaysia waterways from automatic identification system (AIS) / Masnawi Mustaffa ... [et al.]. In: Proceedings of the International MultiConference of Engineers and Computer Scientists 2019 IMECS 2019, 13-15 March 2019, Hong Kong.

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Official URL: https://www.researchgate.net/publication/332172043

Abstract

Abstract— Port Klang is one of the busiest ports in the worlds and have played an important role to ensure the import and export activities towards Malaysian economy sector. Port Klang located in a busy marine sea route of Strait of Malacca received a great amount of vessels making it a high density port and more likely exposed to the collision risk. From the analysis of Automatic Identification System (AIS) data, the marine traffic pattern of the study area will be characterized. The raw AIS data collected through AIS receiver that was installed at Universiti Teknologi Mara, Shah Alam, Malaysia. The data was collected from July 2016 until December 2016. A web-based application was developed to decode the raw data collected for analysis and characteristic purpose. The decoded raw data were presented statically and through graphical method. The variable that need to be consider such as number of vessels, type of vessels, course over ground, and speed over ground of the vessels. The path for dangerous category vessels was also plotted.

Item Type: Conference or Workshop Item (Paper)
Creators:
CreatorsEmail
Mustaffa, MasnawiUNSPECIFIED
Ahmad, ShaharudinUNSPECIFIED
Ali, Ab Malik MarwanUNSPECIFIED
Ahmad, NadimUNSPECIFIED
Mohd Jais, Mohd HamidiUNSPECIFIED
Subjects: Q Science > QA Mathematics > Mathematical statistics. Probabilities
Q Science > QA Mathematics > Control theory
Divisions: Others
Event Title: Proceedings of the International MultiConference of Engineers and Computer Scientists 2019 IMECS 2019
Event Dates: 13-15 March 2019
Page Range: pp. 242-246
Official URL: https://www.researchgate.net/publication/332172043
Item ID: 23902
Uncontrolled Keywords: AIS data, big data analysis, Data mining, ship collision, traffics density, ship navigation.
Last Modified: 16 Apr 2019 04:48
Depositing User: Admin Pendigitan 2 PTAR
URI: http://ir.uitm.edu.my/id/eprint/23902

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