Marine Navigation Collision Preventing System

2014 ◽  
Vol 69 (7) ◽  
Author(s):  
Amirrudin Yaacob ◽  
M. Rashidi ◽  
Jaswar Koto
Keyword(s):  
Search And Rescue ◽  
Maritime Security ◽  
Automatic Identification ◽  
Identification System ◽  
World Community ◽  
Stopping Distance ◽  
Safety Distance ◽  
Entire World ◽  
Security Regulations ◽  
Marine Navigation

Navigation safety has become one of the important issues to the entire world community. Automatic Identification System (AIS) firstly has been used to comply with safety and security regulations, functioning as collision avoidance, vessel traffic services, maritime security, aids to navigation, search and rescue and accident investigation. This paper presents marine navigation collision preventing system between ships and ships using AIS. In the system, the raw data from AIS is crossed with database based MMSI number to find detail information then, location of each ship was plotted on to Google Map. The safety distance is assessed based actual and stopping distance. The system was tested in the Batam and Singapore Channel.   

Prediction of CO2 Emitted by Marine Transport in Batam-Singapore Channel using AIS

2014 ◽  
Vol 69 (7) ◽  
Author(s):  
M. Rashidi ◽  
Jaswar Koto
Keyword(s):  
Air Pollution ◽  
Co2 Emission ◽  
Environmental Damage ◽  
Automatic Identification ◽  
Identification System ◽  
World Community ◽  
Marine Transport ◽  
Entire World ◽  
Straits Of Malacca ◽  
Strait Of Malacca

Global warming and air pollution have become one of the important issues to the entire world community. Exhaust emissions from ships has been contributing to the health problems and environmental damage. This study focuses on the Strait of Malacca area because it is one of the world’s most congested straits used for international shipping where located on the border among three countries of Indonesia, Malaysia and Singapore. This study will predict CO2 emission from the marine transport. This is accomplished by developed a ship database in the Straits of Malacca by using the data which obtained from Automatic Identification System (AIS). From the database, MEET methodology is used to estimate the CO2 emission from ships.

Automatic Identification System (AIS): Data Reliability and Human Error Implications

2007 ◽  
Vol 60 (3) ◽  
pp. 373-389 ◽  
Author(s):  
Abbas Harati-Mokhtari ◽  
Alan Wall ◽  
Philip Brooks ◽  
Jin Wang
Keyword(s):  
Human Error ◽  
Human Factor ◽  
Automatic Identification ◽  
Identification System ◽  
Efficient Performance ◽  
Swiss Cheese Model ◽  
Potential Impact ◽  
Marine Navigation ◽  
Cheese Model ◽  
Different Levels

This paper examines the recent introduction of the AIS to the ship's bridge and its potential impact on the safety of marine navigation. Research has shown that 80 to 85% of all recorded maritime accidents are directly due to human error or associated with human error. Safety is an important element of marine navigation and many people at different levels are involved in its management. The safe and efficient performance of joint systems, is heavily dependent upon how functions are allocated between the human and the machine. This paper investigates different regulations, supervision for proper use, training, and management of AIS users. It uses previous research and three separate AIS studies to identify problems. The potential of the AIS to cause problems is analysed. The classic human factor “Swiss Cheese” Model of system failure has been modified for the AIS to investigate a possible accident trajectory. The paper then concludes with recommendations and suggestions for improvements and further work.

The ‘ALVA CAPE’ and the Automatic Identification System: The Use of VHF in Collision Avoidance at Sea

2002 ◽  
Vol 55 (3) ◽  
pp. 431-442 ◽  
Author(s):  
S. J. Harding
Keyword(s):  
Case Studies ◽  
Collision Avoidance ◽  
Samuel Johnson ◽  
Automatic Identification ◽  
Identification System ◽  
Controversial Issues ◽  
Automatic Identification System ◽  
Radio Technology ◽  
Marine Navigation

One of the most controversial issues relating to marine navigation is the efficacy of ships' crews using VHF radio technology for bridge-to-bridge communications to agree manoeuvres. Through a re-evaluation of historic case studies, this paper provides background on the development of applying VHF technology in collision avoidance and the legislation, national and international, underpinning the practice; a practice that has found little or no support from the legal establishment. Finally the consequential development of a policy to require specific VHF technology to be installed on ships to facilitate agreements in relation to collision avoidance manoeuvres will be reviewed, that is the Automatic Identification System (AIS).Integrity without knowledge is weak and useless, and knowledge without integrity is dangerous and dreadful. Samuel Johnson

scholarly journals A Framework for the Detection of Search and Rescue Patterns Using Shapelet Classification

2019 ◽  
Vol 11 (9) ◽  
pp. 192 ◽  
Author(s):  
Konstantinos Kapadais ◽  
Iraklis Varlamis ◽  
Christos Sardianos ◽  
Konstantinos Tserpes
Keyword(s):  
Automatic Detection ◽  
Feature Space ◽  
Real Data ◽  
Search And Rescue ◽  
Training Data ◽  
Automatic Identification ◽  
Identification System ◽  
Trajectory Data ◽  
Complex Events ◽  
Compression Data

The problem of unmanned supervision of maritime areas has attracted the interest of researchers for the last few years, mainly thanks to the advances in vessel monitoring that the Automatic Identification System (AIS) has brought. Several frameworks and algorithms have been proposed for the management of vessel trajectory data, which focus on data compression, data clustering, classification and visualization, offering a wide variety of solutions from vessel monitoring to automatic detection of complex events. This work builds on our previous work in the topic of automatic detection of Search and Rescue (SAR) missions, by developing and evaluating a methodology for classifying the trajectories of vessels that possibly participate in such missions. The proposed solution takes advantage of a synthetic trajectory generator and a classifier that combines a genetic algorithm (GENDIS) for the extraction of informative shapelets from training data and a transformation to the shapelets’ feature space. Using the generator and several SAR patterns that are formally described in naval operations bibliography, it generates a synthetic dataset that is used to train the classifier. Evaluation on both synthetic and real data has very promising results and helped us to identify vessel SAR maneuvers without putting any effort into manual annotation.

Performance Evaluation of Maritime Search and Rescue Missions Using Automatic Identification System Data

2020 ◽  
Vol 73 (6) ◽  
pp. 1237-1246
Author(s):  
Fan Zhou ◽  
Hua Chen ◽  
Peng Zhang
Keyword(s):  
Large Scale ◽  
Search And Rescue ◽  
Automatic Identification ◽  
Identification System ◽  
Task Execution ◽  
Automatic Identification System ◽  
System Data ◽  
Overall Efficiency ◽  
Maritime Search And Rescue ◽  
The Relationship

In maritime search and rescue (SAR), commanders need to understand the task execution efficiency of each SAR unit in real time to improve the overall efficiency of SAR efforts. This study proposes a method to evaluate the progress of maritime SAR missions using automatic identification system (AIS) data. First, the positioning accuracy of the AIS data was improved according to the relationship between position, speed, and course. Second, the historical track of the SAR ship was used to generate the SAR completion area based on a line buffer algorithm. The SAR completion area and SAR mission area were then superimposed to determine the overall progress of the SAR mission. The proposed method has been deployed within the SAR software on-board Haixun01 (China's largest and most advanced large-scale cruise rescue ship) since 2017 and has played an important role in devising SAR strategies and tracking mission progress, during several SAR actions.

Automatic Identification System Receiver for Small Fishing Vessels

2020 ◽  
Author(s):  
Febus Reidj G. Cruz ◽  
Jeremiah A. Ordiales ◽  
Malvin Angelo C. Reyes ◽  
Pinky T. Salvanera
Keyword(s):  
Automatic Identification ◽  
Identification System ◽  
Automatic Identification System ◽  
Fishing Vessels
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