Viability and Performance Analysis, at a Physical Level, of a Maritime Communication Network on Medium Frequency

This paper analysed the potentialities that have not yet been exploited of the Automatic Vessel Identification System on Medium Frequency (AVISOMEF) that was previously presented to the scientific community. This system expanded the spectrum of possibilities of the Global Maritime Distress and Safety System (GMDSS). By the time AVISOMEF was presented, one of the unexpected benefits was that it could constitute a platform capable of supporting a Maritime Communication Network on Medium Frequency; all remotely located vessels could communicate with each other by using AVISOMEF, making use of the new established network, within the geographic area of implementation, without needing to use satellite techniques. Medium frequency propagation is stable and is not subject to coverage restrictions. To conduct this experiment, we collaborated with the Spanish Maritime Safety Agency (SASEMAR). It was thanks to them that we gathered real-time information about the nationwide maritime traffic that navigated through the Spanish Search and Rescue jurisdiction waters from 2018 to 2020.

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The Management of Marine Traffic, A Survey of Current and Possible Future Measures

Journal of Navigation ◽

10.1017/s0373463300012480 ◽

1995 ◽

Vol 48 (1) ◽

pp. 53-69 ◽

Cited By ~ 2

Author(s):

Thomas Degré

Keyword(s):

Traffic Management ◽

Considerable Increase ◽

Traffic Monitoring ◽

Maritime Transport ◽

General Description ◽

Knowledge Based ◽

Maritime Traffic ◽

Marine Traffic ◽

Real Time Information ◽

Time Information

The risks involved in maritime transport are very much greater now than was formerly the case. This has been accompanied by a considerable increase in the damage resulting from certain accidents. Maritime traffic management has been made necessary not only for reasons of safety but also productivity and comprises two main types of measure: first, laying down and enforcing suitable regulations and secondly, providing navigators with real time information which is not available to them on board from the Vessel Traffic Services (VTS).Section 2 of this paper is a general description of the techniques used in maritime traffic management and an account of possibilities for the future. Section 3 describes a feasibility study for a traffic monitoring aid system based on VTS and using a knowledge based system.This paper is based on one which was first published in the journal, Recherche Transports Sécurité, issue no. 9, 1993.

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Real-Time Neutrosophic Graphs for Communication Networks

Neutrosophic Sets in Decision Analysis and Operations Research - Advances in Logistics, Operations, and Management Science ◽

10.4018/978-1-7998-2555-5.ch015 ◽

2020 ◽

pp. 364-390

Author(s):

Siddhartha Sankar Biswas

Keyword(s):

Communication Network ◽

Real Time ◽

Communication Networks ◽

Complete Graph ◽

Communication Systems ◽

Time Instant ◽

Shortest Path Problem ◽

Real Point ◽

Real Time Information ◽

Time Information

In this century the communication networks are expanding very fast in huge volumes in terms of their nodes and the connecting links. But for a given alive communication network, its complete core topology may not be always available to the concerned communication systems at a given real point of time. Thus, at any real-time instant the complete graph may not be available, but a subgraph of it to the system for executing its communication or transportation activities may be. In this chapter, the author introduces ‘real-time neutrosophic graphs' (RTN-graphs) in which all real-time information (being updated every q quantum of time) are incorporated so that the communication/transportation system can serve very efficiently with optimal results. Although the style and philosophy of Dijkstra's algorithm is followed, the approach is completely new in the sense that the neutrosophic shortest path problem (NSPP) is solved with the real-time information of the network where most of the data are neutrosophic numbers.

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Discovering Knowledge from AIS Database for Application in VTS

Journal of Navigation ◽

10.1017/s0373463310000135 ◽

2010 ◽

Vol 63 (3) ◽

pp. 449-469 ◽

Cited By ~ 21

Author(s):

Ming-Cheng Tsou

Keyword(s):

Data Mining ◽

Theoretical Research ◽

Automatic Identification ◽

Identification System ◽

Observation Data ◽

Data Mining Technique ◽

Marine Traffic ◽

Customer Relation Management ◽

Real Time Information ◽

Time Information

The widespread use of the Automatic Identification System (AIS) has had a significant impact on maritime technology. AIS enables the Vessel Traffic Service (VTS) not only to offer commonly known functions such as identification, tracking and monitoring of vessels, but also to provide rich real-time information that is useful for marine traffic investigation, statistical analysis and theoretical research. However, due to the rapid accumulation of AIS observation data, the VTS platform is often unable quickly and effectively to absorb and analyze it. Traditional observation and analysis methods are becoming less suitable for the modern AIS generation of VTS. In view of this, we applied the same data mining technique used for business intelligence discovery (in Customer Relation Management (CRM) business marketing) to the analysis of AIS observation data. This recasts the marine traffic problem as a business-marketing problem and integrates technologies such as Geographic Information Systems (GIS), database management systems, data warehousing and data mining to facilitate the discovery of hidden and valuable information in a huge amount of observation data. Consequently, this provides the marine traffic managers with a useful strategic planning resource.

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Verification of Personal Location Data Consistency for COVID-19 Dissemination Prevention Cancellation

10.21203/rs.3.rs-817132/v1 ◽

2021 ◽

Author(s):

Seong-Kyu Kim ◽

Dongsan Jun ◽

Jun-Ho Huh ◽

Byung-Gyu Kim

Keyword(s):

Neural Network ◽

Industrial Revolution ◽

Smart Cities ◽

Data Consistency ◽

Model Design ◽

Research Model ◽

Location Data ◽

And Performance ◽

Real Time Information ◽

Time Information

Abstract Recently, several disasters have occurred. In particular, COVID-19 has had the strongest impact of many disasters in recent years. However, the world is also overcoming COVID-19 in line with the era of the Fourth Industrial Revolution. In preparation for these COVID-19 events, this paper aims to use the Moving Query Object to increase CPU performance for these tracking systems by tracking smartphones worldwide, using LBS systems, such as Wifi, 5G, GPS, etc. So we have created an artificial intelligence-based COVID-19 Location-Based Research Model and have presented the Artificial Neural Network Positioning Research Model Design. Based on the model presented, the Architectural Neural Network Positioning COVID-19 Location Forecast Architecture was also designed. We also want to see real-time information from people infected with COVID-19 for smart cities. Finally, these tracing systems were simulated and tested 10 times and 1,000 times for comparative analysis. Therefore, active tracking and performance are studied when COVID-19 viruses and other disasters occur in smart cities in the future.

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