scholarly journals Application Research of Tethered UAV Platform in Marine Emergency Communication Network

2021 ◽  
Author(s):  
Zhiqiang Xu
Keyword(s):  
Communication Network ◽  
Base Station ◽  
Fourth Generation ◽  
Automatic Identification ◽  
Identification System ◽  
Prototype System ◽  
Emergency Communication ◽  
Communication Support ◽  
Long Time ◽  
4G Lte

In order to meet the needs of emergency communication for major emergency disaster rescue, a wireless emergency communication relay system based on tethered UAV platform is studied. From the perspective of practical application, the characteristics and network coverage of the emergency communication system are analyzed. The mooring UAV platform is equipped with various communication loads such as MESH(wireless grid network communication), 4G-LTE( Long term evolution fourth generation mobile communication) base station, AIS (Automatic Identification System) and so on, which are kept on the communication support ship. When the communication support ship enters the scene of maritime emergencies, the tethered UAV platform lifts off ,stays for a long time and realizes the relay communication service of various carriers within a radius of tens of kilometers through its various communication payloads, which provides key communication support for the Marine emergency communication network. The actual field test of the prototype system shows that the data transmission is stable and reliable, and the short message transmission is normal, which can meet the emergency communication demand of disaster rescue.

Create your own data and energy integrated communication network: A brief tutorial and a prototype system

2020 ◽  
Vol 17 (9) ◽  
pp. 193-209
Author(s):  
Yali Zheng ◽  
Yitian Zhang ◽  
Yang Wang ◽  
Jie Hu ◽  
Kun Yang
Keyword(s):  
Communication Network ◽  
Prototype System ◽  
Integrated Communication

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

Automatic identification system data-driven model for analysis of ship domain near bridge-waters

2021 ◽  
pp. 1-22
Author(s):  
Lei Jinyu ◽  
Liu Lei ◽  
Chu Xiumin ◽  
He Wei ◽  
Liu Xinglong ◽  
...  
Keyword(s):  
Least Squares Method ◽  
Automatic Identification ◽  
Identification System ◽  
Collision Risk ◽  
Automatic Identification System ◽  
Domain Models ◽  
System Data ◽  
Quantification Model ◽  
Highly Correlated

Abstract The ship safety domain plays a significant role in collision risk assessment. However, few studies take the practical considerations of implementing this method in the vicinity of bridge-waters into account. Therefore, historical automatic identification system data is utilised to construct and analyse ship domains considering ship–ship and ship–bridge collisions. A method for determining the closest boundary is proposed, and the boundary of the ship domain is fitted by the least squares method. The ship domains near bridge-waters are constructed as ellipse models, the characteristics of which are discussed. Novel fuzzy quaternion ship domain models are established respectively for inland ships and bridge piers, which would assist in the construction of a risk quantification model and the calculation of a grid ship collision index. A case study is carried out on the multi-bridge waterway of the Yangtze River in Wuhan, China. The results show that the size of the ship domain is highly correlated with the ship's speed and length, and analysis of collision risk can reflect the real situation near bridge-waters, which is helpful to demonstrate the application of the ship domain in quantifying the collision risk and to characterise the collision risk distribution near bridge-waters.

scholarly journals Semi-Continuous Spatial Statistical Analysis Using AIS Data for Vessel Traffic Flow Characteristics in Fairway

2021 ◽  
Vol 9 (4) ◽  
pp. 378
Author(s):  
Jong Kwan Kim
Keyword(s):  
Statistical Analysis ◽  
Traffic Flow ◽  
Flow Characteristics ◽  
Automatic Identification ◽  
Identification System ◽  
Spatial Statistical Analysis ◽  
Traffic Characteristics ◽  
Traffic Distribution ◽  
Traffic Flow Characteristics ◽  
Marine Accidents

As high vessel traffic in fairways is likely to cause frequent marine accidents, understanding vessel traffic flow characteristics is necessary to prevent marine accidents in fairways. Therefore, this study conducted semi-continuous spatial statistical analysis tests (the normal distribution test, kurtosis test and skewness test) to understand vessel traffic flow characteristics. First, a vessel traffic survey was conducted in a designated area (Busan North Port) for seven days. The data were collected using an automatic identification system and subsequently converted using semi-continuous processing methods. Thereafter, the converted data were used to conduct three methods of spatial statistical analysis. The analysis results revealed the vessel traffic distribution and its characteristics, such as the degree of use and lateral positioning on the fairway based on the size of the vessel. In addition, the generalization of the results of this study along with that of further studies will aid in deriving the traffic characteristics of vessels on the fairway. Moreover, these characteristics will reduce maritime accidents on the fairway, in addition to establishing the foundation for research on autonomous ships.

scholarly journals Improving Near Miss Detection in Maritime Traffic in the Northern Baltic Sea from AIS Data

2021 ◽  
Vol 9 (2) ◽  
pp. 180
Author(s):  
Lei Du ◽  
Osiris A. Valdez Banda ◽  
Floris Goerlandt ◽  
Pentti Kujala ◽  
Weibin Zhang
Keyword(s):  
Baltic Sea ◽  
Perceived Risk ◽  
Maritime Transportation ◽  
Near Miss ◽  
Automatic Identification ◽  
Identification System ◽  
Collision Risk ◽  
Ship Collision ◽  
The Impact ◽  
Ship Behavior

Ship collision is the most common type of accident in the Northern Baltic Sea, posing a risk to the safety of maritime transportation. Near miss detection from automatic identification system (AIS) data provides insight into maritime transportation safety. Collision risk always triggers a ship to maneuver for safe passing. Some frenetic rudder actions occur at the last moment before ship collision. However, the relationship between ship behavior and collision risk is not fully clarified. Therefore, this work proposes a novel method to improve near miss detection by analyzing ship behavior characteristic during the encounter process. The impact from the ship attributes (including ship size, type, and maneuverability), perceived risk of a navigator, traffic complexity, and traffic rule are considered to obtain insights into the ship behavior. The risk severity of the detected near miss is further quantified into four levels. This proposed method is then applied to traffic data from the Northern Baltic Sea. The promising results of near miss detection and the model validity test suggest that this work contributes to the development of preventive measures in maritime management to enhance to navigational safety, such as setting a precautionary area in the hotspot areas. Several advantages and limitations of the presented method for near miss detection are discussed.

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