scholarly journals Single-Vessel Plume Dispersion Simulation: Method and a Case Study Using CALPUFF in the Yantian Port Area, Shenzhen (China)

2020 ◽  
Vol 17 (21) ◽  
pp. 7831
Author(s):  
Shubin Bai ◽  
Yuanqiao Wen ◽  
Li He ◽  
Yiming Liu ◽  
Yan Zhang ◽  
...  
Keyword(s):  
Simulation Method ◽  
Atmospheric Environment ◽  
Automatic Identification ◽  
Identification System ◽  
Plume Dispersion ◽  
Single Vessel ◽  
Port Area ◽  
Site Monitoring ◽  
The Impact

To study the impact of vessel pollution on the atmospheric environment of the surrounding area, we present a numerical simulation method based on regional emissions inventories. The general spatial resolution is ≥1 km and the temporal resolution is ≥1 h; parameters which are suitable for the study of larger space–time scales. In this paper, the WRF/CALMET/CALPUFF model and Automatic Identification System (AIS) data are employed to develop a single-vessel atmospheric pollution diffusion model. The goal of this research uses existing meteorological models and diffusion models to provide a simulation technology method for studying the diffusion of SO2 from a single ship. We take the outgoing phase of ocean-going container vessels in Yantian Port as an example. It can be used to set the position of sensitive receptors near the port area. Simulations are implemented with CALPUFF and the results are compared with data derived from on-site monitoring instrument. The CALPUFF modelling domain covers an area of 925 km2 with a grid spacing of 500 m. The simulation results demonstrated agreement with the measured data. The ground concentration contribution value ranged from 10 to 102 μg/m3, while the affected area was about 4–26 km2 and the high-value area of the ground concentration contribution was distributed within 1–2 km from the ship track. Emissions generated by the vessels represent a considerable contribution to SO2 pollution around the harbor areas.

scholarly journals AIS Data Vulnerability Indicated by a Spoofing Case-Study

2021 ◽  
Vol 11 (11) ◽  
pp. 5015
Author(s):  
Andrej Androjna ◽  
Marko Perkovič ◽  
Ivica Pavic ◽  
Jakša Mišković
Keyword(s):  
Situational Awareness ◽  
Automatic Identification ◽  
Identification System ◽  
Maritime Industry ◽  
Position Information ◽  
Safe Navigation ◽  
The Face ◽  
The Impact ◽  
Source Of Information

This paper takes a close look at the landscape of the Automatic Identification System (AIS) as a major source of information for maritime situational awareness (MSA) and identifies its vulnerabilities and challenges for safe navigation and shipping. As an important subset of cyber threats affecting many maritime systems, the AIS is subject to problems of tampering and reliability; indeed, the messages received may be inadvertently false, jammed, or intentionally spoofed. A systematic literature review was conducted for this article, complemented by a case study of a specific spoofing event near Elba in December 2019, which confirmed that the typical maritime AIS could be easily spoofed and generate erroneous position information. This intentional spoofing has affected navigation in international waters and passage through territorial waters. The maritime industry is neither immune to cyberattacks nor fully prepared for the risks associated with the use of modern digital systems. Maintaining seaworthiness in the face of the impact of digital technologies requires a robust cybersecurity framework.

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 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.

Research on Ship Classification Based on Trajectory Features

2017 ◽  
Vol 71 (1) ◽  
pp. 100-116 ◽  
Author(s):  
Kai Sheng ◽  
Zhong Liu ◽  
Dechao Zhou ◽  
Ailin He ◽  
Chengxu Feng
Keyword(s):  
Pattern Mining ◽  
Extraction Methods ◽  
Behaviour Pattern ◽  
Automatic Identification ◽  
Identification System ◽  
Trajectory Data ◽  
Trajectory Features ◽  
Ship Classification ◽  
Historical Trajectory

It is important for maritime authorities to effectively classify and identify unknown types of ships in historical trajectory data. This paper uses a logistic regression model to construct a ship classifier by utilising the features extracted from ship trajectories. First of all, three basic movement patterns are proposed according to ship sailing characteristics, with related sub-trajectory partitioning algorithms. Subsequently, three categories of trajectory features with their extraction methods are presented. Finally, a case study on building a model for classifying fishing boats and cargo ships based on real Automatic Identification System (AIS) data is given. Experimental results indicate that the proposed classification method can meet the needs of recognising uncertain types of targets in historical trajectory data, laying a foundation for further research on camouflaged ship identification, behaviour pattern mining, outlier behaviour detection and other applications.

Performance Bounds for VDES R-mode

2019 ◽  
Vol 73 (1) ◽  
pp. 92-114 ◽  
Author(s):  
Jan Šafář ◽  
Alan Grant ◽  
Paul Williams ◽  
Nick Ward
Keyword(s):  
Data Exchange ◽  
Estimation Error ◽  
Additive White Gaussian Noise ◽  
Automatic Identification ◽  
Identification System ◽  
Performance Bounds ◽  
Radio Communication ◽  
Very High Frequency ◽  
Radio Communication System ◽  
The Impact

The Very High Frequency (VHF) Data Exchange System (VDES) is a new radio communication system being developed by the international maritime community, with the principal objectives to safeguard existing Automatic Identification System (AIS) core functions and enhance maritime communication applications, based on robust, efficient and secure data transmission with wider bandwidth than the AIS. VDES is also being considered as a potential component of the R-mode concept, where the same signals used for communication are also used for ranging, thus mitigating the impact of disruptions to satellite positioning services. This paper establishes statistical performance bounds on the ranging precision of VDES R-mode, assuming an additive white Gaussian noise propagation channel. Modified Cramér-Rao bounds on the pseudorange estimation error are provided for all waveforms currently proposed for use in terrestrial VDES communications. These are then used to estimate the maximum usable ranges for AIS/VDES R-mode stations. The results show that, under the assumed channel conditions, all of the new VDES waveforms provide better ranging performance than the AIS waveform, with the best performance being achieved using the 100 kHz bandwidth terrestrial VDE waveforms.

Inference of Single Vessel Behaviour with Incomplete Satellite-based AIS Data

2013 ◽  
Vol 66 (6) ◽  
pp. 813-823 ◽  
Author(s):  
Changqing Liu ◽  
Xiaoqian Chen
Keyword(s):  
Automatic Identification ◽  
Identification System ◽  
Time Stamp ◽  
Dynamic Information ◽  
Automatic Identification System ◽  
Single Vessel ◽  
Complete Process

The problem of analysing a single vessel's behaviour from real but incomplete Automatic Identification System (AIS) data received by satellite has been investigated. The main objective was to infer the route of any single vessel of interest, utilising the dynamic information decoded from AIS messages. A complete process of route inference using position, speed, course over ground and time stamp information is proposed in this paper. Due to the incompleteness of satellite AIS messages, an algorithm incorporating random deviations is also presented to account for the missing sections of obtained vessel routes. Analysis results from a set of real AIS data have demonstrated the applicability of the proposed algorithms in various scenarios.

scholarly journals Automatic Identification of Environment Haptic Properties

1999 ◽  
Vol 8 (4) ◽  
pp. 394-411 ◽  
Author(s):  
Pierre E. Dupont ◽  
Capt. Timothy M. Schulteis ◽  
Paul A. Millman ◽  
Robert D. Howe
Keyword(s):  
Haptic Feedback ◽  
Sensory Information ◽  
Automatic Identification ◽  
Identification System ◽  
General Description ◽  
Research Issues ◽  
Property Identification ◽  
Remote Environment ◽  
Force Data

Many applications can be imagined for a system that processes sensory information collected during telemanipulation tasks in order to automatically identify properties of the remote environment. These applications include generating model-based simulations for training operators in critical procedures and improving real-time performance in unstructured environments or when time delays are large. This paper explores the research issues involved in developing such an identification system, focusing on properties that can be identified from remote manipulator motion and force data. As a case study, a simple block-stacking task, performed with a teleoperated two-fingered planar hand, is considered. An algorithm is presented that automatically segments the data collected during the task, given only a general description of the temporal sequence of task events. Using the segmented data, the algorithm then successfully estimates the weight, width, height, and coefficient of friction of the two blocks handled during the task. This data is used to calibrate a virtual model incorporating visual and haptic feedback. This case study highlights the broader research issues that must be addressed in automatic property identification.

Analysis of Tugboat Activities using AIS Data for the Tianjin Port

2020 ◽  
Vol 2674 (5) ◽  
pp. 498-509
Author(s):  
Shukai Chen ◽  
Feng Wang ◽  
Xiaoyang Wei ◽  
Zhijia Tan ◽  
Hua Wang
Keyword(s):  
Spatial Distribution ◽  
Spatial Analysis ◽  
Service Time ◽  
Automatic Identification ◽  
Identification System ◽  
Crucial Importance ◽  
Two Stage ◽  
Temporal And Spatial ◽  
Shed Light

The tugboat is the vessel that helps to maneuver large ships for berthing and un-berthing operations. To achieve efficient tugboat operations, investigating the features of tugboat activities is of crucial importance. This study aims to use automatic identification system (AIS) data to identify the maneuver services and analyze the characteristics of tugboat activities. A two-stage algorithm is developed to extract the time, locations, and involved tugboats for berthing and un-berthing operations from AIS data. The AIS data from Tianjin port, China, are used in the case study to demonstrate the effectiveness of the proposed method and analyze the pattern of tugboat activities. First, some important features of tugboat jobs are presented, such as the daily number of jobs and the spatial distribution of jobs. Then, a temporal and spatial analysis is conducted to investigate tugboat assignment, service time, tugboat utilization, and locations of berthing and un-berthing operations. The obtained results and implications could shed light on the deployment of tugboat berths, tugboat scheduling, and evaluation of tugboat fleet operation.

scholarly journals Fast computation of the iteration-based simulation method - case study of non-coherent ask with shadowing

2017 ◽  
Vol 14 (3) ◽  
pp. 415-431 ◽  
Author(s):  
Vladimir Mladenovic ◽  
Sergey Makov ◽  
Yigang Cen ◽  
Miroslav Lutovac
Keyword(s):  
Numerical Methods ◽  
Probability Density ◽  
Communication Systems ◽  
Data Transfer ◽  
Joint Probability ◽  
Simulation Method ◽  
Wireless Communication Systems ◽  
Closed Form Solutions ◽  
The Impact

This article presents a new method of fast symbolic computations of very complex calculations, which are necessary for the analysis, simulation, and design of wireless communication systems using CAS (Computer Algebra System). CAS is applied to formulate hypotheses and define joint probability density functions of certain modulation technique. This is used to prepare for the semi-symbolic calculation to complete specify wireless system by using CAS. We have developed an iteration-based simulation method that aids to solve semisymbolic expressions and gives closed form solutions (with some parameters specified as numbers and some as symbols). So far, they are solved by numerical methods. Students can perform performance analysis and understand the processes in the data transfer. Engineers and researchers may have a better insight into the impact of the important parameters necessary to properly transmit and detect information unlike traditional numerical methods. The main contribution is to obtain solutions for the probability density function, and outage probability where no solution can be obtained using numerical methods. A strong emphasis is placed on very fast calculations that significantly save the time of analysis, simulation, and design.

Sign in / Sign up

Export Citation Format

Share Document