198 results about "Ship safety" patented technology

The invention provides a ship video concentration and intelligent retrieval method and system based on edge nodes, and belongs to the technical field of edge computing, and the method comprises the steps: S1, collecting ship video data; s2, an edge node generates a concentrated video and metadata through an improved Gaussian mixture model, an improved DeepSORT algorithm and a dynamic concentration proportion adjustment algorithm; s3, synchronously concentrating the index information of the videos and the metadata by each edge node through a publishing-subscribing mode; s4, training a lightweight intelligent retrieval model through a knowledge distillation algorithm; s5, calling the lightweight intelligent retrieval model to match the corresponding concentrated video clip, and returning a retrieval result; and S6, collecting feedback information of the user on the retrieval result, and performing incremental optimization on the lightweight intelligent retrieval model through an elastic weight consolidation algorithm. According to the invention, efficient monitoring management is realized through edge localization processing, cross-node cooperation and closed-loop optimization architecture, and the actual requirements of ship safety monitoring and operation management are met.

The invention discloses a LoRa-based ship environment multi-parameter intelligent wireless monitoring system, which is characterized in that environment state data and ship operation auxiliary data are acquired through a data acquisition module, and a data processing module is used for preprocessing and standardizing the acquired data to obtain a standardized data frame; the environment safety quantification module calculates a single parameter safety score, a comprehensive safety index and a safety situation level SL, the intelligent LoRa communication module dynamically selects a communication strategy according to the SL and the current link quality and generates and sends a safety data packet, the LoRa gateway receives the safety data packet, redundancy filtering is carried out, receiving metadata is added, a final data record is formed and uploaded, and the LoRa gateway sends the final data record to the intelligent LoRa communication module. And the data center performs visual display and data storage on the final data record, and generates a network optimization instruction based on the network performance data, so that the problem that transmission reliability, real-time performance and low power consumption are difficult to consider in ship environment monitoring is solved, and the intelligent level of ship safety management is improved.

The invention discloses a sailing ship safety situation awareness system, and belongs to the technical field of data analysis. The method is used for solving the technical problem that in an existing scheme, multi-dimensional data analysis and timely and reliable early warning cannot be carried out on complex sea conditions, and consequently the coping capacity of the complex sea conditions is weak. Through the whole process of biological anchoring anomaly suppression, data fusion and dynamic feature extraction, the limitation that traditional ship perception depends on a physical sensor can be broken through, high-precision perception of environmental risks and ship states under complex sea conditions is achieved, and compared with a traditional method, the abnormal sea conditions can be recognized in advance, and the method has the advantages of being high in practicability. The robustness of the data and the detection rate of small probability and high influence events can be effectively improved; cross-scale modeling is realized through deep coupling of a microscopic physical mechanism and macroscopic data features; the constructed multi-dimensional risk assessment matrix not only can output a risk value, but also can provide a risk propagation path, and can effectively improve the risk assessment precision of the ship under a complex sea condition.

The invention relates to the technical field of ship navigation risk assessment, in particular to a ship navigation risk assessment system based on multi-source heterogeneous data fusion, which comprises a multi-source data integration module, a spatial-temporal feature mapping module, a dynamic risk detection module, a linkage decision control module and a feedback optimization module. According to the method, standardized operation data is generated through multi-source data cleaning and fusion, a spatial-temporal feature distribution map is generated by using a multi-dimensional dynamic clustering algorithm, a risk index set is extracted in combination with adaptive boundary adjustment and a nonlinear optimization algorithm, and accurate path planning and real-time regulation are realized. In addition, a global sensitivity analysis framework and an early warning module are introduced into the system, and the ship navigation safety and reliability are improved. According to the method, the risk prediction accuracy can be remarkably improved, the navigation accident probability is reduced, the navigation efficiency is optimized, and safe operation of the ship is guaranteed.

The invention discloses an under-actuated unmanned surface vehicle safe formation tracking control method based on robust obstacle control. The method comprises the following steps: establishing a multi-unmanned ship group and performing real-time communication, and enabling each follower to follow a leader according to a formation configuration and to avoid an obstacle; a safe formation tracking control framework of the underactuated unmanned surface vehicle is established, during formation tracking, followers input state information into the control framework, processing is carried out according to a reference trajectory of a leader and real-time information of a current follower and an obstacle, and forward and steering control torque instructions are output to control the current follower. Obstacles are avoided and formation configuration is restored to continue following the leader. According to the method, the underactuation characteristic problem of the unmanned surface vehicle is solved, the worst case error generated when the neural network approaches the unknown dynamic state can be effectively compensated, it is ensured that the unmanned surface vehicle can strictly avoid collision with the obstacle in the complex environment, and meanwhile the formation tracking performance is optimally kept.

The invention discloses a dynamic feature and physical gating fused wave height prediction system and method, belongs to the technical field of artificial intelligence and machine learning, is used for marine environment monitoring, and comprises a data acquisition and preprocessing module, a feature screening module and a model prediction module. The method comprises the steps of obtaining and preprocessing marine meteorological variable data, constructing a Shapley additive interpretation lightweight gradient elevator regression model to screen a core variable set, constructing a physical guidance gating feature perception Transform prediction model, constructing a mixed loss function constraint prediction model, and outputting a sea wave significant wave height prediction value after prediction model training is completed. According to the method, through a feature screening and dynamic weight distribution mechanism, the utilization efficiency and scene adaptability of multi-source marine meteorological features are remarkably improved, the method can be flexibly expanded to sea wave prediction tasks of different sea areas and spatial-temporal scales, and high-precision and high-reliability technical support is provided for ocean engineering, shipping safety and disaster early warning.

A large ship safety supervision system, configured to realize shipmen monitoring and ship safety supervision, wherein shipmen monitoring comprising monitoring of real time positions of shipmen in cabins and shipmen health data, and ship safety supervision comprises oceanic condition warning, on board devices running condition monitoring, ship navigation / construction monitoring and ship remote guidance. Data transmission in between ships and shores is realized by the hybrid self-adaptive compression technology based on model classification and the data transmission link intelligent selection technology based on fuzzy neural network creatively, in the meanwhile, real time safety management and supervision and ship remote work analysis and guidance can be realized.

The invention relates to the technical field of ship safety, and discloses a ship safety management monitoring system based on the Internet and a Beidou satellite, the system comprises a coordinate analysis module, a ship state module, a data fusion module, an abnormity identification module and an early warning message sending module, a satellite positioning signal is analyzed, and real-time latitude and longitude coordinates of a ship are obtained; generating comprehensive operation parameters of the ship according to the attitude, the navigational speed, the load and the main engine operation parameters of the ship; performing data fusion on the longitude and latitude coordinates after timestamp alignment and the comprehensive operation parameters to obtain an operation feature vector of the ship; performing abnormal mode identification on the operation feature vector based on historical navigation data and a preset safety threshold to obtain a risk category of the ship; when a risk category occurs, generating a treatment measure message of the risk category, and sending the treatment measure message to a ship-end display terminal and a shore-based management terminal through communication between the Internet and a Beidou short message; the ship safety management efficiency can be improved.

The embodiment of the invention discloses a ship AI safety monitoring model training data processing method and system. The method comprises the following steps: acquiring ship image data and image metadata in real time through a camera, and performing associated storage; performing service information labeling on the ship image data; performing data cleaning, association integration and structured conversion on the annotation information to generate training data available for the AI model; classifying and storing the data, and establishing an index; and outputting the training data to the ship AI safety monitoring model through the interface for training. The method has the following advantages: (1) the scene adaptability of the AI model is improved; (2) the training data acquisition cost is reduced; (3) seamless connection of business data and training data is realized; and (4) supporting multi-subject data multiplexing and model iteration.

The invention relates to a safety early warning communication method and system among multiple ships. The method comprises the following steps: acquiring real-time dynamic data of a running ship in a current running state; performing quality score determination on the real-time dynamic data; when the quality score is lower than a first threshold value, performing feature reconstruction compensation on the real-time dynamic data corresponding to the quality score; conflict perception attention weighted fusion is carried out on the high-quality modal data, and a risk confidence coefficient and a conflict flag bit corresponding to a ship driving risk event are generated; based on the risk event and the high-quality modal data, generating driving early warning information; and switching a networking router network link required by data transmission based on the risk confidence and the conflict flag bit, and sending driving early warning information to the driving ship by the own ship. The low-quality mode is converted into the high-quality mode, the fusion strategy is carried out through the high-quality mode, the safety early warning information is obtained, and the technical effect of reducing the influence of the low-quality mode on the subsequent decision accuracy is achieved.

The invention relates to the technical field of ship safety, in particular to a ship navigation monitoring management system and method based on edge computing, and the system comprises seven cooperation modules: a data collection module synchronously obtains ship multi-source data, and a processing storage module achieves the data compression, marking and storage. The encryption security module completes full-process AES-256 encryption through a hardware encryption chip, the dual-power supply module guarantees stable power supply, the satellite positioning module obtains accurate positioning through Beidou / GPS dual modes, the self-inspection maintenance module monitors faults in real time, and the AI edge calculation unit achieves channel object recognition, track analysis and violation warning through a deep neural network model. According to the method, closed-loop processes of data acquisition, encryption, processing, intelligent analysis and fault handling are completed through module cooperation; the invention aims to solve the problems of high monitoring delay, insufficient data security, unreliable power supply and the like of the existing system.

The present disclosure relates to a ship safety control method and ship safety control system. According to an embodiment of the present disclosure, the ship safety control method may include determining a sea condition in an area, in which a ship is located, based on a video feature of a first video of a ship situation, preprocessing the first video based on the sea condition, designating a control area in a second video based on the second video generated through the preprocessing, and detecting at least one of an object and occurrence of an event within the control area.

The application discloses a kind of ship's multiple propeller collaborative propulsion control method and system, it is related to ship automation control technical field.For by the control system of ship collaborative control multiple propeller to carry out ship propulsion, collaborative propulsion control method includes: obtaining the speed of ship, main station handle position and power station available power;Based on speed and main station handle position, identify the current navigation condition of ship;Based on the matching relationship of pre-set, obtain the operation mode matched with navigation condition;Based on navigation condition, operation mode and the switching control strategy between different navigation conditions of pre-set, available power of power station is distributed to multiple propeller, and the collaborative propulsion of ship is carried out.Such, by based on speed and main station handle position, identify navigation condition, and match operation mode, to distribute available power of power station to multiple propeller, improve the response speed of ship propulsion control, improve the adaptability to complex navigation environment, improve ship safety.

The invention relates to the technical field of unmanned ship safety control, and discloses an anti-spoofing-attack self-adaptive sliding mode control method and system for an unmanned ship and a medium, and the method comprises the steps: S1, constructing an unmanned ship T-S fuzzy model under the spoofing attack and external disturbance; s2, designing a dual-adaptive sliding mode observer based on the unmanned ship T-S fuzzy model constructed in S1; s3, designing a sliding mode controller based on S1 and S2; and S4, forming a closed-loop control system based on S1-S3 to perform sliding mode control: integrating the unmanned ship T-S fuzzy model constructed in S1, the dual-adaptive sliding mode observer designed in S2 and the sliding mode controller designed in S3 to form the closed-loop control system, and realizing sliding mode control. According to the method, the dynamic suppression capability of the composite threat can be remarkably improved, precise compensation of a spoofing attack signal and external disturbance of the ocean is realized, high-precision zero-flutter control is realized under the coexistence of the spoofing attack and the external disturbance, and an autonomous control solution with safety, robustness and real-time performance is provided for the unmanned ship.

The invention provides an ultrahigh ship identification method and system based on a self-adaptive Norenz matrix, and relates to the field of ship safety monitoring. The first matrix is a sea wave adaptive Norenz matrix which adapts to sea wave environment and ship height measurement requirements through dynamic phase adjustment and beam angle grading; correcting the deviation of the detection wave beam in real time according to the sea wave monitoring data to obtain a corrected detection wave beam; and finally, receiving a reflected light beam formed by reflecting the corrected detection wave beam through a ship, analyzing the reflected light beam to obtain the height of the ship, and generating early warning information in combination with the average height of the sea waves. Static angle grading adaptive ship height and dynamic phase adjustment offset sea wave interference can be realized, so that the accuracy of ultrahigh ship identification is improved.

The invention discloses an intelligent method and system for safety monitoring of a water transportation engineering construction ship. The system comprises a multi-mode sensing device, an on-board server, an alarm notification module and a cloud platform server. The intelligent method comprises the following steps: S1, collecting videos, infrared images, temperature and humidity, smog, gas concentration, vibration, position and equipment state data of different parts of a ship through multi-mode sensing equipment, and storing the data in a server on the ship; s2, performing deep integration on the video monitoring data from different sources and various sensor data by adopting a multi-modal data fusion method; carrying out labeling, data enhancement and balancing on the fused multi-modal data, and constructing a training set; and S3, training the constructed alarm model by adopting the training set, and storing the optimal alarm model. According to the method, video data and sensor data are combined, a multi-modal fusion algorithm is adopted, and the accuracy and reliability of ship safety monitoring can be improved.

According to the ship stabilization system based on the electromagnetic actuators and the control method, the upper electromagnetic actuator, the lower electromagnetic actuator, the left electromagnetic actuator and the right electromagnetic actuator serve as executing mechanisms and are arranged on the upper portion, the lower portion, the left portion and the right portion of the central axis of a ship respectively. Rapid response in a full-wave period range is achieved, hydraulic oil or water tank liquid is not needed, a pure electrification scheme is adopted, energy consumption is low, occupied space is small, maintenance convenience is high, and an excellent stabilization effect is achieved; according to the method, actual current output values of the upper electromagnetic actuator, the lower electromagnetic actuator, the left electromagnetic actuator and the right electromagnetic actuator can be solved according to attitude signals collected by a ship, inherent parameters of the ship and a ship rolling kinetic equation, and the service life balance of the electromagnetic actuators and the reliable stabilization effect of the system are achieved. And the method is of great significance in improving the safety and comfort of the ship.

An orientation fault detection system is configured to detect improper installation of the dynamic active control system (DACS) controller / software module by receiving data output from a plurality of sensors to determine whether an orientation fault is detected corresponding to an improper installation of the controller / software module. Such determination is made based upon sensor data when corresponding environmental and operational conditions are met, so the orientation fault detection system is further configured to determine whether the requisite conditions are met for orientation fault detection based upon the sensor data. If an orientation fault is detected, the orientation fault detection system initiates a safe state protocol that renders the vessel safe to operate.

The invention discloses an unmanned ship safe dynamic positioning method based on a switching fuzzy wavelet network, and the method comprises the steps: building and constructing a switching LPV networked unmanned ship system according to the number of shipborne equipment, designing an event triggering mechanism, and constructing an attack detection observer and a detector in a shore-based system for possible spoofing attacks in communication; designing a safety controller in combination with a switching fuzzy wavelet network and an attack detector, introducing a shore-ship event triggering mechanism, further designing a special attack detector and a control input compensator, and generating a safe event triggering control input; a closed-loop system is constructed by integrating an attack detection observer, an unmanned ship system and control input, and a stable condition of the system is given through theoretical analysis, so that safe dynamic positioning of the unmanned ship under potential network attacks is realized; according to the method, the estimation accuracy can be improved, the safety is improved, and safe dynamic positioning of the networked unmanned ship is realized.

The invention relates to the field of ship navigation, in particular to a safety analysis method and device for ships connected with elevated cables in waves, electronic equipment and a computer readable storage medium. The method comprises the steps that a ship coupling motion equation set is constructed, and the ship coupling motion equation set comprises force and torque, acting on a first ship and a second ship, of an elevated cable; solving a ship coupling motion equation set based on the set wave data, and obtaining first ship coupling motion data, second ship coupling motion data and elevated cable mechanical data under the set wave data; and determining the safety of the first ship and the second ship based on the first ship coupling motion data, the second ship coupling motion data and the elevated cable mechanical data. According to the safety analysis method and device for the ship connected with the elevated cable in the wave, the electronic equipment and the computer readable storage medium, the technical effect of improving the navigation safety of the ship connected with the elevated cable in the wave can be achieved.

The application relates to a ship encounter space-time danger degree evaluation method and system considering the influence of a navigation environment, and belongs to the technical field of ship safe driving. The application is aimed at solving the problem that the action time of collision avoidance in a complex sea environment cannot be accurately determined. A ship environment sensing module and a positioning module are used to obtain channel environment information of a ship navigation area and ship position, heading and speed information; the closest encounter distance of two ships, the encounter time of the ship from the current position to the closest intersection point of the two ships, the safe encounter distance of the two ships, the absolute safe encounter distance, the latest avoidance distance and the distance that can be avoided by taking measures are calculated; the collision danger degree in the space position and the collision danger degree of the two ships in the time dimension are further calculated; the space danger degree and the time danger degree are combined by using a synthesis operator to solve the space-time collision danger degree; and the danger degree of ship collision is evaluated according to the danger degree. The application is suitable for ship encounter space-time danger degree evaluation.

The application discloses a method for generating a safety inspection report of an offshore oil production ship shape of a multimodal large model, relates to the technical field of intelligent generation of ship safety inspection, and first collects an offshore oil production ship image, matches a corresponding safety inspection report, and constructs a data set; subsequently, a multimodal report generation model is constructed, the offshore oil production ship image and the corresponding safety inspection report are input into the model to generate a safety inspection report of an offshore oil production ship shape; subsequently, the model is trained, and after multiple rounds of training, a final multimodal report generation model is obtained; finally, the offshore oil production ship image is input into the final model, and a safety inspection report of an offshore oil production ship shape is output. The application enhances the controllability and pertinence of the content generated by the large language model, improves the accuracy and compliance of the shape safety inspection report, and can be widely applied to scenes such as daily operation management of offshore oil production ships, safety guarantee of ocean navigation, compliance review of ports and ship classification societies, and accident prevention and subsequent maintenance disposal.

This invention relates to a method for predicting ship maneuvering motions under high sea states, comprising the following steps: establishing a three-dimensional numerical model of ship-wave coupling under high sea states based on computational fluid dynamics; installing sensors on the ship to collect real-time motion data of the ship under high sea states, and preprocessing the collected data; extracting feature parameters related to the ship's six degrees of freedom motion based on the preprocessed data; using the feature parameters as input, constructing a ship maneuvering motion prediction model using a neural network model, the output of which is the prediction result of the ship's six degrees of freedom motion over a future period; training and validating the prediction model using historical data; inputting the real-time collected data into the trained prediction model to perform real-time prediction of the ship's six degrees of freedom motion; generating ship maneuvering suggestions based on the prediction results; and providing real-time feedback and correction to the model based on the comparison between actual operating data and the prediction results. This invention has the effects of improving prediction accuracy, ensuring ship safety, and improving prediction precision.

The present application relates to a kind of ship navigation risk prediction method, device, electronic equipment and medium, belong to ship safety technical field, wherein, the method includes: the fault tree of ship capsizing is constructed;The fuzzy failure rate of each node in fault tree is calculated;The end value and the median of the range interval of index parameter risk interval table are fitted with correction coefficient, and the risk correction formula between the evaluation index parameter in interval and fuzzy failure rate is obtained;Data extraction is carried out in the range interval of index parameter by Latin hypercube sampling, and multiple sets of index data are obtained, multiple sets of index data are input into the risk correction formula obtained, and multiple sets of risk fuzzy failure rate are input into the preset formula to obtain multiple sets of risk probability data, to obtain sample data;The physical quantity data corresponding to target ship is input into the BP neural network model trained perfectly, and the risk probability value of target ship capsizing is obtained.The present application improves the precision of ship navigation risk prediction.

The invention relates to a carbon dioxide reliquefaction method used in the storage and transportation process, which comprises the following steps: monitoring the pressure in a carbon dioxide storage tank in real time, and when the pressure is higher than a preset threshold value, enabling gaseous carbon dioxide to enter a refrigerating unit through a gas connecting pipeline; the liquefied carbon dioxide is stored in a low-temperature container through a pipeline; when the liquid level in the carbon dioxide storage tank reaches a set value, liquefied carbon dioxide is pumped back to the carbon dioxide storage tank through a liquid spraying system; the supercooled carbon dioxide is directly sprayed into the carbon dioxide storage tank, so that the temperature and the pressure in the carbon dioxide storage tank are reduced, the safety of the carbon dioxide storage tank in the transportation process can be guaranteed, meanwhile, high efficiency, energy conservation, labor conservation and environmental protection are achieved, and the transportation cost is reduced. According to the method for re-liquefying and recovering the carbon dioxide overflowed by flash evaporation, the loss of the carbon dioxide in the transportation process is reduced, the transportation cost is reduced, zero leakage is realized, carbon dioxide leakage is avoided, and ship safety and environmental protection are guaranteed.

The utility model discloses a telescopic camera support, which relates to the field of camera supports and comprises a fixing support, the fixing support is composed of a fixing sleeve, an installation fixing plate and four reinforcing plates, the installation fixing plate is fixedly installed at one end of the fixing sleeve, the number of the reinforcing plates is four, and the reinforcing plates are symmetrically and fixedly installed on the fixing sleeve and the installation fixing plate. The telescopic support is installed on the fixing sleeve in a sliding mode, the telescopic support is composed of a telescopic rod, an anti-disengagement sliding block, a bent pipe and a camera base, and by arranging the telescopic camera support composed of the fixing support, the telescopic support and the fixing assembly, when a cargo hold area is not full of cargoes, the telescopic camera support can be used as a common support; when the cargo hold area is full of cargos, the camera main body can extend outwards through the telescopic camera bracket, so that the pedestrian state in the side compartment area and the cargo state in the cargo hold area can be observed through the camera main body, and the safe driving of a ship is ensured.

The application provides a ship field supervision knowledge graph construction method and device and electronic equipment, the method comprises the following steps: constructing an ontology model and a knowledge base of a ship field supervision knowledge graph, and extracting target project class entities from the knowledge base; determining to-be-fused entities in the target project class entities, and corresponding Jaccard coefficient similarity, Jaro-Winkler similarity and uSIF similarity; inputting the similarity into a knowledge fusion model to obtain a result of whether to fuse; the knowledge fusion model is obtained by training based on an XGBoosT model; in the case of needing to fuse, performing entity attribute completion and association alignment on the to-be-fused entities to obtain knowledge fusion data; and mapping the ontology model to the knowledge fusion data to obtain a ship field supervision knowledge graph. The application can assist maritime law enforcement personnel in decision-making in ship field inspection, and make ship safety supervision work informatized, intelligentized and specialized.

The invention discloses a design optimization method for an intelligent ship air route and speed, and belongs to the technical field of intelligent ship navigation. Comprising the following steps: receiving a ship navigation task instruction, and obtaining task related information; establishing a ship safety detection situation model; checking the availability of the starting point and the target point; performing route planning based on the environment map data and the meteorological data; carrying out navigational speed optimization based on a route planning result and a task mode; evaluating the safety and efficiency of the route and speed planning result; detecting the availability of the route and speed planning result; outputting and storing a route and speed planning result; monitoring a planning result and judging whether re-planning is needed or not; and establishing a continuous monitoring mechanism. The method has the advantages that the safety is improved, the meteorological data, the environmental map and the ship characteristics are comprehensively considered, the ship safety detection situation model is combined, dangerous areas and severe meteorological conditions are effectively avoided, and the safety of ship navigation is remarkably improved.

The invention provides an inland river intersection water area intelligent cooperative scheduling method based on multi-model fusion, and belongs to the technical field of inland river intelligent shipping. A three-degree-of-freedom ship kinematics model is adopted to define a ship safety distance, and a state space and an action space are defined; designing a multi-objective mixed reward function; the MADDPG algorithm architecture is improved, and the LSTM is introduced to enhance the time sequence processing capability; a centralized training and distributed execution training mode is adopted, an Actor network processes time sequence data at high frequency, a Critic network provides global value evaluation, and cooperative ship selection and multi-ship cooperative training are combined to improve the cooperative scheduling capability of ships in a complex dynamic environment; a simulation test is carried out based on AIS data, and a scheduling effect is verified by using a reward function, a collision rate, an average speed and an action change stability index. According to the method, the problem of ship scheduling in the inland river intersection water area can be solved, so that efficient dynamic scheduling optimization is realized.

The invention relates to the technical field of windscreen wipers for ships, and discloses a split screen control method for a windscreen wiper for a ship, which comprises the following steps of: 1, carrying out region division planning on a window of a closed bridge cab, which needs to be provided with the windscreen wiper, and determining a region division scheme; 2, according to the partitioning scheme, an independent windscreen wiper control panel is configured for each partitioned region; step 3, establishing connection between the windscreen wiper corresponding to each area and the windscreen wiper control panel of the area; and 4, independent control operation is conducted on the windscreen wipers in the areas through the windscreen wiper control panels in the areas, and on-demand starting and stopping, speed adjustment and water spraying control of the windscreen wipers in the different areas are achieved. By means of timely and convenient windscreen wiper control, a driver can rapidly respond to various weather and sight changes, the clear view field is kept all the time, the navigation risk caused by sight blocking is reduced, and powerful support is provided for safe navigation of a ship.