Ship remote control system and method based on 5G communication technology and artificial intelligence

Abstract

The present invention discloses a ship remote control system and method based on 5G communication technology and artificial intelligence, including a sensor system, a data processing unit, a 5G communication module, a remote control center, and a remote control interface; the sensor system is used to collect the state data of the ship, and its output end is connected to the data processing unit, the data processing unit receives the data of the sensor system and processes it, the data processing unit is connected to the remote control center via the 5G communication module, and is used to upload the processing results of the data processing unit to the remote control center, the remote control center is connected to the remote control interface, and the remote control interface is used to display the control information of the ship and input the control instructions of the remote operator; the remote control center feeds back the control instructions to the data processing unit via the 5G communication module, and the data processing unit is connected to the ship power system to realize the control of the ship. This solution realizes the remote control of the ship, making the ship control simpler.

Description

Technical Field

[0001] The present invention relates to the field of ship intelligent control, and in particular to a ship remote control system and method based on 5G communication technology and artificial intelligence. Background Art

[0002] The remote control of ships is limited by the requirements of transmission distance and stability, and has not been greatly improved. The existing technology for remote control of ships still has the following shortcomings:

[0003] Insufficient data acquisition: Traditional ship remote control systems may be limited by the means and scope of data acquisition and cannot obtain enough data to fully understand the ship's operating status. This may result in the remote operator being unable to make accurate decisions or predict possible problems with the ship.

[0004] Poor data quality: Even with limited data acquisition, the data quality may be poor, and there may be data noise, errors or inaccuracies. This may affect the performance and accuracy of the remote control system, leading to misjudgment or incorrect operation.

[0005] Insufficient data processing capabilities: Traditional data processing technologies may not be able to handle large amounts of data, nor can they perform complex data analysis and mining. This may result in the inability to fully utilize the potential information and value in the data, limiting the intelligence level and decision support capabilities of the remote control system.

[0006] Limited communication bandwidth: Previous communication technologies, such as 4G LTE, usually have lower bandwidth limitations and may not meet the needs of large-scale data transmission. This may result in slow data transmission rates and high latency, affecting the real-time performance and response speed of remote control systems.

[0007] Large communication delay: Traditional communication technologies may have large communication delays. Especially when remote ship control systems need to operate in real time, delays will become a serious problem, affecting the operator's real-time perception and response capabilities.

[0008] Therefore, limited by the above-mentioned shortcomings, the existing technology can only use manual on-site judgment to control the ship. The captain adjusts and controls the ship according to the on-site environment of the ship based on his driving experience. This method requires manual on-site control, resulting in at least one captain for a ship, etc., which cannot meet the requirements of remote control. With the requirements of automation, intelligence and safety of ship operations, the traditional manual control of ships will not meet the requirements of intelligent control of ships. Summary of the invention

[0009] The purpose of the present invention is to overcome the shortcomings of the prior art, provide a ship remote control system and method based on 5G communication technology and artificial intelligence, and realize the requirements for remote control of ships based on 5G technology and artificial intelligence. At the same time, remote control can also meet the user's understanding and acquisition of ship status information and meet the captain's needs for remote reliability control of the ship.

[0010] In order to achieve the above-mentioned purpose, the technical solution adopted by the present invention is: a ship remote control system based on 5G communication technology and artificial intelligence, the control system comprising a sensor system, a data processing unit, a 5G communication module, a remote control center, and a remote control interface; the sensor system is used to collect the status data of the ship, and its output end is connected to the data processing unit, the data processing unit receives the data of the sensor system and processes it, the data processing unit is connected to the remote control center via the 5G communication module, and is used to upload the processing results of the data processing unit to the remote control center, the remote control center is connected to a remote control interface, and the remote control interface is used to display the control information of the ship and enter the control instructions of the remote operator; the remote control center feeds back the control instructions to the data processing unit via the 5G communication module, and the data processing unit is connected to the ship power system to realize control of the ship.

[0011] The sensor system includes GPS, inertial navigation system, camera, meteorological sensor, obstacle detection sensor, which is used to monitor the position, speed, heading and environmental condition information of the ship in real time.

[0012] The data processing unit is used to process and mine the ship data sent by the sensor system based on an artificial intelligence algorithm to obtain prediction information for ship control and ship status information.

[0013] The data processed by the data processing unit include hydrostatic curves, main engine parameters and shaft generator parameters, ship model test and ship trial reports, ship wind and wave resistance levels, environmental meteorological data and real-time ship information, as well as calculation and alarm strategies for potential collision and grounding risk factors.

[0014] The remote control interface is connected to the remote control center through security authentication and encryption.

[0015] The data processing unit integrates a pre-trained multi-layer perceptron neural network to predict the control of the ship and obtain the predicted heading and speed of the ship.

[0016] A control method for a ship remote control system based on 5G communication technology and artificial intelligence, the control method comprising:

[0017] (1) The sensor system monitors and collects the ship's status parameter data in real time;

[0018] (2) The data processing unit receives the data from the sensors and processes them to obtain prediction information for ship control and ship status information;

[0019] (3) Use 5G communication module to transmit ship control prediction information and ship status information to the remote control center and display it through the remote operation interface;

[0020] (4) After the remote ship operator obtains the information of the remote operation interface, the operator enters the control instructions based on the remote operation interface;

[0021] (5) The remote control center sends the control instructions to the data processing module via the 5G communication module, and the data processing module sends the control instructions to the ship power system, which executes the control instructions to realize the transmitted driving control.

[0022] The predicted information of ship control in step (2) refers to the optimal control parameters of the ship predicted by the data processing unit based on the data collected by the sensor system.

[0023] In step (2), a pre-trained neural network model MLP is integrated in the data processing unit, and the optimal control parameters corresponding to the input ship sensor data are predicted and output based on the neural network model MLP.

[0024] The neural network model is trained using a data set containing ship sensor data and corresponding ship control parameters. The back propagation algorithm and gradient descent method are used to optimize the neural network parameters. The weights and bias of the neural network are adjusted according to the principle of minimizing the loss function, so that the prediction results of the neural network model are close to the optimal ship control parameters.

[0025] The advantages of the present invention are: it realizes remote control of ships, improves the remote automation of ships, and integrates artificial intelligence algorithms to predict the control parameters of ships, thereby improving the intelligence level of ship control. At the same time, the predicted parameters can provide control references for operators, and automatic control can be achieved through estimated parameters, thereby expanding the automatic operation capability of the transmission; various types of data collected by the sensor system can be displayed on the user interface for convenient remote viewing; at the same time, it supports encryption and authentication connections between the control interface and the remote control center, thereby improving the security and reliability of data interaction. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The following is a brief description of the contents expressed in the drawings of the present invention and the symbols in the drawings:

[0027] Figure 1 It is the principle diagram of the control system of the present invention. DETAILED DESCRIPTION

[0028] The specific implementation of the present invention will be further explained in detail below by describing the optimal embodiment with reference to the accompanying drawings.

[0029] Ships need to obtain information and build remote control systems on a remote basis. The remote control system and solution provided by this solution can realize remote control of ships, solving the defects of existing technologies that require on-site control of ships. It can also realize automatic control on the basis of remote control, expand the way of ship control, and provide a basis for the automation and intelligent control of ships. The following technologies are used in this solution:

[0030] 5G communication technology: 5G communication technology is a new generation of mobile communication technology with the characteristics of high bandwidth, low latency and large connectivity. Compared with traditional communication technologies such as 4G LTE, 5G communication technology can provide more efficient data transmission rate and lower latency, which is suitable for real-time remote control applications.

[0031] Artificial intelligence technology: Artificial intelligence technology includes machine learning, deep learning, natural language processing and other technologies, which can realize intelligent processing and analysis of data. In ship remote control technology, artificial intelligence technology can be used in ship status prediction, anomaly detection, decision support and other aspects to improve the intelligence level of remote control systems.

[0032] Sensor technology: Sensor technology is used to monitor various physical quantities and environmental parameters of the ship, such as position, speed, temperature, humidity, etc. These sensors can be GPS, inertial navigation systems, cameras, meteorological sensors, etc., providing real-time ship status information to the remote control system.

[0033] Big data technology: Big data technology is used to process massive amounts of data and extract valuable information and knowledge. In ship remote control technology, big data technology can be used to analyze and mine sensor data, discover hidden patterns and trends, and provide decision support for ship operations.

[0034] Network security technology: Network security technology includes data encryption, identity authentication, network firewall and other technologies, which are used to protect the security and privacy of remote control systems and prevent network attacks and data leakage risks.

[0035] Real-time operating system: Real-time operating system can provide reliable real-time performance, ensuring that remote operators can control the ship in a timely manner and obtain the latest status information.

[0036] like Figure 1 As shown, it is a schematic diagram of a ship remote control system based on 5G communication technology and artificial intelligence in this embodiment. The control system includes a sensor system, a data processing unit, a 5G communication module, a remote control center, and a remote control interface;

[0037] The sensor system is used to collect the status data of the ship, and its output end is connected to the data processing unit. The data processing unit receives and processes the data from the sensor system. The data processing unit is connected to the remote control center via the 5G communication module, and is used to upload the processing results of the data processing unit to the remote control center. The remote control center is connected to a remote control interface, which is used to display the control information of the ship and enter the control instructions of the remote operator; the remote control center feeds back the control instructions to the data processing unit via the 5G communication module, and the data processing unit is connected to the ship's power system to realize control of the ship.

[0038] The sensor system is mainly used to collect various status data of the ship's operation, including the ship's own data and external environmental data, including but not limited to GPS, inertial navigation system, camera, meteorological sensor, obstacle detection sensor and other sensors, used to monitor the ship's position, speed, heading, environmental conditions and other ship and environmental parameters in real time. Sensor system: including GPS, inertial navigation system, camera, meteorological sensor, etc., used to monitor the ship's position, speed, heading, environmental conditions and other parameters in real time. The data of the sensor system provides the basis for the accurate assessment of the ship's status.

[0039] The data processing unit is used to process and mine the ship data sent by the sensor system based on artificial intelligence algorithms to obtain prediction information for ship control and ship status information. The data processing unit is responsible for receiving, processing and analyzing data from the sensor system, and performing intelligent data processing based on big data and artificial intelligence algorithms. The data processing unit uses big data technology to analyze and mine massive data, extract valuable information, and perform intelligent processing through artificial intelligence algorithms to achieve accurate assessment and prediction of the ship's status.

[0040] The prediction information of ship control is the optimal control parameters of the ship, such as the optimal speed and heading, obtained based on artificial intelligence algorithms and big data mining algorithms. Ship status information refers to the ship's own operating status parameters, such as real-time ambient temperature, weather, ship speed, position, and other ship parameters directly obtained through sensors and status parameters obtained through the data processing unit. The prediction of the optimal control parameters in the ship prediction information includes: the pre-trained multi-layer perceptron neural network integrated in the data processing unit predicts the control of the ship to obtain the predicted heading and speed of the ship.

[0041] In order to improve the remote control interface, it is connected to the remote control center through secure authentication and encryption. The remote operation interface is a user interface provided to the remote operator for real-time monitoring of the ship's status, issuing control instructions, etc. The remote operation interface uses secure authentication and encryption technology to ensure the security and privacy of remote operations.

[0042] 5G communication module: responsible for high-speed, low-latency data transmission and communication with the ship's remote control center. 5G communication technology provides higher bandwidth and lower latency, making data transmission more real-time and reliable.

[0043] The data processed by the data processing unit include hydrostatic curves, main engine parameters and shaft generator parameters, ship model test and ship trial reports, ship wind and wave resistance level, environmental meteorological data and ship real-time information, as well as calculation and alarm strategies of potential collision and grounding risk factors; the processed data include:

[0044] (1) Ship general arrangement drawing: This provides the overall structure and layout information of the ship and is one of the initial configuration parameters of the system, which facilitates users to understand the data and confirm its rationality and reliability.

[0045] (2) Hydrostatic curve: These data can help evaluate the stability and navigation performance of the ship. During the estimation process, the hydrostatic curve can be used to predict the performance of the ship under different load conditions, and the seaworthiness of the system can be evaluated to obtain the performance parameters of the ship under the current load condition. The parameters are used to transmit to the user control interface for easy viewing and use by the user.

[0046] (3) Main engine parameters and shaft generator detailed parameters: Main engine parameters and generator detailed information are crucial to evaluating the power system performance of the ship. In the estimation and evaluation, the power performance and energy management of the ship can be evaluated based on the main engine parameters. The data processing unit obtains the parameters corresponding to the power performance and energy management of the ship based on the main engine parameters. The parameters are used to transmit to the user control interface for easy viewing and use by the user.

[0047] (4) Ship model test and ship trial reports: These reports provide performance data of the ship during model tests and actual ship trials, which help to evaluate the ship's navigation performance and stability. During the estimation process, the data processing unit can evaluate the system's seaworthiness and navigation performance parameters based on the trial reports.

[0048] (5) Ship's wind and wave resistance level: These data indicate the ship's seaworthiness under different wind and wave conditions and are one of the important indicators for evaluating the safety and stability of a ship. In the estimation and evaluation, the data processing unit evaluates the ship's performance parameters under real-time severe weather conditions based on the real-time wind and wave parameters collected by the sensor system and the wind and wave resistance level.

[0049] (6) Environmental meteorological data and real-time ship information: These data include real-time information on environmental conditions and ship status during navigation, which are essential for evaluating the seaworthiness and safety of the system under different environmental conditions. In the estimation and evaluation, the data processing unit can evaluate the performance and safety performance parameters of the system based on the environmental meteorological data and real-time ship information.

[0050] (7) Calculation and alarm strategy of potential collision and grounding risk factors: These data involve the safety management and risk warning of the ship and are one of the important indicators for evaluating the safety performance of the system. In the estimation and evaluation, the safety performance and risk control ability of the ship can be evaluated based on the collision and grounding risk factors. The data processing unit estimates the collision and grounding risks based on the data information collected by the sensor system and obtains the corresponding estimation parameters.

[0051] The above parameters estimated by the data processing unit are transmitted to the remote control center through the 5G communication module when the system is working, and are displayed through the remote control interface, making it convenient for operators to view relevant information during operation.

[0052] In this embodiment, the connection relationship between the various components of the control system is as follows: the sensor system is connected to the data processing unit by wired or wireless means, and transmits the real-time collected ship status data to the data processing unit. The data processing unit is connected to the 5G communication module, and the processed ship status information is transmitted to the ship remote control center through the 5G network. The remote operation interface is connected to the ship remote control center through a secure network to realize real-time communication and control between the remote operator and the ship.

[0053] Based on the control method of the ship remote control system in the above embodiment, the control method includes two modes: manual remote control and automatic remote control. The two modes can be switched according to the switching function button on the remote control interface connected to the remote control center. When the manual remote control mode is switched, the manual control steps include:

[0054] (1) The sensor system monitors and collects the ship's status parameter data in real time;

[0055] (2) The data processing unit receives the data from the sensors and processes them to obtain prediction information for ship control and ship status information;

[0056] (3) Use 5G communication module to transmit ship control prediction information and ship status information to the remote control center and display it through the remote operation interface;

[0057] (4) After the remote ship operator obtains the information of the remote operation interface, the operator enters the control instructions based on the remote operation interface;

[0058] (5) The remote control center sends the control instructions to the data processing module via the 5G communication module, and the data processing module sends the control instructions to the ship power system, which executes the control instructions to realize the transmitted driving control.

[0059] The prediction information of the ship control in step (2) refers to the optimal control parameters of the ship predicted by the data processing unit based on the data collected by the sensor system. The optimal control parameters are displayed through the operation interface to provide basic reference control data for the user's operation; the user can refer to the given optimal control parameters or make manual fine adjustments based on the optimal control parameters, and feedback is given to the data processing unit based on the user's control. The data processing unit forwards the control parameters to the power control system of the ship. The power control system of the ship can control the heading, speed, etc. of the ship, thereby controlling the driving of the ship.

[0060] The optimal control parameters of a ship are explained by taking heading and speed as examples. A pre-trained neural network model MLP is integrated in the data processing unit. Based on the neural network model MLP, the input ship sensor data is predicted and the corresponding optimal control parameters are output. The ship sensor data: current ship speed, heading, tilt angle, external obstacles, etc. are used as inputs to the neural network model, and then the optimal heading and speed are used as outputs. When the real-time parameters are sent to the neural network model, the neural network model predicts and outputs the corresponding optimal heading and speed. The neural network model needs to be trained before use to output accurate prediction results. During training, the neural network model is trained using a data set with ship sensor data and corresponding ship control parameters. The back propagation algorithm and gradient descent method are used to optimize the neural network parameters. The weights and biases of the neural network are adjusted according to the principle of minimizing the loss function, so that the prediction results of the neural network model are close to the optimal ship control parameters.

[0061] In a preferred embodiment of the present application, the user remote control interface includes a pair of MR glasses, and the sensor system includes a camera with at least a forward perspective of the ship, which is used to collect video data of the ship's travel direction. The video data is transmitted to the AR glasses via 5G, and the processor built into the AR glasses processes the received data to obtain AR video data. The operator wears the AR glasses and can view augmented reality ship video data through the AR glasses, thereby improving the immersive feeling of remote control and the operator's real perception of the environment during manual remote control, thereby making more accurate manual control.

[0062] Automatic control modes include:

[0063] (1) The sensor system monitors and collects the ship's status parameter data in real time;

[0064] (2) The data processing unit receives the data from the sensors and processes them to obtain prediction information for ship control and ship status information;

[0065] (3) The data processing unit sends the predicted information of ship control to the power control system of the ship, which executes the predicted information to control the ship. At the same time, the 5G communication module is used to transmit the predicted information of ship control and the ship status information to the remote control center and display them through the remote operation interface to achieve the purpose of remote monitoring.

[0066] In the predictive control method of the data processing module, 1. The sensor system monitors the position, speed, heading, weather conditions and other parameters of the ship in real time and transmits the data to the data processing unit.

[0067] 2. After receiving the sensor data, the data processing unit uses big data technology to process and analyze the data, converting massive data into visual ship status information.

[0068] 3. Based on artificial intelligence algorithms, the data processing unit conducts intelligent assessment and prediction of the ship's status, identifies possible abnormal conditions of the ship, and outputs the optimal control parameters for transmission.

[0069] 4. The logic of the intelligent algorithm is as follows:

[0070] (1) Use a multilayer perceptron (MLP) neural network as our intelligent computing model.

[0071] (2) Input: Ship sensor data: current ship speed, heading, tilt angle, external obstacles, etc.

[0072] (3) Output: predicted optimal course and speed of the ship for the next step.

[0073] (4) Calculation logic:

[0074] Input layer: Receives ship sensor data.

[0075] Hidden layer: multiple neurons, each with weights and biases.

[0076] Output layer: contains 2 neurons, representing heading and speed respectively.

[0077] (5) Calculation formula:

[0078] Calculation formula:

[0079] Hidden layer calculation:

[0080] For the jth hidden layer neuron:

[0081]

[0082] a j =σ(z j )

[0083] Among them, w ji is the weight of the jth neuron and input i, x i is the input feature, b j is the bias of the jth neuron, and σ is the activation function (such as ReLU or Sigmoid).

[0084] Output layer calculation:

[0085] For the kth output layer neuron (heading and speed):

[0086]

[0087]

[0088] Among them, w kj is the weight of the kth output neuron and the hidden layer j, a j is the hidden layer output, b k is the bias of the kth output neuron.

[0089] Loss function:

[0090] We use Mean Squared Error (MSE) as the loss function:

[0091]

[0092] Among them, y i is the actual next course and speed of the ship, are the heading and speed predicted by the model.

[0093] (6) Training process:

[0094] The training is performed using a dataset containing ship sensor data and the corresponding next heading and speed. The back propagation algorithm and gradient descent method are used to optimize the neural network parameters. According to the principle of minimizing the loss function, the weights and biases are continuously adjusted to make the prediction results close to the actual next heading and speed of the ship.

[0095] 5. The processed ship driving advice information is transmitted to the ship remote control center through the 5G communication module for real-time monitoring by the remote operator.

[0096] 6. The remote operator monitors the status of the ship in real time through the remote operation interface, and makes corresponding control decisions based on the intelligent ship status assessment, such as adjusting the ship's heading, speed, etc.

[0097] 7. The control instructions are sent to the ship control system through the 5G communication module for execution, realizing remote control.

[0098] Advantages of big data and artificial intelligence: Through big data and artificial intelligence technologies, this patent can intelligently process and analyze massive amounts of data, improve the ability to accurately assess and predict ship status, and make up for the problem of insufficient traditional data processing capabilities.

[0099] 5G communication security: This patent adopts 5G communication technology, provides a higher level of data encryption and authentication mechanism, ensures the security and privacy of data transmission, and solves the security risks of traditional communication technology.

[0100] Real-time monitoring and response: Combining 5G communication and artificial intelligence technology, this patent can realize real-time monitoring and response to changes in ship status, improve the real-time and accuracy of remote operations, and make up for the problem of large communication delays in traditional communication technologies.

[0101] The technical advantages of this application include:

[0102] 1. Improve safety: The present invention adopts advanced ship remote control technology, combined with big data and artificial intelligence technology, which can monitor the ship's environmental conditions, ship status and potential risks in real time, and take corresponding measures for early warning and safety management, greatly improving the safety of the ship.

[0103] 2. Optimize navigation performance: The present invention can optimize the navigation path, speed and ship attitude of the ship according to information such as the ship's structure, ship power system and environmental conditions, optimize navigation time and energy consumption, and improve the navigation efficiency and economy of the ship.

[0104] 3. Improve operational convenience: The present invention adopts an intelligent operation interface and information display system, which can clearly and intuitively display various status information and operation instructions of the ship, thereby improving the operational convenience and work efficiency of the remote operator.

[0105] 4. Enhanced environmental adaptability: The present invention can make intelligent navigation decisions and control adjustments based on the ship's real-time environmental meteorological data and ship status information, so that the ship can maintain stable navigation under adverse weather conditions, thereby enhancing the ship's environmental adaptability and seaworthiness.

[0106] 5. Reduce the risk of collision and grounding: The present invention can effectively reduce the risk of ship collision and grounding and improve the safety and stability of ships by calculating potential collision and grounding risk factors and adopting sound and light alarm strategies for early warning and risk control.

[0107] 6. Realize intelligent information management: The present invention can monitor, analyze and process various data of the ship in real time, realize intelligent information management and decision support, and provide a scientific basis for ship operation and management.

[0108] 7. In summary, compared with the background technology, the present invention has many beneficial effects such as improving safety, optimizing navigation performance, improving operational convenience, enhancing environmental adaptability, reducing collision and grounding risks, and realizing intelligent information management, which can effectively improve the operating efficiency and safety level of ships.

[0109] Obviously, the specific implementation of the present invention is not limited to the above-mentioned methods. As long as various non-substantial improvements are made using the method concept and technical solution of the present invention, they are all within the protection scope of the present invention.

Claims

1. A control method for a ship remote control system based on 5G communication technology and artificial intelligence, characterized in that: The control system includes a sensor system, a data processing unit, a 5G communication module, a remote control center, and a remote control interface; the sensor system is used to collect the status data of the ship, and its output end is connected to the data processing unit. The data processing unit receives and processes the data of the sensor system. The data processing unit is connected to the remote control center via the 5G communication module, and is used to upload the processing results of the data processing unit to the remote control center. The remote control center is connected to the remote control interface, and the remote control interface is used to display the control information of the ship and input the control instructions of the remote operator; the remote control center feeds back the control instructions to the data processing unit via the 5G communication module, and the data processing unit is connected to the ship power system to realize the control of the ship; The sensor system includes GPS, inertial navigation system, camera, meteorological sensor, obstacle detection sensor, which is used to monitor the position, speed, heading and environmental condition information of the ship in real time; The data processing unit is used to process and mine the ship data sent by the sensor system based on an artificial intelligence algorithm to obtain prediction information on ship control and ship status information; The data processed by the data processing unit include static hydrodynamic curves, main engine parameters and shaft generator parameters, ship model test and ship trial reports, ship wind and wave resistance level, environmental meteorological data and ship real-time information, as well as calculation and alarm strategies of potential collision and grounding risk factors; The remote control interface is connected to the remote control center through security authentication and encryption; The data processing unit integrates a pre-trained multi-layer perceptron neural network to predict the control of the ship to obtain the predicted heading and speed of the ship; The control method includes two modes: manual remote control and automatic remote control. The two modes are switched according to the switching function button on the remote control interface connected to the remote control center. When switching to manual remote control mode, the steps to enter manual control include: (1) The sensor system monitors and collects the ship's status parameter data in real time; (2) The data processing unit receives the data from the sensors and processes them to obtain prediction information for ship control and ship status information. The prediction information provides control reference for the operator. (3) Use 5G communication module to transmit ship control prediction information and ship status information to the remote control center and display it through the remote operation interface; (4) After the remote ship operator obtains the information of the remote operation interface, he / she enters the operator's control instructions based on the remote operation interface; (5) The remote control center sends the control instructions to the data processing module via the 5G communication module, and the data processing module sends the control instructions to the ship power system, which executes the control instructions to realize the ship's driving control; The prediction information of the ship control in step (2) refers to the optimal control parameters of the ship predicted by the data processing unit based on the data collected by the sensor system, and the user manually fine-tunes based on the optimal control parameters; The user remote control interface includes a pair of MR glasses. The sensor system includes a camera with at least a forward view of the ship, which is used to collect video data of the ship's travel direction. The video data is transmitted to the AR glasses via 5G. The processor built into the AR glasses processes the received data to obtain AR video data. The operator wears the AR glasses and views the augmented reality ship video data through the AR glasses. When entering the automatic control mode, the steps include: (1) The sensor system monitors and collects the ship's status parameter data in real time; (2) The data processing unit receives the data from the sensors and processes them to obtain prediction information for ship control and ship status information; (3) The data processing unit sends the predicted information of ship control to the ship's power control system, which executes the predicted information to control the ship. At the same time, the 5G communication module is used to transmit the predicted information of ship control and ship status information to the remote control center and display them through the remote operation interface.

2. The control method of the ship remote control system based on 5G communication technology and artificial intelligence as claimed in claim 1, characterized in that: In step (2), a pre-trained neural network model MLP is integrated in the data processing unit, and the optimal control parameters corresponding to the input ship sensor data are predicted and output based on the neural network model MLP.

3. The control method of the ship remote control system based on 5G communication technology and artificial intelligence as claimed in claim 2, characterized in that: The neural network model is trained using a data set containing ship sensor data and corresponding ship control parameters. The back propagation algorithm and gradient descent method are used to optimize the neural network parameters. The weights and bias of the neural network are adjusted according to the principle of minimizing the loss function, so that the prediction results of the neural network model are close to the optimal ship control parameters.

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