An unmanned boat electronic control system based on multi-source data

Abstract

The present invention relates to the field of unmanned boat control technology, and in particular to an unmanned boat electronic control system based on multi-source data. The present invention provides an electronic control monitoring module, wherein a wide-area monitoring unit thereof obtains monitoring data, determines a dynamic disturbance value and a characteristic distribution value, and an attention monitoring unit responds to a determination result of an electronic control adjustment module to determine a ripple characterization value and a bubble characteristic value of an attention area. The electronic control adjustment module calculates an abnormal risk value of a sub-target area, divides the attention area, and determines whether it is necessary to start the attention monitoring unit. The electronic control analysis module calculates a drowning characterization coefficient in response to the start-up state of the attention monitoring unit, determines the drowning state of the area, and determines whether it is necessary to issue an early warning signal. The electronic control rescue module controls the unmanned boat to implement rescue and determines a rescue method. The present invention can monitor drowning over a large area and quickly deploy unmanned boats while saving computing power, thereby improving the efficiency of drowning monitoring and the efficiency of unmanned boat deployment.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned boat control, and in particular to an unmanned boat electronic control system based on multi-source data. Background Art

[0002] Unmanned boats need to have accurate and comprehensive perception of the surrounding environment when navigating in complex and changeable water environments. With the development of automatic control technology, some unmanned boats can already automatically navigate to the target location through electronic control systems. At present, unmanned boats have broad application prospects, especially in the field of water rescue. Combined with drowning monitoring systems, unmanned boats can be quickly deployed to improve safety.

[0003] Chinese patent publication number CN118395347A discloses a method and system for unmanned vehicle mission decision-making based on multi-source data. The method specifically includes: collecting operational information of the unmanned vehicle; evaluating the health status of the unmanned vehicle based on the operational information to obtain a health status assessment result; establishing a decision database based on the health status assessment result and the task decision corresponding to the health status assessment result; and making a task decision for the unmanned vehicle to be determined using the decision database. This invention can solve the problem of command conflicts when the unmanned vehicle is executing a mission, ensure the safety of the unmanned vehicle itself, and improve decision-making speed.

[0004] Chinese patent publication number CN119088004A discloses an intelligent, all-weather, autonomous cruising unmanned rescue boat and its electronic control method. The intelligent, all-weather, autonomous cruising unmanned rescue boat includes a hull and a multi-source energy supply system, an environmental and target perception system, an intelligent electronic control system, a propulsion system, a satellite positioning system, and an autonomous navigation system. The rescue boat can autonomously acquire environmental data and drowning victim information and dynamically plan the optimal cruising route using a deep reinforcement learning algorithm. The intelligent electronic control system is responsible for electronically controlling the cruising, identifying drowning victims, generating rescue strategies, and executing the rescue mission. After the rescue is complete, the system automatically replans the cruising route to continue the mission. This design enables all-weather, fully autonomous water cruising and rescue operations, significantly improving rescue coverage and efficiency, reducing manpower consumption and safety risks, shortening rescue response time, and increasing rescue success rates. Rescue capabilities, in particular, are significantly enhanced in complex environments.

[0005] However, the prior art still has the following problems:

[0006] High-precision video data is usually required when monitoring drowning in large areas, and the data to be analyzed is massive. Existing technologies do not consider abnormal tendencies in different areas and then adjust monitoring resources and analysis methods in a targeted manner. The monitoring process consumes high computing power and has poor accuracy. Summary of the Invention

[0007] To this end, the present invention provides an unmanned boat electronic control system based on multi-source data to solve the problems in actual situations where high-precision video data is usually required when monitoring drowning in large areas, and the data to be analyzed is massive. The existing technology does not take into account the abnormal tendencies of different areas and then adjust the monitoring resources and analysis methods in a targeted manner, resulting in high computing power consumption and poor accuracy in the monitoring process.

[0008] To achieve the above objectives, the present invention provides an unmanned boat electronic control system based on multi-source data, which includes:

[0009] an electronically controlled monitoring module, comprising a wide-area monitoring unit and an attention monitoring unit. The wide-area monitoring unit is configured to acquire monitoring data of a target area and determine a dynamic disturbance index based on basic motion characteristics of moving targets in each sub-target area. The attention monitoring unit is configured to adjust a monitoring direction in response to a determination result of the electronically controlled adjustment module to acquire monitoring data of an attention area and determine a ripple characterization value and a bubble characteristic value of the attention area.

[0010] an electronic control adjustment module connected to the electronic control monitoring module, calculating an abnormal risk value of a sub-target area based on the dynamic disturbance index, and determining a plurality of attention areas to control the attention monitoring unit;

[0011] an electronic control analysis module connected to the electronic control monitoring module, responsive to an activation state of the attention monitoring unit, calculating a drowning characterization coefficient based on the ripple characterization value and the bubble characteristic value, determining a drowning state in the area, and determining whether a warning signal needs to be issued;

[0012] The electronically controlled rescue module is connected to the electronically controlled analysis module and is used to judge whether it is necessary to control the unmanned boat to carry out rescue based on the status of the early warning signal and to determine the rescue method.

[0013] Furthermore, the electronic control monitoring module is used to determine the dynamic disturbance index based on the basic motion characteristics of the moving target in each sub-target area, including:

[0014] To determine the basic motion characteristics of the moving target in the sub-target area, including the moving speed of the moving target center and the contour area of ​​the moving target;

[0015] The absolute variance of the moving speed of the moving target center at each moment is used as the dynamic disturbance index of the moving speed;

[0016] The absolute variance of the moving target contour area at each moment is used as the contour area dynamic disturbance index.

[0017] Furthermore, the electronic control monitoring module determines the ripple characterization value and the bubble characteristic value of the attention area, including:

[0018] Identifying the frequency of ripples within the reference time of the attention area, and determining the frequency as the ripple representation value;

[0019] To determine the difference in contour lengths of consecutive bubbles;

[0020] The variance used to determine the contour length difference is the bubble characteristic value.

[0021] Furthermore, the electronic control adjustment module is used to calculate the abnormal risk value of the sub-target area, including:

[0022] used to determine the ratio of the moving speed dynamic disturbance index to the reference moving speed dynamic disturbance threshold as the first abnormal risk factor;

[0023] The ratio of the contour area dynamic disturbance index to the reference contour area dynamic disturbance threshold is used to determine the second abnormal risk factor;

[0024] The weighted sum of the first abnormal risk factor and the second abnormal risk factor is used to determine the abnormal risk value of the sub-target area.

[0025] Furthermore, the electronically controlled adjustment module is used to divide the attention area, wherein:

[0026] If the abnormal risk value of the sub-target area is greater than the preset abnormal risk threshold, the sub-target area is determined to be an attention area, and the attention monitoring unit needs to be activated;

[0027] If the abnormal risk value of the sub-target area is less than or equal to the preset abnormal risk threshold, it is determined that there is no need to start the attention monitoring unit, and the wide-area monitoring unit continues to be used to monitor the sub-target area.

[0028] Furthermore, the electronic control analysis module calculates the drowning characterization coefficient, including:

[0029] used to determine the ratio of the ripple characterization value to the reference ripple characterization value as a first characterization factor;

[0030] A second characterization factor is used to determine the ratio of the bubble characteristic value to the reference bubble characteristic value;

[0031] The weighted sum of the first characterization factor and the second characterization factor is used to determine the drowning characterization coefficient.

[0032] Furthermore, the electronic control analysis module determines the drowning status of the area and determines whether it is necessary to issue an early warning signal, wherein:

[0033] If the drowning characterization coefficient is greater than the drowning characterization coefficient threshold, it is determined that the drowning state in the area is a drowning state and an early warning signal needs to be issued;

[0034] If the drowning characterization coefficient is less than or equal to the drowning characterization coefficient threshold, it is determined that the drowning state of the area is a non-drowning state, and there is no need to issue a warning signal.

[0035] Furthermore, the electronically controlled rescue module determines whether it is necessary to control the unmanned boat to carry out rescue based on the status of the early warning signal, wherein:

[0036] If the warning signal is in the state of issuing a warning signal, it is necessary to control the unmanned boat to carry out rescue;

[0037] If the warning signal issuance status is that no warning signal is issued, there is no need to control the unmanned boat to carry out rescue, and the warning signal issuance status is continuously obtained.

[0038] Furthermore, the electronically controlled rescue module determines the rescue method, including:

[0039] Used to locate rescue coordinates based on the attention area of ​​the drowning state;

[0040] Used to determine and locate the unmanned boat closest to the rescue coordinates;

[0041] Used to control the unmanned boat to go to the rescue coordinates.

[0042] Furthermore, the electronic control adjustment module is used to determine a number of attention areas, and control the attention monitoring unit to include:

[0043] It is used to adjust the shooting angle of the attention monitoring unit, monitor each of the attention areas one by one for a predetermined period of time, and obtain monitoring data of each attention area.

[0044] Compared with the prior art, the present invention sets up an electronically controlled monitoring module, and its wide-area monitoring unit obtains monitoring data, determines the dynamic disturbance value and the characteristic distribution value, and the attention monitoring unit responds to the judgment result of the electronically controlled adjustment module to determine the ripple characterization value and the bubble characteristic value of the attention area, calculates the abnormal risk value of the sub-target area through the electronically controlled adjustment module, divides the attention area, and determines whether it is necessary to start the attention monitoring unit; through the electronically controlled analysis module, the drowning characterization coefficient is calculated in response to the start-up state of the attention monitoring unit, the drowning state of the area is determined, and it is judged whether it is necessary to issue an early warning signal; the unmanned boat is controlled to carry out rescue through the electronically controlled rescue module, and the rescue method is determined. The present invention can monitor drowning over a large area and quickly deploy unmanned boats while saving computing power, thereby improving the efficiency of drowning monitoring and the efficiency of unmanned boat deployment.

[0045] In particular, by calculating the abnormal risk value of the sub-target area, the attention area is determined, and then the corresponding attention monitoring unit is mobilized. In actual situations, there are few abnormal situations in large-area target areas. Therefore, it is considered to introduce an attention mechanism, and determine the dynamic disturbance index through the basic motion characteristics of the moving target to characterize the abnormal tendency in the sub-target area, and then divide the corresponding sub-target area into attention areas. The dynamic disturbance index of the moving speed and the dynamic disturbance index of the contour area are considered when calculating the dynamic disturbance index. The above two indicators are easy to analyze and can preliminarily characterize whether there is a tendency to drown. For example, in the case of drowning, the moving speed of the moving target is uncontrollable, which is reflected in the moving speed in the monitoring data. The moving speed is highly discrete and relatively disturbed. Under normal circumstances, there are relatively few cases of speed mutations and disturbances. On the other hand, in the case of drowning, the moving target fluctuates in the water, which is reflected in the monitoring data as the target contour area is highly discrete and relatively disturbed. Based on this, the calculated abnormal risk value provides a basis for the subsequent call of the attention monitoring unit. In most cases, a wide-area monitoring unit is used to cover a large target area. When there is an attention area, the attention monitoring unit is quickly called for accurate analysis and positioning, which can ensure the monitoring of a large area, save computing power to achieve drowning monitoring while ensuring reliability, quickly deploy unmanned boats, and improve the efficiency of drowning monitoring and unmanned boat deployment.

[0046] In particular, by determining the ripple characterization value and bubble characteristic value of the attention area, a data basis is provided for calculating the drowning characterization coefficient. In actual situations, when judging the drowning status of the target area, most of the time, human key point detection and behavior analysis are used. However, the non-rigid structure of the human body makes the posture changes diverse, especially in the case of self-occlusion and complex postures, which increases the difficulty of key point detection and behavior judgment, resulting in misjudgment. Based on this, the present invention analyzes the ripples and bubbles in the attention area, calculates the drowning characterization coefficient, and then determines the drowning status of the area, providing a forward data basis for the subsequent control of the unmanned boat to carry out rescue, thereby improving the regional rescue speed and rescue accuracy.

[0047] In particular, by calculating the drowning characterization coefficient, the drowning status of the area can be determined, and then it can be judged whether it is necessary to issue an early warning signal to control the unmanned boat to carry out rescue, so as to ensure the smooth progress of the rescue work and improve the regional rescue speed and accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 This is a schematic structural diagram of an unmanned boat electronic control system based on multi-source data according to an embodiment of the invention;

[0049] Figure 2 A logic block diagram of dividing the attention area by the electronically controlled adjustment module according to an embodiment of the invention;

[0050] Figure 3 This is a logic block diagram for determining the drowning status of an area and judging whether it is necessary to issue an early warning signal according to an embodiment of the invention;

[0051] Figure 4 This is a logic block diagram of an embodiment of the invention for determining whether it is necessary to control an unmanned boat to carry out rescue based on the status of the early warning signal. DETAILED DESCRIPTION

[0052] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are merely used to explain the present invention and are not intended to limit the present invention.

[0053] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0054] It should be noted that, in the description of the present invention, unless otherwise expressly specified or limited, the term "connection" should be understood in a broad sense. For example, it can mean a fixed connection, a detachable connection, or an integral connection; it can mean a mechanical connection or an electrical connection; it can mean a direct connection or an indirect connection through an intermediate medium; it can mean internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0055] See also Figure 1 , Figure 1 The schematic diagram of the structure of the unmanned boat electronic control system based on multi-source data according to an embodiment of the invention is shown in FIG. The unmanned boat electronic control system based on multi-source data according to an embodiment of the invention comprises:

[0056] an electronically controlled monitoring module, comprising a wide-area monitoring unit and an attention monitoring unit. The wide-area monitoring unit is configured to acquire monitoring data of a target area and determine a dynamic disturbance index based on basic motion characteristics of moving targets in each sub-target area. The attention monitoring unit is configured to adjust a monitoring direction in response to a determination result of the electronically controlled adjustment module to acquire monitoring data of an attention area and determine a ripple characterization value and a bubble characteristic value of the attention area.

[0057] an electronic control adjustment module connected to the electronic control monitoring module, calculating an abnormal risk value of a sub-target area based on the dynamic disturbance index, and determining a plurality of attention areas to control the attention monitoring unit;

[0058] an electronic control analysis module connected to the electronic control monitoring module, responsive to an activation state of the attention monitoring unit, calculating a drowning characterization coefficient based on the ripple characterization value and the bubble characteristic value, determining a drowning state in the area, and determining whether a warning signal needs to be issued;

[0059] The electronically controlled rescue module is connected to the electronically controlled analysis module and is used to judge whether it is necessary to control the unmanned boat to carry out rescue based on the status of the early warning signal and to determine the rescue method.

[0060] Specifically, there is no limitation on the specific forms of the electronic control adjustment module, the electronic control analysis module and the electronic control rescue module, which can be composed of logic components or a combination of logic components, and the logic components include field programmable processors, computers or microprocessors in computers.

[0061] Specifically, there is no limitation on the area and division method of the target area and sub-target area. For example, the area of ​​the target area can be the maximum area that can be monitored by the wide-area monitoring unit, and the area of ​​the sub-target area can be 0.1 to 0.2 times the area of ​​the target area. Of course, those skilled in the art can also make adjustments according to actual conditions. It is only necessary to ensure that the target area and sub-target area can be fully monitored. This will not be repeated.

[0062] Specifically, there is no limitation on the specific forms of the wide-area monitoring unit and the attention monitoring unit. For example, it can be a photographic device placed at a high place. Preferably, it can be a combination of a photographic device and a logic component, which can analyze the monitoring data obtained by the photographic device through the logic component. At the same time, the photographic device needs to be able to adjust the monitoring angle, which will not be elaborated here.

[0063] Specifically, there is no limitation on the form of the warning signal and the transmission target. For example, it can be a warning light, a warning bell, or a combination of a warning light and a warning bell. Those skilled in the art can choose according to actual conditions. It only needs to ensure that it can have a warning effect. The transmission target can be only the system's electronic control module. The auxiliary module can be called via the warning signal to synchronously call medical personnel. This will not be repeated.

[0064] Specifically, the electronic control monitoring module is used to determine the dynamic disturbance index based on the basic motion characteristics of the moving target in each sub-target area, including:

[0065] To determine the basic motion characteristics of the moving target in the sub-target area, including the moving speed of the moving target center and the contour area of ​​the moving target;

[0066] The absolute variance of the moving speed of the moving target center at each moment is used as the dynamic disturbance index of the moving speed;

[0067] The absolute variance of the moving target contour area at each moment is used as the contour area dynamic disturbance index.

[0068] Specifically, there is no limitation on the method of determining the moving target. For example, an image segmentation algorithm can be used to identify the target outline, and the moving target outline can be determined as the moving target. Then, the moving speed of the moving target center and the area of ​​the moving target outline can be determined. This will not be repeated here.

[0069] Specifically, the electronic control monitoring module determines the ripple characterization value and the bubble characteristic value of the attention area, including:

[0070] To identify the frequency of ripples within the reference time of the attention area, and determine the frequency as the ripple characterization value, with the reference time being 1s;

[0071] To determine the difference in contour lengths of consecutive bubbles;

[0072] The variance used to determine the contour length difference is the bubble characteristic value.

[0073] Specifically, in implementation, continuous bubbles are bubbles that appear on the water surface successively in the same area, and the difference in contour lengths of the bubbles that appear successively can be calculated, which will not be repeated here.

[0074] There is no limitation on the method of identifying ripples and bubbles. An image processing model or algorithm that can identify the corresponding features can be pre-trained, and logical components can be imported to implement the corresponding functions. This will not be repeated here.

[0075] Specifically, by determining the ripple characterization value and bubble characteristic value of the attention area, a data basis is provided for calculating the drowning characterization coefficient. In actual situations, when judging the drowning status of the target area, most of the time, human key point detection and behavior analysis are used. However, the non-rigid structure of the human body makes the posture changes diverse, especially in the case of self-occlusion and complex postures, which increases the difficulty of key point detection and behavior judgment, resulting in errors in judgment. Based on this, the present invention analyzes the ripples and bubbles in the attention area, calculates the drowning characterization coefficient, and then determines the drowning status of the area, providing a forward data basis for the subsequent control of the unmanned boat to carry out rescue, thereby improving the regional rescue speed and rescue accuracy.

[0076] Specifically, the electronic control adjustment module is used to calculate the abnormal risk value of the sub-target area, including:

[0077] used to determine the ratio of the moving speed dynamic disturbance index to the reference moving speed dynamic disturbance threshold as the first abnormal risk factor;

[0078] The ratio of the contour area dynamic disturbance index to the reference contour area dynamic disturbance threshold is used to determine the second abnormal risk factor;

[0079] The weighted sum of the first abnormal risk factor and the second abnormal risk factor is used to determine the abnormal risk value of the sub-target area.

[0080] Specifically, the benchmark moving speed dynamic disturbance threshold is calculated in advance, wherein the moving speed dynamic disturbance indicators of several moving targets without abnormalities are obtained in advance, the average of the moving speed dynamic disturbance indicators is determined, and the benchmark moving speed dynamic disturbance threshold is set to be selected between 1.15 times and 1.3 times the average of the moving speed dynamic disturbance indicators.

[0081] Specifically, the baseline contour area dynamic disturbance threshold is calculated in advance, wherein the contour area dynamic disturbance indicators of several moving targets without abnormalities are obtained in advance, the average value of the contour area dynamic disturbance indicator is determined, and the baseline contour area dynamic disturbance threshold is set between 1.25 times and 1.5 times the average value of the contour area dynamic disturbance indicator.

[0082] Specifically, the sum of the weight coefficients of the first abnormal risk factor and the second abnormal risk factor is 1, the weight coefficient of the first abnormal risk factor is 0.57, and the weight coefficient of the second abnormal risk factor is 0.43.

[0083] See also Figure 2 , Figure 2 This is a logic block diagram of the electronically controlled adjustment module for dividing the attention area according to an embodiment of the invention. Specifically, the electronically controlled adjustment module is used to divide the attention area, wherein:

[0084] If the abnormal risk value of the sub-target area is greater than the preset abnormal risk threshold, the sub-target area is determined to be an attention area, and the attention monitoring unit needs to be activated;

[0085] If the abnormal risk value of the sub-target area is less than or equal to the preset abnormal risk threshold, it is determined that there is no need to start the attention monitoring unit, and the wide-area monitoring unit continues to be used to monitor the sub-target area.

[0086] Specifically, the preset abnormal risk threshold is selected within the interval [0.65, 0.85].

[0087] Specifically, when the attention monitoring unit is in an inactive state, the target area is continuously monitored based on the monitoring data of the wide-area monitoring unit.

[0088] Specifically, by calculating the abnormal risk value of the sub-target area, the attention area is determined, and then the corresponding attention monitoring unit is mobilized. In actual situations, there are only a few abnormal situations in large target areas. Therefore, it is considered to introduce an attention mechanism, and determine the dynamic disturbance index through the basic motion characteristics of the moving target to characterize the abnormal tendency in the sub-target area, and then divide the corresponding sub-target area into attention areas. The dynamic disturbance index of the moving speed and the dynamic disturbance index of the contour area are considered when calculating the dynamic disturbance index. The above two indicators are easy to analyze and can preliminarily characterize whether there is a tendency to drown. For example, in the case of drowning, the moving speed of the moving target is uncontrollable, which is reflected in the monitoring data. The moving speed is highly discrete and relatively disturbed. Under normal circumstances, there are few cases of speed mutations and disturbances. On the other hand, in the case of drowning, the moving target fluctuates in the water, which is reflected in the monitoring data as the target contour area is highly discrete and relatively disturbed. Based on this, the calculation of the abnormal risk value provides a basis for the subsequent call of the attention monitoring unit. In most cases, a wide-area monitoring unit is used to cover a large target area. When there is an attention area, the attention monitoring unit is quickly called for precise analysis and positioning, which can ensure the monitoring of a large area, save computing power to achieve drowning monitoring while ensuring reliability, quickly deploy unmanned boats, and improve the efficiency of drowning monitoring and unmanned boat deployment.

[0089] Specifically, the electronic control analysis module calculates the drowning characterization coefficient, including:

[0090] used to determine the ratio of the ripple characterization value to the reference ripple characterization value as a first characterization factor;

[0091] A second characterization factor is used to determine the ratio of the bubble characteristic value to the reference bubble characteristic value;

[0092] The weighted sum of the first characterization factor and the second characterization factor is used to determine the drowning characterization coefficient.

[0093] Specifically, the baseline bubble characteristic value is calculated in advance, and image data of the sub-target area in several cycles when drowning does not occur is obtained in advance, the bubble characteristic value in each cycle is determined, the mean of the bubble characteristic value is solved, and the baseline bubble characteristic value is set between 1.15 times and 1.35 times the mean.

[0094] The baseline ripple characterization value is calculated in advance. Image data of several cycles of the sub-target area when drowning does not occur is obtained in advance, the ripple characterization value in each cycle is determined, the mean of the ripple characterization value is solved, and the baseline ripple characterization value is set between 1.15 times and 1.35 times the mean.

[0095] Specifically, the sum of the weight coefficients of the first characterization factor and the second characterization factor is 1, the weight coefficient of the first characterization factor is 0.51, and the weight coefficient of the second characterization factor is 0.49.

[0096] See also Figure 3 , Figure 3 This is a logic block diagram of an embodiment of the invention for determining the drowning status of an area and judging whether a warning signal needs to be issued. Specifically, the electronic control analysis module determines the drowning status of an area and judges whether a warning signal needs to be issued, wherein:

[0097] If the drowning characterization coefficient is greater than the drowning characterization coefficient threshold, it is determined that the drowning state in the area is a drowning state and an early warning signal needs to be issued;

[0098] If the drowning characterization coefficient is less than or equal to the drowning characterization coefficient threshold, it is determined that the drowning state of the area is a non-drowning state, and there is no need to issue a warning signal.

[0099] Specifically, the drowning characterization coefficient threshold represents the lowest value when drowning occurs in the target area, so the drowning characterization coefficient threshold is set to be selected within the interval [1.25, 1.65].

[0100] See also Figure 4 , Figure 4 This is a logic block diagram of an embodiment of the invention for judging whether it is necessary to control an unmanned boat for rescue based on the status of the warning signal. Specifically, the electronically controlled rescue module judges whether it is necessary to control an unmanned boat for rescue based on the status of the warning signal, wherein:

[0101] If the warning signal is in the state of issuing a warning signal, it is necessary to control the unmanned boat to carry out rescue;

[0102] If the warning signal issuance status is that no warning signal is issued, there is no need to control the unmanned boat to carry out rescue, and the warning signal issuance status is continuously obtained.

[0103] Specifically, the electronically controlled rescue module determines the rescue method, including:

[0104] Used to locate rescue coordinates based on the attention area of ​​the drowning state;

[0105] Used to determine and locate the unmanned boat closest to the rescue coordinates;

[0106] Used to control the unmanned boat to go to the rescue coordinates.

[0107] Specifically, there is no limitation on the control method of the unmanned boat. The unmanned boat can be equipped with a navigation control system and a GPS positioning device, and move to the corresponding position based on the rescue coordinates. Those skilled in the art can adopt the existing unmanned boat navigation control system, and it is only necessary to enable the unmanned boat to move to the target position based on the predetermined rescue coordinates. This will not be repeated.

[0108] Specifically, the electronic control adjustment module is used to determine a number of attention areas, and control the attention monitoring unit to include:

[0109] It is used to adjust the shooting angle of the attention monitoring unit, monitor each of the attention areas one by one for a predetermined period of time, and obtain monitoring data of each attention area.

[0110] The scheduled duration is selected within the interval [3s, 5s].

[0111] Specifically, by calculating the drowning characterization coefficient, the drowning status of the area is determined, and then it is judged whether it is necessary to issue an early warning signal to control the unmanned boat to carry out rescue, so as to ensure the smooth progress of the rescue work and improve the regional rescue speed and accuracy.

[0112] Thus far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art may make equivalent changes or substitutions to the relevant technical features, and the technical solutions after such changes or substitutions will fall within the scope of protection of the present invention.

[0113] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that the present invention is susceptible to various modifications and variations. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. An unmanned boat electronic control system based on multi-source data, characterized in that: include: an electronically controlled monitoring module, comprising a wide-area monitoring unit and an attention monitoring unit. The wide-area monitoring unit is configured to acquire monitoring data of a target area and determine a dynamic disturbance index based on basic motion characteristics of moving targets in each sub-target area. The attention monitoring unit is configured to adjust a monitoring direction in response to a determination result of the electronically controlled adjustment module to acquire monitoring data of an attention area and determine a ripple characterization value and a bubble characteristic value of the attention area. an electronic control adjustment module connected to the electronic control monitoring module, calculating an abnormal risk value of a sub-target area based on the dynamic disturbance index, and determining a plurality of attention areas to control the attention monitoring unit; an electronic control analysis module connected to the electronic control monitoring module, responsive to an activation state of the attention monitoring unit, calculating a drowning characterization coefficient based on the ripple characterization value and the bubble characteristic value, determining a drowning state in the area, and determining whether a warning signal needs to be issued; An electronically controlled rescue module, connected to the electronically controlled analysis module, is used to determine whether it is necessary to control the unmanned boat to carry out rescue based on the status of the early warning signal and to determine the rescue method; The electronic control monitoring module determines the ripple characterization value and the bubble characteristic value of the attention area, include, Identifying the frequency of ripples within the reference time of the attention area, and determining the frequency as the ripple representation value; To determine the difference in contour lengths of consecutive bubbles; The variance of the contour length difference is used to determine the bubble characteristic value; The electronic control adjustment module is used to divide the attention area, wherein: If the abnormal risk value of the sub-target area is greater than the preset abnormal risk threshold, the sub-target area is determined to be an attention area, and the attention monitoring unit needs to be activated; If the abnormal risk value of the sub-target area is less than or equal to the preset abnormal risk threshold, it is determined that there is no need to start the attention monitoring unit, and the wide-area monitoring unit continues to be used to monitor the sub-target area.

2. The unmanned boat electronic control system based on multi-source data according to claim 1 is characterized in that: The electronic control monitoring module is used to determine the dynamic disturbance index based on the basic motion characteristics of the moving target in each sub-target area, including: To determine the basic motion characteristics of the moving target in the sub-target area, including the moving speed of the moving target center and the contour area of ​​the moving target; The absolute variance of the moving speed of the moving target center at each moment is used as the dynamic disturbance index of the moving speed; The absolute variance of the moving target contour area at each moment is used as the contour area dynamic disturbance index.

3. The unmanned boat electronic control system based on multi-source data according to claim 2 is characterized in that: The electronic control adjustment module is used to calculate the abnormal risk value of the sub-target area, including: used to determine the ratio of the moving speed dynamic disturbance index to the reference moving speed dynamic disturbance threshold as the first abnormal risk factor; The ratio of the contour area dynamic disturbance index to the reference contour area dynamic disturbance threshold is used to determine the second abnormal risk factor; The weighted sum of the first abnormal risk factor and the second abnormal risk factor is used to determine the abnormal risk value of the sub-target area.

4. The unmanned boat electronic control system based on multi-source data according to claim 1, characterized in that: The electronic control analysis module calculates the drowning characterization coefficient, including: used to determine the ratio of the ripple characterization value to the reference ripple characterization value as a first characterization factor; A second characterization factor is used to determine the ratio of the bubble characteristic value to the reference bubble characteristic value; The weighted sum of the first characterization factor and the second characterization factor is used to determine the drowning characterization coefficient.

5. The unmanned boat electronic control system based on multi-source data according to claim 1 is characterized in that: The electronic control analysis module determines the drowning status of the area and determines whether an early warning signal needs to be issued, wherein: If the drowning characterization coefficient is greater than the drowning characterization coefficient threshold, it is determined that the drowning state in the area is a drowning state and an early warning signal needs to be issued; If the drowning characterization coefficient is less than or equal to the drowning characterization coefficient threshold, it is determined that the drowning state of the area is a non-drowning state, and there is no need to issue a warning signal.

6. The unmanned boat electronic control system based on multi-source data according to claim 1 is characterized in that: The electronically controlled rescue module determines whether it is necessary to control the unmanned boat to carry out rescue based on the status of the warning signal, wherein: If the warning signal is in the state of issuing a warning signal, it is necessary to control the unmanned boat to carry out rescue; If the warning signal issuance status is that no warning signal is issued, there is no need to control the unmanned boat to carry out rescue, and the warning signal issuance status is continuously obtained.

7. The unmanned boat electronic control system based on multi-source data according to claim 1 is characterized in that: The electronically controlled rescue module determines the rescue method, including: Used to locate rescue coordinates based on the attention area of ​​the drowning state; Used to determine and locate the unmanned boat closest to the rescue coordinates; Used to control the unmanned boat to go to the rescue coordinates.

8. The unmanned boat electronic control system based on multi-source data according to claim 1 is characterized in that: The electronic control adjustment module is used to determine a number of attention areas, and control the attention monitoring unit to include: It is used to adjust the shooting angle of the attention monitoring unit, monitor each of the attention areas one by one for a predetermined period of time, and obtain monitoring data of each attention area.

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