Marine satellite IoT monitoring method, system and storage medium based on cloud-edge-end collaboration

Abstract

The present invention relates to the field of ocean monitoring and analysis technology, and provides an ocean satellite IoT monitoring method, system and storage medium based on cloud-edge-end collaboration, including: obtaining ocean environmental parameters through an ocean environmental parameter monitoring model in a preset terminal layer and obtaining ocean meteorological parameters through an ocean meteorological parameter monitoring model; sending ocean environmental parameters and ocean meteorological parameters to a cloud layer through an IoT sensor and a satellite communication model in an edge layer; analyzing ocean environmental parameters through an environmental state analysis model in a cloud layer to generate an environmental state change coefficient, and analyzing ocean meteorological parameters through a meteorological state analysis model in a cloud layer to generate a meteorological state change coefficient; performing a comprehensive analysis based on the environmental state change coefficient and the meteorological state change coefficient through an environmental meteorological trend analysis model in a cloud layer, generating an environmental meteorological state and storing it in a cloud database. The present invention solves the problems of poor timeliness and inaccurate monitoring results of existing ocean environmental monitoring.

Description

Technical Field

[0001] The present invention relates to the field of ocean monitoring and analysis technology, and in particular to an ocean satellite Internet of Things monitoring method, system and storage medium based on cloud-edge-end collaboration. Background Art

[0002] The Ocean Satellite Internet of Things System is a comprehensive system that integrates satellite communications, Internet of Things (IoT) technology and ocean monitoring equipment; the system is designed to achieve real-time monitoring, data transmission and intelligent analysis of the global ocean environment to support applications such as marine scientific research, resource management, disaster warning and marine environmental protection.

[0003] In order to more accurately understand the environmental status of ocean waters, it is necessary to monitor multiple parameter information in ocean waters and then send the monitored parameter information to the processing terminal for further analysis. However, due to geographical restrictions, parameter information of different waters in the ocean cannot be collected in real time, and the timeliness of parameter information is poor, which results in inaccurate data provided for marine operations, navigation safety, disaster warning and scientific research. Summary of the invention

[0004] The present invention provides a marine satellite Internet of Things monitoring method, system and storage medium based on cloud-edge-end collaboration, which are used to solve the problems of poor timeliness and inaccurate monitoring results of existing marine environment monitoring.

[0005] The present invention provides a marine satellite IoT monitoring method based on cloud-edge-end collaboration, comprising:

[0006] Obtaining ocean environmental parameters through an ocean environmental parameter monitoring model in a preset terminal layer and obtaining ocean meteorological parameters through an ocean meteorological parameter monitoring model;

[0007] The ocean environment parameters and ocean meteorological parameters are sent to the cloud layer through the Internet of Things sensors and satellite communication models of the preset edge layer;

[0008] The ocean environment parameters are analyzed by the environmental state analysis model of the cloud layer to generate an environmental state change coefficient, and the ocean meteorological parameters are analyzed by the meteorological state analysis model of the cloud layer to generate a meteorological state change coefficient;

[0009] Based on the environmental state change coefficient and the meteorological state change coefficient, a comprehensive analysis is performed through the environmental meteorological trend analysis model of the cloud layer to generate the environmental meteorological state and store it in the cloud database.

[0010] According to a marine satellite IoT monitoring method based on cloud-edge-end collaboration provided by the present invention, the marine environment parameters are obtained through a marine environment parameter monitoring model preset in a terminal layer and the marine meteorological parameters are obtained through a marine meteorological parameter monitoring model, specifically including:

[0011] The environmental parameters of each monitoring period in each monitoring water area of ​​the ocean are monitored in real time through the marine environmental parameter monitoring model, and the environmental parameters of each monitoring period in each monitoring water area of ​​the ocean are obtained, wherein the environmental parameters include water body temperature, water body salinity and water body pH;

[0012] The marine meteorological parameter monitoring model is used to monitor the meteorological parameters in each monitoring period in each monitoring water area of ​​the ocean in real time, and obtain the meteorological parameters in each monitoring period in each monitoring water area of ​​the ocean, wherein the meteorological parameters include wind direction and wind speed in the water area.

[0013] According to a marine satellite IoT monitoring method based on cloud-edge-end collaboration provided by the present invention, the marine meteorological parameter monitoring model is used to monitor the meteorological parameters in each monitoring period in each monitoring water area of ​​the ocean in real time to obtain the meteorological parameters in each monitoring period in each monitoring water area of ​​the ocean, specifically including:

[0014] The wind speed sensor is used to monitor the wind speed of the water area at each monitoring time point in each monitoring cycle in the monitoring water area in real time, and the wind speed of the water area in each monitoring cycle in the ocean corresponding to each monitoring water area is obtained;

[0015] The wind direction of the water area at each monitoring time point in each monitoring period in the monitoring water area is monitored in real time by means of a wind direction sensor, and the wind direction of the water area in each monitoring period in the corresponding monitoring water area of ​​the ocean is obtained;

[0016] The wind speed sensor and the wind direction sensor are installed on buoy platforms in each monitoring water area.

[0017] According to a marine satellite IoT monitoring method based on cloud-edge-end collaboration provided by the present invention, the ocean environmental parameters are analyzed by the environmental state analysis model of the cloud layer to generate an environmental state change coefficient, specifically including:

[0018] The environmental status analysis model of the cloud layer is used to calculate the number of monitoring time points in each monitoring period in each monitoring water area of ​​the ocean. The water temperature, salinity and pH value of each monitoring time point in each monitoring period in each monitoring water area of ​​the ocean are summed up and divided by the number of monitoring time points to obtain the average water temperature, salinity and pH value of each monitoring period in each monitoring water area of ​​the ocean.

[0019] Based on the average water temperature, average water salinity and average water pH, the standard deviation of water temperature, water salinity and water pH in each monitoring period in each monitoring water area of ​​the ocean is obtained through the standard deviation calculation formula.

[0020] The coefficient of change of water temperature, water salinity and water pH in each monitoring period in each monitoring water area corresponding to the ocean is calculated by comparing the standard deviation of water temperature, water salinity and water pH in each monitoring period in each monitoring water area corresponding to the ocean with the average water temperature, average water salinity and average water pH in each monitoring period in each monitoring water area corresponding to the ocean and multiplying them by percentage;

[0021] The environmental state variation coefficient of each monitoring water area in the ocean during each monitoring period is composed of the water temperature variation coefficient, water salinity variation coefficient and water pH variation coefficient in each monitoring water area in the ocean during each monitoring period.

[0022] According to a marine satellite IoT monitoring method based on cloud-edge-end collaboration provided by the present invention, the marine meteorological parameters are analyzed by a meteorological state analysis model at the cloud layer to generate a meteorological state change coefficient, specifically including:

[0023] Substitute the water area wind speed at each monitoring time point in each monitoring period in each monitoring water area of ​​the ocean and the average water area wind speed at each monitoring time point in each monitoring period in each monitoring water area of ​​the ocean into the standard deviation calculation formula for calculation, and obtain the water area wind speed standard deviation in each monitoring period in each monitoring water area of ​​the ocean;

[0024] Extract the water area wind speed at each monitoring time point in each monitoring period in each monitoring water area corresponding to the ocean from the meteorological parameters in each monitoring period in each monitoring water area corresponding to the ocean, obtain the water area wind speed at each monitoring time point in each monitoring period in each monitoring water area corresponding to the ocean, sum the water area wind speed at each monitoring time point in each monitoring period in each monitoring water area corresponding to the ocean and divide the sum by the number of each monitoring time point to obtain the average water area wind speed in each monitoring period in each monitoring water area corresponding to the ocean;

[0025] The water wind speed variation coefficient of each monitoring period in each monitoring water area corresponding to the ocean is calculated by comparing the standard deviation of the water wind speed in each monitoring period in each monitoring water area corresponding to the ocean with the average water wind speed in each monitoring period in each monitoring water area corresponding to the ocean and multiplying the result by percentage. At the same time, the number of water wind direction changes in each monitoring period in each monitoring water area corresponding to the ocean is multiplied by the percentage to obtain the water wind direction variation coefficient of each monitoring period in each monitoring water area corresponding to the ocean.

[0026] The meteorological state variation coefficient of each monitoring water area in the ocean corresponding to each monitoring period is composed of the water area wind speed variation coefficient of each monitoring water area in the ocean corresponding to each monitoring period and the water area wind direction variation coefficient of each monitoring water area in the ocean corresponding to each monitoring period.

[0027] According to a marine satellite IoT monitoring method based on cloud-edge-end collaboration provided by the present invention, the environmental state change coefficient and the meteorological state change coefficient are comprehensively analyzed through the environmental meteorological trend analysis model of the cloud layer, and the environmental meteorological state is generated and stored in the cloud database, specifically including:

[0028] Compare the change differences corresponding to the water temperature change coefficient, water salinity change coefficient, water pH change coefficient, water wind speed change coefficient and water wind direction change coefficient in each monitoring water area corresponding to the ocean in each monitoring period with the corresponding preset change thresholds to obtain the water salinity status, water pH status, water wind speed status and water wind direction change status in each monitoring water area corresponding to the ocean in each monitoring period;

[0029] Combine the water temperature state, water salinity state, water pH state, water wind speed state and water wind direction change state in the monitoring water area corresponding to the ocean during the monitoring period to construct the environmental meteorological state in each monitoring period of each monitoring water area corresponding to the ocean, and save the environmental meteorological state in the cloud database;

[0030] Among them, if the difference between the maximum and minimum values ​​of the change differences corresponding to the water temperature change coefficient, the water salinity change coefficient, the water pH change coefficient, the water area wind speed change coefficient and the water area wind direction change coefficient is greater than the preset change threshold, then the water environment state in the ocean corresponding to the monitored water area during the monitoring period is abnormal.

[0031] The present invention also provides a marine satellite IoT monitoring system based on cloud-edge-end collaboration, the system comprising:

[0032] A data acquisition module, used to acquire ocean environmental parameters through an ocean environmental parameter monitoring model in a preset terminal layer and to acquire ocean meteorological parameters through an ocean meteorological parameter monitoring model;

[0033] A data transmission module, used for sending the ocean environment parameters and ocean meteorological parameters to the cloud layer through the Internet of Things sensors and satellite communication models of the preset edge layer;

[0034] A data analysis module, used to analyze the ocean environmental parameters through the environmental state analysis model of the cloud layer to generate an environmental state change coefficient, and to analyze the ocean meteorological parameters through the meteorological state analysis model of the cloud layer to generate a meteorological state change coefficient;

[0035] The result generation module is used to perform a comprehensive analysis based on the environmental state change coefficient and the meteorological state change coefficient through the environmental meteorological trend analysis model of the cloud layer, generate the environmental meteorological state and store it in the cloud database.

[0036] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements any of the above-mentioned methods for monitoring ocean satellite Internet of Things based on cloud-edge-end collaboration.

[0037] The present invention also provides a non-transitory computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, it implements any of the above-mentioned ocean satellite Internet of Things monitoring methods based on cloud-edge-end collaboration.

[0038] The present invention also provides a computer program product, including a computer program, which, when executed by a processor, implements any of the above-mentioned ocean satellite Internet of Things monitoring methods based on cloud-edge-end collaboration.

[0039] The present invention provides an ocean satellite Internet of Things monitoring method, system and storage medium based on cloud-edge-end collaboration. By collecting various environmental parameters and meteorological parameters and performing analysis and calculation, the water temperature variation coefficient, the water salinity variation coefficient and the water pH variation coefficient are obtained, and the environmental status of each monitored water area corresponding to the ocean is comprehensively evaluated. At the same time, according to the water area wind speed variation coefficient and the water area wind direction variation coefficient, natural disasters such as storms and hurricanes are warned. The meteorological status of various aspects such as wave conditions, sea surface temperature, climate patterns, marine ecosystems and fishery resources can be understood, providing reliable scientific data support for marine operations, navigation safety, disaster warning and scientific research. Through comprehensive analysis, the environmental meteorological status of the monitored water area is evaluated from multiple angles, and possible environmental meteorological problems are determined according to specific change differences. At the same time, the dynamic change process of the marine ecosystem can be understood, providing important data support for marine environmental protection and management. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0041] Figure 1 It is a flow chart of the ocean satellite Internet of Things monitoring method based on cloud-edge-end collaboration provided by the present invention.

[0042] Figure 2It is a principle block diagram of the ocean satellite Internet of Things system based on cloud-edge-end collaboration provided by the present invention.

[0043] Figure 3 It is a principle block diagram of the terminal layer, edge layer and cloud layer provided by the present invention.

[0044] Figure 4 It is a line graph of the environmental meteorological status assessment diagram within the first five monitoring periods provided by the present invention.

[0045] Figure 5 This is a module connection diagram of the ocean satellite Internet of Things monitoring system based on cloud-edge-end collaboration provided by the present invention.

[0046] Figure 6 It is a structural schematic diagram of the electronic device provided by the present invention.

[0047] Reference numerals:

[0048] 110: data acquisition module; 120: data transmission module; 130: data analysis module; 140: result generation module;

[0049] 610: processor; 620: communication interface; 630: memory; 640: communication bus. DETAILED DESCRIPTION

[0050] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0051] Combine the following Figure 1 The present invention describes an ocean satellite Internet of Things monitoring method based on cloud-edge-end collaboration, including: step 100, obtaining ocean environmental parameters through an ocean environmental parameter monitoring model in a preset terminal layer and obtaining ocean meteorological parameters through an ocean meteorological parameter monitoring model.

[0052] In the present invention, please refer to Figure 2 and Figure 3 As shown, the terminal layer includes a marine environmental parameter monitoring model and a marine meteorological parameter monitoring model, the edge layer includes an Internet of Things sensor network model and a satellite communication model, and the cloud layer includes an environmental status analysis model, a meteorological status analysis model, an environmental meteorological trend analysis model and a cloud database.

[0053] The marine environmental parameter monitoring model is used to monitor the environmental parameters of each monitoring water area in the ocean in real time during each monitoring period, and obtain the environmental parameters of each monitoring water area in the ocean in each monitoring period, wherein the environmental parameters include water body temperature, water body salinity and water body pH;

[0054] The marine meteorological parameter monitoring model is used to monitor the meteorological parameters of each monitoring period in each monitoring water area of ​​the ocean in real time, and obtain the meteorological parameters of each monitoring period in each monitoring water area of ​​the ocean, wherein the meteorological parameters include the wind direction and wind speed of the water area;

[0055] The environmental state analysis model is used to analyze the state of environmental parameters in each monitoring period in each monitoring water area of ​​the ocean, and obtain the environmental state change coefficient in each monitoring period in each monitoring water area of ​​the ocean;

[0056] The meteorological state analysis model is used to analyze the state of meteorological parameters in each monitoring period in each monitoring water area corresponding to the ocean, and obtain the meteorological state change coefficient in each monitoring period in each monitoring water area corresponding to the ocean;

[0057] The environmental meteorological trend analysis model is used to comprehensively analyze the environmental state change coefficient and meteorological state change coefficient in each monitoring period in each monitoring water area of ​​the ocean, and obtain the environmental meteorological state in each monitoring period in each monitoring water area of ​​the ocean;

[0058] The cloud database is used to classify and store the monitoring data of each monitoring time point in each monitoring period in each monitoring water area of ​​the ocean.

[0059] In the present invention, the ocean performs real-time monitoring of environmental parameters in each monitoring period in each monitoring water area as follows:

[0060] A buoy platform is installed in each monitoring water area corresponding to the ocean, and a CTD instrument, a pH monitoring instrument and a lifting water sample collection device are installed on the buoy platform. Water samples at different heights in the monitoring water area are collected at several monitoring time points within a monitoring cycle through the lifting water sample collection device, and the collected water samples are respectively sent to the CTD instrument and the pH monitoring instrument for measurement to obtain the water temperature, water conductivity and water depth at each monitoring time point in each monitoring cycle in each monitoring water area corresponding to the ocean. The water conductivity in each monitoring cycle in each monitoring water area corresponding to the ocean is calculated using a salinity calculation formula based on conductivity to obtain the water salinity at each monitoring time point in each monitoring cycle in each monitoring water area corresponding to the ocean. The pH of the water in each monitoring cycle in the monitoring water area is measured by the pH monitoring instrument to obtain the pH of the water at each monitoring time point in each monitoring cycle in the monitoring water area corresponding to the ocean.

[0061] The marine meteorological parameter monitoring model is used to monitor the meteorological parameters in each monitoring period in each monitoring water area of ​​the ocean in real time, and obtain the meteorological parameters in each monitoring period in each monitoring water area of ​​the ocean, wherein the meteorological parameters include the wind direction and wind speed in the water area.

[0062] Specifically, the method of real-time monitoring of meteorological parameters in each monitoring period in each monitoring water area of ​​the ocean is as follows:

[0063] By installing wind speed sensors on buoy platforms in the ocean corresponding to each monitoring water area, the wind speed of the water area at each monitoring time point in each monitoring cycle in the monitoring water area is monitored in real time, and the wind speed of the water area in each monitoring cycle in the ocean corresponding to each monitoring water area is obtained;

[0064] By installing wind direction sensors on buoy platforms in the corresponding monitoring waters of the ocean, the wind direction of the waters at each monitoring time point in each monitoring cycle in the monitoring waters is monitored in real time to obtain the wind direction of the waters in each monitoring cycle in the corresponding monitoring waters of the ocean.

[0065] In a specific embodiment, the present invention performs real-time monitoring and collection of data on environmental parameters and meteorological parameters at each monitoring time point in each monitoring period in each monitoring water area of ​​the ocean, thereby providing a more comprehensive understanding of the changing trends and laws of the marine environment, providing strong scientific data support for marine scientific research, resource management and environmental protection, while also providing a reliable scientific basis for marine activities to ensure the safety of ongoing marine activities.

[0066] By real-time monitoring and collecting data on environmental parameters and meteorological parameters at each monitoring time point in each monitoring period in each monitoring water area of ​​the ocean, we can have a more comprehensive understanding of the changing trends and patterns of the marine environment, provide strong scientific data support for marine scientific research, resource management and environmental protection, and also provide a reliable scientific basis for marine activities to ensure the safety of ongoing marine activities.

[0067] Step 200: Send the ocean environment parameters and ocean meteorological parameters to the cloud layer through the preset edge layer Internet of Things sensors and satellite communication models.

[0068] In the present invention, several terminal layers are distributed in the ocean waters, and all of the terminal layers are connected to the cloud layer through the edge layer. The Internet of Things sensors and satellite communication models in the edge layer transmit data, so that the collected data can be transmitted to the cloud layer in real time for calculation and analysis.

[0069] Step 300: Analyze the ocean environmental parameters through the environmental state analysis model of the cloud layer to generate an environmental state variation coefficient, and analyze the ocean meteorological parameters through the meteorological state analysis model of the cloud layer to generate a meteorological state variation coefficient.

[0070] In the present invention, the environmental state analysis model is used to perform state analysis on the environmental parameters in each monitoring period in each monitoring water area corresponding to the ocean, and obtain the environmental state change coefficient in each monitoring period in each monitoring water area corresponding to the ocean. The specific analysis method is as follows:

[0071] The water temperature, salinity and pH value of each monitoring time point in each monitoring period in each monitoring water area of ​​the ocean are extracted from the environmental parameters in each monitoring period in each monitoring water area of ​​the ocean, and the water temperature, salinity and pH value of each monitoring time point in each monitoring period in each monitoring water area of ​​the ocean are obtained, which are recorded as WT i，j k , WY i，j k and WS i，j k , i represents the number of each monitoring water area, i=1,2,...,n, n represents the total number of numbers of each monitoring water area, j represents the number of each monitoring period, j=1,2,...,m, m represents the total number of numbers of each monitoring period, k represents the number of each monitoring time point, k=1,2,...,g, g represents the total number of numbers of each monitoring time point; specifically, the monitoring water areas in the ocean are numbered, i.e., monitoring water area No. 1, monitoring water area No. 2,..., monitoring water area No. n, and at the same time, each monitoring period in each monitoring water area is numbered from the beginning to the end, i.e., monitoring period No. 1, monitoring period No. 2,..., monitoring water area No. m, and then each monitoring time point in each monitoring period is numbered from the beginning to the end, i.e., monitoring time point No. 1, monitoring time point No. 2,..., monitoring time point No. g. For example, the water temperature at the 8th monitoring time point in the 3rd monitoring period in the No. 6 monitoring water area of ​​the ocean is WT 6，3 8.

[0072] Obtain the number of monitoring time points in each monitoring period in each monitoring water area corresponding to the ocean, recorded as N, sum the water temperature, water salinity and water pH at each monitoring time point in each monitoring period in each monitoring water area corresponding to the ocean, and divide by the number of monitoring time points to obtain the average water temperature, average water salinity and average water pH in each monitoring period in each monitoring water area corresponding to the ocean, recorded as , and ;

[0073] Substitute the water temperature, salinity and pH value of each monitoring time point in each monitoring period in each monitoring water area corresponding to the ocean and the average water temperature, salinity and pH value of each monitoring period in each monitoring water area corresponding to the ocean into the standard deviation calculation formula for calculation, and obtain the standard deviation of water temperature, salinity and pH value of each monitoring period in each monitoring water area corresponding to the ocean, which is recorded as and The specific calculation method is as follows: Substitute the water temperature at each monitoring time point in each monitoring period in each monitoring water area of ​​the ocean, the average water temperature at each monitoring time point in each monitoring period in each monitoring water area of ​​the ocean, and the number of each monitoring time point into the formula The standard deviation of water temperature in each monitoring period in each monitoring water area of ​​the ocean is calculated. The same formula and calculation method are used to obtain the standard deviation of water salinity in each monitoring period in each monitoring water area of ​​the ocean. and standard deviation of water pH .

[0074] The coefficient of change of water temperature, water salinity and water pH in each monitoring period in each monitoring water area corresponding to the ocean is calculated by comparing the standard deviation of water temperature, water salinity and water pH in each monitoring period in each monitoring water area corresponding to the ocean with the average water temperature, average water salinity and average water pH in each monitoring period in each monitoring water area corresponding to the ocean and multiplying them by percentage;

[0075] The environmental state variation coefficient of each monitoring water area in the ocean during each monitoring period is composed of the water temperature variation coefficient, water salinity variation coefficient and water pH variation coefficient in each monitoring water area in the ocean during each monitoring period.

[0076] In a specific embodiment, the present invention simultaneously processes and analyzes the data of water temperature, water salinity and water pH at each monitoring time point in each monitoring period in each monitoring water area corresponding to the ocean, and obtains the water temperature variation coefficient, water salinity variation coefficient and water pH variation coefficient in each monitoring period in each monitoring water area corresponding to the ocean. According to the water temperature variation coefficient, water salinity variation coefficient and water pH variation coefficient, a comprehensive evaluation can be made on the environmental status of each monitoring water area corresponding to the ocean, and the environmental status of each monitoring water area corresponding to the ocean can be understood more accurately, providing a scientific basis for marine environmental protection and management. If the three variation coefficients are all small, it means that the water environment is relatively stable, which is conducive to the healthy development of the marine ecosystem. If one or several variation coefficients are large, it is necessary to specifically analyze the possible causes and impacts, and take corresponding measures for protection and governance.

[0077] By simultaneously processing and analyzing the data of water temperature, water salinity and water pH at each monitoring time point in each monitoring period in each monitoring water area corresponding to the ocean, the water temperature variation coefficient, water salinity variation coefficient and water pH variation coefficient in each monitoring period in each monitoring water area corresponding to the ocean are obtained. Based on the water temperature variation coefficient, water salinity variation coefficient and water pH variation coefficient, a comprehensive evaluation can be made on the environmental status of each monitoring water area corresponding to the ocean, so as to more accurately understand the environmental status of each monitoring water area corresponding to the ocean and provide a scientific basis for marine environmental protection and management.

[0078] The meteorological state analysis model is used to analyze the state of meteorological parameters in each monitoring period in each monitoring water area of ​​the ocean, and obtain the meteorological state change coefficient in each monitoring period in each monitoring water area of ​​the ocean. The specific analysis method is as follows:

[0079] The wind speed of the water area at each monitoring time point in each monitoring period in each monitoring water area of ​​the ocean is extracted from the meteorological parameters in each monitoring period in each monitoring water area of ​​the ocean, and the wind speed of the water area at each monitoring time point in each monitoring period in each monitoring water area of ​​the ocean is obtained, which is recorded as WF i，j k , the wind speed of each monitoring time point in each monitoring period in each monitoring water area of ​​the ocean is summed and divided by the number of monitoring time points to obtain the average wind speed of each monitoring water area in each monitoring period, which is recorded as .

[0080] Substitute the wind speed of the water area at each monitoring time point in each monitoring period in the ocean corresponding to each monitoring water area and the average wind speed of the water area at each monitoring time point in each monitoring period in the ocean corresponding to each monitoring water area into the standard deviation calculation formula for calculation, and obtain the standard deviation of the wind speed of the water area in each monitoring period in the ocean corresponding to each monitoring water area, recorded as ; Among them, the specific calculation method of the standard deviation of wind speed in each monitoring water area corresponding to the ocean during each monitoring period can be calculated according to the calculation method of the standard deviation of water salinity in each monitoring water area corresponding to the ocean during each monitoring period.

[0081] The water wind speed variation coefficient of each monitoring water area in each monitoring period in the ocean corresponding to each monitoring water area is calculated by comparing the standard deviation of water wind speed in each monitoring period in each monitoring water area in the ocean corresponding to each monitoring period and multiplying the result by percentage. Meanwhile, the number of water wind direction changes in each monitoring period in each monitoring water area in the ocean corresponding to each monitoring water area is obtained by multiplying the number by percentage to obtain the water wind direction variation coefficient of each monitoring period in each monitoring water area in the ocean corresponding to each monitoring period.

[0082] The meteorological state variation coefficient of each monitoring water area in the ocean corresponding to each monitoring period is composed of the water area wind speed variation coefficient of each monitoring water area in the ocean corresponding to each monitoring period and the water area wind direction variation coefficient of each monitoring water area in the ocean corresponding to each monitoring period.

[0083] In a specific embodiment, the present invention conducts real-time monitoring and analysis of the water area wind speed and water area wind direction in each monitoring period in each monitoring water area corresponding to the ocean, and obtains the water area wind speed variation coefficient in each monitoring period in each monitoring water area corresponding to the ocean. At the same time, the number of water area wind direction changes in each monitoring period in each monitoring water area corresponding to the ocean is multiplied by a percentage to obtain the water area wind direction variation coefficient in each monitoring period in each monitoring water area corresponding to the ocean. This can not only warn of natural disasters such as storms and hurricanes, but also understand the meteorological conditions of various aspects such as wave conditions, ocean surface temperature, climate patterns, marine ecosystems and fishery resources, and provide reliable scientific data support for marine operations, navigation safety, disaster warnings and scientific research.

[0084] By conducting real-time monitoring and analysis of the wind speed and wind direction in each monitoring period in the corresponding monitoring waters of the ocean, the wind speed variation coefficient in each monitoring period in the corresponding monitoring waters of the ocean is obtained. At the same time, the number of wind direction changes in each monitoring period in the corresponding monitoring waters of the ocean is multiplied by the percentage to obtain the wind direction variation coefficient in each monitoring period in the corresponding monitoring waters of the ocean. This can not only warn of natural disasters such as storms and hurricanes, but also understand the meteorological conditions of many aspects such as wave conditions, ocean surface temperature, climate patterns, marine ecosystems and fishery resources, providing reliable scientific data support for marine operations, navigation safety, disaster warning and scientific research.

[0085] Step 400: Based on the environmental state change coefficient and the meteorological state change coefficient, a comprehensive analysis is performed through the environmental meteorological trend analysis model at the cloud layer to generate the environmental meteorological state and store it in the cloud database.

[0086] In the present invention, the environmental meteorological trend analysis model is used to comprehensively analyze the environmental state change coefficient and the meteorological state change coefficient in each monitoring period in each monitoring water area corresponding to the ocean, and obtain the environmental meteorological state in each monitoring period in each monitoring water area corresponding to the ocean. The specific analysis method is as follows:

[0087] See also Figure 4As shown, by plotting the water temperature variation coefficient, water salinity variation coefficient, water pH variation coefficient, water wind speed variation coefficient and water wind direction variation coefficient in each monitoring period in the ocean corresponding to each monitoring water area on the same line graph, an environmental meteorological status assessment diagram of each monitoring period in the ocean corresponding to each monitoring water area is obtained. By obtaining the change difference between the maximum and minimum values ​​of the water temperature variation coefficient, water salinity variation coefficient, water pH variation coefficient, water wind speed variation coefficient and water wind direction variation coefficient from the environmental meteorological status assessment diagram of each monitoring period in the ocean corresponding to each monitoring water area, if the ocean corresponds to a certain monitoring water area in a certain monitoring period If the change difference of the water temperature variation coefficient is greater than the preset change threshold, it means that the water temperature state of the ocean corresponding to the monitored water area during the monitoring period is abnormal; otherwise, it means that the water temperature environment state of the ocean corresponding to the monitored water area during the monitoring period is normal. Similarly, the change differences corresponding to the water salinity variation coefficient, water pH variation coefficient, water area wind speed variation coefficient and water area wind direction variation coefficient in each monitoring water area corresponding to the ocean during each monitoring period are compared with the corresponding preset change threshold to obtain the water salinity state, water pH state, water area wind speed state and water area wind direction change state in each monitoring water area corresponding to the ocean during each monitoring period.

[0088] The environmental meteorological status of each monitoring water area in the ocean during each monitoring period is composed of the water temperature status, water salinity status, water pH status, water wind speed status and water wind direction change status in the ocean corresponding to the monitoring water area during the monitoring period.

[0089] In a specific embodiment, the present invention draws an environmental meteorological status assessment map by analyzing the water temperature variation coefficient, water salinity variation coefficient, water pH variation coefficient, water area wind speed variation coefficient and water area wind direction variation coefficient in each monitoring water area corresponding to the ocean during each monitoring period, and analyzes the change difference of the environmental meteorological status assessment map, evaluates the environmental meteorological status of the monitored water area from multiple angles, and determines possible environmental meteorological problems based on specific change differences, and at the same time, understands the dynamic change process of the marine ecosystem, providing important data support for marine environmental protection and management.

[0090] The cloud database is used to classify and store the monitoring data of each monitoring time point in each monitoring period in each monitoring water area of ​​the ocean.

[0091] The above formulas are all dimensionless and numerical calculations. The formula is a formula that is obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The size of the coefficient is to quantify each parameter to obtain a specific value. Regarding the size of the coefficient, it is acceptable as long as it does not affect the proportional relationship between the parameter and the quantified value.

[0092] By drawing an environmental meteorological status assessment map for the water temperature variation coefficient, water salinity variation coefficient, water pH variation coefficient, water wind speed variation coefficient and water wind direction variation coefficient in each monitoring water area corresponding to the ocean during each monitoring period, and analyzing the change difference of the environmental meteorological status assessment map, the environmental meteorological status of the monitored water area is evaluated from multiple angles, and the possible environmental meteorological problems are determined based on the specific change difference. At the same time, the dynamic change process of the marine ecosystem can be understood, providing important data support for marine environmental protection and management.

[0093] refer to Figure 5 The present invention also discloses a marine satellite IoT monitoring system based on cloud-edge-end collaboration, the system comprising:

[0094] The data acquisition module 110 is used to acquire ocean environment parameters through the ocean environment parameter monitoring model in the preset terminal layer and acquire ocean meteorological parameters through the ocean meteorological parameter monitoring model;

[0095] The data transmission module 120 is used to send the ocean environment parameters and ocean meteorological parameters to the cloud layer through the Internet of Things sensors and satellite communication models of the preset edge layer;

[0096] A data analysis module 130, configured to analyze the ocean environmental parameters through the environmental state analysis model of the cloud layer to generate an environmental state variation coefficient, and to analyze the ocean meteorological parameters through the meteorological state analysis model of the cloud layer to generate a meteorological state variation coefficient;

[0097] The result generation module 140 is used to perform a comprehensive analysis based on the environmental state change coefficient and the meteorological state change coefficient through the environmental meteorological trend analysis model of the cloud layer, generate the environmental meteorological state and store it in the cloud database.

[0098] The marine environment parameters are obtained by using the marine environment parameter monitoring model in the preset terminal layer and the marine meteorological parameters are obtained by using the marine meteorological parameter monitoring model, specifically including:

[0099] The environmental parameters of each monitoring period in each monitoring water area of ​​the ocean are monitored in real time through the marine environmental parameter monitoring model, and the environmental parameters of each monitoring period in each monitoring water area of ​​the ocean are obtained, wherein the environmental parameters include water body temperature, water body salinity and water body pH;

[0100] The marine meteorological parameter monitoring model is used to monitor the meteorological parameters in each monitoring period in each monitoring water area of ​​the ocean in real time, and obtain the meteorological parameters in each monitoring period in each monitoring water area of ​​the ocean, wherein the meteorological parameters include wind direction and wind speed in the water area.

[0101] The ocean meteorological parameter monitoring model is used to monitor the meteorological parameters of each monitoring period in each monitoring water area of ​​the ocean in real time, and obtains the meteorological parameters of each monitoring period in each monitoring water area of ​​the ocean, including:

[0102] By installing a buoy platform in each monitoring water area of ​​the ocean, a wind speed sensor and a wind direction sensor are installed on the buoy platform;

[0103] The wind speed sensor monitors the wind speed of the water area at each monitoring time point in each monitoring period in the monitoring water area in real time, and obtains the wind speed of the water area in each monitoring period in each monitoring water area corresponding to the ocean;

[0104] The wind direction sensor monitors the wind direction of the water area at each monitoring time point in each monitoring period in the monitoring water area in real time, and obtains the wind direction of the water area in each monitoring period in each monitoring water area corresponding to the ocean.

[0105] The ocean environment parameters are analyzed by the cloud layer environment state analysis model to generate an environment state change coefficient, specifically including:

[0106] The environmental status analysis model of the cloud layer is used to calculate the number of monitoring time points in each monitoring period in each monitoring water area of ​​the ocean. The water temperature, salinity and pH value of each monitoring time point in each monitoring period in each monitoring water area of ​​the ocean are summed up and divided by the number of monitoring time points to obtain the average water temperature, salinity and pH value of each monitoring period in each monitoring water area of ​​the ocean.

[0107] Based on the average water temperature, average water salinity and average water pH, the standard deviation of water temperature, water salinity and water pH in each monitoring period in each monitoring water area of ​​the ocean is obtained through the standard deviation calculation formula.

[0108] The coefficient of change of water temperature, water salinity and water pH in each monitoring period in each monitoring water area corresponding to the ocean is calculated by comparing the standard deviation of water temperature, water salinity and water pH in each monitoring period in each monitoring water area corresponding to the ocean with the average water temperature, average water salinity and average water pH in each monitoring period in each monitoring water area corresponding to the ocean and multiplying them by percentage;

[0109] The environmental state variation coefficient of each monitoring water area in the ocean during each monitoring period is composed of the water temperature variation coefficient, water salinity variation coefficient and water pH variation coefficient in each monitoring water area in the ocean during each monitoring period.

[0110] The meteorological state analysis model of the cloud layer is used to analyze the ocean meteorological parameters to generate a meteorological state change coefficient, specifically including:

[0111] Substitute the water area wind speed at each monitoring time point in each monitoring period in each monitoring water area of ​​the ocean and the average water area wind speed at each monitoring time point in each monitoring period in each monitoring water area of ​​the ocean into the standard deviation calculation formula for calculation, and obtain the water area wind speed standard deviation in each monitoring period in each monitoring water area of ​​the ocean;

[0112] Extract the water area wind speed at each monitoring time point in each monitoring period in each monitoring water area corresponding to the ocean from the meteorological parameters in each monitoring period in each monitoring water area corresponding to the ocean, obtain the water area wind speed at each monitoring time point in each monitoring period in each monitoring water area corresponding to the ocean, sum the water area wind speed at each monitoring time point in each monitoring period in each monitoring water area corresponding to the ocean and divide the sum by the number of each monitoring time point to obtain the average water area wind speed in each monitoring period in each monitoring water area corresponding to the ocean;

[0113] The water wind speed variation coefficient of each monitoring period in each monitoring water area corresponding to the ocean is calculated by comparing the standard deviation of the water wind speed in each monitoring period in each monitoring water area corresponding to the ocean with the average water wind speed in each monitoring period in each monitoring water area corresponding to the ocean and multiplying the result by percentage. At the same time, the number of water wind direction changes in each monitoring period in each monitoring water area corresponding to the ocean is multiplied by the percentage to obtain the water wind direction variation coefficient of each monitoring period in each monitoring water area corresponding to the ocean.

[0114] The meteorological state variation coefficient of each monitoring water area in the ocean corresponding to each monitoring period is composed of the water area wind speed variation coefficient of each monitoring water area in the ocean corresponding to each monitoring period and the water area wind direction variation coefficient of each monitoring water area in the ocean corresponding to each monitoring period.

[0115] Based on the environmental state change coefficient and the meteorological state change coefficient, a comprehensive analysis is performed through the environmental meteorological trend analysis model of the cloud layer to generate the environmental meteorological state and store it in the cloud database, specifically including:

[0116] Compare the change differences corresponding to the water temperature change coefficient, water salinity change coefficient, water pH change coefficient, water wind speed change coefficient and water wind direction change coefficient in each monitoring water area corresponding to the ocean in each monitoring period with the corresponding preset change thresholds to obtain the water salinity status, water pH status, water wind speed status and water wind direction change status in each monitoring water area corresponding to the ocean in each monitoring period;

[0117] Combine the water temperature state, water salinity state, water pH state, water wind speed state and water wind direction change state in the monitoring water area corresponding to the ocean during the monitoring period to construct the environmental meteorological state in each monitoring period of each monitoring water area corresponding to the ocean, and save the environmental meteorological state in the cloud database;

[0118] Among them, if the difference between the maximum and minimum values ​​of the change differences corresponding to the water temperature change coefficient, the water salinity change coefficient, the water pH change coefficient, the water area wind speed change coefficient and the water area wind direction change coefficient is greater than the preset change threshold, then the water environment state in the ocean corresponding to the monitored water area during the monitoring period is abnormal.

[0119] Based on the ocean satellite Internet of Things monitoring system based on cloud-edge-end collaboration provided by the present invention, various environmental parameters and meteorological parameters are collected and analyzed and calculated to obtain the water temperature variation coefficient, water salinity variation coefficient and water pH variation coefficient, and the environmental status of each monitored water area in the ocean is comprehensively evaluated. At the same time, according to the water area wind speed variation coefficient and the water area wind direction variation coefficient, natural disasters such as storms and hurricanes are warned, and the meteorological status of various aspects such as wave conditions, ocean surface temperature, climate patterns, marine ecosystems and fishery resources can be understood, providing reliable scientific data support for marine operations, navigation safety, disaster warning and scientific research; through comprehensive analysis, the environmental meteorological status of the monitored water area is evaluated from multiple angles, and the possible environmental meteorological problems are determined according to the specific change difference. At the same time, the dynamic change process of the marine ecosystem can be understood, providing important data support for marine environmental protection and management.

[0120] Figure 6 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 6 As shown, the electronic device may include: a processor 610, a communication interface 620, a memory 630 and a communication bus 640, wherein the processor 610, the communication interface 620 and the memory 630 communicate with each other through the communication bus 640. The processor 610 may call the logic instructions in the memory 630 to execute the ocean satellite IoT monitoring method based on cloud-edge-end collaboration, the method comprising: obtaining ocean environmental parameters through an ocean environmental parameter monitoring model in a preset terminal layer and obtaining ocean meteorological parameters through an ocean meteorological parameter monitoring model; sending the ocean environmental parameters and ocean meteorological parameters to the cloud layer through an IoT sensor and a satellite communication model in a preset edge layer; analyzing the ocean environmental parameters through an environmental state analysis model in the cloud layer to generate an environmental state change coefficient, and analyzing the ocean meteorological parameters through a meteorological state analysis model in the cloud layer to generate a meteorological state change coefficient; performing a comprehensive analysis based on the environmental state change coefficient and the meteorological state change coefficient through an environmental meteorological trend analysis model in the cloud layer, generating an environmental meteorological state and storing it in a cloud database.

[0121] In addition, the logic instructions in the above-mentioned memory 630 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0122] On the other hand, the present invention also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the ocean satellite Internet of Things monitoring method based on cloud-edge-end collaboration provided by the above methods. The method includes: obtaining ocean environmental parameters through an ocean environmental parameter monitoring model in a preset terminal layer and obtaining ocean meteorological parameters through an ocean meteorological parameter monitoring model; sending the ocean environmental parameters and ocean meteorological parameters to the cloud layer through the Internet of Things sensors and satellite communication models of the preset edge layer; analyzing the ocean environmental parameters through the environmental state analysis model of the cloud layer to generate an environmental state change coefficient, and analyzing the ocean meteorological parameters through the meteorological state analysis model of the cloud layer to generate a meteorological state change coefficient; based on the environmental state change coefficient and the meteorological state change coefficient, a comprehensive analysis is performed through the environmental meteorological trend analysis model of the cloud layer to generate an environmental meteorological state and store it in a cloud database.

[0123] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, it is implemented to execute the ocean satellite Internet of Things monitoring method based on cloud-edge-end collaboration provided by the above-mentioned methods. The method includes: obtaining ocean environmental parameters through an ocean environmental parameter monitoring model in a preset terminal layer and obtaining ocean meteorological parameters through an ocean meteorological parameter monitoring model; sending the ocean environmental parameters and ocean meteorological parameters to the cloud layer through the Internet of Things sensors and satellite communication models of the preset edge layer; analyzing the ocean environmental parameters through the environmental state analysis model of the cloud layer to generate an environmental state change coefficient, and analyzing the ocean meteorological parameters through the meteorological state analysis model of the cloud layer to generate a meteorological state change coefficient; based on the environmental state change coefficient and the meteorological state change coefficient, a comprehensive analysis is performed through the environmental meteorological trend analysis model of the cloud layer to generate an environmental meteorological state and store it in a cloud database.

[0124] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0125] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0126] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A marine satellite IoT monitoring method based on cloud-edge-end collaboration, characterized in that: include: Obtaining ocean environmental parameters through an ocean environmental parameter monitoring model in a preset terminal layer and obtaining ocean meteorological parameters through an ocean meteorological parameter monitoring model; The ocean environment parameters and ocean meteorological parameters are sent to the cloud layer through the Internet of Things sensors and satellite communication models of the preset edge layer; The ocean environment parameters are analyzed by the environmental state analysis model of the cloud layer to generate an environmental state change coefficient, and the ocean meteorological parameters are analyzed by the meteorological state analysis model of the cloud layer to generate a meteorological state change coefficient; Based on the environmental state change coefficient and the meteorological state change coefficient, a comprehensive analysis is performed through an environmental meteorological trend analysis model at the cloud layer to generate an environmental meteorological state and store it in a cloud database; The step of analyzing the ocean environment parameters by the cloud layer environment state analysis model to generate an environment state change coefficient specifically includes: The environmental status analysis model of the cloud layer is used to calculate the number of monitoring time points in each monitoring period in each monitoring water area of ​​the ocean. The water temperature, salinity and pH value of each monitoring time point in each monitoring period in each monitoring water area of ​​the ocean are summed up and divided by the number of monitoring time points to obtain the average water temperature, salinity and pH value of each monitoring period in each monitoring water area of ​​the ocean. Based on the average water temperature, average water salinity and average water pH, the standard deviation of water temperature, water salinity and water pH in each monitoring period in each monitoring water area of ​​the ocean is obtained through the standard deviation calculation formula. The coefficient of change of water temperature, water salinity and water pH in each monitoring period in each monitoring water area corresponding to the ocean is calculated by comparing the standard deviation of water temperature, water salinity and water pH in each monitoring period in each monitoring water area corresponding to the ocean with the average water temperature, average water salinity and average water pH in each monitoring period in each monitoring water area corresponding to the ocean and multiplying them by percentage; The environmental state variation coefficient of each monitoring water area in each monitoring period in the ocean is composed of the water temperature variation coefficient, water salinity variation coefficient and water pH variation coefficient in each monitoring water area in each monitoring period; The analyzing the ocean meteorological parameters by the meteorological state analysis model of the cloud layer to generate the meteorological state change coefficient specifically includes: Substitute the water area wind speed at each monitoring time point in each monitoring period in each monitoring water area of ​​the ocean and the average water area wind speed at each monitoring time point in each monitoring period in each monitoring water area of ​​the ocean into the standard deviation calculation formula for calculation, and obtain the water area wind speed standard deviation in each monitoring period in each monitoring water area of ​​the ocean; Extract the water area wind speed at each monitoring time point in each monitoring period in each monitoring water area corresponding to the ocean from the meteorological parameters in each monitoring period in each monitoring water area corresponding to the ocean, obtain the water area wind speed at each monitoring time point in each monitoring period in each monitoring water area corresponding to the ocean, sum the water area wind speed at each monitoring time point in each monitoring period in each monitoring water area corresponding to the ocean and divide the sum by the number of each monitoring time point to obtain the average water area wind speed in each monitoring period in each monitoring water area corresponding to the ocean; The water wind speed variation coefficient of each monitoring period in each monitoring water area corresponding to the ocean is calculated by comparing the standard deviation of the water wind speed in each monitoring period in each monitoring water area corresponding to the ocean with the average water wind speed in each monitoring period in each monitoring water area corresponding to the ocean and multiplying the result by percentage. At the same time, the number of water wind direction changes in each monitoring period in each monitoring water area corresponding to the ocean is multiplied by the percentage to obtain the water wind direction variation coefficient of each monitoring period in each monitoring water area corresponding to the ocean. The coefficient of change of the meteorological state in each monitoring water area corresponding to the ocean in each monitoring period is composed of the coefficient of change of the wind speed in each monitoring water area corresponding to the ocean in each monitoring period and the coefficient of change of the wind direction in each monitoring water area corresponding to the ocean in each monitoring period; The method of performing a comprehensive analysis based on the environmental state change coefficient and the meteorological state change coefficient through the environmental meteorological trend analysis model of the cloud layer to generate the environmental meteorological state and store it in the cloud database specifically includes: Compare the change differences corresponding to the water temperature change coefficient, water salinity change coefficient, water pH change coefficient, water wind speed change coefficient and water wind direction change coefficient in each monitoring water area corresponding to the ocean in each monitoring period with the corresponding preset change thresholds to obtain the water salinity status, water pH status, water wind speed status and water wind direction change status in each monitoring water area corresponding to the ocean in each monitoring period; The water temperature state, water salinity state, water pH state, water wind speed state and water wind direction change state in the monitoring water area corresponding to the ocean during the monitoring period are combined to construct the environmental meteorological state in each monitoring water area corresponding to the ocean during each monitoring period, and the environmental meteorological state is stored in the cloud database; wherein, if the change difference between the maximum value and the minimum value of the change difference corresponding to the water temperature change coefficient, the water salinity change coefficient, the water pH change coefficient, the water wind speed change coefficient and the water wind direction change coefficient is greater than the preset change threshold, then the water environment state in the monitoring water area corresponding to the ocean during the monitoring period is abnormal.

2. The method for monitoring ocean satellite IoT based on cloud-edge-end collaboration according to claim 1 is characterized in that: The obtaining of ocean environment parameters through the ocean environment parameter monitoring model in the preset terminal layer and the obtaining of ocean meteorological parameters through the ocean meteorological parameter monitoring model specifically include: The environmental parameters of each monitoring period in each monitoring water area of ​​the ocean are monitored in real time through the marine environmental parameter monitoring model, and the environmental parameters of each monitoring period in each monitoring water area of ​​the ocean are obtained, wherein the environmental parameters include water body temperature, water body salinity and water body pH; The marine meteorological parameter monitoring model is used to monitor the meteorological parameters in each monitoring period in each monitoring water area of ​​the ocean in real time, and obtain the meteorological parameters in each monitoring period in each monitoring water area of ​​the ocean, wherein the meteorological parameters include wind direction and wind speed in the water area.

3. The ocean satellite IoT monitoring method based on cloud-edge-end collaboration according to claim 2 is characterized in that: The method of performing real-time monitoring of the meteorological parameters in each monitoring period in each monitoring water area corresponding to the ocean by using the marine meteorological parameter monitoring model to obtain the meteorological parameters in each monitoring period in each monitoring water area corresponding to the ocean specifically includes: The wind speed sensor is used to monitor the wind speed of the water area at each monitoring time point in each monitoring cycle in the monitoring water area in real time, and the wind speed of the water area in each monitoring cycle in the ocean corresponding to each monitoring water area is obtained; The wind direction of the water area at each monitoring time point in each monitoring period in the monitoring water area is monitored in real time by means of a wind direction sensor, and the wind direction of the water area in each monitoring period in the corresponding monitoring water area of ​​the ocean is obtained; The wind speed sensor and the wind direction sensor are installed on buoy platforms in each monitoring water area.

4. A marine satellite IoT monitoring system based on cloud-edge-end collaboration, characterized in that: The system comprises: A data acquisition module, used to acquire ocean environmental parameters through an ocean environmental parameter monitoring model in a preset terminal layer and to acquire ocean meteorological parameters through an ocean meteorological parameter monitoring model; A data transmission module, used for sending the ocean environment parameters and ocean meteorological parameters to the cloud layer through the Internet of Things sensors and satellite communication models of the preset edge layer; A data analysis module, used to analyze the ocean environmental parameters through the environmental state analysis model of the cloud layer to generate an environmental state change coefficient, and to analyze the ocean meteorological parameters through the meteorological state analysis model of the cloud layer to generate a meteorological state change coefficient; A result generation module is used to perform a comprehensive analysis based on the environmental state change coefficient and the meteorological state change coefficient through the environmental meteorological trend analysis model of the cloud layer, generate the environmental meteorological state and store it in the cloud database; The step of analyzing the ocean environment parameters by the cloud layer environment state analysis model to generate an environment state change coefficient specifically includes: The environmental status analysis model of the cloud layer is used to calculate the number of monitoring time points in each monitoring period in each monitoring water area of ​​the ocean. The water temperature, salinity and pH value of each monitoring time point in each monitoring period in each monitoring water area of ​​the ocean are summed up and divided by the number of monitoring time points to obtain the average water temperature, salinity and pH value of each monitoring period in each monitoring water area of ​​the ocean. Based on the average water temperature, average water salinity and average water pH, the standard deviation of water temperature, water salinity and water pH in each monitoring period in each monitoring water area of ​​the ocean is obtained through the standard deviation calculation formula. The coefficient of change of water temperature, water salinity and water pH in each monitoring period in each monitoring water area corresponding to the ocean is calculated by comparing the standard deviation of water temperature, water salinity and water pH in each monitoring period in each monitoring water area corresponding to the ocean with the average water temperature, average water salinity and average water pH in each monitoring period in each monitoring water area corresponding to the ocean and multiplying them by percentage; The environmental state variation coefficient of each monitoring water area in each monitoring period in the ocean is composed of the water temperature variation coefficient, water salinity variation coefficient and water pH variation coefficient in each monitoring water area in each monitoring period; The analyzing the ocean meteorological parameters by the meteorological state analysis model of the cloud layer to generate the meteorological state change coefficient specifically includes: Substitute the water area wind speed at each monitoring time point in each monitoring period in each monitoring water area of ​​the ocean and the average water area wind speed at each monitoring time point in each monitoring period in each monitoring water area of ​​the ocean into the standard deviation calculation formula for calculation, and obtain the water area wind speed standard deviation in each monitoring period in each monitoring water area of ​​the ocean; Extract the water area wind speed at each monitoring time point in each monitoring period in each monitoring water area corresponding to the ocean from the meteorological parameters in each monitoring period in each monitoring water area corresponding to the ocean, obtain the water area wind speed at each monitoring time point in each monitoring period in each monitoring water area corresponding to the ocean, sum the water area wind speed at each monitoring time point in each monitoring period in each monitoring water area corresponding to the ocean and divide the sum by the number of each monitoring time point to obtain the average water area wind speed in each monitoring period in each monitoring water area corresponding to the ocean; The water wind speed variation coefficient of each monitoring period in each monitoring water area corresponding to the ocean is calculated by comparing the standard deviation of the water wind speed in each monitoring period in each monitoring water area corresponding to the ocean with the average water wind speed in each monitoring period in each monitoring water area corresponding to the ocean and multiplying the result by percentage. At the same time, the number of water wind direction changes in each monitoring period in each monitoring water area corresponding to the ocean is multiplied by the percentage to obtain the water wind direction variation coefficient of each monitoring period in each monitoring water area corresponding to the ocean. The coefficient of change of the meteorological state in each monitoring water area corresponding to the ocean in each monitoring period is composed of the coefficient of change of the wind speed in each monitoring water area corresponding to the ocean in each monitoring period and the coefficient of change of the wind direction in each monitoring water area corresponding to the ocean in each monitoring period; The method of performing a comprehensive analysis based on the environmental state change coefficient and the meteorological state change coefficient through the environmental meteorological trend analysis model of the cloud layer to generate the environmental meteorological state and store it in the cloud database specifically includes: Compare the change differences corresponding to the water temperature change coefficient, water salinity change coefficient, water pH change coefficient, water wind speed change coefficient and water wind direction change coefficient in each monitoring water area corresponding to the ocean in each monitoring period with the corresponding preset change thresholds to obtain the water salinity status, water pH status, water wind speed status and water wind direction change status in each monitoring water area corresponding to the ocean in each monitoring period; The water temperature state, water salinity state, water pH state, water wind speed state and water wind direction change state in the monitoring water area corresponding to the ocean during the monitoring period are combined to construct the environmental meteorological state in each monitoring water area corresponding to the ocean during each monitoring period, and the environmental meteorological state is stored in the cloud database; wherein, if the change difference between the maximum value and the minimum value of the change difference corresponding to the water temperature change coefficient, the water salinity change coefficient, the water pH change coefficient, the water wind speed change coefficient and the water wind direction change coefficient is greater than the preset change threshold, then the water environment state in the monitoring water area corresponding to the ocean during the monitoring period is abnormal.

5. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, it implements the marine satellite Internet of Things monitoring method based on cloud-edge-end collaboration as described in any one of claims 1 to 3.

6. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the ocean satellite Internet of Things monitoring method based on cloud-edge-end collaboration as described in any one of claims 1 to 3.

7. A computer program product, comprising a computer program, characterized in that When the computer program is executed by the processor, it implements the ocean satellite Internet of Things monitoring method based on cloud-edge-end collaboration as described in any one of claims 1 to 3.

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