An Ocean Monitoring Data Processing Method Based on AI and Internet of Things Technologies

Abstract

The present invention relates to the field of marine information processing technology, and in particular to a marine monitoring data processing method based on AI and Internet of Things technology. The method divides a marine area into multiple independent monitoring areas, calculates real-time monitoring data in the marine independent monitoring areas in combination with historical monitoring data, obtains a trust coefficient, and then performs effective data judgment on the real-time monitoring data according to the trust coefficient, thereby improving the accuracy of the marine monitoring data; at the same time, the independent monitoring areas in the marine area are divided into multiple regional transmission routes, and a remote area is obtained according to the regional transmission route, after which a marine information center transmits an instruction transmission packet to the remote area, and the remote area transmits signals layer by layer to hierarchical receiving stations in turn, so that the marine receiving center keeps the same time for receiving data packets, thereby reducing data sorting time and further improving data processing efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of marine information processing, and particularly relates to a method for processing marine monitoring data based on AI and Internet of Things technologies. Background Art

[0002] In order to more effectively manage and utilize marine monitoring data, the concept of the marine Internet has been proposed. This is an integrated marine information network integrating various functions such as marine monitoring, information transmission, data mining, and result feedback. Through the marine Internet of Things, the interconnection and interoperability of various types of sensing and monitoring terminals above and below water can be realized, and the monitoring and systematic management of complex marine data can be achieved.

[0003] The prior art CN116298151A discloses a method and device for processing data based on marine environmental monitoring. The processing method includes: obtaining a plurality of node data sets monitored by a plurality of sensors at different time nodes in a certain period and the time nodes corresponding to the node data sets, wherein there are multiple of each type of sensor; dividing the node data sets into multiple node category data sets according to the sensor type, and performing primary fusion on multiple node category sub-data in each node category data set to obtain a fusion value corresponding to each node category data set; performing secondary heterogeneous fusion according to the fusion values corresponding to each node category data set to obtain a preliminary evaluation result corresponding to each node data set; performing tertiary time node fusion according to each preliminary evaluation result to obtain a comprehensive evaluation result of the water quality of the monitored sea area within a certain period.

[0004] However, when monitoring data of the ocean, due to the large coverage area of the ocean region, there are many external influencing factors when the Internet of Things devices collect data. When the Internet of Things devices monitor data of the ocean, the accuracy of the monitored data needs to be further confirmed. Moreover, due to the vast coverage area of the ocean, when the information center sends signal requests to Internet of Things devices in different regions, due to the different distances of the devices, there are differences in the receiving and sending times of the devices in the regional signals, resulting in relatively messy signals when the information center receives the monitoring data. It takes a lot of time for the information center to process and integrate the data signals, reducing the data processing efficiency. Summary of the Invention

[0005] The purpose of the present invention is to solve the problems in the background art, and a method for processing marine monitoring data based on AI and Internet of Things technologies is proposed.

[0006] In order to achieve the above purpose, the present invention adopts the following technical scheme:

[0007] A method for processing marine monitoring data based on AI and Internet of Things technologies, the method specifically includes the following steps:

[0008] Step 1: According to the area covered by the Internet of Things devices, divide the ocean area into several independent monitoring areas, and collect the monitoring data of the independent monitoring areas to obtain real-time monitoring data;

[0009] Step 2: Obtain the historical monitoring data in the independent monitoring area, perform data calculation on the real-time monitoring data and the historical monitoring data to obtain a trust coefficient. According to the trust coefficient, judge the validity of the real-time monitoring data. If the real-time monitoring data is valid data, store the real-time monitoring data in the data storage center of the independent monitoring area;

[0010] Step 3: When the ocean information general station performs information integration processing on the independent monitoring area, first select the independent monitoring area corresponding to the maximum transmission distance according to the transmission distance between the ocean information general station and the independent monitoring area, and mark it as the long-distance area. Set the regional transmission route according to the signal transmission route between the long-distance area and the ocean information general station;

[0011] Step 4: Set up level receiving stations for the independent monitoring areas in the regional transmission route, receive according to the level, and set the normal transmission direction and the negative transmission direction according to the signal transmission direction between the ocean information general station and the independent monitoring area;

[0012] Step 5: According to the transmission distance of the long-distance area in each regional transmission route and the transmission speed of the medium, obtain the one-way transmission time. Determine the transmission time difference of each regional transmission route from the maximum value in the one-way transmission time. Then, the ocean information general station binds the transmission time difference with the command information and generates command data packets, and transmits them to the long-distance areas respectively;

[0013] Step 6: The long-distance area determines the data sending time of this receiving station according to the transmission time difference in the command transmission packet, and sequentially emits signals layer by layer to the level receiving stations according to the set level receiving stations. And when the real-time time is the same as the data sending time, this receiving station sends data packets and transmission signals to the ocean information general station and the next receiving station respectively.

[0014] As a further solution of the present invention, the method for obtaining real-time monitoring data includes:

[0015] Optionally select an independent monitoring area and mark it as the target area. Obtain the area information of the target area. Based on AI technology, use the area information as the input value, and the AI device constructs a simulation model for the area information to obtain a single-area model, where the area information includes the shape and area of the target area;

[0016] According to the area of the target area, the target area is divided into N equal-area regions, and the equal-area regions are marked in the single-region model. The midpoints of the equal-area regions are identified through image recognition processing technology, and the midpoint of the single-region model is used as the detection point. The monitoring data of the ocean is collected according to the position of each detection point to obtain real-time monitoring data.

[0017] As a further solution of the present invention, the method for obtaining the trust coefficient includes:

[0018] Mark the real-time monitoring data as HSn, where n represents different detection points in the target area, and n = 1, 2,..., N. Based on the data storage center in the target area, extract the historical monitoring data, and mark the most recently collected monitoring data in the historical monitoring data as the reference data HZn;

[0019] Based on the formula Obtain the trust coefficient Xn. Here, the trust coefficient refers to the value obtained by the real-time monitoring data based on the reference data, and C1 is the difference threshold;

[0020] Adopt Obtain the data trust value Rs, where XCp is the non-zero value in the trust coefficient Xn, a1 is the number of XCp in the trust coefficient Xn, a2 refers to the number of the trust coefficient Xn equal to 0, and a1 + a2 = N, and Kl is the monitoring coefficient;

[0021] When the comprehensive data trust value reaches the data threshold Ry1, that is, Rs ≥ Ry1, mark the real-time monitoring data of the target area as valid data and transmit it to the data storage center of the target area for storage. On the contrary, when the data trust value is less than the data threshold Ry1, that is, Rs < Ry1, generate a data warning signal and transmit it to the terminal device.

[0022] As a further solution of the present invention, the calculation process of the monitoring coefficient Kl includes:

[0023] Taking the real-time monitoring data in the target area as the final node, extract the first i historical monitoring data in the target area in chronological order, and at the same time take the average value of each historical monitoring data and use the average value as the monitoring representative data BSi, i = 1, 2,..., I;

[0024] Taking the monitoring representative data BSi as the input value, adopt Obtain the monitoring coefficient Kl.

[0025] As a further solution of the present invention, the method for setting the regional transmission route includes:

[0026] Obtain the transmission distances DSj between the ocean information general station and the independent monitoring areas in sequence, where j represents the independent monitoring area, and j = 1, 2,..., J, indicating that there are J independent monitoring areas in this ocean area;

[0027] Select the independent monitoring area corresponding to the maximum value of the transmission distance DSj and mark it as the long-distance area. At the same time, obtain the signal transmission route of the long-distance area;

[0028] Based on this signal transmission route, calculate the distances between the positions of the remaining independent monitoring areas and their signal transmission routes to obtain the short-distance values. If the short-distance value is less than or equal to Yd, mark the independent monitoring area corresponding to this short-distance value as the covered area point in this signal transmission route. Otherwise, if the short-distance value is greater than Yd, do not process this independent monitoring area. Yd is the distance threshold;

[0029] After the covered area points in this signal transmission route are marked, take this signal transmission line and its covered area points as the area transmission route. At the same time, in the independent monitoring areas, remove the marked area covered points, and process the remaining independent monitoring areas in the above manner to obtain the second area transmission route, and so on, dividing the ocean area into multiple area transmission routes.

[0030] As a further solution of the present invention, the method for setting the level receiving stations and the signal transmission directions is as follows:

[0031] Select any one area transmission route as the target transmission route. Take the direction of signal transmission from the ocean information general station to the independent monitoring area as the forward transmission. At this time, the direction of data information transmission from the independent monitoring area to the ocean information general station is the reverse transmission;

[0032] When the command signal is transmitted in the forward transmission direction, set up level receiving stations according to the transmission distances DSa between each area covered point in the target transmission line and the ocean information general station, where a ∈ j and a is the independent monitoring area in the target transmission line. The level receiving stations include the first receiving station, the second receiving station,..., the a-th receiving station.

[0033] As a further solution of the present invention, the method for generating the command data packet includes:

[0034] Obtain the long-distance areas in each area transmission route in sequence. According to the transmission speed of the medium, divide the transmission distance by the transmission speed to obtain the one-way transmission time Tm of this long-distance area, where m represents different area transmission routes;

[0035] Identify the maximum value Tx in the one-way transmission times, where Tx ∈ Tm. Subtract Tx from the one-way transmission times Tm respectively to obtain the transmission time differences SCm of each area transmission route;

[0036] Obtain the device receiving addresses of the remote areas in each regional transmission route, bind the device receiving addresses with the transmission time difference, add the instruction information to the bound data packet at the same time, and generate an instruction transmission packet. Then, the marine information general station transmits the instruction transmission packet to the corresponding remote areas respectively;

[0037] As a further solution of the present invention, the specific transmission method of layer-by-layer signal emission includes:

[0038] According to the hierarchical receiving stations, sequentially obtain the station distances between adjacent receiving stations in the target transmission route, divide the station distances by the signal transmission speed to obtain the station transfer time Tza;

[0039] Obtain the transmission distance DSa between the area coverage point and the marine information general station, divide the transmission distance DSa by the signal transmission speed to obtain the signal receiving time Tsa;

[0040] Use Tx - Tza - Tsa = Tca to obtain the real-time signal time difference Tca of each hierarchical receiving station, and at the same time use Tca + TL = Tdl to obtain the station delay time difference Tdl, where TL is the station delay time difference of the previous receiving station;

[0041] If the station delay time difference Tdl of the current receiving station is less than 0, the signal receiving device will generate an immediate transmission signal, bind the station delay time difference Tdl with the data information of this area coverage point at the same time, generate a data packet, and transmit it to the marine signal general station. If the station delay time difference is greater than or equal to 0, starting from the time when the area coverage point receives the transmission signal, use the station delay time difference as the interval time to obtain the data sending time of this receiving station. When the real-time time is the same as the data sending time of this station, at this time, the receiving station generates a data packet according to the instruction information, and the signal transmitting end transmits the data packet to the marine information general station.

[0042] As a further solution of the present invention, when the marine information general station receives the data packet transmitted by the area coverage point, at this time, the marine information general station first identifies the station delay time difference in the data packet, and uses the station delay time difference as the time compensation factor to perform time consistency compensation on the data receiving time of the marine monitoring data in this instruction information.

[0043] As a further solution of the present invention, the specific method for the value of TL includes:

[0044] If the station delay time difference Tdl in the previous receiving station is greater than or equal to 0, at this time, the value of TL is 0. If the station delay time difference Tdl in the previous receiving station is less than 0, at this time, use the station delay time difference in the previous station as TL here.

[0045] Compared with the existing technologies, the advantages of the present invention are:

[0046] The present invention divides the ocean area into multiple independent monitoring areas, and performs distributed data processing on the real-time monitoring data and historical monitoring data in each independent monitoring area to obtain a real-time data trust value, and makes an effective data judgment on the real-time monitoring data according to the real-time data trust value, thereby improving the accuracy of ocean monitoring data;

[0047] The present invention sets up an area transmission route according to the distribution position and transmission distance of the independent monitoring area. In the area transmission route, level receiving stations are sequentially set according to the transmission distance. At the same time, according to the one-way transmission time of the long-distance areas in all area transmissions, the maximum value in the one-way transmission time is obtained, and the transmission time difference in each area transmission route is obtained according to the maximum value. Then, the ocean information general station generates an instruction transmission packet from the transmission time difference and instruction information and transmits it to the long-distance areas in each area transmission route respectively. After that, the long-distance areas determine the data sending time of this receiving station according to the transmission time difference in the instruction transmission packet. When the real-time time is consistent with the data sending time, this receiving station sends a data packet and a transmission signal to the ocean information general station and the next receiving station respectively. Here, the ocean information general station directly sends the instruction transmission packet to the long-distance areas. Compared with the ocean information general station sending the instruction transmission packet to all independent monitoring areas, the transmission distance of the instruction transmission packet is shortened, thereby improving the data transmission resources. The next receiving station then determines the data sending time of this receiving station according to the transmission signal, so that the ocean receiving general station keeps the time of receiving the data packet consistent, thereby reducing the data sorting time and further improving the data processing efficiency. Description of the Drawings

[0048] Figure 1 It is a schematic structural diagram of the system of the present invention. Detailed Embodiment

[0049] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments.

[0050] Refer to Figure 1 , a method for processing ocean monitoring data based on AI and Internet of Things technologies, which specifically includes the following steps:

[0051] Step 1: Based on the Internet of Things technology, mark the ocean area covered by the Internet of Things devices as independent monitoring areas. Specifically, Internet of Things monitoring devices are set in each independent monitoring area, and all independent monitoring areas are combined into a complete monitored ocean area. Then, monitoring data collection is performed on the independent monitoring areas. The specific method for collecting monitoring data is:

[0052] Optionally select an independent monitoring area and mark this independent monitoring area as the target area. Then obtain the area information of the target area. Based on AI technology, use the area information as the input value, and let the AI device construct a simulation model for the area information to obtain a single-area model. The area information includes the shape and area of the target area. Further, the shape of the target area can be obtained by using image acquisition and recognition technology;

[0053] Then divide the target area into N equal parts according to the area of the target area, and mark each part of the area as an equal-area area. At this time, the target area is divided into N equal-area areas. Then mark the equal-area areas in the single-area model, identify the midpoints of the equal-area areas through image recognition processing technology, and mark them in the single-area model. Then use the points marked as midpoints in the single-area model as detection points, and according to the Internet of Things devices in the target area, collect the monitoring data of the ocean at the positions of each detection point, so as to monitor the ocean data;

[0054] It should be further noted that N in the N equal parts is a threshold value, and its specific value is set by those skilled in the art. And the image recognition processing technology is an existing technology, so it will not be elaborated here. The monitoring data includes parameters related to the ocean such as water temperature, salinity, pH value, and dissolved oxygen. The specific monitoring data is confirmed according to the actual monitoring needs;

[0055] Step 2: Obtain real-time monitoring data and historical monitoring data respectively, and perform distributed data processing to obtain a real-time data trust value. The specific processing methods of the distributed data processing include:

[0056] Mark the monitoring data collected in real time by the Internet of Things devices for the target area as real-time monitoring data HSn, where n represents different detection points in the target area, and n = 1, 2,..., N. Based on the data storage center in the target area, extract historical monitoring data, and mark the most recently collected monitoring data in the historical monitoring data as reference data HZn;

[0057] Based on the formula Obtain the trust coefficient Xn. Here, the trust coefficient refers to the value obtained by the real-time monitoring data based on the reference data, and C1 is the difference threshold value, and its specific value is obtained through multiple calculations of the historical monitoring data;

[0058] Further, use the formula Obtain the data trust value Rs, where XCp is the non-zero value in the trust coefficient Xn, that is, XCp = e -|HSn-HZn| |HSn - HZn| ≤ C1, a1 is the number of XCp in the trust coefficient Xn, a2 refers to the number of the trust coefficient Xn equal to 0, and a1 + a2 = N, and Kl is the monitoring coefficient;

[0059] It should be further noted that the data trust value here represents the comprehensive data trust value in the target area. When the comprehensive data trust value reaches the data threshold Ry1, that is, Rs≥Ry1, the real-time monitoring data of the target area is marked as valid data and transmitted to the data storage center of the target area for storage. On the contrary, when the data trust value is less than the data threshold Ry1, that is, Rs<Ry1, a data warning signal is generated and transmitted to the terminal device. The terminal device generates an audible and visual reminder message according to the received warning signal to remind relevant management personnel. The specific value of the data threshold Ry1 is set by those skilled in the art;

[0060] In another embodiment of the present invention, the calculation process of the monitoring coefficient Kl includes:

[0061] Based on the data storage center in the target area, taking the real-time monitoring data in the target area as the final node, extracting the first i historical monitoring data in the target area in chronological order, and at the same time taking the average value of each historical monitoring data, and taking the average value as the monitoring representative data BSi, i = 1, 2,..., I. Further, when i takes the value of I in BSi, it represents the monitoring representative data of the control data HZn;

[0062] Taking the monitoring representative data BSi as the input value, using the formula to obtain the monitoring coefficient Kl.

[0063] Embodiment 2. On the basis of Embodiment 1, the difference between this embodiment and Embodiment 1 is that this embodiment also includes data integration processing of ocean monitoring data. The specific data integration processing method is as follows:

[0064] S1: Sequentially obtain the transmission distance DSj between the ocean information general station and the independent monitoring area, where j represents the independent monitoring area, and j = 1, 2,..., J, indicating that there are J independent monitoring areas in this ocean area;

[0065] According to the transmission distance DSj, set the regional transmission route. Specifically, the method for setting the regional transmission route includes:

[0066] First, take the independent monitoring area corresponding to the maximum value of the transmission distance DSj and mark it as the long-distance area. At the same time, obtain the signal transmission route of the long-distance area, where the signal transmission route refers to the signal movement trajectory in which the independent monitoring area transmits the data signal to the ocean information general station through the transmission medium;

[0067] Based on this signal transmission route, calculate the distance between the positions of the remaining independent monitoring areas and the signal transmission route to obtain the proximity value. If the proximity value is less than or equal to Yd, mark the independent monitoring area corresponding to this proximity value as the covered area point in this signal transmission route. Conversely, if the proximity value is greater than Yd, do not process this independent monitoring area. Yd is the distance threshold, which is determined by those skilled in the art according to the actual transmission medium of the ocean data signal;

[0068] After the covered area points in this signal transmission route are marked, take this signal transmission line and its covered area points as the regional transmission route. At the same time, in the independent monitoring area, remove the marked area covered points, and process the remaining independent monitoring areas in the above manner to obtain the second regional transmission route, and so on, dividing the ocean area into multiple regional transmission routes;

[0069] S2: Select any one of the regional transmission routes as the target transmission route. Take the direction of the ocean information station transmitting signals to the independent monitoring area as the forward transmission. At this time, the direction of the independent monitoring area transmitting data information to the ocean information station is the reverse transmission;

[0070] When the command signal is transmitted in the forward transmission direction, according to the transmission distance DSa between each area covered point in the target transmission line and the ocean information station, set up level receiving stations, where a ∈ j, and a is the independent monitoring area in the target transmission line. The level receiving stations include the first receiving station, the second receiving station,..., the a-th receiving station;

[0071] Among them, the level receiving stations are set according to the transmission distance values, that is, mark the independent monitoring area corresponding to the minimum value of the transmission distance value DSa as the first receiving station, mark the independent monitoring area corresponding to the second smallest value of the transmission distance value DSa as the second receiving station,..., at this time, the last receiving station in the target transmission line is the receiving end of the signal transmission route;

[0072] S3: Sequentially obtain the far-distance areas in each regional transmission route. Divide the transmission distance by the transmission speed according to the transmission speed of the medium to obtain the one-way transmission time Tm of this far-distance area, where m represents different regional transmission routes;

[0073] It should be further noted that the one-way transmission time here specifically refers to the one-way information transmission time between the far-distance area in the regional transmission route and the ocean information station in this embodiment;

[0074] Identify the maximum value Tx in the one-way transmission time, where Tx ∈ Tm, and subtract Tx from the one-way transmission time Tm respectively to obtain the transmission time difference SCm of each regional transmission route;

[0075] Obtain the device receiving address of the remote area in the transmission route of each area, bind the device receiving address to the transmission time difference, add the instruction information to the bound data packet at the same time, and generate an instruction transmission packet. Then, the ocean information center station transmits the instruction transmission packet to the corresponding remote area respectively;

[0076] It should be further noted that the ocean information center station only sends the instruction transmission packet to the remote area in the transmission route of each area;

[0077] S4: When the receiving end of the remote area receives the instruction transmission packet, obtain the transmission time difference of this device according to the device receiving address of the receiving end. At the same time, taking the time when the device receives the instruction transmission packet as the starting time, use the transmission time difference as the interval time, and then obtain the data signal transmission time of this remote area;

[0078] It should be further noted that if the remote area is the one corresponding to the maximum value in the one-way transmission time of the area transmission route, at this time, the transmission time difference SCm = 0, and when the receiving end of this remote area receives the instruction transmission packet and identifies that the transmission time difference SCm = 0 at this time, the signal transmitting end immediately sends the data information of this area to the ocean information center station;

[0079] S5: Then, taking the remote area as the sending starting point and performing negative transmission on the data information, according to the set level receiving stations, signal is emitted layer by layer to the level receiving stations in sequence. Specifically, the method of signal layer-by-layer emission includes:

[0080] According to the level receiving stations, obtain the station distance between adjacent receiving stations in the target transmission route in sequence, divide the station distance by the signal transmission speed to get the station transfer time Tza;

[0081] Then obtain the transmission distance DSa between the area coverage point and the ocean information center station, divide the transmission distance DSa by the signal transmission speed to get the signal receiving time Tsa;

[0082] Use Tx - Tza - Tsa = Tca to obtain the real-time signal time difference Tca of each level receiving station. Then use Tca + TL = Tdl to obtain the station delay time difference Tdl, where TL is the station delay time difference of the previous receiving station, and if the station delay time difference Tdl in the previous receiving station is greater than or equal to 0, at this time, TL takes the value of 0. If the station delay time difference Tdl in the previous receiving station is less than 0, at this time, take the station delay time difference in the previous station as TL here;

[0083] Further, if the site delay time difference Tdl of this receiving site is less than 0, the signal receiving device will generate an immediate transmission signal, and at the same time bind the site delay time difference Tdl with the data information of the coverage points in this area to generate a data packet, and transmit it to the ocean signal main station. If the site delay time difference is greater than or equal to 0, starting from the time when the coverage point in the area receives the transmission signal, taking the site delay time difference as the interval time, the data sending time of this receiving site is obtained. When the real-time time is consistent with the data sending time of this site, at this time, this receiving site generates a data packet according to the instruction information, and the signal transmitting end transmits the data packet to the ocean information main station;

[0084] It should be further noted that when the a-th receiving site receives the transmission signal, the a-th signal receiving site sends the transmission signal to the (a - 1)-th receiving site according to the site delay time difference of its own site. The (a - 1)-th receiving site sends the transmission signal to the (a - 2)-th receiving site according to the receiving time of the transmission signal and the calculation of the site delay time difference;

[0085] S6: When the ocean information main station receives the data packet transmitted by the coverage point in the area, at this time, the ocean information main station first identifies the site delay time difference in the data packet, and takes the site delay time difference as the time compensation factor to perform time consistency compensation on the data receiving time of the ocean monitoring data in this instruction information. Then, when the ocean information main station receives the ocean monitoring data, it can ensure the consistency of the data receiving time, thereby reducing the data sorting time and further improving the data processing efficiency.

[0086] Embodiment 3. This embodiment is based on Embodiment 1 and Embodiment 2, and is used to fuse and implement Embodiment 1 and Embodiment 2.

[0087] The above is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention, according to the technical solution of the present invention and its inventive concept, makes equivalent substitutions or changes, and should be covered by the protection scope of the present invention.

Claims

1. A method for processing ocean monitoring data based on AI and Internet of Things technologies, characterized in that, The method specifically includes the following steps: Step 1: According to the area covered by the Internet of Things devices, divide the ocean area into several independent monitoring areas, and collect the monitoring data of the independent monitoring areas to obtain real-time monitoring data; Step 2: Obtain the historical monitoring data in the independent monitoring area, perform data calculation on the real-time monitoring data and the historical monitoring data to obtain a trust coefficient. According to the trust coefficient, judge the valid data of the real-time monitoring data. If the real-time monitoring data is valid data, store the real-time monitoring data in the data storage center of the independent monitoring area; Among them, the method for obtaining the trust coefficient includes: Mark the real-time monitoring data as HSn, where n represents different detection points in the target area, and n = 1, 2,..., N. Based on the data storage center in the target area, extract the historical monitoring data, and mark the most recently collected monitoring data in the historical monitoring data as the reference data HZn; Based on the formula The trust coefficient Xn is obtained, where the trust coefficient refers to the value obtained from the real-time monitoring data based on the reference data, and C1 is the difference threshold; Adopt to obtain the data trust value Rs, where XCp is the non-zero value in the trust coefficient Xn, a1 is the number of XCps in the trust coefficient Xn, a2 refers to the number of trust coefficients Xn equal to 0, and a1 + a2 = N, and Kl is the monitoring coefficient; When the data trust value reaches the data threshold Ry1, that is, Rs ≥ Ry1, mark the real-time monitoring data of the target area as valid data and transmit it to the data storage center of the target area for storage. On the contrary, when the data trust value is less than the data threshold Ry1, that is, Rs < Ry1, generate a data warning signal and transmit it to the terminal device; Further, the calculation process of the monitoring coefficient Kl includes: Taking the real-time monitoring data in the target area as the final node, extract the first i historical monitoring data in the target area in chronological order, and at the same time take the average value of each historical monitoring data and use the average value as the monitoring representative data BSi, where i = 1, 2,..., I; Taking the monitoring representative data BSi as the input value, using to obtain the monitoring coefficient Kl; Step 3: When the ocean information general station performs information integration processing on the independent monitoring area, first select the independent monitoring area corresponding to the maximum transmission distance according to the transmission distance between the ocean information general station and the independent monitoring area, and mark it as the long-distance area. Set the area transmission route according to the signal transmission route between the long-distance area and the ocean information general station; Step 4: Set a hierarchical receiving station for the independent monitoring area in the area transmission route, receive according to the level, and set the forward transmission direction and the reverse transmission direction according to the signal transmission direction between the ocean information general station and the independent monitoring area; Step 5: According to the transmission distance of the long-distance area in each area transmission route and the transmission speed of the medium, obtain the one-way transmission time. Determine the transmission time difference of each area transmission route from the maximum value in the one-way transmission time. Then the ocean information general station binds the transmission time difference with the command information and generates a command data packet, and transmits it to the long-distance area respectively; Step 6: The long-distance area determines the data sending time of this receiving station according to the transmission time difference in the command transmission packet, and sequentially emits signals layer by layer to the hierarchical receiving stations according to the set hierarchical receiving stations. And when the real-time time is the same as the data sending time, this receiving station sends a data packet and a transmission signal to the ocean information general station and the next receiving station respectively.

2. The marine monitoring data processing method based on AI and Internet of Things technology according to claim 1, characterized in that, The method for obtaining real-time monitoring data includes: Optionally select an independent monitoring area, mark it as the target area, obtain the area information of the target area, and based on AI technology, use the area information as the input value. Let the AI device construct a simulation model for the area information to obtain a single-area model, where the area information includes the shape and area of the target area; According to the area of the target area, divide the target area into N equal-area regions, mark the equal-area regions in the single-area model, identify the midpoints of the equal-area regions through image recognition processing technology, and use the midpoint of the single-area model as the detection point. Collect the monitoring data of the ocean according to the position of each detection point to obtain real-time monitoring data.

3. A method for processing marine monitoring data based on AI and Internet of Things technologies according to claim 1, characterized in that, The setting method of the area transmission route includes: Successively obtain the transmission distance DSj between the ocean information general station and the independent monitoring area, where j represents the independent monitoring area, and j = 1, 2, ……, J, indicating that there are J independent monitoring areas in this ocean area; Select the independent monitoring area corresponding to the maximum value of the transmission distance DSj and mark it as the long-distance area, and at the same time obtain the signal transmission route of the long-distance area; Based on this signal transmission route, calculate the distance between the positions of the remaining independent monitoring areas and the signal transmission route to obtain a short-distance value. If the short-distance value is less than or equal to Yd, mark the independent monitoring area corresponding to this short-distance value as the coverage area point in this signal transmission route. Otherwise, if the short-distance value is greater than Yd, do not process this independent monitoring area. Yd is the distance threshold; After the coverage area points in this signal transmission route are marked, use this signal transmission line and its coverage area points as the area transmission route. At the same time, in the independent monitoring area, remove the marked area coverage points, and process the remaining independent monitoring areas in the above manner to obtain the second area transmission route, and so on, dividing the ocean area into multiple area transmission routes.

4. The marine monitoring data processing method based on AI and Internet of Things technology according to claim 3, characterized in that, The setting method of the level receiving station and the signal transmission direction is: Select any one area transmission route as the target transmission route, and take the direction of the signal transmission from the ocean information general station to the independent monitoring area as the forward transmission. At this time, the direction of the data information transmission from the independent monitoring area to the ocean information general station is the reverse transmission; When the command signal is transmitted in the forward transmission direction, establish level receiving stations according to the transmission distance DSa between each area coverage point in the target transmission line and the ocean information general station, where a ∈ j, and a is the independent monitoring area in the target transmission line. The level receiving stations include the first receiving station, the second receiving station, ……, the a-th receiving station.

5. A method for processing ocean monitoring data based on AI and Internet of Things technologies according to claim 1, characterized in that, The generation method of the command data packet includes: Successively obtain the long-distance areas in each area transmission route, and divide the transmission distance by the transmission speed according to the transmission speed of the medium to obtain the one-way transmission time Tm of this long-distance area, where m represents different area transmission routes; Identify the maximum value Tx in the one-way transmission time, where Tx ∈ Tm, and subtract Tx from the one-way transmission time Tm respectively to obtain the transmission time difference SCm of each area transmission route; Obtain the device receiving address of the remote area in each regional transmission route, bind the device receiving address to the transmission time difference, add the instruction information to the bound data packet at the same time, and generate an instruction transmission packet. Then, the ocean information terminal station transmits the instruction transmission packet to the corresponding remote area respectively.

6. The marine monitoring data processing method based on AI and Internet of Things technology according to claim 1, wherein The specific transmission method of signal layer-by-layer emission includes: According to the hierarchical receiving stations, sequentially obtain the station distance between adjacent receiving stations in the target transmission route, divide the station distance by the signal transmission speed to obtain the station transmission time Tza; Obtain the transmission distance DSa between the area coverage point and the ocean information terminal station, divide the transmission distance DSa by the signal transmission speed to obtain the signal receiving time Tsa; Use Tx - Tza - Tsa = Tca to obtain the real-time signal time difference Tca of each hierarchical receiving station. At the same time, use Tca + TL = Td1 to obtain the station delay time difference Tdl, where TL is the station delay time difference of the previous receiving station; If the station delay time difference Tdl of the current receiving station is less than 0, the signal receiving device will generate an immediate transmission signal, bind the station delay time difference Tdl to the data information of this area coverage point at the same time, generate a data packet, and transmit it to the ocean information terminal station. If the station delay time difference is greater than or equal to 0, starting from the time when the area coverage point receives the transmission signal, use the station delay time difference as the interval time to obtain the data sending time of this receiving station. When the real-time time is the same as the data sending time of this station, the receiving station generates a data packet according to the instruction information at this time, and the signal transmitting end transmits the data packet to the ocean information terminal station.

7. A method for processing ocean monitoring data based on AI and Internet of Things technologies according to claim 6, characterized in that, When the ocean information terminal station receives the data packet transmitted by the area coverage point, the ocean information terminal station first identifies the station delay time difference in the data packet at this time, and uses the station delay time difference as a time compensation factor to perform time consistency compensation on the data receiving time of the ocean monitoring data in this instruction information.

8. A method for processing ocean monitoring data based on AI and Internet of Things technologies according to claim 7, characterized in that, The specific method for the value of TL includes: If the station delay time difference Tdl in the previous receiving station is greater than or equal to 0, at this time, the value of TL is 0. If the station delay time difference Tdl in the previous receiving station is less than 0, at this time, use the station delay time difference in the previous station as TL here.

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