A mobile delivery control system and method for intelligent weather detection device

Abstract

The present invention relates to the field of delivery control technology, and is a mobile delivery control system and method for intelligent meteorological detection devices. The specific method includes: collecting historical working performance data of meteorological detection points and meteorological data processing center base stations; calculating the processing capacity fluctuation value of the meteorological data processing center base station where the meteorological detection point is located, and determining the delivery strategy of the intelligent meteorological detection device in the meteorological area under the jurisdiction of the meteorological data processing center base station; controlling the delivery of the intelligent meteorological detection device, and performing landing posture compliance verification processing and working range compliance verification processing after the delivery is completed; evaluating the delivery success rate according to the landing posture compliance rate and the working range compliance rate, and performing subsequent adjustment processing on the intelligent meteorological detection device that has been delivered through the delivery success rate. The present invention solves the problems in the prior art that the coverage of meteorological detection devices is limited, the system flexibility is poor, and the timeliness of data cannot be guaranteed.

Description

Technical Field

[0001] The invention relates to the technical field of delivery control, and is a motorized delivery control system and method for an intelligent meteorological detection device. Background Art

[0002] In the application field of intelligent meteorological detection devices, traditional meteorological detection methods usually rely on detection equipment in fixed positions. These devices have certain limitations in the collection and processing of meteorological data, including: the processing capacity of the existing meteorological data processing center base station fluctuates greatly, making it difficult to ensure the real-time and accuracy of the data. At the same time, the traditional deployment strategy lacks dynamic adjustment of the processing capacity of the meteorological data processing center base station and cannot be flexibly deployed according to actual needs. In addition, during the deployment of intelligent meteorological detection devices, there is a lack of effective landing posture, working range verification and subsequent adjustment mechanisms, resulting in a low deployment success rate and uneven quality of the meteorological data transmitted back. Summary of the invention

[0003] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0004] The technical problem to be solved by the present invention is to address the problems in the prior art that meteorological detection devices have limited coverage, poor system flexibility and data timeliness cannot be guaranteed; a mobile deployment control system and method for intelligent meteorological detection devices are proposed.

[0005] In order to achieve the above object, the technical solution of a mobile deployment control method for an intelligent meteorological detection device of the present invention comprises the following steps:

[0006] S1: Collect and organize the historical performance data of meteorological detection points and meteorological data processing center base stations in the target meteorological monitoring area during the previous deployment cycle;

[0007] S2: Calculate the historical timeliness guarantee value of the meteorological data transmitted back by the meteorological detection point through the historical work performance data, and calculate the processing capacity fluctuation value of the meteorological data processing center base station where the meteorological detection point is located according to the historical timeliness guarantee value;

[0008] S3: Determine the deployment strategy of the intelligent meteorological detection device in the meteorological area under the jurisdiction of the meteorological data processing center base station according to the processing capacity fluctuation value of the meteorological data processing center base station;

[0009] S4: According to the delivery strategy, the intelligent meteorological detection device is controlled and delivered by using a drone, and after the delivery is completed, a landing posture compliance verification process and a working range compliance verification process are performed;

[0010] S5: Evaluate the placement success rate based on the landing posture compliance rate and the working range compliance rate, and make subsequent adjustments to the deployed intelligent meteorological detection device based on the placement success rate.

[0011] Specifically, in S2, the calculation strategy of the historical timeliness guarantee value of the meteorological data transmitted back by the meteorological detection point is as follows:

[0012] ;

[0013] Among them, there are N meteorological data processing center base stations in the target meteorological monitoring area, and n is the index number of the meteorological data processing center base station;

[0014] There are I meteorological detection points in the nth meteorological data processing center base station, where i is the index of the meteorological detection point;

[0015] The total number of meteorological data transmitted from the ith meteorological detection point to the meteorological data processing center base station during the last launch cycle is Group, It is the label index of meteorological data;

[0016] is the historical timeliness guarantee value of the meteorological data transmitted back from the ith meteorological detection point;

[0017] They are respectively the average number of meteorological data sets processed per day and the maximum number of meteorological data sets processed per day by the nth meteorological data processing center base station in the previous launch cycle;

[0018] Respectively The data delay impact ratio coefficient and the data packet loss impact ratio coefficient of the group meteorological data;

[0019] Respectively The delay time and number of packet losses when the meteorological data is transmitted back to the base station of the meteorological data processing center.

[0020] Specifically, S2 also includes the following steps:

[0021] S21: Extract the average value of the historical timeliness guarantee value of I meteorological detection points in the nth meteorological data processing center base station ;

[0022] S22: According to S21, the processing capacity fluctuation value of the meteorological data processing center base station where the meteorological detection point is located is calculated. The calculation strategy is as follows:

[0023] .

[0024] Specifically, S3 includes the following specific steps:

[0025] S31: extracting the processing capacity fluctuation values ​​of all meteorological data processing center base stations in the target meteorological monitoring area, and arranging the processing capacity fluctuation values ​​of all meteorological data processing center base stations in descending order, and selecting the median processing capacity fluctuation value in the sequence as the evaluation standard value;

[0026] S32: when the processing capacity fluctuation value of the nth meteorological data processing center base station is greater than the evaluation standard value, it is determined that the meteorological area under the jurisdiction of the nth meteorological data processing center base station needs to adjust the deployment of the intelligent meteorological detection device, otherwise, the deployment of the intelligent meteorological detection device is adjusted;

[0027] S33: Extract the processing capacity fluctuation values ​​of the meteorological data processing center base stations that do not need to be adjusted, forming a processing capacity fluctuation value set A, and at the same time extract the number of meteorological detection points in the meteorological data processing center base stations that do not need to be adjusted, forming a meteorological detection point number set B.

[0028] Specifically, S3 also includes the following specific steps:

[0029] S34: When it is determined that the meteorological area under the jurisdiction of the nth meteorological data processing center base station needs to adjust the deployment of intelligent meteorological detection devices, the number of intelligent meteorological detection devices that need to be adjusted in the nth meteorological data processing center base station is calculated. The calculation strategy is:

[0030] ;

[0031] in, are the maximum processing capacity fluctuation value and the maximum processing capacity fluctuation value in the processing capacity fluctuation value set A respectively;

[0032] for The number of meteorological detection points contained in the meteorological area under the jurisdiction of the corresponding meteorological data processing center base station;

[0033] for The number of meteorological detection points contained in the meteorological area under the jurisdiction of the corresponding meteorological data processing center base station;

[0034] is the processing capacity fluctuation value set A, and The processing capacity fluctuation value with the smallest difference;

[0035] for The number of meteorological detection points contained in the meteorological area under the jurisdiction of the corresponding meteorological data processing center base station;

[0036] is the number of meteorological detection points in the previous launch cycle;

[0037] S35: Extract the number of intelligent meteorological detection devices that need to be adjusted ;

[0038] when When it is a positive number, the deployment of intelligent meteorological detection devices in the meteorological area under the jurisdiction of the nth meteorological data processing center base station is increased;

[0039] Among them, the candidate placement location with the highest solar irradiance in the meteorological area under the jurisdiction of the nth meteorological data processing center base station is preferentially selected as the placement target location of this placement cycle;

[0040] when When it is a negative number, in the meteorological area under the jurisdiction of the nth meteorological data processing center base station, the meteorological detection point with the smallest historical timeliness guarantee value is preferentially selected for work suspension processing.

[0041] Specifically, in S4, the landing posture compliance verification process includes the following specific steps:

[0042] S41: Use IMU and GPS system to monitor and record the attitude data of meteorological device in real time when it is deployed;

[0043] S42: Fusing IMU and GPS data to calculate the attitude information of the meteorological device, including: assuming the initial attitude quaternion is ;

[0044] S43: Update quaternion according to gyroscope data, , is the rate of change of the quaternion, The time step is The quaternion state at time ; is quaternion multiplication, is the angular velocity collected by the gyroscope;

[0045] S44: Update the quaternion by integration at the same time, , is the currently updated quaternion state, is the time step;

[0046] S45: Perform attitude correction using accelerometer data, including: , , ,in, They are the attitude angle difference, latitude difference and altitude difference of the deployed intelligent meteorological detection device respectively; They are the attitude angle calculated by the accelerometer and the attitude angle calculated by the gyroscope respectively; They are the latitude collected by the GPS system and the latitude collected by the IMU; They are the altitude collected by the GPS system and the altitude collected by the IMU;

[0047] S46: Extraction , and update the quaternion, specifically:

[0048] ;

[0049] in, is the updated quaternion;

[0050] S47: Convert the updated quaternion into a pitch angle , and calculate the landing posture compliance rate , , This is the standard delivery pitch angle.

[0051] Specifically, in S4, the working range compliance verification process includes the following specific steps:

[0052] S48: Using the GPS system to collect the geographic coordinates of the meteorological device in real time, the geographic coordinates are expressed as ;

[0053] S49: Setting a preset working range of the intelligent weather detection device, wherein the preset working range is a polygonal area, and the coordinates of the kth vertex are , k is the index of the vertex sequence of the polygonal area, and the polygonal area has a total of K vertices;

[0054] S410: Collect the meteorological data points Convert to projected coordinates, including:

[0055] , where R is the radius of the earth;

[0056] S411: Determining the coverage ratio between the actual working range of the intelligent meteorological detection device and the preset working range, including: ;

[0057] Among them, from point Send a horizontal ray to the right, and count the number of intersections between this ray and the polygon edge. , indicating the judgment point Whether it falls on the line segment If it is on the right side, The function returns 1, otherwise, The function returns 0;

[0058] It means calculating the total number of intersections of all line segments and taking the modulo 2;

[0059] S412: Calculate the work scope compliance rate based on S48-S412 ,

[0060] ;

[0061] in, The number of inspection points determined to fall within the preset working range in S411; is the total number of inspection points.

[0062] Specifically, in S5, the evaluation strategy of the delivery success rate is:

[0063] ;

[0064] Among them, E is the delivery success rate.

[0065] Specifically, in S5, the subsequent adjustment process includes: presetting a delivery success rate threshold, and when the delivery success rate of the intelligent meteorological detection device is lower than the delivery success rate threshold, sending a delivery failure to be adjusted prompt to the management personnel.

[0066] In addition, the present invention provides a mobile delivery control system for an intelligent weather detection device, including the following modules:

[0067] Historical work performance data collection module, processing capacity fluctuation value calculation module, delivery strategy confirmation module, delivery verification module and delivery success rate evaluation module;

[0068] The historical work performance data collection module is used to collect and organize the historical work performance data of the meteorological detection points and the meteorological data processing center base stations in the target meteorological monitoring area during the previous delivery cycle;

[0069] The processing capacity fluctuation value calculation module calculates the historical timeliness guarantee value of the meteorological data transmitted back by the meteorological detection point through the historical work performance data, and calculates the processing capacity fluctuation value of the meteorological data processing center base station where the meteorological detection point is located according to the historical timeliness guarantee value;

[0070] The deployment strategy confirmation module determines the deployment strategy of the intelligent meteorological detection device in the meteorological area under the jurisdiction of the meteorological data processing center base station according to the processing capacity fluctuation value of the meteorological data processing center base station;

[0071] The delivery verification module controls the delivery of the intelligent meteorological detection device using a drone according to the delivery strategy, and performs landing posture compliance verification processing and working range compliance verification processing after the delivery is completed;

[0072] The delivery success rate evaluation module evaluates the delivery success rate according to the landing posture compliance rate and the working range compliance rate, and performs subsequent adjustment processing on the intelligent meteorological detection device that has been delivered.

[0073] A storage medium stores instructions, and when a computer reads the instructions, the computer executes the mobile delivery control method for an intelligent meteorological detection device.

[0074] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the above-mentioned mobile delivery control method for an intelligent meteorological detection device is implemented.

[0075] Compared with the prior art, the technical effects of the present invention are as follows:

[0076] 1. The present invention comprehensively considers the impact of data delay and packet loss, and the calculation of the historical time guarantee value is more accurate. At the same time, by comprehensively evaluating the processing capacity fluctuation values ​​of different meteorological data processing center base stations, the data processing is made more balanced and efficient, thereby improving the real-time and accuracy of the data.

[0077] 2. The present invention dynamically determines the delivery strategy according to the processing capacity fluctuation value of the base station of the meteorological data processing center, making the delivery strategy more flexible and adaptable, and being able to effectively cope with the complex and changeable meteorological environment.

[0078] 3. The present invention monitors and records the delivery posture data in real time, combines the IMU and GPS systems to perform posture correction, and ensures that the delivery posture meets the standard. At the same time, the GPS system collects geographic coordinates in real time to determine the coverage rate of the actual working range and the preset working range to ensure that the working range meets the standard. A scientific delivery success rate evaluation model is established by comprehensively evaluating the landing posture compliance rate and the working range compliance rate to accurately reflect the delivery effect and improve the delivery success rate. BRIEF DESCRIPTION OF THE DRAWINGS

[0079] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0080] Figure 1 A schematic flow chart of a method for controlling the motorized deployment of an intelligent meteorological detection device according to the present invention;

[0081] Figure 2 The present invention is a schematic structural diagram of a mobile delivery control system for an intelligent meteorological detection device. DETAILED DESCRIPTION

[0082] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0083] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0084] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0085] Embodiment 1:

[0086] like Figure 1 As shown, a method for controlling the mobile deployment of an intelligent meteorological detection device according to an embodiment of the present invention is as follows: Figure 1 As shown, the specific steps are as follows:

[0087] S1: Collect and organize the historical performance data of meteorological detection points and meteorological data processing center base stations in the target meteorological monitoring area during the previous deployment cycle;

[0088] S2: Calculate the historical timeliness guarantee value of the meteorological data transmitted back by the meteorological detection point through the historical work performance data, and calculate the processing capacity fluctuation value of the meteorological data processing center base station where the meteorological detection point is located according to the historical timeliness guarantee value;

[0089] In S2, the calculation strategy of the historical timeliness guarantee value of the meteorological data transmitted back by the meteorological detection point is as follows:

[0090] ;

[0091] Among them, there are N meteorological data processing center base stations in the target meteorological monitoring area, and n is the index number of the meteorological data processing center base station;

[0092] There are I meteorological detection points in the nth meteorological data processing center base station, where i is the index of the meteorological detection point;

[0093] The total number of meteorological data transmitted from the ith meteorological detection point to the meteorological data processing center base station during the last launch cycle is Group, It is the label index of meteorological data;

[0094] is the historical timeliness guarantee value of the meteorological data transmitted back from the ith meteorological detection point;

[0095] They are respectively the average number of meteorological data sets processed per day and the maximum number of meteorological data sets processed per day by the nth meteorological data processing center base station in the previous launch cycle;

[0096] Respectively The data delay impact ratio coefficient and the data packet loss impact ratio coefficient of the group meteorological data;

[0097] Respectively The delay time and number of packet losses when the meteorological data is transmitted back to the base station of the meteorological data processing center.

[0098] S2 also includes the following steps:

[0099] S21: Extract the average value of the historical timeliness guarantee value of I meteorological detection points in the nth meteorological data processing center base station ;

[0100] S22: According to S21, the processing capacity fluctuation value of the meteorological data processing center base station where the meteorological detection point is located is calculated. The calculation strategy is as follows:

[0101] .

[0102] S3: Determine the deployment strategy of the intelligent meteorological detection device in the meteorological area under the jurisdiction of the meteorological data processing center base station according to the processing capacity fluctuation value of the meteorological data processing center base station;

[0103] S3 includes the following specific steps:

[0104] S31: extracting the processing capacity fluctuation values ​​of all meteorological data processing center base stations in the target meteorological monitoring area, and arranging the processing capacity fluctuation values ​​of all meteorological data processing center base stations in descending order, and selecting the median processing capacity fluctuation value in the sequence as the evaluation standard value;

[0105] S32: when the processing capacity fluctuation value of the nth meteorological data processing center base station is greater than the evaluation standard value, it is determined that the meteorological area under the jurisdiction of the nth meteorological data processing center base station needs to adjust the deployment of the intelligent meteorological detection device, otherwise, the deployment of the intelligent meteorological detection device is adjusted;

[0106] S33: Extract the processing capacity fluctuation values ​​of the meteorological data processing center base stations that do not need to be adjusted, forming a processing capacity fluctuation value set A, and at the same time extract the number of meteorological detection points in the meteorological data processing center base stations that do not need to be adjusted, forming a meteorological detection point number set B.

[0107] S3 also includes the following specific steps:

[0108] S34: When it is determined that the meteorological area under the jurisdiction of the nth meteorological data processing center base station needs to adjust the deployment of intelligent meteorological detection devices, the number of intelligent meteorological detection devices that need to be adjusted in the nth meteorological data processing center base station is calculated. The calculation strategy is:

[0109] ;

[0110] in, are the maximum processing capacity fluctuation value and the maximum processing capacity fluctuation value in the processing capacity fluctuation value set A respectively;

[0111] for The number of meteorological detection points contained in the meteorological area under the jurisdiction of the corresponding meteorological data processing center base station;

[0112] for The number of meteorological detection points contained in the meteorological area under the jurisdiction of the corresponding meteorological data processing center base station;

[0113] is the processing capacity fluctuation value set A, and The processing capacity fluctuation value with the smallest difference;

[0114] for The number of meteorological detection points contained in the meteorological area under the jurisdiction of the corresponding meteorological data processing center base station;

[0115] is the number of meteorological detection points in the previous launch cycle;

[0116] S35: Extract the number of intelligent meteorological detection devices that need to be adjusted ;

[0117] when When it is a positive number, the deployment of intelligent meteorological detection devices in the meteorological area under the jurisdiction of the nth meteorological data processing center base station is increased;

[0118] Among them, the candidate placement location with the highest solar irradiance in the meteorological area under the jurisdiction of the nth meteorological data processing center base station is preferentially selected as the placement target location of this placement cycle;

[0119] when When it is a negative number, in the meteorological area under the jurisdiction of the nth meteorological data processing center base station, the meteorological detection point with the smallest historical timeliness guarantee value is preferentially selected for work suspension processing.

[0120] S4: According to the delivery strategy, the intelligent meteorological detection device is controlled and delivered by using a drone, and after the delivery is completed, a landing posture compliance verification process and a working range compliance verification process are performed;

[0121] In S4, the landing posture compliance verification process includes the following specific steps:

[0122] S41: Use IMU and GPS systems to monitor and record the attitude data of meteorological devices in real time when they are deployed;

[0123] S42: Fusing IMU and GPS data to calculate the attitude information of the meteorological device, including: assuming the initial attitude quaternion is ;

[0124] S43: Update quaternion according to gyroscope data, , is the rate of change of the quaternion, The time step is The quaternion state at time ; is quaternion multiplication, is the angular velocity collected by the gyroscope;

[0125] S44: Update the quaternion by integration at the same time, , is the currently updated quaternion state, is the time step;

[0126] S45: Perform attitude correction using accelerometer data, including: , , ,in, They are the attitude angle difference, latitude difference and altitude difference of the deployed intelligent meteorological detection device respectively; They are the attitude angle calculated by the accelerometer and the attitude angle calculated by the gyroscope respectively; They are the latitude collected by the GPS system and the latitude collected by the IMU; They are the altitude collected by the GPS system and the altitude collected by the IMU;

[0127] S46: Extraction , and update the quaternion, specifically:

[0128] ;

[0129] in, is the updated quaternion;

[0130] S47: Convert the updated quaternion into a pitch angle , and calculate the landing posture compliance rate , , This is the standard delivery pitch angle.

[0131] In S4, the working range compliance verification process includes the following specific steps:

[0132] S48: Using the GPS system to collect the geographic coordinates of the meteorological device in real time, the geographic coordinates are expressed as ;

[0133] S49: Setting a preset working range of the intelligent weather detection device, wherein the preset working range is a polygonal area, and the coordinates of the kth vertex are , k is the index of the vertex sequence of the polygonal area, and the polygonal area has a total of K vertices;

[0134] S410: Collect the meteorological data points Convert to projected coordinates, including:

[0135] , where R is the radius of the earth;

[0136] S411: Determining the coverage ratio between the actual working range of the intelligent meteorological detection device and the preset working range, including: ;

[0137] Among them, from point Send a horizontal ray to the right, and count the number of intersections between this ray and the polygon edge. , indicating the judgment point Whether it falls on the line segment If it is on the right side, The function returns 1, otherwise, The function returns 0;

[0138] It means calculating the total number of intersections of all line segments and taking the modulus 2;

[0139] S412: Calculate the work scope compliance rate based on S48-S412 ,

[0140] ;

[0141] in, The number of inspection points determined to fall within the preset working range in S411; is the total number of inspection points.

[0142] S5: Evaluate the placement success rate based on the landing posture compliance rate and the working range compliance rate, and make subsequent adjustments to the deployed intelligent meteorological detection device based on the placement success rate.

[0143] In S5, the evaluation strategy of the delivery success rate is:

[0144] ;

[0145] Among them, E is the delivery success rate.

[0146] In S5, the subsequent adjustment process includes: presetting a delivery success rate threshold, and when the delivery success rate of the intelligent meteorological detection device is lower than the delivery success rate threshold, sending a delivery failure to be adjusted prompt to the management personnel.

[0147] Embodiment 2:

[0148] like Figure 2 As shown, a mobile delivery control system for an intelligent weather detection device according to an embodiment of the present invention is as follows: Figure 2 As shown, it includes the following modules:

[0149] Historical work performance data collection module, processing capacity fluctuation value calculation module, delivery strategy confirmation module, delivery verification module and delivery success rate evaluation module;

[0150] The historical work performance data collection module is used to collect and organize the historical work performance data of the meteorological detection points and the meteorological data processing center base stations in the target meteorological monitoring area during the previous delivery cycle;

[0151] The processing capacity fluctuation value calculation module calculates the historical timeliness guarantee value of the meteorological data transmitted back by the meteorological detection point through the historical work performance data, and calculates the processing capacity fluctuation value of the meteorological data processing center base station where the meteorological detection point is located according to the historical timeliness guarantee value;

[0152] The deployment strategy confirmation module determines the deployment strategy of the intelligent meteorological detection device in the meteorological area under the jurisdiction of the meteorological data processing center base station according to the processing capacity fluctuation value of the meteorological data processing center base station;

[0153] The delivery verification module controls the delivery of the intelligent meteorological detection device using a drone according to the delivery strategy, and performs landing posture compliance verification processing and working range compliance verification processing after the delivery is completed;

[0154] The delivery success rate evaluation module evaluates the delivery success rate according to the landing posture compliance rate and the working range compliance rate, and performs subsequent adjustment processing on the intelligent meteorological detection device that has been delivered.

[0155] Embodiment three:

[0156] This embodiment provides an electronic device, including: a processor and a memory, wherein the memory stores a computer program that can be called by the processor;

[0157] The processor executes the above-mentioned mobile delivery control method for the intelligent meteorological detection device by calling the computer program stored in the memory.

[0158] The electronic device may have relatively large differences due to different configurations or performances, and may include one or more processors (Central Processing Units, CPU) and one or more memories, wherein the memory stores at least one computer program, and the computer program is loaded and executed by the processor to implement a mobile delivery control method for an intelligent meteorological detection device provided in the above method embodiment. The electronic device may also include other components for realizing the functions of the device. For example, the electronic device may also have components such as a wired or wireless network interface and an input and output interface to input and output data. This embodiment will not be described in detail here.

[0159] Embodiment 4:

[0160] This embodiment provides a computer-readable storage medium having a rewritable computer program stored thereon;

[0161] When the computer program runs on a computer device, the computer device executes the above-mentioned method for controlling the motorized deployment of an intelligent meteorological detection device.

[0162] For example, the computer readable storage medium can be a read-only memory (ROM), a random access memory (RAM), a compact disc (CD-ROM), a magnetic tape, a floppy disk, an optical data storage device, etc.

[0163] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0164] It should be understood that determining B based on A does not mean determining B only based on A. B can also be determined based on A and / or other information.

[0165] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When a computer instruction or computer program is loaded or executed on a computer, a process or function according to an embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. Computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center through a wired network or / and a wireless network. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0166] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in the present invention can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0167] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0168] In the several embodiments provided by the present invention, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of units is only one, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0169] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0170] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0171] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0172] In summary, compared with the prior art, the technical effects of the present invention are as follows:

[0173] 1. The present invention comprehensively considers the impact of data delay and packet loss, and the calculation of the historical time guarantee value is more accurate. At the same time, by comprehensively evaluating the processing capacity fluctuation values ​​of different meteorological data processing center base stations, the data processing is made more balanced and efficient, thereby improving the real-time and accuracy of the data.

[0174] 2. The present invention dynamically determines the delivery strategy according to the processing capacity fluctuation value of the base station of the meteorological data processing center, making the delivery strategy more flexible and adaptable, and being able to effectively cope with the complex and changeable meteorological environment.

[0175] 3. The present invention monitors and records the delivery posture data in real time, combines the IMU and GPS system to perform posture correction, and ensures that the delivery posture meets the standard. At the same time, the GPS system collects geographic coordinates in real time, determines the coverage rate of the actual working range and the preset working range, ensures that the working range meets the standard, and uses a comprehensive evaluation of the landing posture compliance rate and the working range compliance rate to establish a scientific delivery success rate evaluation model, accurately reflect the delivery effect, and improve the delivery success rate.

[0176] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A method for controlling the mobile deployment of an intelligent meteorological detection device, characterized in that: The method comprises the following specific steps: S1: Collect and organize the historical performance data of meteorological detection points and meteorological data processing center base stations in the target meteorological monitoring area during the previous deployment cycle; S2: Calculate the historical timeliness guarantee value of the meteorological data transmitted back by the meteorological detection point through the historical work performance data, and calculate the processing capacity fluctuation value of the meteorological data processing center base station where the meteorological detection point is located according to the historical timeliness guarantee value; The calculation strategy of the historical timeliness guarantee value of the meteorological data transmitted back by the meteorological detection point is as follows: ； Among them, there are N meteorological data processing center base stations in the target meteorological monitoring area, and n is the index number of the meteorological data processing center base station; There are I meteorological detection points in the nth meteorological data processing center base station, where i is the index of the meteorological detection point; The total number of meteorological data transmitted from the ith meteorological detection point to the meteorological data processing center base station during the last launch cycle is Group, It is the label index of meteorological data; is the historical timeliness guarantee value of the meteorological data transmitted back from the ith meteorological detection point; They are respectively the average number of meteorological data sets processed per day and the maximum number of meteorological data sets processed per day by the nth meteorological data processing center base station in the previous launch cycle; Respectively The data delay impact ratio coefficient and the data packet loss impact ratio coefficient of the group meteorological data; Respectively The delay time and number of packet losses when the meteorological data is transmitted back to the base station of the meteorological data processing center; S2 also includes the following steps: S21: Extract the average value of the historical timeliness guarantee value of I meteorological detection points in the nth meteorological data processing center base station ; S22: According to S21, the processing capacity fluctuation value of the meteorological data processing center base station where the meteorological detection point is located is calculated. The calculation strategy is as follows: ； S3: Determine the deployment strategy of the intelligent meteorological detection device in the meteorological area under the jurisdiction of the meteorological data processing center base station according to the processing capacity fluctuation value of the meteorological data processing center base station; S4: According to the delivery strategy, the intelligent meteorological detection device is controlled and delivered by using a drone, and after the delivery is completed, a landing posture compliance verification process and a working range compliance verification process are performed; S5: Evaluate the placement success rate based on the landing posture compliance rate and the working range compliance rate, and make subsequent adjustments to the deployed intelligent meteorological detection device based on the placement success rate.

2. A method for controlling the mobile deployment of an intelligent meteorological detection device according to claim 1, characterized in that: S3 includes the following specific steps: S31: extracting the processing capacity fluctuation values ​​of all meteorological data processing center base stations in the target meteorological monitoring area, and arranging the processing capacity fluctuation values ​​of all meteorological data processing center base stations in descending order, and selecting the median processing capacity fluctuation value in the sequence as the evaluation standard value; S32: when the processing capacity fluctuation value of the nth meteorological data processing center base station is greater than the evaluation standard value, it is determined that the meteorological area under the jurisdiction of the nth meteorological data processing center base station needs to adjust the deployment of the intelligent meteorological detection device, otherwise, the deployment of the intelligent meteorological detection device is adjusted; S33: Extract the processing capacity fluctuation values ​​of the meteorological data processing center base stations that do not need to be adjusted, forming a processing capacity fluctuation value set A, and at the same time extract the number of meteorological detection points in the meteorological data processing center base stations that do not need to be adjusted, forming a meteorological detection point number set B.

3. A method for controlling the mobile deployment of an intelligent meteorological detection device according to claim 2, characterized in that: S3 also includes the following specific steps: S34: When it is determined that the meteorological area under the jurisdiction of the nth meteorological data processing center base station needs to adjust the deployment of intelligent meteorological detection devices, the number of intelligent meteorological detection devices that need to be adjusted in the nth meteorological data processing center base station is calculated. The calculation strategy is: ； in, are the maximum processing capacity fluctuation value and the maximum processing capacity fluctuation value in the processing capacity fluctuation value set A respectively; for The number of meteorological detection points contained in the meteorological area under the jurisdiction of the corresponding meteorological data processing center base station; for The number of meteorological detection points contained in the meteorological area under the jurisdiction of the corresponding meteorological data processing center base station; is the processing capacity fluctuation value set A, and The processing capacity fluctuation value with the smallest difference; for The number of meteorological detection points contained in the meteorological area under the jurisdiction of the corresponding meteorological data processing center base station; is the number of meteorological detection points in the previous launch cycle; S35: Extract the number of intelligent meteorological detection devices that need to be adjusted ; when When it is a positive number, the deployment of intelligent meteorological detection devices in the meteorological area under the jurisdiction of the nth meteorological data processing center base station is increased; Among them, the candidate placement location with the highest solar irradiance in the meteorological area under the jurisdiction of the nth meteorological data processing center base station is preferentially selected as the placement target location of this placement cycle; when When it is a negative number, in the meteorological area under the jurisdiction of the nth meteorological data processing center base station, the meteorological detection point with the smallest historical timeliness guarantee value is preferentially selected for work suspension processing.

4. A method for controlling the mobile deployment of an intelligent meteorological detection device according to claim 3, characterized in that: In S4, the landing posture compliance verification process includes the following specific steps: S41: Use IMU and GPS systems to monitor and record the attitude data of meteorological devices in real time when they are deployed; S42: Fusing IMU and GPS data to calculate the attitude information of the meteorological device, including: assuming the initial attitude quaternion is ; S43: Update quaternion according to gyroscope data, , is the rate of change of the quaternion, The time step is The quaternion state at time ; is quaternion multiplication, is the angular velocity collected by the gyroscope; S44: Update the quaternion by integration at the same time, , is the currently updated quaternion state, is the time step; S45: Perform attitude correction using accelerometer data, including: , , ,in, They are the attitude angle difference, latitude difference and altitude difference of the deployed intelligent meteorological detection device respectively; They are the attitude angle calculated by the accelerometer and the attitude angle calculated by the gyroscope respectively; They are the latitude collected by the GPS system and the latitude collected by the IMU; They are the altitude collected by the GPS system and the altitude collected by the IMU; S46: Extraction , and update the quaternion, specifically: ； in, is the updated quaternion; S47: Convert the updated quaternion into a pitch angle , and calculate the landing posture compliance rate , , This is the standard delivery pitch angle.

5. A method for controlling the motorized deployment of an intelligent meteorological detection device according to claim 4, characterized in that: In S4, the working range compliance verification process includes the following specific steps: S48: Using the GPS system to collect the geographic coordinates of the meteorological device in real time, the geographic coordinates are expressed as ; S49: Setting a preset working range of the intelligent weather detection device, wherein the preset working range is a polygonal area, and the coordinates of the kth vertex are , k is the index of the vertex sequence of the polygonal area, and the polygonal area has a total of K vertices; S410: Collect the meteorological data points Convert to projected coordinates, including: , where R is the radius of the earth; S411: Determining the coverage ratio between the actual working range of the intelligent meteorological detection device and the preset working range, including: ； Among them, from point Send a horizontal ray to the right, and count the number of intersections between this ray and the polygon edge. , indicating the judgment point Whether it falls on the line segment If it is on the left side, The function returns 1, otherwise, The function returns 0; It means calculating the total number of intersections of all line segments and taking the modulus 2; S412: Calculate the work scope compliance rate based on S48-S411 , ； in, The number of inspection points determined to fall within the preset working range in S411; is the total number of inspection points.

6. A method for controlling the mobile deployment of an intelligent meteorological detection device according to claim 5, characterized in that: In S5, the evaluation strategy of the delivery success rate is: ； Among them, E is the delivery success rate.

7. A method for controlling the motorized deployment of an intelligent meteorological detection device according to claim 6, characterized in that: In S5, the subsequent adjustment process includes: presetting a delivery success rate threshold, and when the delivery success rate of the intelligent meteorological detection device is lower than the delivery success rate threshold, sending a delivery failure to be adjusted prompt to the management personnel.

8. A mobile delivery control system for an intelligent meteorological detection device, used to implement a mobile delivery control method for an intelligent meteorological detection device as claimed in any one of claims 1 to 7, characterized in that: The system includes the following modules: Historical work performance data collection module, processing capacity fluctuation value calculation module, delivery strategy confirmation module, delivery verification module and delivery success rate evaluation module; The historical work performance data collection module is used to collect and organize the historical work performance data of the meteorological detection points and the meteorological data processing center base stations in the target meteorological monitoring area during the previous delivery cycle; The processing capacity fluctuation value calculation module calculates the historical timeliness guarantee value of the meteorological data transmitted back by the meteorological detection point through the historical work performance data, and calculates the processing capacity fluctuation value of the meteorological data processing center base station where the meteorological detection point is located according to the historical timeliness guarantee value; The deployment strategy confirmation module determines the deployment strategy of the intelligent meteorological detection device in the meteorological area under the jurisdiction of the meteorological data processing center base station according to the processing capacity fluctuation value of the meteorological data processing center base station; The delivery verification module controls the delivery of the intelligent meteorological detection device using a drone according to the delivery strategy, and performs landing posture compliance verification processing and working range compliance verification processing after the delivery is completed; The delivery success rate evaluation module evaluates the delivery success rate according to the landing posture compliance rate and the working range compliance rate, and performs subsequent adjustment processing on the intelligent meteorological detection device that has been delivered.

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