Environmental monitoring data processing method and system based on UAV

Abstract

The invention discloses an environmental monitoring data processing method and system based on a UAV, and relates to the technical field of environmental monitoring. The system discloses a UAV environmental monitoring module, a hidden danger problem marking module, a hidden danger impact scoring module, and a hidden danger processing determination module. The UAV environmental monitoring module, the hidden danger problem marking module, and the hidden danger impact scoring module are provided. Various types of environmental monitoring data can be monitored during the driving of the UAV, and then various types of environmental hidden danger problems can be deeply analyzed. Independent analysis and impact analysis of environmental hidden danger problems can be completed through a neural network model and a simulation model. A hidden danger processing determination module is provided to comprehensively analyze the environmental hidden danger problems on the path passed by the UAV, determine whether the environmental hidden danger problems on the path passed by the UAV need to be processed in priority, and then dynamically adjust the processing standards of the environmental hidden danger problems.

Description

Technical Field

[0001] The present invention relates to the technical field of environmental monitoring, and more specifically, to an environmental monitoring data processing method and system based on a traveling vehicle. Background Art

[0002] With the acceleration of industrialization and urbanization, environmental pollution problems have become increasingly prominent, and the demand for environmental monitoring and governance has become more urgent. Traditional environmental monitoring methods mostly rely on fixed-point monitoring stations. Although they can provide a certain degree of environmental data, they are limited by the distribution and number of monitoring points and are difficult to fully and real-time reflect the environmental conditions of the entire region. In particular, for some sudden environmental pollution incidents, fixed-point monitoring stations often find it difficult to detect and respond in a timely manner.

[0003] In order to overcome the limitations of fixed-point monitoring, the environmental monitoring technology of UAVs came into being. UAVs are equipped with various environmental monitoring sensors, which can collect environmental data such as air, water quality, soil, etc. in real time during driving, and realize all-round and dynamic monitoring of environmental conditions. However, it is not enough to rely solely on UAVs to collect a large amount of environmental data. How to efficiently process this data, accurately identify and evaluate environmental hazards, and then formulate scientific and reasonable treatment strategies has become an urgent problem to be solved in the current field of environmental monitoring technology.

[0004] Most of the existing environmental monitoring data processing methods remain at the level of data collection and preliminary analysis, lacking in-depth exploration and comprehensive analysis of environmental hazards. At the same time, there is often a lack of scientific judgment standards and flexible treatment strategies for environmental hazards along the route of the UAV, resulting in untimely and incomplete treatment of hazards, and even causing greater environmental problems. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention aims to provide an environmental monitoring data processing method and system based on a UAV.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] The environmental monitoring data processing system based on the UAV includes a UAV environmental monitoring module, a hidden danger problem marking module, a hidden danger impact scoring module, and a hidden danger treatment determination module;

[0008] The cruise environment monitoring module controls the cruise vehicle to collect various types of environmental monitoring data in real time during driving, sets a monitoring data processing cycle, and obtains independent scores of various types of environmental hidden dangers after each monitoring data processing cycle;

[0009] The hidden danger problem marking module determines whether to mark the environmental hidden danger problem as a target hidden danger problem based on the comparison result of the hidden danger independent score and the hidden danger independent limit score;

[0010] The hidden danger impact scoring module is used to determine the target hidden danger problem marked by the UAV and obtain the hidden danger impact score of each target hidden danger problem;

[0011] The hidden danger processing determination module obtains the hidden danger radius of the environment according to the hidden danger impact score of each target hidden danger problem, obtains the initial position and the terminal position of the UAV in the monitoring data processing cycle, draws a circle with the initial position and the terminal position as the center and the hidden danger radius as the radius, and obtains an initial position circle and a terminal position circle. When the initial position circle and the terminal position circle intersect, it is determined to give priority to processing the target hidden danger problems on the path passed by the UAV in the monitoring data processing cycle; when the initial position circle and the terminal position circle do not intersect, it is determined to postpone processing the target hidden danger problems on the path passed by the UAV in the monitoring data processing cycle.

[0012] Furthermore, the independent score of hidden dangers of environmental hidden danger problems is obtained in the following manner: various types of environmental monitoring data involved in a type of environmental hidden danger problems are determined, various types of environmental monitoring data involved in this type of environmental hidden danger problems are marked as hidden danger impact data, real data of all hidden danger impact data within the monitoring data processing cycle are collected, the real data of all hidden danger impact data are pre-processed and integrated into a hidden danger impact data set, an environmental hidden danger scoring model for this type of environmental hidden danger problems is obtained, the hidden danger impact data set is used as input data of the environmental hidden danger scoring model, and the environmental hidden danger scoring model outputs the hidden danger independent score Dth of the environmental hidden danger problem.

[0013] Furthermore, the hidden danger impact score of the target hidden danger problem is obtained in the following way: obtain the real data of each type of environmental monitoring data involved in the target hidden danger problem, mark the remaining types of environmental monitoring data as irrelevant monitoring data, obtain the ideal data of each irrelevant monitoring data, build an environmental simulation model based on the real data of each type of environmental monitoring data and the ideal data of each irrelevant monitoring data, perform environmental simulation of a monitoring data processing cycle on the environmental simulation model, divide the monitoring data processing cycle into J environmental monitoring periods of equal length, obtain the period monitoring value Bjm of each environmental monitoring period, j=1, 2, ..., J, j is the serial number of the environmental monitoring period, set the period monitoring coefficient to Rm, obtain the number of consecutive pollution monitoring Kyc, and use the formula Get the hidden danger impact score Aed of the target hidden danger problem.

[0014] Furthermore, the number of consecutive pollution monitoring times Kyc is obtained in the following way: all period monitoring values ​​are sorted in sequence according to the order of the environmental monitoring periods, the monitoring values ​​of two adjacent period monitoring values ​​after sorting are summed to obtain the continuous period monitoring value, and the continuous period monitoring boundary value is set. When the continuous period monitoring value is greater than or equal to the continuous period monitoring boundary value, the number of consecutive pollution monitoring times is increased by one. When the continuous period monitoring value is less than the continuous period monitoring boundary value, no further processing is performed and the number of consecutive pollution monitoring times is marked as Kyc.

[0015] Furthermore, the hidden danger radius of the environment is obtained by the following method: obtaining the actual hidden danger score of each target hidden danger problem, setting the actual hidden danger difference score, when the actual hidden danger score of the target hidden danger problem is greater than or equal to the actual hidden danger difference score, marking the target hidden danger problem as a prominent hidden danger, when the actual hidden danger score of the target hidden danger problem is less than the actual hidden danger difference score, marking the target hidden danger problem as an ordinary hidden danger, marking the total number of prominent hidden dangers as PRob, marking the total number of ordinary hidden dangers as Ordg, and using the formula Get the hidden danger radius HGC of the environment.

[0016] Furthermore, the actual score of the target hidden danger problem is obtained by the following method: Obtain the hidden danger independent score Dth and hidden danger impact score Aed of the target hidden danger problem, and use the formula The actual hidden danger score ACtu of the target hidden danger problem is obtained, where qa is the hidden danger independent score coefficient and qb is the hidden danger impact score coefficient.

[0017] Furthermore, the period monitoring value of the environmental monitoring period is obtained in the following manner: real data of various types of environmental monitoring data within the environmental monitoring period are collected, the real data of various types of environmental monitoring data are preprocessed and integrated into a real data set, a period monitoring model is obtained, the real data set is used as input data of the period monitoring model, and the period monitoring model outputs the period monitoring value of the environmental monitoring period.

[0018] Furthermore, the environmental monitoring data processing method based on the UAV includes the following steps:

[0019] Step 1: Control the UAV to collect various types of environmental monitoring data in real time during driving, set the monitoring data processing cycle, and obtain the independent hidden danger scores of various types of environmental hidden dangers after each monitoring data processing cycle;

[0020] Step 2: Based on the comparison result between the hidden danger independent score and the hidden danger independent limit score, determine whether to mark the environmental hidden danger problem as a target hidden danger problem;

[0021] Step 3: Determine the target hidden danger problem marked by the UAV, and obtain the hidden danger impact score of each target hidden danger problem;

[0022] Step 4: Obtain the hidden danger radius of the environment according to the hidden danger impact score of each target hidden danger problem, obtain the initial position and the terminal position of the UAV in the monitoring data processing cycle, draw a circle with the initial position and the terminal position as the center and the hidden danger radius as the radius, and obtain an initial position circle and a terminal position circle. When the initial position circle and the terminal position circle intersect, it is determined to give priority to processing the target hidden danger problems on the path passed by the UAV in the monitoring data processing cycle. When the initial position circle and the terminal position circle do not intersect, it is determined to postpone the processing of the target hidden danger problems on the path passed by the UAV in the monitoring data processing cycle.

[0023] Compared with the prior art, the present invention has the following beneficial effects:

[0024] 1. The method of the present invention can comprehensively analyze the environmental hazards along the route of the vehicle, and then dynamically adjust the treatment standards for the environmental hazards;

[0025] 2. Set up a navigation environment monitoring module, a hidden danger marking module and a hidden danger impact scoring module. It can monitor various types of environmental monitoring data during the driving process of the UAV, and then conduct in-depth analysis of various environmental hidden dangers. Through the neural network model and simulation model, complete independent analysis and impact analysis of environmental hidden dangers, set up a hidden danger handling judgment module to determine whether the environmental hidden dangers in the path passed by the UAV need to be handled as a priority. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 A method flow chart of a method for processing environmental monitoring data based on a UAV;

[0027] Figure 2 A flowchart for obtaining monitoring values ​​for a period of time;

[0028] Figure 3 This is the system module diagram of the environmental monitoring data processing system based on the UAV. DETAILED DESCRIPTION

[0029] Example 1: Reference Figure 1 The environmental monitoring data processing method based on the UAV includes the following steps:

[0030] Step 1: Control the UAV to collect various types of environmental monitoring data in real time during driving, set the monitoring data processing cycle, and obtain independent hidden danger scores for various types of environmental hidden dangers after each monitoring data processing cycle.

[0031] Step 2: Based on the comparison between the hidden danger independent score and the hidden danger independent limit score, determine whether to mark the environmental hidden danger problem as a target hidden danger problem.

[0032] Step 3: Determine the target hidden danger problems marked by the UAV, and obtain the hidden danger impact score of each target hidden danger problem.

[0033] Step 4: Obtain the hidden danger radius of the environment according to the hidden danger impact score of each target hidden danger problem, obtain the initial position and the terminal position of the UAV in the monitoring data processing cycle, draw a circle with the initial position and the terminal position as the center and the hidden danger radius as the radius, and obtain an initial position circle and a terminal position circle. When the initial position circle and the terminal position circle intersect, it is determined to give priority to processing the target hidden danger problems on the path passed by the UAV in the monitoring data processing cycle. When the initial position circle and the terminal position circle do not intersect, it is determined to postpone the processing of the target hidden danger problems on the path passed by the UAV in the monitoring data processing cycle.

[0034] Through the above method, a comprehensive analysis of the environmental hazards along the route of the UAV can be conducted, and the standards for handling the environmental hazards can be dynamically adjusted.

[0035] Example 2: Reference Figures 2 to 3 The environmental monitoring data processing system based on the UAV includes a UAV environmental monitoring module, a hidden danger problem marking module, a hidden danger impact scoring module, and a hidden danger handling judgment module.

[0036] Cruise environment monitoring module: The cruise vehicle collects various types of environmental monitoring data in real time during driving, sets a monitoring data processing cycle (the length of the monitoring data processing cycle is adjusted according to system requirements), and obtains independent scores for various types of environmental potential hazards after each monitoring data processing cycle (types of environmental potential hazards include particulate matter pollution potential hazards, gaseous pollutant potential hazards, water quality pollution potential hazards, noise pollution potential hazards, ecological pollution potential hazards, etc.).

[0037] Hidden danger problem marking module: set the hidden danger independence limit score (the hidden danger independence limit score is the system preset score). When the hidden danger independence score of the environmental hidden danger problem is greater than or equal to the hidden danger independence limit score, the environmental hidden danger problem will be marked as a target hidden danger problem. When the hidden danger independence score of the environmental hidden danger problem is less than the hidden danger independence limit score, no further processing will be performed.

[0038] The hidden danger independence score of environmental hidden danger problems is obtained in the following way: determine the various types of environmental monitoring data involved in a type of environmental hidden danger problem (a type of environmental hidden danger problem usually involves multiple types of environmental monitoring data, such as particulate matter pollution hidden danger problems involving environmental monitoring data of types such as particulate matter concentration data, wind speed data, wind direction data, temperature data, humidity data, etc., and water pollution hidden danger problems involving heavy metal concentration data, organic matter concentration data, temperature data, wind speed data, wind direction data, etc., so different types of environmental hidden danger problems may involve repeated environmental monitoring data, and all data are monitored by corresponding types of sensors on the UAV), mark the various types of environmental monitoring data involved in this type of environmental hidden danger problem as hidden danger impact data, collect the real data of all hidden danger impact data within the monitoring data processing cycle (the real data is the data actually collected by the corresponding sensor), pre-process the real data of all hidden danger impact data and integrate them into a hidden danger impact data set, obtain the environmental hidden danger scoring model for this type of environmental hidden danger problem, use the hidden danger impact data set as the input data of the environmental hidden danger scoring model, and the environmental hidden danger scoring model outputs the hidden danger independence score Dth of the environmental hidden danger problem.

[0039] The hidden danger impact data set is obtained by the following method: data cleaning, data integration, data transformation, data reduction and other processing are performed on the real data of the hidden danger impact data, and then the hidden danger impact data is integrated into a data set to obtain the hidden danger impact data set.

[0040] Different types of environmental hazard problems correspond to different environmental hazard scoring models. Each environmental hazard scoring model is constructed based on a neural network model. The difference in the construction methods of different types of environmental hazard scoring models lies in the difference in training data. This embodiment takes the particulate matter pollution hazard problem as an example and discloses a method for constructing an environmental hazard scoring model for the particulate matter pollution hazard problem: collect s hazard impact data sets of the particulate matter pollution hazard problem, build a neural network model, and use the hazard impact data sets of the particulate matter pollution hazard problem as training data for the neural network model (if it is an environmental hazard scoring model for the water quality pollution hazard problem, collect s hazard impact data sets of the water quality pollution hazard problem), and assign an independent hazard score to each training data. The scoring range of hidden danger independence score is (1.1~9.9). The closer the hidden danger independence score is to 9.9, the greater the hidden danger of particulate matter pollution, and the closer the hidden danger independence score is to 1.1, the smaller the hidden danger of particulate matter pollution (if it is an environmental hidden danger scoring model for water quality pollution hidden dangers, the closer the hidden danger independence score is to 9.9, the greater the hidden danger of water quality pollution hidden dangers, and the closer the hidden danger independence score is to 1.1, the smaller the hidden danger of water quality pollution hidden dangers). The training data is divided into training set, validation set and test set in a ratio of 2:1:1. The neural network is iteratively trained on the training set, validation set and test set. After the training is completed, an environmental hidden danger scoring model for particulate matter pollution hidden dangers is constructed.

[0041] Hidden danger impact scoring module: determine the target hidden danger problems marked by the UAV, and obtain the hidden danger impact score of each target hidden danger problem.

[0042] The hidden danger impact score of the target hidden danger problem is obtained in the following way: obtain the real data of each type of environmental monitoring data involved in the target hidden danger problem (the real data is limited to the data collected within the monitoring data processing cycle), mark the remaining types of environmental monitoring data as irrelevant monitoring data (all environmental monitoring data except the various types of environmental monitoring data involved in the target hidden danger problem are marked as irrelevant monitoring data), obtain the ideal data of each irrelevant monitoring data (that is, the expected data of each irrelevant monitoring data within the monitoring data processing cycle under ideal conditions), build an environmental simulation model based on the real data of each type of environmental monitoring data and the ideal data of each irrelevant monitoring data, perform environmental simulation of a monitoring data processing cycle on the environmental simulation model, divide the monitoring data processing cycle into J environmental monitoring periods of equal length, and obtain the period monitoring value Bjm of each environmental monitoring period, j=1, 2,…, J, j is the environmental monitoring period. The serial number of the measurement period is set to Rm, m=1, 2, 3, ..., m, R1<R2<R3<...<Rm, each period monitoring coefficient corresponds to a period monitoring value within a range, and the range of the period monitoring value includes (0, Bj1], (Bj1, Bj2], ..., (Bjm-1, Bjm], when Bjm∈(0, Bj1], the period monitoring coefficient is R1, all period monitoring values ​​are sorted in the order of the environmental monitoring period, and the two adjacent period monitoring values ​​after sorting are summed to obtain the continuous period monitoring value, and the continuous period monitoring boundary value is set (the continuous period monitoring boundary value is the system preset value). When the continuous period monitoring value is greater than or equal to the continuous period monitoring boundary value, the number of consecutive pollution monitoring is increased by one. When the continuous period monitoring value is less than the continuous period monitoring boundary value, no further processing is performed, and the number of consecutive pollution monitoring is marked as Kyc. The formula is used Get the hidden danger impact score Aed of the target hidden danger problem.

[0043] The period monitoring value of the environmental monitoring period is obtained in the following way: collecting real data of various types of environmental monitoring data within the environmental monitoring period, preprocessing the real data of various types of environmental monitoring data and integrating them into a real data set, obtaining a period monitoring model, using the real data set as input data of the period monitoring model, and the period monitoring model outputs the period monitoring value of the environmental monitoring period.

[0044] The construction method of the time period monitoring model is as follows: collect g real data sets, build a neural network model, use the real data sets as training data for the neural network model, assign a time period monitoring value to each training data, and the value range of the time period monitoring value is (3~5). The closer the time period monitoring value is to 5, the more serious the environmental pollution in the simulation environment is, and the closer the time period monitoring value is to 3, the lighter the environmental pollution in the simulation environment is. The training data is divided into training set, validation set and test set in a ratio of 4:3:2. The neural network is iteratively trained on the training set, validation set and test set. After the training is completed, the time period monitoring model is constructed.

[0045] The environmental simulation model is constructed as follows: select simulation software such as MATLAB Simulink and ANSYS, create a new model in the equipment simulation software, add corresponding entities and set corresponding parameters in the model according to the real data of various types of environmental monitoring data and the ideal data of various irrelevant monitoring data, and then construct the environmental simulation model.

[0046] By setting up a cruise environment monitoring module, a hidden danger marking module and a hidden danger impact scoring module, various types of environmental monitoring data can be monitored during the driving of the cruise vehicle, and then various environmental hidden dangers can be deeply analyzed. The independent analysis and impact analysis of environmental hidden dangers can be completed through neural network models and simulation models.

[0047] Hidden danger processing and determination module: the hidden danger radius of the environment is obtained according to the hidden danger impact score of each target hidden danger problem, and the initial position and the terminal position of the UAV in the monitoring data processing cycle are obtained (the initial position is the position of the UAV at the beginning of the monitoring data processing cycle, and the terminal position is the position of the UAV at the end of the monitoring data processing cycle). With the initial position and the terminal position as the center, a circle is drawn with the hidden danger radius as the radius to obtain an initial position circle and a terminal position circle. When the initial position circle and the terminal position circle intersect, it is determined to give priority to processing the target hidden danger problems on the path passed by the UAV in the monitoring data processing cycle. When the initial position circle and the terminal position circle do not intersect, it is determined to postpone the processing of the target hidden danger problems on the path passed by the UAV in the monitoring data processing cycle.

[0048] The hidden danger radius of the environment is obtained in the following way: obtain the actual hidden danger score of each target hidden danger problem, set the actual hidden danger difference score (the actual hidden danger difference score is the system preset score), when the actual hidden danger score of the target hidden danger problem is greater than or equal to the actual hidden danger difference score, mark the target hidden danger problem as a prominent hidden danger, when the actual hidden danger score of the target hidden danger problem is less than the actual hidden danger difference score, mark the target hidden danger problem as an ordinary hidden danger, mark the total number of prominent hidden dangers as PRob, and mark the total number of ordinary hidden dangers as Ordg, using the formula Get the hidden danger radius HGC of the environment.

[0049] The actual score of the target hidden danger problem is obtained by the following method: Get the hidden danger independent score Dth and hidden danger impact score Aed of the target hidden danger problem, and use the formula The actual score of the hidden danger of the target hidden danger problem ACtu is obtained, where qa is the hidden danger independent score coefficient, qb is the hidden danger impact score coefficient, the value of qa is 0.65, and the value of qb is 0.84.

[0050] A hidden danger handling determination module is set up to conduct a comprehensive analysis of the environmental hidden dangers on the path passed by the UAV, determine whether the environmental hidden dangers on the path passed by the UAV need to be handled with priority, and then dynamically adjust the handling standards of the environmental hidden dangers.

[0051] The above formulas are all dimensionless and numerical calculations are performed, and the preset parameters in the formulas are set by technicians in this field according to actual conditions.

[0052] 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 the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application 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. The 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, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access 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.

[0053] 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.

[0054] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein 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 this application.

[0055] 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.

[0056] In the several embodiments provided in the present application, 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 the units is only a logical function division. 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.

[0057] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage media include: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks or optical disks.

[0058] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. The environmental monitoring data processing system based on the UAV is characterized by: It includes the navigation environment monitoring module, the hidden danger problem marking module, the hidden danger impact scoring module, and the hidden danger treatment determination module; The cruise environment monitoring module controls the cruise vehicle to collect various types of environmental monitoring data in real time during driving, sets a monitoring data processing cycle, and obtains independent scores of various types of environmental hidden dangers after each monitoring data processing cycle; The hidden danger problem marking module determines whether to mark the environmental hidden danger problem as a target hidden danger problem based on the comparison result of the hidden danger independent score and the hidden danger independent limit score; The hidden danger impact scoring module is used to determine the target hidden danger problem marked by the UAV and obtain the hidden danger impact score of each target hidden danger problem; The hidden danger processing determination module obtains the hidden danger radius of the environment according to the hidden danger impact score of each target hidden danger problem, obtains the initial position and the terminal position of the UAV in the monitoring data processing cycle, takes the initial position and the terminal position as the center of the circle, and draws circles with the hidden danger radius as the radius to obtain an initial position circle and a terminal position circle. When the initial position circle and the terminal position circle intersect, it is determined to give priority to processing the target hidden danger problems on the path passed by the UAV in the monitoring data processing cycle; when the initial position circle and the terminal position circle do not intersect, it is determined to postpone processing the target hidden danger problems on the path passed by the UAV in the monitoring data processing cycle.

2. The environmental monitoring data processing system based on a UAV according to claim 1 is characterized in that: The independent score of hidden dangers in environmental hidden danger problems is obtained in the following way: determine various types of environmental monitoring data involved in a type of environmental hidden danger problems, mark various types of environmental monitoring data involved in this type of environmental hidden danger problems as hidden danger impact data, collect real data of all hidden danger impact data within the monitoring data processing cycle, pre-process the real data of all hidden danger impact data and integrate them into a hidden danger impact data set, obtain an environmental hidden danger scoring model for this type of environmental hidden danger problems, use the hidden danger impact data set as input data of the environmental hidden danger scoring model, and the environmental hidden danger scoring model outputs the hidden danger independent score Dth of the environmental hidden danger problem.

3. The environmental monitoring data processing system based on a UAV according to claim 1 is characterized in that: The hidden danger impact score of the target hidden danger problem is obtained in the following way: obtain the real data of each type of environmental monitoring data involved in the target hidden danger problem, mark the remaining types of environmental monitoring data as irrelevant monitoring data, obtain the ideal data of each irrelevant monitoring data, build an environmental simulation model based on the real data of each type of environmental monitoring data and the ideal data of each irrelevant monitoring data, perform environmental simulation of a monitoring data processing cycle on the environmental simulation model, divide the monitoring data processing cycle into J environmental monitoring periods of equal length, obtain the period monitoring value Bjm of each environmental monitoring period, j=1, 2, ..., J, j is the serial number of the environmental monitoring period, set the period monitoring coefficient to Rm, obtain the number of consecutive pollution monitoring Kyc, and use the formula Get the hidden danger impact score Aed of the target hidden danger problem.

4. The environmental monitoring data processing system based on a UAV according to claim 3 is characterized in that: The number of consecutive pollution monitoring times Kyc is obtained in the following way: all period monitoring values ​​are sorted in sequence according to the sequence of environmental monitoring periods, the monitoring values ​​of two adjacent period monitoring values ​​after sorting are summed up to obtain the continuous period monitoring value, and the continuous period monitoring boundary value is set. When the continuous period monitoring value is greater than or equal to the continuous period monitoring boundary value, the number of consecutive pollution monitoring times is increased by one. When the continuous period monitoring value is less than the continuous period monitoring boundary value, no further processing is performed and the number of consecutive pollution monitoring times is marked as Kyc.

5. The environmental monitoring data processing system based on a UAV according to claim 1 is characterized in that: The hidden danger radius of the environment is obtained by the following method: obtain the actual hidden danger score of each target hidden danger problem, set the actual hidden danger difference score, when the actual hidden danger score of the target hidden danger problem is greater than or equal to the actual hidden danger difference score, mark the target hidden danger problem as a prominent hidden danger, when the actual hidden danger score of the target hidden danger problem is less than the actual hidden danger difference score, mark the target hidden danger problem as an ordinary hidden danger, mark the total number of prominent hidden dangers as PRob, and mark the total number of ordinary hidden dangers as Ordg, using the formula Get the hidden danger radius HGC of the environment.

6. The environmental monitoring data processing system based on a UAV according to claim 5 is characterized in that: The actual score of the target hidden danger problem is obtained by the following method: Get the hidden danger independent score Dth and hidden danger impact score Aed of the target hidden danger problem, and use the formula The actual hidden danger score ACtu of the target hidden danger problem is obtained, where qa is the hidden danger independent score coefficient and qb is the hidden danger impact score coefficient.

7. The environmental monitoring data processing system based on a UAV according to claim 3 is characterized in that: The period monitoring value of the environmental monitoring period is obtained in the following way: collecting real data of various types of environmental monitoring data within the environmental monitoring period, preprocessing the real data of various types of environmental monitoring data and integrating them into a real data set, obtaining a period monitoring model, using the real data set as input data of the period monitoring model, and the period monitoring model outputs the period monitoring value of the environmental monitoring period.

8. A method for processing environmental monitoring data based on a UAV, applied to an environmental monitoring data processing system based on a UAV according to any one of claims 1 to 7, characterized in that: The steps include: Step 1: Control the UAV to collect various types of environmental monitoring data in real time during driving, set the monitoring data processing cycle, and obtain the independent hidden danger scores of various types of environmental hidden dangers after each monitoring data processing cycle; Step 2: Based on the comparison result between the hidden danger independent score and the hidden danger independent limit score, determine whether to mark the environmental hidden danger problem as a target hidden danger problem; Step 3: Determine the target hidden danger problem marked by the UAV, and obtain the hidden danger impact score of each target hidden danger problem; Step 4: Obtain the hidden danger radius of the environment according to the hidden danger impact score of each target hidden danger problem, obtain the initial position and the terminal position of the UAV in the monitoring data processing cycle, draw a circle with the initial position and the terminal position as the center and the hidden danger radius as the radius, and obtain an initial position circle and a terminal position circle. When the initial position circle and the terminal position circle intersect, it is determined to give priority to processing the target hidden danger problems on the path passed by the UAV in the monitoring data processing cycle. When the initial position circle and the terminal position circle do not intersect, it is determined to postpone the processing of the target hidden danger problems on the path passed by the UAV in the monitoring data processing cycle.

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