UAV data collection method, system, computer equipment and medium
By generating animal data acquisition paths and using drones to automatically determine data acquisition points, the problems of high labor costs and difficult maintenance in existing technologies are solved, and low-cost and low-maintenance wildlife data collection is achieved.
Patent Information
- Application Number
- CN202510050976.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2025-01-13
- Publication Date
- 2025-09-30
- Estimated Expiration
- 2045-01-13
AI Technical Summary
Existing drone data collection methods for monitoring wildlife in the wild have the problems of high labor costs, heavy workload, and rigid requirements on mobile communication signal coverage areas, which makes maintenance difficult.
By generating an animal data acquisition path that traverses preset data acquisition points, using a drone to fly along the path to acquire data, and combining integer linear programming and dual decision planning, it is automatically determined whether to start data acquisition at the data acquisition point, reducing manual intervention and communication signal coverage requirements.
It eliminates the need for manual data acquisition, reduces the workload and labor costs of data recovery, reduces dependence on mobile communication signal coverage, and reduces the maintenance difficulty and cost of the monitored area.
Smart Images
Figure CN119806189B_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of data collection, and in particular to a method, system, computer equipment and medium for collecting data from unmanned aerial vehicles. Background Art
[0002] Wildlife resources are depletable and important ecological resources with both ecological and practical value. They are an indicator of a country's comprehensive national strength. Therefore, their rational development, utilization, and protection are crucial. A crucial step in this process is wildlife data collection. Given the widespread distribution and range of wildlife, data collection requires extensive coverage, high reliability, and minimal environmental impact. Currently, mainstream drone data collection methods include field surveys and infrared camera monitoring. Infrared camera monitoring, due to its wildlife-friendly nature, rich and intuitive data, and ease of installation, is widely used in wildlife monitoring and conservation, becoming one of the most important drone data collection methods. However, traditional infrared camera monitoring requires manual image data collection, which carries drawbacks such as high labor costs, heavy workload, and the risk of data loss. Improved infrared trigger cameras equipped with 4G modules capable of real-time image uploads must be deployed within areas with mobile communication coverage. This poses significant cost and maintenance challenges for protected areas. Therefore, developing a low-cost and low-maintenance data collection method has become an urgent challenge. Summary of the Invention
[0003] Based on this, it is necessary to propose a drone data collection method, system, computer equipment and medium with low use cost and low maintenance difficulty to address the above problems.
[0004] The present invention provides a drone data collection method for collecting data on wild animals in a monitoring area, comprising:
[0005] S1: Generate and traverse preset data acquisition points within the monitoring area The animal data acquisition path;
[0006] S2: When the drone arrives at the data acquisition point along the animal data acquisition path When the data acquisition point is Start animal data acquisition in
[0007] S3: If started, the UAV is at the data acquisition point Execute the animal data acquisition process and fly to the next data acquisition point after completion After that, the data acquisition point Replaced with the data acquisition point , and return to step S2;
[0008] S4. If not started, the drone will fly directly to the data acquisition point , and the data acquisition point Replaced with the data acquisition point Then, return to step S2;
[0009] S5. After traversing all the data acquisition points, the drone returns to the set starting point of the animal data acquisition path and outputs the data collection results.
[0010] Furthermore, the step S1 specifically includes:
[0011] S1a, obtaining each of the data acquisition points The data collection cost and the set energy budget of the UAV are recorded as data collection cost and setting energy budget b;
[0012] S1b, setting the data acquisition point Matched decision variable coefficients ;
[0013] S1c, according to the data collection cost , the set energy budget b and the decision variable coefficient Generate a traversal of the data acquisition points The animal data acquisition path.
[0014] Furthermore, the step S1c specifically includes:
[0015] S1d, generating and traversing the data acquisition points based on preset constraints The animal data acquisition path, the starting point and the end point of the animal data acquisition path are the same data acquisition point , and the preset constraints are as follows:
[0016] ;
[0017] Wherein, V is each of the data acquisition points The set of V= , E is the path between each of the data acquisition points, E , c and y are both referential vectors, when or When the vector value is 0, it means that the drone has not flown through the path ,when or When the vector value is 1, it means that the drone is flying through the path .
[0018] Furthermore, after step S1c, the method further includes:
[0019] S1g, setting and each of the data acquisition points Matching data collection benefits ;
[0020] S1h, obtaining a set integer linear programming formula, which is used to maximize the value of each data acquisition point The corresponding data collection income , the integer linear programming formula is specifically embodied as follows:
[0021]
[0022]
[0023] Then the integer linear programming output is That is, the data collection income in the animal data acquisition path Maximize results, It is used to indicate that the formula is a dual relation formula, and T is the transpose symbol of the matrix formula.
[0024] Furthermore, the step S2 specifically includes:
[0025] S2a, when the drone arrives at the data acquisition point along the animal data acquisition path When the data acquisition point is obtained The matching online search planning formula is specifically embodied as follows:
[0026]
[0027] in For the data acquisition point The corresponding final decision coefficient is, To obtain each of the data acquisition points The data collection cost, For each of the data acquisition points The corresponding data collection income That is, the data acquisition points that the drone has passed Corresponding historical sensor information;
[0028] S2b, performing integer constraints and dual decision planning on the online search planning formula, and calculating the final decision coefficient based on the results of the integer constraints and the dual decision planning. The value of
[0029] S2c, when the final decision coefficient When it is 1, execute step S3;
[0030] S2d, when the final decision coefficient When it is 0, execute step S4.
[0031] Furthermore, the step S2b specifically includes:
[0032] S2e, performing integer constraints on the online search planning formula to obtain a corresponding linear planning formula, which is specifically embodied as follows:
[0033]
[0034] in, Get the point for the data The matching decision variable coefficients, To set the energy budget, It is used to indicate that the formula is a dual relation formula, and T is the transpose symbol of the matrix formula;
[0035] S2f, record the optimal solution output by the linear programming formula as the linear programming optimal solution;
[0036] S2g, performing dual decision planning on the online search planning formula, thereby obtaining a corresponding dual decision planning formula, wherein the dual decision planning formula is specifically embodied as follows:
[0037]
[0038]
[0039] in, and p are the preset dual decision variable values;
[0040] S2h, recording the optimal solution output by the dual decision planning formula as the dual decision optimal solution;
[0041] S2i, based on the optimal solution of the linear programming and the optimal solution of the dual decision, the complementary conditions are calculated to obtain the final decision coefficient .
[0042] Furthermore, the step S2i specifically includes:
[0043] S2j, obtain the set complementary condition calculation formula, which is specifically embodied as follows:
[0044]
[0045] S2k, then the output result of the complementary condition calculation formula is the final decision coefficient .
[0046] The present invention also provides a drone data acquisition system for collecting data on wild animals in a monitoring area, comprising:
[0047] A path generation unit is used to generate a path through the preset data acquisition points within the monitoring area. The animal data acquisition path;
[0048] A judgment unit is used to determine when the drone reaches the data acquisition point along the animal data acquisition path. When the data acquisition point is Start animal data acquisition in
[0049] The data acquisition unit is used to determine if the drone is started at the data acquisition point Execute the animal data acquisition process and fly to the next data acquisition point after completion After that, the data acquisition point Replaced with the data acquisition point , and returns to execute the corresponding execution steps of the judgment unit;
[0050] The path control unit is used to determine if it is not started, and the UAV will fly directly to the data acquisition point , and the data acquisition point Replaced with the data acquisition point After that, return to execute the corresponding execution steps of the judgment unit;
[0051] A flight control unit is used to enable the drone to return to the set starting point of the animal data acquisition path after traversing all the data acquisition points and output the data collection results.
[0052] The present invention further provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the following steps:
[0053] S1: Generate and traverse preset data acquisition points within the monitoring area The animal data acquisition path;
[0054] S2: When the drone arrives at the data acquisition point along the animal data acquisition path When the data acquisition point is Start animal data acquisition in
[0055] S3: If started, the UAV is at the data acquisition point Execute the animal data acquisition process and fly to the next data acquisition point after completion After that, the data acquisition point Replaced with the data acquisition point , and return to step S2;
[0056] S4. If not started, the drone will fly directly to the data acquisition point , and the data acquisition point Replaced with the data acquisition point Then, return to step S2;
[0057] S5. After traversing all the data acquisition points, the drone returns to the set starting point of the animal data acquisition path and outputs the data collection results.
[0058] The present invention further provides a computer-readable medium storing a computer program, wherein when the computer program is executed by a processor, the processor is caused to perform the following steps:
[0059] S1: Generate and traverse preset data acquisition points within the monitoring area The animal data acquisition path;
[0060] S2: When the drone arrives at the data acquisition point along the animal data acquisition path When the data acquisition point is Start animal data acquisition in
[0061] S3: If started, the UAV is at the data acquisition point Execute the animal data acquisition process and fly to the next data acquisition point after completion After that, the data acquisition point Replaced with the data acquisition point , and return to step S2;
[0062] S4. If not started, the drone will fly directly to the data acquisition point , and the data acquisition point Replaced with the data acquisition point Then, return to step S2;
[0063] S5. After traversing all the data acquisition points, the drone returns to the set starting point of the animal data acquisition path and outputs the data collection results.
[0064] The above-mentioned drone data collection method, system, computer equipment and medium achieve the goal of eliminating the need for manual data acquisition at each data acquisition point by generating an animal data acquisition path that traverses preset data acquisition points within the monitoring area, and having the drone fly along the animal data acquisition path to the data acquisition point to acquire data, thereby reducing the workload and labor costs of data recovery. At the same time, since the drone does not need to be required to work in an area covered by mobile communication signals when acquiring data, the requirements for mobile communication signal coverage and maintenance in the monitoring area are reduced, solving the problem in the prior art of manual data recovery when using infrared cameras for field data monitoring, which results in high workload and labor costs, and the rigid requirement for mobile communication signal coverage in the monitoring area, which makes maintenance of the monitoring area difficult. This reduces the difficulty of maintaining the monitoring area and the workload and labor costs when conducting field data monitoring in the monitoring area. BRIEF DESCRIPTION OF THE DRAWINGS
[0065] In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.
[0066] Figure 1 A schematic diagram of an animal data acquisition path in one embodiment;
[0067] Figure 2 This is a flow chart of a method for collecting drone data in one embodiment;
[0068] Figure 3 This is a system structure diagram of a UAV data acquisition system in one embodiment;
[0069] Figure 4 1 is a structural block diagram of a computer device in one embodiment. DETAILED DESCRIPTION
[0070] The technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments.
[0071] The components of the embodiments of the present application generally described and illustrated in the drawings herein may be arranged and designed in a variety of different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the claimed application, but rather merely represents selected embodiments of the present application. All other embodiments obtained by those skilled in the art based on the embodiments of the present application without creative effort are within the scope of protection of the present application.
[0072] Hereinafter, the terms "including", "having" and their cognates, which may be used in various embodiments of the present application, are intended only to indicate specific features, numbers, steps, operations, elements, components or combinations of the foregoing items, and should not be understood as first excluding the existence of one or more other features, numbers, steps, operations, elements, components or combinations of the foregoing items or the possibility of adding one or more features, numbers, steps, operations, elements, components or combinations of the foregoing items.
[0073] Furthermore, the terms “first,” “second,” “third,” etc., are merely used for distinguishing descriptions and are not to be understood as indicating or implying relative importance.
[0074] Unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by those skilled in the art to which the various embodiments of the present application belong. The terms (such as those defined in generally used dictionaries) will be interpreted as having the same meaning as in the context of the relevant technical field and will not be interpreted as having an idealized meaning or an overly formal meaning unless clearly defined in the various embodiments of the present application.
[0075] refer to Figure 1 and Figure 2 The present invention provides a method for collecting data from a drone, which is used to collect data on wild animals in a monitoring area, comprising:
[0076] S1: Generate and traverse preset data acquisition points within the monitoring area The animal data acquisition path;
[0077] As described in step S1 above, there are several data acquisition points preset in the monitoring area. It is understandable that the = , the data acquisition point For allowing the drone to arrive at the data acquisition point Then determine whether to execute the animal data acquisition process, and fly to the data acquisition point after determining that the data acquisition process is completed or it is determined that the data acquisition process does not need to be executed , and the animal data acquisition path is used to set the drone to traverse the data acquisition points The flight path, the animal data acquisition path and each of the preset data acquisition points The setting method can be referred to Figure 1 ;
[0078] It is understandable that when the background system is calculating the animal data acquisition path, the drone is not actually in the take-off state, so at this time, compared with the various data acquisition points , the drone is in an offline state. In addition, the starting point and the end point of the animal data acquisition path are both the same data acquisition point .
[0079] S2: When the drone arrives at the data acquisition point along the animal data acquisition path When the data acquisition point is Start animal data acquisition in
[0080] As described in step S2 above, when the drone switches to the online state and takes off along the animal data acquisition path to reach the data acquisition point When the remaining energy constraint is used, it is determined whether the data acquisition point Start animal data acquisition in
[0081] It is understandable that, due to the size of the drone itself, the battery capacity of the drone is also subject to corresponding limitations. In this embodiment, the battery capacity of the drone can ensure that the drone can reach the data acquisition point. Do not start data acquisition and traverse the data acquisition points However, there is no guarantee that the drone will be at the data acquisition point Start animal data acquisition and traverse the data acquisition points Therefore, in this embodiment, it is used to ensure that the UAV is at each of the data acquisition points Do not start data acquisition and traverse the data acquisition points The energy required is the remaining energy constraint of the drone itself. The drone can then determine whether to acquire energy at the data acquisition point based on the remaining energy constraint of the drone itself. In the process of starting animal data acquisition, if the remaining energy exceeds the remaining energy constraint of the animal itself, data acquisition is started, otherwise it is not executed.
[0082] S3: If started, the UAV is at the data acquisition point Execute the animal data acquisition process and fly to the next data acquisition point after completion After that, the data acquisition point Replaced with the data acquisition point , and return to step S2;
[0083] As described in step S3 above, when the UAV determines that it can When data acquisition is started at a certain point, the drone directly starts data acquisition and flies to the next data acquisition point after data acquisition is completed. , that is, the data acquisition point , then when the drone reaches the data acquisition point After that, the data acquisition point Replaced with the data acquisition point , and return to step S2.
[0084] S4. If not started, the drone will fly directly to the data acquisition point , and the data acquisition point Replaced with the data acquisition point Then, return to step S2;
[0085] As described in step S4 above, when the UAV determines that it cannot be at the data acquisition point according to its own remaining energy constraint, When data acquisition is started at a certain point, the drone directly flies to the next data acquisition point. , that is, the data acquisition point , then when the drone reaches the data acquisition point After that, the data acquisition point Replaced with the data acquisition point , and return to step S2.
[0086] S5. After traversing all the data acquisition points, the drone returns to the set starting point of the animal data acquisition path and outputs the data collection results.
[0087] As described in step S5 above, when the drone determines that it has traversed all the data acquisition points, the drone returns to the set starting point of the animal data acquisition path and outputs the data at all the data acquisition points. The data collection results obtained in the
[0088] It is understood that, in this embodiment, the set starting point is one of the data acquisition points set in the animal data acquisition path. .
[0089] This embodiment uses the above method to generate an animal data acquisition path that traverses preset data acquisition points in the monitoring area, and uses a drone to fly along the animal data acquisition path to reach the data acquisition point to acquire data, thereby eliminating the need for manual data acquisition of each data acquisition point, thereby reducing the workload and labor costs of data recovery. At the same time, since the drone does not need to be required to work in an area covered by mobile communication signals when acquiring data, the requirements for mobile communication signal coverage and maintenance in the monitoring area are reduced, solving the problems in the prior art of manual data recovery when using infrared cameras for field data monitoring, resulting in high workload and labor costs, and the rigid requirement of mobile communication signal coverage in the monitoring area, which makes maintenance of the monitoring area difficult. This reduces the maintenance difficulty of the monitoring area and the workload and labor costs when performing field data monitoring in the monitoring area.
[0090] In one embodiment, step S1 specifically includes:
[0091] S1a, obtaining each of the data acquisition points The data collection cost and the set energy budget of the UAV are recorded as data collection cost and setting energy budget b;
[0092] S1b, setting the data acquisition point Matched decision variable coefficients ;
[0093] S1c, according to the data collection cost , the set energy budget b and the decision variable coefficient Generate a traversal of the data acquisition points The animal data acquisition path.
[0094] As described in the above embodiment, the background system sets the first point set V as each of the data acquisition points The first point set V is specifically embodied as V= At the same time, the background system sets a second point set E to represent the path between each of the data acquisition points. The second point set E is specifically embodied as: , then the network G = (V, E) represents the problem environment of the entire UAV data collection method, and the background system also sets the vector To indicate that the drone obtains data from the point To the data acquisition point Energy consumption, and obtain the data acquisition points The data collection cost and the set energy budget of the UAV are recorded as data collection cost And set the energy budget b. It can be understood that the set energy budget b is the above-mentioned remaining energy constraint. The data collection cost With each of the data acquisition points One-to-one correspondence, used to represent each of the data acquisition points The cost of data collection is affected by factors including but not limited to data volume differences, altitude, harsh environment, network transmission speed, etc. The amount of data collected is different, so the benefits of data collection are also different. In addition, the background system also sets the data acquisition point Matched decision variable coefficients and each of the data acquisition points Matching data collection benefits ;
[0095] In the first application scenario of this embodiment, the data acquisition point It can be an energy supply point. When the drone reaches the data acquisition point of the energy supply point When the drone can directly execute the energy replenishment process, the drone deducts the data acquisition cost at the data acquisition point. When the corresponding data collection cost and data collection benefits It can be directly recognized as a negative number, thus achieving the effect of increasing energy.
[0096] In one embodiment, step S1c specifically includes:
[0097] S1d, generating and traversing the data acquisition points based on preset constraints The animal data acquisition path, the starting point and the end point of the animal data acquisition path are the same data acquisition point , and the preset constraints are as follows:
[0098] ;
[0099] Wherein, V is each of the data acquisition points The set of V= , E is the path between each of the data acquisition points, E , c and y are both referential vectors, when or When the vector value is 0, it means that the drone has not flown through the path ,when or When the vector value is 1, it means that the drone is flying through the path .
[0100] As described in the above embodiment, the background system generates a data acquisition point traversal The animal data acquisition path, the starting point and the end point of the animal data acquisition path are the same data acquisition point , and the animal data acquisition path meets the following constraints:
[0101] .
[0102] It is understood that the above constraints Indicates that the drone is at each of the data acquisition points Do not start data acquisition and traverse the data acquisition points The total energy consumption, Indicates that the drone is at each of the data acquisition points The sum of energy consumption of the startup data acquisition, and the decision variable coefficient Specifically manifested as ,when The drone will be at the data acquisition point Data collection is performed, and when it is 0, data collection is not performed, and the purpose of the constraint is to maximize the data collection benefit of the animal data acquisition path.
[0103] In one embodiment, after step S1f, the method further includes:
[0104] After step S1c, the method further includes:
[0105] S1g, setting and each of the data acquisition points Matching data collection benefits ;
[0106] S1h, obtaining a set integer linear programming formula, which is used to maximize the value of each data acquisition point The corresponding data collection income , the integer linear programming formula is specifically embodied as follows:
[0107]
[0108]
[0109] Then the integer linear programming output is That is, the data collection income in the animal data acquisition path Maximize results, It is used to indicate that the formula is a dual relation formula, and T is the transpose symbol of the matrix formula.
[0110] As described in the above embodiment, the background system settings and each of the data acquisition points Matching data collection benefits , then the background system obtains the set integer linear programming formula, which is used to maximize the value of each data acquisition point The corresponding data collection income , the integer linear programming formula is specifically embodied as follows:
[0111]
[0112]
[0113] It can be understood that the integer linear programming output That is, the data collection income in the animal data acquisition path Maximize the results, Used to indicate that the equation is a dual relation.
[0114] In one embodiment, step S2 specifically includes:
[0115] S2a, when the drone arrives at the data acquisition point along the animal data acquisition path When the data acquisition point is obtained The matching online search planning formula is specifically embodied as follows:
[0116]
[0117] in For the data acquisition point The corresponding final decision coefficient is, To obtain each of the data acquisition points The data collection cost, For each of the data acquisition points The corresponding data collection income That is, the data acquisition points that the drone has passed Corresponding historical sensor information;
[0118] S2b, performing integer constraints and dual decision planning on the online search planning formula, and calculating the final decision coefficient based on the results of the integer constraints and the dual decision planning. The value of
[0119] S2c, when the final decision coefficient When it is 1, execute step S3;
[0120] S2d, when the final decision coefficient When it is 0, execute step S4.
[0121] As described in the above embodiment, when the drone arrives at the data acquisition point along the animal data acquisition path When the background system obtains the data acquisition point The matching online search planning formula is specifically embodied as follows:
[0122]
[0123] It is understandable that For the data acquisition point The corresponding final decision coefficient is, To obtain each of the data acquisition points The data collection cost, For each of the data acquisition points The corresponding data collection income That is, the data acquisition points that the drone has passed The corresponding historical sensor information, after which the background system performs integer constraints and dual decision planning on the online search planning formula, and infers the data acquisition point according to the results of the integer constraints and the results of the dual decision planning. Corresponding to the final decision coefficient The value of the final decision coefficient is When it is 1, the drone is controlled at the data acquisition point Start animal data acquisition in the same way when the final decision coefficient When it is 0, the drone is controlled at the data acquisition point Data acquisition is not started.
[0124] In one embodiment, step S2b specifically includes:
[0125] S2e, performing integer constraints on the online search planning formula to obtain a corresponding linear planning formula, which is specifically embodied as follows:
[0126]
[0127] in, Get the point for the data The matching decision variable coefficients, To set the energy budget, It is used to indicate that the formula is a dual relation formula, and T is the transpose symbol of the matrix formula;
[0128] S2f, record the optimal solution output by the linear programming formula as the linear programming optimal solution;
[0129] S2g, performing dual decision planning on the online search planning formula, thereby obtaining a corresponding dual decision planning formula, wherein the dual decision planning formula is specifically embodied as follows:
[0130]
[0131]
[0132] in, and p are the preset dual decision variable values;
[0133] S2h, recording the optimal solution output by the dual decision planning formula as the dual decision optimal solution;
[0134] S2i, based on the optimal solution of the linear programming and the optimal solution of the dual decision, the complementary conditions are calculated to obtain the final decision coefficient .
[0135] As described in the above embodiment, the background system performs integer constraints on the online search planning formula to obtain a corresponding linear planning formula, which is specifically embodied as follows:
[0136]
[0137] It is understandable that the background system records the optimal solution output by the linear programming formula as the optimal solution of the linear programming formula. At the same time, the background system performs dual decision planning on the online search planning formula to obtain the corresponding dual decision planning formula. The dual decision planning formula is specifically embodied as follows:
[0138]
[0139]
[0140] It is understandable that the And the p are all preset dual decision variable values, then the background system records the optimal solution output by the dual decision programming as the dual decision optimal solution. Finally, the background system performs complementary condition calculation based on the linear programming optimal solution and the dual decision optimal solution to obtain the final decision coefficient The value of .
[0141] In one embodiment, the step S2i specifically includes:
[0142] S2j, obtain the set complementary condition calculation formula, which is specifically embodied as follows:
[0143]
[0144] S2k, then the output result of the complementary condition calculation formula is the final decision coefficient .
[0145] As described in the above embodiment, the background system obtains the set complementary condition calculation formula, which is specifically embodied as follows:
[0146]
[0147] The output result of the complementary condition calculation formula determined by the background system is the final decision coefficient .
[0148] refer to Figure 3 The present invention also provides a drone data acquisition system for collecting data on wild animals in a monitoring area, comprising:
[0149] The path generation unit 10 is used to generate a path through the preset data acquisition points in the monitoring area. The animal data acquisition path;
[0150] The judgment unit 20 is used to determine when the drone reaches the data acquisition point along the animal data acquisition path. When the data acquisition point is Start animal data acquisition in
[0151] The data acquisition unit 30 is used to determine if the drone is activated at the data acquisition point. Execute the animal data acquisition process and fly to the next data acquisition point after completion After that, the data acquisition point Replaced with the data acquisition point , and returns to execute the corresponding execution steps of the judgment unit;
[0152] The path control unit 40 is used to determine if it is not started, and the UAV directly flies to the data acquisition point , and the data acquisition point Replaced with the data acquisition point After that, return to execute the corresponding execution steps of the judgment unit;
[0153] The flight control unit 50 is configured to enable the drone to return to the set starting point of the animal data acquisition path after traversing all the data acquisition points and output the data collection results.
[0154] The above units are used to implement the above-mentioned drone data acquisition system, and will not be introduced one by one here.
[0155] Figure 4 FIG1 shows an internal structure diagram of a computer device in an embodiment. The computer device may be a server, including but not limited to a high-performance computer and a high-performance computer cluster. Figure 4 As shown, the computer device includes a processor, memory, and a network interface connected via a system bus. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium of the computer device stores an operating system and may also store a computer program. When executed by the processor, the computer program causes the processor to implement the described drone data collection method. The internal memory may also store a computer program. When executed by the processor, the computer program causes the processor to perform the described drone data collection method.
[0156] In one embodiment, the drone data collection method provided by the present invention can be implemented in the form of a computer program. The computer program can be used in Figure 4 The computer device shown in FIG. The computer device's memory can store various program templates that make up the drone data acquisition system. For example, 10 - path generation unit, 20 - judgment unit, 30 - data acquisition unit, 40 - path control unit, and 50 - flight control unit.
[0157] A computer device comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the following steps are implemented:
[0158] S1: Generate and traverse preset data acquisition points within the monitoring area The animal data acquisition path;
[0159] S2: When the drone arrives at the data acquisition point along the animal data acquisition path When the data acquisition point is Start animal data acquisition in
[0160] S3: If started, the UAV is at the data acquisition point Execute the animal data acquisition process and fly to the next data acquisition point after completion After that, the data acquisition point Replaced with the data acquisition point , and return to step S2;
[0161] S4. If not started, the drone will fly directly to the data acquisition point , and the data acquisition point Replaced with the data acquisition point Then, return to step S2;
[0162] S5. After traversing all the data acquisition points, the drone returns to the set starting point of the animal data acquisition path and outputs the data collection results.
[0163] From the above embodiments, it can be seen that the greatest beneficial effect of the present invention is that by generating an animal data acquisition path that traverses preset data acquisition points in the monitoring area, and by using a drone to fly along the animal data acquisition path to reach the data acquisition point to acquire data, it is possible to achieve manual acquisition of data from each data acquisition point without the need for manual labor, thereby reducing the workload and labor costs of data recovery. At the same time, since the drone does not need to be required to work in an area covered by mobile communication signals when acquiring data, the requirements for mobile communication signal coverage and maintenance in the monitoring area are reduced, solving the problem in the prior art that manual data recovery is required when performing field data monitoring through infrared cameras, resulting in high workload and labor costs, and the rigid requirement for mobile communication signal coverage in the monitoring area, which makes maintenance of the monitoring area difficult. This reduces the difficulty of maintaining the monitoring area and the workload and labor costs when performing field data monitoring in the monitoring area.
[0164] The above description is only a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by any technician familiar with this technical field within the technical scope disclosed in the present invention should be covered by the scope of protection of the present invention.
Claims
1. A drone data collection method for collecting data on wild animals in a monitoring area, characterized in that: include: S1: Generate and traverse preset data acquisition points within the monitoring area The animal data acquisition path; S2: When the drone arrives at the data acquisition point along the animal data acquisition path When the data acquisition point is Start animal data acquisition in S3: If started, the UAV is at the data acquisition point Execute the animal data acquisition process and fly to the next data acquisition point after completion After that, the data acquisition point Replaced with the data acquisition point , and return to step S2; S4. If not started, the drone will fly directly to the data acquisition point , and the data acquisition point Replaced with the data acquisition point Then, return to step S2; S5. After traversing all the data acquisition points, the drone returns to the set starting point of the animal data acquisition path and outputs the data collection results; in The step S2 specifically includes: S2a, when the drone arrives at the data acquisition point along the animal data acquisition path When the data acquisition point is obtained The matching online search planning formula is specifically embodied as follows: ； in For the data acquisition point The corresponding final decision coefficient is, To obtain each of the data acquisition points The data collection cost, For each of the data acquisition points The corresponding data collection income That is, the data acquisition points that the drone has passed Corresponding historical sensor information; S2b, performing integer constraints and dual decision planning on the online search planning formula, and calculating the final decision coefficient based on the results of the integer constraints and the dual decision planning. The value of S2c, when the final decision coefficient When it is 1, execute step S3; S2d, when the final decision coefficient When it is 0, execute step S4; The step S2b specifically includes: S2e, performing integer constraints on the online search planning formula to obtain a corresponding linear planning formula, which is specifically embodied as follows: ； in, Get the point for the data The matching decision variable coefficients, To set the energy budget, It is used to indicate that the formula is a dual relation formula, and T is the transpose symbol of the matrix formula; S2f, record the optimal solution output by the linear programming formula as the linear programming optimal solution; S2g, performing dual decision planning on the online search planning formula, thereby obtaining a corresponding dual decision planning formula, wherein the dual decision planning formula is specifically embodied as follows: ； ； in, and p are the preset dual decision variable values, For each of the data acquisition points Matching data collection benefits; S2h, recording the optimal solution output by the dual decision planning formula as the dual decision optimal solution; S2i, based on the optimal solution of the linear programming and the optimal solution of the dual decision, the complementary conditions are calculated to obtain the final decision coefficient .
2. The drone data collection method according to claim 1, wherein: The step S1 specifically includes: S1a, obtaining each of the data acquisition points The data collection cost and the set energy budget of the UAV are recorded as data collection cost and setting energy budget b; S1b, setting the data acquisition point Matched decision variable coefficients ; S1c, according to the data collection cost , the set energy budget b and the decision variable coefficient Generate a traversal of the data acquisition points The animal data acquisition path.
3. The drone data collection method according to claim 2, wherein: The step S1c specifically includes: S1d, generating and traversing the data acquisition points based on preset constraints The animal data acquisition path, the starting point and the end point of the animal data acquisition path are the same data acquisition point , and the preset constraints are as follows: ； Wherein, V is each of the data acquisition points The set of V= , E is the path between each of the data acquisition points, E , c and y are both referential vectors, when or When the vector value of is 0, it means that the UAV has not flown through the path ( ,when or When the vector value of is 1, it means the drone is flying through the path ( ).
4. The drone data collection method according to claim 2, wherein: After step S1c, the method further includes: S1g, setting and each of the data acquisition points Matching data collection benefits ; S1h, obtaining a set integer linear programming formula, which is used to maximize the value of each data acquisition point The corresponding data collection income , the integer linear programming formula is specifically embodied as follows: ； ； Then the integer linear programming output is That is, the data collection income in the animal data acquisition path Maximize results, It is used to indicate that the formula is a dual relation formula, and T is the transpose symbol of the matrix formula.
5. The drone data collection method according to claim 1, wherein: The step S2i specifically includes: S2j, obtain the set complementary condition calculation formula, which is specifically embodied as follows: ； S2k, then the output result of the complementary condition calculation formula is the final decision coefficient .
6. A drone data collection system for collecting data on wild animals in a monitoring area, characterized in that: include: A path generation unit is used to generate a path through the preset data acquisition points within the monitoring area. The animal data acquisition path; A judgment unit is used to determine when the drone reaches the data acquisition point along the animal data acquisition path. When the data acquisition point is Start animal data acquisition in The data acquisition unit is used to determine if the drone is started at the data acquisition point Execute the animal data acquisition process and fly to the next data acquisition point after completion After that, the data acquisition point Replaced with the data acquisition point , and returns to execute the corresponding execution steps of the judgment unit; The path control unit is used to determine if it is not started, and the UAV will fly directly to the data acquisition point , and the data acquisition point Replaced with the data acquisition point After that, return to execute the corresponding execution steps of the judgment unit; A flight control unit, configured to cause the drone to return to a set starting point of the animal data acquisition path after traversing all the data acquisition points, and output data acquisition results; When the drone arrives at the data acquisition point along the animal data acquisition path When the data acquisition point is The process of starting animal data acquisition specifically includes: S2a, when the drone arrives at the data acquisition point along the animal data acquisition path When the data acquisition point is obtained The matching online search planning formula is specifically embodied as follows: ； in For the data acquisition point The corresponding final decision coefficient is, To obtain each of the data acquisition points The data collection cost, For each of the data acquisition points The corresponding data collection income That is, the data acquisition points that the drone has passed Corresponding historical sensor information; S2b, performing integer constraints and dual decision planning on the online search planning formula, and calculating the final decision coefficient based on the results of the integer constraints and the dual decision planning. The value of S2c, when the final decision coefficient When it is 1, the UAV is at the data acquisition point Execute the animal data acquisition process and fly to the next data acquisition point after completion After that, the data acquisition point Replaced with the data acquisition point , and returns to execute the corresponding execution steps of the judgment unit; S2d, when the final decision coefficient When it is 0, the drone flies directly to the data acquisition point , and the data acquisition point Replaced with the data acquisition point After that, return to execute the corresponding execution steps of the judgment unit; The step S2b specifically includes: S2e, performing integer constraints on the online search planning formula to obtain a corresponding linear planning formula, which is specifically embodied as follows: ； in, Get the point for the data The matching decision variable coefficients, To set the energy budget, It is used to indicate that the formula is a dual relation formula, and T is the transpose symbol of the matrix formula; S2f, record the optimal solution output by the linear programming formula as the linear programming optimal solution; S2g, performing dual decision planning on the online search planning formula, thereby obtaining a corresponding dual decision planning formula, wherein the dual decision planning formula is specifically embodied as follows: ； ； in, and p are the preset dual decision variable values, For each of the data acquisition points Matching data collection benefits; S2h, recording the optimal solution output by the dual decision planning formula as the dual decision optimal solution; S2i, based on the optimal solution of the linear programming and the optimal solution of the dual decision, the complementary conditions are calculated to obtain the final decision coefficient .
7. A computer device, characterized in that: The method comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the drone data acquisition method according to any one of claims 1 to 5 when executing the computer program.
8. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the drone data collection method according to any one of claims 1 to 5 is implemented.