Deinsectization system, cooperative control system and computer equipment

Abstract

The invention provides a deinsectization system, a cooperative control system and computer equipment. The deinsectization system comprises a standardization module, a data processing module and a deinsectization lamp module, the standardization module is used for receiving first detection data sent by the agricultural system and converting the first detection data into second detection data, and the second detection data is in a preset data format; the data processing module is used for generating a first control instruction according to the second detection data, and the first control instruction is used for controlling the working state of the deinsectization lamp module.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to an insect extermination system, a collaborative control system and a computer device. Background Art

[0002] At present, pest control systems have been widely used in agricultural production, which can effectively control crop pests, reduce the use of pesticides, and improve crop yield and quality. In the prior art, pest control systems usually adopt a single control strategy and cannot be adjusted according to the data of other agricultural systems (such as weather stations, soil monitoring systems, etc.), resulting in low pest control efficiency. Summary of the invention

[0003] A technical problem to be solved by this application is: how to achieve coordinated control between the insect killing lamp system and other agricultural systems to improve the insect killing effect and agricultural production efficiency.

[0004] In order to solve the above technical problems, the embodiments of the present application provide an insect extermination system, a collaborative control system and a computer device.

[0005] An embodiment of the present application provides an insect extermination system, which includes: a standardization module, a data processing module and an insect extermination lamp module; the standardization module is used to receive first detection data sent by an agricultural system and convert the first detection data into second detection data, and the second detection data is in a preset data format; the data processing module is used to generate a first control instruction based on the second detection data, and the first control instruction is used to control the working state of the insect extermination lamp module.

[0006] In some embodiments, the standardization module includes a data exchange unit and a format conversion unit. The data exchange unit is used to receive first detection data sent by the agricultural system; the format conversion unit is used to convert the first detection data into second detection data, and the second detection data is in a preset data format.

[0007] In some embodiments, the data processing module includes a data preprocessing unit and a control instruction generating unit; the data preprocessing unit is used to clean, standardize and fuse the second detection data to generate third detection data; the control instruction generating unit is used to generate a first control instruction based on the third detection data.

[0008] In some embodiments, the standardization module also includes a control instruction receiving unit and a protocol adapter unit; the control instruction receiving unit is used to receive a first control instruction and send the first control instruction to the protocol adapter unit; the protocol adapter unit is used to convert the first control instruction into a second control instruction, and the second control instruction uses a communication protocol adapted by the insect killer lamp module.

[0009] In some embodiments, the data preprocessing unit is used to remove outliers in the second detection data to achieve cleaning of the second detection data, wherein when |x_t-MA_t|>k×σ, x_t is considered to be an outlier, where k is a preset constant, σ is the standard deviation, and MA_t=(x_(tn)+...+x_(t-1)+x_t) / (n+1).

[0010] In some embodiments, the data processing module also includes a model prediction unit, which is used to predict the insect activity trend based on the third detection data, and obtain the working parameters of the insect killing lamp module based on the insect activity trend; the control instruction generation unit is also used to generate a first control instruction based on the working parameters of the insect killing lamp module.

[0011] In some embodiments, the control instruction generating unit is further used to generate a third control instruction according to the second detection data, and the third control instruction is used to control the working state of the agricultural system.

[0012] In some embodiments, the first detection data includes: one or more of pest monitoring data, meteorological data, and soil data.

[0013] An embodiment of the present application provides a collaborative control system, which includes: an agricultural system and an insect extermination system; the insect extermination system is used to receive first detection data from the agricultural system.

[0014] An embodiment of the present application provides a computer device, including a processor and a memory storing a computer program, and the processor runs a collaborative control system when executing the program.

[0015] Through the above technical scheme, various detection data detected by the agricultural system can be converted into a data format supported by the data processing module through the standardization module, so that the data processing module can adjust the working state of the insect-killing lamp module according to the various detection data detected by the agricultural system, thereby realizing data sharing between the insect-killing lamp module and other agricultural systems, breaking the data island, realizing coordinated control with other agricultural equipment, and improving the insect control effect and energy utilization efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0017] Figure 1 It is a schematic diagram of the structure of the collaborative control system disclosed in the embodiment of the present application;

[0018] Figure 2 It is a structural schematic diagram of the insect extermination system disclosed in the embodiment of the present application;

[0019] Figure 3 It is a structural schematic diagram of the insect killer lamp module disclosed in the embodiment of the present application;

[0020] Figure 4 It is a schematic diagram of the structure of the standardized module disclosed in the embodiment of the present application;

[0021] Figure 5 is a schematic diagram of the structure of a standardized module disclosed in yet another embodiment of the present application;

[0022] Figure 6 It is a structural diagram of a data processing module disclosed in an embodiment of the present application;

[0023] Figure 7 is a structural diagram of a data processing module disclosed in yet another embodiment of the present application;

[0024] Figure 8 is a structural schematic diagram of an insect extermination system disclosed in yet another embodiment of the present application;

[0025] Fig. 9 is a structural schematic diagram of an insect extermination system disclosed in yet another embodiment of the present application;

[0026] Fig.10 It is a flowchart of the collaborative control method disclosed in the embodiment of the present application;

[0027] Fig.11 A schematic diagram of the structure of a computer device disclosed in an embodiment of the present application.

[0028] Description of reference numerals:

[0029] 100. Insect killing system; 110. Standardization module; 112. Data exchange unit; 113. Format conversion unit; 114. Control instruction receiving unit; 115. Protocol adaptation unit; 120. Data processing module; 121. Data preprocessing unit; 122. Control instruction generating unit; 123. Model prediction unit; 130. Insect killing lamp module; 131. Insect attractant lamp; 132. Insect killer; 140. Cooperative control module; 150. Security authentication module; 200. Agricultural system; 201. Weather station; 202. Soil monitoring system; 203. Automatic irrigation system; 204. UAV spraying system; 501. Processor; 502. Communication interface; 503. Memory; 504. Communication bus. DETAILED DESCRIPTION

[0030] The following is a further detailed description of the implementation methods of the present application in conjunction with the accompanying drawings and examples. The detailed descriptions of the following examples and the accompanying drawings are used to exemplarily illustrate the principles of the present application, but cannot be used to limit the scope of the present application. The present application can be implemented in many different forms and is not limited to the specific embodiments disclosed herein, but includes all technical solutions that fall within the scope of the claims.

[0031] The present application provides these embodiments to make the present application thorough and complete, and to fully express the scope of the present application to those skilled in the art. It should be noted that unless otherwise specifically stated, the relative arrangement of the parts and steps, the composition of the materials, the numerical expressions and the numerical values ​​set forth in these embodiments should be interpreted as being merely exemplary, and not as limiting.

[0032] In addition, words such as “include” or “comprises” and the like used in the present application mean that the elements before the word include the elements listed after the word, and do not exclude the possibility of also including other elements.

[0033] It should also be noted that in the description of this application, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be directly connected or indirectly connected through an intermediate medium. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to the specific circumstances. When a specific device is described as being located between a first device and a second device, there may or may not be an intermediate device between the specific device and the first device or the second device.

[0034] All terms used in this application have the same meaning as those understood by those of ordinary skill in the art to which this application belongs, unless otherwise specifically defined. It should also be understood that terms defined in general dictionaries, such as general dictionaries, should be interpreted as having a meaning consistent with their meaning in the context of the relevant technology, and should not be interpreted in an idealized or extremely formal sense, unless explicitly defined herein.

[0035] Technologies, methods, and equipment known to ordinary technicians in the relevant art may not be discussed in detail, but where appropriate, the technologies, methods, and equipment should be considered part of the specification.

[0036] At present, insect-killing lamp modules have been widely used in agricultural production, which can effectively control crop pests, reduce the use of pesticides, and improve crop yield and quality. In the prior art, insect-killing lamp modules usually adopt a single control strategy, such as turning on at a fixed time period or based on light intensity control. Insect-killing lamp modules generally control the switch of lamps by detecting the ambient light intensity through a photosensitive sensor.

[0037] However, this control method has the following problems:

[0038] 1. The pest monitoring data generated by the insect killer lamp module cannot be shared with other agricultural systems, making it difficult to achieve comprehensive agricultural decision support. 2. The working mode of the insect killer lamp module cannot be intelligently adjusted according to the data of other agricultural systems (such as weather stations, soil monitoring systems, etc.). 3. It is difficult to achieve coordinated control with other agricultural systems (such as automatic irrigation systems, drone spraying systems, etc.). 4. Poor scalability, making it difficult to quickly integrate new smart agricultural equipment and systems.

[0039] To this end, the present application embodiment provides a collaborative control system, such as Figure 1 As shown, the collaborative control system includes: an agricultural system 200 and an insect extermination system 100 .

[0040] The agricultural system 200 may include a weather station 201, a soil monitoring system 202, an automatic irrigation system 203, a drone spraying system 204, and the like.

[0041] The meteorological station 201 is a facility used to monitor and record weather phenomena. It can measure atmospheric parameters such as temperature, air pressure, humidity, wind speed, wind direction, precipitation, etc. Changes in these atmospheric parameters will affect the activity trajectory of insects.

[0042] The soil monitoring system 202 can monitor various environmental factors in the soil (such as soil moisture, temperature, pH, salinity, etc.) in real time. These environmental factors will affect the distribution density of insects.

[0043] The automatic irrigation system 203 and the drone spraying system 204 can change the humidity in the air, which will also affect the movement trajectory of insects, thereby affecting the insect killing effect of the insect killing system 100.

[0044] The network is used as a medium for providing a communication link between multiple agricultural systems 200 and the pest control system 100. The agricultural system 200 and the pest control system 100 can communicate directly or indirectly through the network, and the embodiments of the present application are not limited here. For example, the agricultural system 200 can directly send the first detection data to the pest control system 100 through the network. The network can include various connection types, such as wired, wireless communication links or optical fiber cables, etc. The embodiments of the present application are also not limited here.

[0045] like Figure 2As shown, the insect killing system 100 includes a standardization module 110, a data processing module 120 and an insect killing lamp module 130; the standardization module 110 is used to receive the first detection data sent by the agricultural system 200, and convert the first detection data into second detection data, and the second detection data is a preset data format; the data processing module 120 is used to generate a first control instruction according to the second detection data, and the first control instruction is used to control the working state of the insect killing lamp module 130.

[0046] In the embodiment of the present application, various detection data detected by the agricultural system 200 can be converted into a data format supported by the data processing module 120 through the standardization module 110, so that the data processing module 120 can adjust the working state of the insect-killing lamp module 130 according to the various detection data detected by the agricultural system 200, thereby realizing data sharing between the insect-killing lamp module 130 and other agricultural systems 200, breaking data silos, realizing coordinated control with other agricultural equipment, and improving insect control effects and energy utilization efficiency.

[0047] In a specific embodiment, each module in the above-mentioned pest control system 100 is specifically introduced below.

[0048] like Figure 3 As shown, the insect killer lamp module 130 includes an insect trap lamp 131 and an insect killer 132. The insect trap lamp 131 can emit light of a specific wavelength to attract insects, such as light with a wavelength in the ultraviolet range. Since many insects are very sensitive to such light, insects can be attracted to the vicinity of the insect trap lamp 131.

[0049] The insect killer 132 is arranged around the insect trap light 131. When the insect trap light 131 attracts the insects to the insect killing range of the insect killer 132, the insect killer 132 can capture the insects. For example, the insect killer 132 may include at least one electric grid. When the insects approach the electric shock range of the electric grid, the insects are given electric shocks, thereby killing them. Alternatively, the insecticide includes a sticky material. The insects are attracted by the insect trap light 131 and approach the sticky material and are captured by the sticky material, thereby achieving the effect of killing insects.

[0050] The standardization module 110 adopts a (Representational State Transfer) architecture, and the RESTful architecture implements communication between systems by operating resources (such as obtaining, creating, updating, and deleting) through the HTTP protocol.

[0051] For example, the following example uses HTTP methods to represent operations:

[0052] GET is used to obtain a resource or resource collection. For example, to obtain pest monitoring data: GET

[0053] / api / v1 / pest-data; POST is used to create new resources. For example, send control commands: POST / api / v1 / control-commands; PUT is used to update existing resources. For example, update device settings: PUT / api / v1 / device-settings; DELETE is used to delete existing resources. For example, delete historical data: DELETE / api / v1 / historical-data.

[0054] In a specific embodiment, Figure 4 As shown, the standardization module 110 includes a data exchange unit 112 and a format conversion unit 113. The data exchange unit 112 is used to receive first detection data sent by the agricultural system 200. The first detection data includes one or more of pest monitoring data, meteorological data, and soil data.

[0055] The format conversion unit 113 is used to convert the first detection data into second detection data, where the second detection data is in a preset data format, and the preset data format is a standard JSON format to ensure the consistency and availability of the second detection data.

[0056] The following is an example of the standard JSON format:

[0057] {

[0058] "device_id":"LT001",

[0059] "timestamp":1623456789,

[0060] "data_type":"pest_count",

[0061] "value":56,

[0062] "unit":"count / hour"

[0063] }

[0064] In a specific embodiment, Figure 5 As shown, the standardization module 110 also includes a control instruction receiving unit 114 and a protocol adapter unit. The control instruction receiving unit 114 receives and forwards control instructions to achieve collaborative control between systems. For example, the control instruction receiving unit 114 can receive a first control instruction and send the first control instruction to the protocol adapter unit. The protocol adapter unit is responsible for adapting the communication protocols of different systems to achieve seamless docking. For example, the protocol adapter unit can convert the first control instruction into a second control instruction, and the second control instruction uses the communication protocol adapted by the insect killer module 130.

[0065] In a specific embodiment, Figure 6 As shown, the data processing module 120 includes a data preprocessing unit 121 and a control instruction generating unit 122 .

[0066] The data preprocessing unit 121 is used to clean, standardize and fuse the second detection data to generate third detection data.

[0067] Specifically, the data preprocessing unit 121 removes abnormal values ​​in the second detection data by using a moving average method to clean the second detection data.

[0068] Among them, when |x_t-MA_t|>k×σ, x_t is considered to be an outlier, where k is a preset constant, σ is the standard deviation, and MA_t=(x_(tn)+...+x_(t-1)+x_t) / (n+1).

[0069] Then, the data preprocessing unit 121 performs standardization processing on the second detection data by a Z-score standardization method (also known as zero mean unit variance standardization), which can convert features of different scales into a unified scale. The purpose of Z-score standardization is to make the mean of each data in the second detection data 0 and the standard deviation 1, thereby eliminating the dimensional differences between different features, so that the subsequent data processing module 120 can process the second detection data.

[0070] Each data in the second detection data can be converted by the following formula:

[0071] z=(x-μ) / σ

[0072] Among them, x is the original value, μ is the mean, and σ is the standard deviation.

[0073] Then, the data preprocessing unit 121 performs spatiotemporal alignment of multiple data in the second detection data through a Kalman filter calculation method. Spatiotemporal alignment generally refers to the unified processing and matching of data from different sources in the spatiotemporal dimension. For example, the sampling frequencies and timestamps of different agricultural systems 200 (such as a weather station 201, a soil monitoring system 202, an automatic irrigation system 203, an unmanned aerial vehicle spraying system 204, etc.) may not be completely consistent, so it is necessary to interpolate and align the timestamps of each data in the second detection data to estimate the optimal state at a certain moment. For example, a prediction model is used to compensate for data in a time period in the second detection data so that data at different time points are aligned in space so that subsequent analysis and processing can be performed.

[0074] The Kalman filter calculation method estimates the state of a dynamic system through a set of recursive formulas. It consists of two parts: prediction and update.

[0075] Prediction: Based on the current system state model (dynamic equation), predict the system state at the next moment. This step does not depend on the second detection data obtained at the new moment. The specific calculation method of the prediction value is as follows:

[0076] x_k=F×x_(k-1)+B×u_k+w_k

[0077] Update: Use the second detection data obtained at the new time to correct the predicted result. Assume that the difference between the second detection data and the predicted value is the residual, and use the residual to adjust the predicted value. The specific calculation method is as follows:

[0078] y_k=z_k-H×x_k

[0079] K_k=P_k×H T ×(H×P_k×H T +R) -1

[0080] x_k=x_k+K_k×y_k

[0081] P_k=(I-K_k×H)×P_(k-1)

[0082] Among them, x_k is the predicted value, x_(k-1) is the second detection data at the previous moment, F is the state transfer matrix, B is the control matrix, w_k is the process noise, u_k is the control input, H is the observation matrix, z_k is the second detection data obtained at the new moment, K_k is the Kalman gain, which represents the trade-off between the predicted value and the second detection data. P_k is the error covariance matrix, R is the observation noise covariance, and I is the unit matrix.

[0083] Finally, the data preprocessing unit 121 extracts key features by applying the principal component analysis (PCA) method to obtain the third detection data. The principal component analysis method can select the most representative principal component in the second detection data, which can effectively reduce the number of features, avoid dimensionality disaster, and improve computing efficiency. This part can refer to the relevant content in the prior art, and the embodiment of the present application will not be described in detail.

[0084] Correspondingly, the control instruction generation unit 122 generates a first control instruction according to the third detection data. The first control instruction is used to control the working state of the insect-killing lamp module 130. The control instruction generation unit 122 sends the first control instruction to the protocol adapter unit through the control instruction receiving unit 114. The protocol adapter unit converts the first control instruction into a second control instruction that can adapt to the communication protocol supported by the insect-killing lamp module 130, thereby achieving seamless docking.

[0085] In some specific embodiments, Figure 7 As shown, the data processing module 120 further includes a model prediction unit 123. The model prediction unit 123 is used to predict the insect activity trend according to the third detection data, so as to dynamically adjust the working state of the insect killing lamp unit.

[0086] Specifically, the model prediction unit 123 uses a random forest model to predict the trend of insect activity. The random forest model can be obtained by training in advance. During the training process, it is necessary to first establish a training set, and the data in the training set includes multiple sample data. The sample data includes multiple feature data that affect insect activity, such as the ambient temperature, humidity, precipitation, season, etc. of the insects in the third detection data. The sample data also includes the insect activity data corresponding to each feature data. Then a decision tree is constructed by non-parametric resampling (bootstrap sampling) and feature random selection. In the process of bootstrap sampling, each decision tree randomly selects sample data from the training set with replacement, that is, the sample data selected by different decision trees can be repeated. This allows each decision tree to use only part of the sample data for training, thereby increasing the diversity of the random forest model.

[0087] In the process of random feature selection, each tree randomly selects a subset of features when splitting a node, and splits the node in these features until the tree reaches a predetermined maximum depth or the number of samples in the node is less than a certain threshold. That is, instead of using all features, a portion of features is randomly selected for splitting, thereby reducing the overfitting of the random forest model.

[0088] In the above training process, multiple decision trees are generated, for example, 100-500 decision trees are generated, and each tree makes predictions independently. The average of the prediction results of all trees is taken as the final result, thereby predicting the insect activity trend.

[0089] Then, the model prediction unit 123 adjusts the working state of the insect-killing lamp module 130 through a genetic algorithm based on the predicted insect activity trend. The genetic algorithm is an optimization method that imitates natural selection and genetic mechanisms. By simulating the genetic variation, crossover, selection and other processes of organisms, it can calculate the working time, brightness, frequency and other parameters of the insect-killing lamp module 130 under different environmental conditions and pest activity conditions to improve the insect-killing effect.

[0090] In a specific example, an initial population is first generated, and each individual (chromosome) represents a possible working state of the insect-killing lamp module 130. Since each working parameter of the insect-killing lamp module 130 may affect the insect-killing effect and energy-saving effect, for example, the brightness of the insect-attracting lamp 131 in the insect-killing lamp module 130 may affect the effect of attracting pests; the light color wavelength (wavelength) of the insect-attracting lamp 131 has different attraction effects on different types of pests. The daily lighting time of the insect-attracting lamp 131 also needs to be set according to the activity pattern of the pests, and the lighting time of the insect-attracting lamp 131 will also affect the power consumption of the insect-killing lamp module 130. To this end, it is necessary to combine the various working parameters of the above-mentioned insect-killing lamp module 130. For example, the brightness, switching time, power, etc. of the insect-attracting lamp 131 are combined. The brightness, switching time and power of the insect-attracting lamp 131 are represented by binary coding.

[0091] Then the fitness of each individual is evaluated by the fitness function, that is, the insect extermination effect and energy saving effect of the strategy.

[0092] For example, the fitness function is f=w1×insect elimination effect+w2×energy efficiency.

[0093] Next, select the better individuals according to fitness. Common methods include roulette selection and tournament selection. Generate new individuals through crossover operation, usually by exchanging some genes of two parents to produce offspring. Crossover operation helps genetic diversity. Finally, make random small changes to individuals through mutation operation until the maximum number of iterations (usually set to 100) or fitness value converges. In this way, genetic diversity is maintained and local optimality is prevented.

[0094] Therefore, under different environmental conditions and pest activities, the working time, brightness, frequency and other parameters of the insect-killing lamp module 130 can be calculated, and the working state of the insect-killing lamp module 130 can be adjusted to improve the insect-killing effect.

[0095] Correspondingly, the control instruction generation unit 122 generates a first control instruction according to the calculated working parameters such as working time, brightness, frequency, etc. of the insect-killing lamp module 130. The first control instruction is used to control the working state of the insect-killing lamp module 130. The control instruction generation unit 122 sends the first control instruction to the protocol adapter unit through the control instruction receiving unit 114. The protocol adapter unit converts the first control instruction into a second control instruction that can adapt to the communication protocol supported by the insect-killing lamp module 130, thereby achieving seamless docking.

[0096] In some specific embodiments, the model prediction unit 123 can also calculate the working parameters of other agricultural systems 200 based on the insect activity trend. The control instruction generation unit 122 generates a third control instruction based on the calculated working parameters of other agricultural systems 200. The third control instruction is used to control the working state of other agricultural systems 200. The control instruction generation unit 122 sends the third control instruction to the protocol adaptation unit through the control instruction receiving unit 114. The protocol adaptation unit converts the third control instruction into a fourth control instruction that can adapt to the communication protocol supported by other agricultural systems 200, thereby achieving seamless docking.

[0097] In some specific embodiments, Figure 8 As shown, the pest control system 100 also includes a collaborative control module 140, which can realize the collaborative work of the pest control system 100 and other agricultural systems 200. Specifically, after the control instruction generation unit 122 sends the third control instruction to the protocol adaptation unit through the control instruction receiving unit 114, the protocol adaptation unit converts the third control instruction into a fifth control instruction that can adapt to the communication protocol supported by the collaborative control module 140. Then, after the collaborative control module 140 determines other agricultural systems 200 (such as automatic irrigation system 203, drone spraying system 204, etc.) that need to be coordinated according to the fifth control instruction, the device association network based on graph theory uses an adjacency matrix to represent the relationship between the agricultural systems 200, and applies the Floyd-Warshall algorithm to calculate the shortest path between the agricultural systems 200 that need to be coordinated. The algorithm complexity is O(n 3 ), where n is the number of agricultural systems 200. Then, a sixth control instruction is generated, which carries a collaborative control plan, which may include the working time, parameters, etc. of each agricultural system 200 and the shortest path between the agricultural systems 200 that need to be coordinated. Finally, the collaborative control module 140 sends the sixth control instruction to the protocol adaptation unit through the control instruction receiving unit 114. The protocol adaptation unit converts the sixth control instruction into a seventh control instruction that can adapt to the communication protocol supported by other agricultural systems 200, thereby achieving seamless docking.

[0098] In some specific embodiments, Fig. 9 As shown, the pest control system 100 also includes a security authentication module 150, which uses the OAuth 2.0 identity authentication mechanism and the HTTPS encryption transmission protocol to ensure the security of data exchange and control instruction transmission between the various modules of the pest control system 100. Exemplarily, HTTPS uses the TLS1.3 protocol and uses the RSA-2048 bit key for encryption. The authorization process of OAuth 2.0 is as follows: the client requests authorization from the authorization server, and after the user agrees to the authorization, the authorization server sends an authorization code to the client. The client uses the authorization code to request an access token from the authorization server, and the authorization server sends the access token to the client.

[0099] In some specific embodiments, the standardization module 110, the data processing module 120, the collaborative control module 140 and the security authentication module 150 in the above embodiments are all integrated in the server. An independent microservice is created for each module in the server. An exemplary multi-container application is orchestrated using Docker Compose, and the sample configuration file is as follows:

[0100] ```yaml

[0101] version:'3'

[0102] services:

[0103] api-gateway:

[0104] build:. / api-gateway

[0105] ports:

[0106] -"8080:8080"

[0107] auth-service:

[0108] build:. / auth-service

[0109] Data-processing:

[0110] build:. / data-processing

[0111] control-algorithm:

[0112] build:. / control-algorithm

[0113] coordination-service:

[0114] build:. / coordination-service

[0115] In some other examples, Kafka message queues are used to implement asynchronous communication between modules, and the theme designs include pest-data, weather-data, control-commands, etc. Elasticsearch+Kibana is deployed for data visualization and analysis, and dashboards are created to display key indicators such as insect acquisition trends, energy efficiency, and equipment coordination status.

[0116] It should be noted that the embodiments of the present application do not limit the type of server. The server can be an independent physical server, a server cluster or a distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms.

[0117] The present application also provides a collaborative control method, which can be applied to a server, such as Fig.10 As shown, the method includes: S10: receiving first detection data sent by the agricultural system, and converting the first detection data into second detection data, the second detection data is a preset data format; S20: generating a first control instruction according to the second detection data, the first control instruction is used to control the working state of the insect killer lamp module.

[0118] In an embodiment of the present application, by converting various detection data detected by the agricultural system into a preset data format, the server can adjust the working state of the insect-killing lamp module according to the various detection data detected by the agricultural system, thereby realizing data sharing between the insect-killing lamp module and other agricultural systems, breaking the data island, realizing coordinated control with other agricultural equipment, and improving the insect control effect and energy utilization efficiency.

[0119] Based on the above embodiments, the present application further provides a computer device, Fig.11 A schematic diagram of a computer device structure provided in an embodiment of the present application is shown in FIG. Fig.11 As shown, the computer device includes: a processor 501 , a communication interface 502 , a memory 503 and a communication bus 504 , wherein the processor 501 , the communication interface 502 , and the memory 503 communicate with each other via the communication bus 504 .

[0120] The memory 503 stores a computer program. When the program is executed by the processor 501, the processor 501 performs the following steps:

[0121] S10: receiving first detection data sent by the agricultural system, and converting the first detection data into second detection data, where the second detection data is in a preset data format;

[0122] S20: Generate a first control instruction according to the second detection data, where the first control instruction is used to control the working state of the insect killer lamp module.

[0123] The communication bus mentioned in the above computer device can be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. The communication bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, only one thick line is used in the figure, but it does not mean that there is only one bus or one type of bus.

[0124] The communication interface 502 is used for communication between the above-mentioned computer device and other devices.

[0125] The memory may include RAM (Random Access Memory) or NVM (Non-Volatile Memory), such as at least one disk memory. Optionally, the memory may also be at least one storage device located away from the aforementioned processor.

[0126] The above-mentioned processor can be a general-purpose processor, including a central processing unit, NP (Network Processor), etc.; it can also be a DSP (Digital Signal Processing), an application-specific integrated circuit, a field programmable gate array or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component, etc.

[0127] Based on the above embodiments, an embodiment of the present application provides a computer-readable storage medium, in which a computer program executable by a computer device is stored. When the program is run on the computer device, the computer device implements the following steps when executing:

[0128] S10: receiving first detection data sent by the agricultural system, and converting the first detection data into second detection data, where the second detection data is in a preset data format;

[0129] S20: Generate a first control instruction according to the second detection data, where the first control instruction is used to control the working state of the insect killer lamp module.

[0130] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0131] So far, various embodiments of the present application have been described in detail. In order to avoid obscuring the concept of the present application, some details known in the art are not described. Based on the above description, those skilled in the art can fully understand how to implement the technical solution disclosed herein.

[0132] Although some specific embodiments of the present application have been described in detail by way of examples, it should be understood by those skilled in the art that the above examples are for illustration only and are not intended to limit the scope of the present application. It should be understood by those skilled in the art that the above embodiments may be modified or some technical features may be replaced by equivalents without departing from the scope and spirit of the present application. In particular, the various technical features mentioned in the various embodiments may be combined in any manner as long as there is no structural conflict.

Claims

1. An insect extermination system, characterized in that: include: Standardization module, data processing module and insect killer lamp module; The standardization module is used to receive the first detection data sent by the agricultural system and convert the first detection data into second detection data, where the second detection data is in a preset data format; The data processing module is used to generate a first control instruction according to the second detection data, and the first control instruction is used to control the working state of the insect killer lamp module.

2. The system according to claim 1, characterized in that The standardized module includes a data exchange unit and a format conversion unit. The data exchange unit is used to receive first detection data sent by the agricultural system; The format conversion unit is used to convert the first detection data into second detection data, and the second detection data is in a preset data format.

3. The system according to claim 1, characterized in that The data processing module includes a data preprocessing unit and a control instruction generating unit; The data preprocessing unit is used to clean, standardize and fuse the second detection data to generate third detection data; The control instruction generating unit is used to generate a first control instruction according to the third detection data.

4. The system according to claim 3, characterized in that The standardization module also includes a control instruction receiving unit and a protocol adaption unit; The control instruction receiving unit is used to receive the first control instruction and send the first control instruction to the protocol adaptation unit; The protocol adaptation unit is used to convert the first control instruction into a second control instruction, and the second control instruction uses a communication protocol adapted by the insect killer lamp module.

5. The system according to claim 3, characterized in that The data preprocessing unit is used to remove abnormal values ​​in the second detection data to clean the second detection data. Among them, when |x_t-MA_t|>k×σ, x_t is considered to be an outlier, where k is a preset constant, σ is the standard deviation, and MA_t=(x_(tn)+...+x_(t-1)+x_t) / (n+1).

6. The system according to claim 5, characterized in that The data processing module also includes a model prediction unit. The model prediction unit is used to predict the insect activity trend according to the third detection data, and obtain the working parameters of the insect killing lamp module based on the insect activity trend; The control instruction generating unit is also used to generate a first control instruction according to the working parameters of the insect killer lamp module.

7. A system according to any one of claims 3 to 6, characterized in that The control instruction generating unit is further used to generate a third control instruction according to the second detection data, and the third control instruction is used to control the working state of the agricultural system.

8. A system according to any one of claims 1 to 6, characterised in that The first detection data includes: one or more of pest monitoring data, meteorological data, and soil data.

9. A collaborative control system, characterized in that: include: An agricultural system and an insecticide control system as claimed in any one of claims 1 to 8; The pest control system is used for receiving first detection data from the agricultural system.

10. A computer device comprising a processor and a memory storing a computer program, characterized in that: When the processor executes the program, the insect extermination system according to any one of claims 1 to 8 is operated.

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