Agricultural information monitoring mechanism and method based on big data

Abstract

The invention relates to the field of agricultural information, and particularly discloses an agricultural information monitoring mechanism and method based on big data. The communication controller, the storage battery and the photovoltaic panel are arranged in the field, the communication controller can convert light energy into electric energy through the photovoltaic panel and store the electric energy in the storage battery, then the storage battery supplies power to the detection unmanned aerial vehicle, and the communication controller sends a control instruction to the detection unmanned aerial vehicle. The detection unmanned aerial vehicle is controlled to fly in the field according to an instruction and collect related data, the farmland related data collected by the detection unmanned aerial vehicle is transmitted to a far-end monitoring center through the communication controller, and the detection unmanned aerial vehicle can stay on the placement plate to supplement electric energy. And the detection unmanned aerial vehicle transmits collected data to the monitoring center through the communication controller, so that the energy consumption of the detection unmanned aerial vehicle can be effectively reduced, the detection unmanned aerial vehicle can fly for a long time to collect related data, continuous monitoring of the farmland is realized, and an operator can conveniently obtain complete farmland data.

Description

Technical Field

[0001] The present invention belongs to the field of agricultural information technology, and in particular relates to an agricultural information monitoring mechanism and method based on big data. Background Art

[0002] With the rapid development of drone technology, it is common for all walks of life to use drones for operations. In the agricultural field, operators can operate drones to monitor vegetation. Drones are equipped with a variety of sensors, such as infrared, high-definition cameras and multi-spectral imagers, to obtain high-definition images of farmland in real time, helping migrant workers monitor the health of crops, pests and diseases, and soil moisture. The images and data taken by drones can also be used to judge the growth status of crops, discover crop growth problems in a timely manner, and make accurate agricultural management decisions. In addition, drones can also be used to accurately control the area and amount of fertilization and spraying, thereby avoiding waste of resources and reducing negative impacts on the environment.

[0003] When using drones to survey agricultural land, operators are required to control the drones in the fields, and the flying drones obtain field image data. This operation method still requires operators to go to the fields to control the drones, and the electricity consumed by the drones cannot be replenished in the fields, making it impossible to form continuous monitoring of the farmland, which is not conducive to operators obtaining complete farmland data. Summary of the invention

[0004] In order to overcome the shortcomings of the prior art, the purpose of the present invention is to provide an agricultural information monitoring mechanism and method based on big data to solve the problems that traditional drones have short operating time and short flight time, cannot form continuous monitoring of agriculture, and are not conducive to operators obtaining complete farmland data.

[0005] To achieve the above object, the present invention provides the following technical solutions: An agricultural information monitoring agency based on big data, including: A column, to which a communication controller for communication and a storage battery for function are connected, the communication controller is equipped with a data processing and analysis system for processing collected agricultural information, and the storage battery is connected to a placement board used as a take-off platform; A detection drone, which is placed on the placement board and is used to detect and collect agricultural information data, wherein the agricultural information data includes air temperature and humidity, carbon dioxide concentration, oxygen concentration, light intensity and farmland images; The mounting frame is arranged on one side of the column, the mounting frame is rotatably connected to a rotating frame, the inner wall of the rotating frame is fixedly connected to a photovoltaic panel electrically connected to the battery, and the rotating frame is provided with a cleaning component for cleaning the photovoltaic panel.

[0006] Preferably, a sealing cover that covers the detection drone is hinged on the placement plate, and a first electric telescopic rod is hinged between the sealing cover and the placement plate.

[0007] Preferably, a charging plate electrically connected to the battery is fixedly connected to the placement plate, a first motor is fixedly connected to the mounting frame, a first sprocket is fixedly connected to the end of the first motor, a chain is movably connected to the first sprocket, and both ends of the chain are respectively fixedly connected to the rotating frame.

[0008] Preferably, a second electric telescopic rod is fixedly connected to the mounting frame, and an end of the second electric telescopic rod is rotatably connected to a second sprocket abutting against the chain.

[0009] Preferably, the cleaning assembly includes a second motor slidably connected to the rotating frame, a cleaning rod fixedly mounted on the second motor, and an abutment plate fixedly mounted on the rotating frame and abutting against the cleaning rod, the cleaning rod includes an outer cylinder fixedly mounted on the second motor, an inner rod slidably inserted into the outer cylinder, and a cleaning rod fixedly mounted on the inner rod, the lower end of the cleaning rod protrudes out of the lower wall of the outer cylinder, a spring is provided inside the outer cylinder at both ends abutting against the outer cylinder and the inner rod respectively, and the end of the inner rod abuts against the wavy surface on the side of the abutment plate.

[0010] Preferably, a slide rail is fixedly connected to the rotating frame, a slider fixedly connected to the second motor is slidably connected to the slide rail, the slider is fixedly connected to the outer cylinder, a rack is fixedly connected to the rotating frame, and a gear meshing with the rack is fixedly connected to the output shaft of the second motor.

[0011] Preferably, the data processing and analysis system comprises: A data preprocessing unit, used for cleaning and standardizing the agricultural information data to obtain standardized complete agricultural information data; The data analysis unit uses crop pest and disease prediction models to process standardized complete agricultural information data and predict the risk of farmland pest and disease outbreaks; The crop pest and disease prediction model establishment method comprises: Collect multiple crop images of different climatic conditions, growth stages, and varieties, and mark the location and type of pests and diseases in the crop images; Preprocess the crop images to remove the background noise of the crop photos to obtain noise-free crop images, and use rotation, mirroring, and flipping to perform data enhancement to obtain a crop image dataset; The crop image dataset was divided into a training set and a test set in a ratio of 8:2, and the convolutional neural network model was trained using the training set to obtain a pest and disease prediction model. The test set was used to evaluate the pest and disease prediction model. The pest and disease prediction model was evaluated by accuracy, precision, recall and F1-score. The learning rate, number of network layers and regularization parameters of the pest and disease prediction model were adjusted to optimize the pest and disease prediction model and obtain the final pest and disease prediction model.

[0012] A method for monitoring agricultural information based on big data, applied to an agricultural information monitoring institution based on big data, comprising: The communication controller controls the rotation of the rotating frame so that the photovoltaic panel faces the sun, absorbs light energy and converts it into electrical energy to transmit to the storage battery, and controls the cleaning component to clean the photovoltaic panel at the same time; The communication controller controls the battery to supply power to the detection drone, and the communication controller controls the detection drone to fly over the agricultural land to obtain monitoring image data of the agricultural land. The detection drone transmits the monitoring image data to the communication controller, and transmits it to the remote monitoring center via the communication controller.

[0013] Compared with the prior art, the present invention has the following beneficial effects: The present invention arranges a communication controller, a battery and a photovoltaic panel in the field. The communication controller can convert light energy into electrical energy through the photovoltaic panel and store it in the battery. The battery then powers the detection drone. The communication controller sends control instructions to the detection drone, controls the detection drone to fly in the field according to the instructions and collect relevant data. The farmland-related data collected by the detection drone is transmitted to a remote monitoring center through the communication controller. The detection drone can stay on the placement board to replenish power. The detection drone transmits the collected data to the monitoring center through the communication controller, which can effectively reduce the energy consumption of the detection drone, so that the detection drone can fly for a long time to collect relevant data, realize continuous monitoring of the farmland, and is beneficial for operators to obtain complete farmland data. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 It is a schematic diagram of the overall structure of the present invention; Figure 2 It is a schematic diagram of the column structure of the present invention; Figure 3 It is a schematic diagram of the structure of the mounting frame of the present invention; Figure 4 For the present invention Figure 3 A magnified image of the middle part; Figure 5 For the present invention Figure 3 Enlarged view of part B in the middle; Figure 6 It is a schematic diagram of the structure of the cleaning component of the present invention; Figure 7 It is a structural block diagram of the data processing and analysis system of the present invention; Figure 8 A method block diagram for establishing a crop pest prediction model of the present invention; In the figure: 1. column; 2. communication controller; 3. battery; 4. placement plate; 5. sealing cover; 6. first electric telescopic rod; 7. charging plate; 8. detection drone; 9. mounting frame; 10. rotating frame; 11. photovoltaic panel; 12. first motor; 13. first sprocket; 14. chain; 15. second electric telescopic rod; 16. second sprocket; 17. second motor; 18. slide rail; 19. slider; 20. gear; 21. rack; 22. outer cylinder; 23. inner rod; 24. cleaning strip; 25. spring; 26. stop plate. DETAILED DESCRIPTION

[0015] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. Embodiment 1:

[0016] See also Figure 1 - Figure 8 As shown, an agricultural information monitoring agency based on big data includes: A column 1, to which a communication controller 2 for communication and a storage battery 3 for function are connected, the communication controller 2 has a built-in data processing and analysis system for processing collected agricultural information, and the storage battery 3 is connected to a placement board 4 used as a take-off platform; A detection drone 8, the detection drone 8 is placed on the placement board 4, and is used to detect and collect agricultural information data, the agricultural information data includes air temperature and humidity, carbon dioxide concentration, oxygen concentration, light intensity and farmland images; The mounting frame 9 is arranged on one side of the column 1. The mounting frame 9 is rotatably connected to a rotating frame 10. The inner wall of the rotating frame 10 is fixedly connected to a photovoltaic panel 11 electrically connected to the battery 3. The rotating frame 10 is provided with a cleaning component for cleaning the photovoltaic panel 11.

[0017] As can be seen from the above, by setting up a communication controller 2, a battery 3 and a photovoltaic panel 11 in the field, the communication controller 2 can convert light energy into electrical energy through the photovoltaic panel 11 and store it in the battery 3, and then the battery 3 supplies power to the detection drone 8. The communication controller 2 issues a control instruction to the detection drone 8 to control the detection drone 8 to fly in the field according to the instruction and collect relevant information. The farmland-related information collected by the detection drone 8 is transmitted to the remote monitoring center through the communication controller 2. At the same time, the communication controller 2 can analyze the collected farmland-related data through the built-in processing and analysis system, determine the risk of pests and diseases in the farmland, and then transmit the risk to the corresponding terminal or monitoring center. The detection drone 8 can stay on the placement board 4 to replenish electricity, and the detection drone 8 transmits the collected data to the monitoring center through the communication controller 2, which can effectively reduce the energy consumption of the detection drone 8, so that the detection drone 8 can fly for a long time to collect relevant information, realize continuous monitoring of the farmland, and facilitate the operators to obtain complete farmland information.

[0018] See also Figure 1 - Figure 2 As shown, a sealing cover 5 for covering the detection drone 8 is hinged on the placement plate 4, and a first electric telescopic rod 6 is hinged between the sealing cover 5 and the placement plate 4. When the detection drone 8 stays on the placement plate 4 for trimming, in order to ensure that the drone is not affected by the outside world, such as preventing the drone from being eroded by wind and rain, the sealing cover 5 can be driven to rotate by the extension of the first electric telescopic rod 6, so that the sealing cover 5 rotates to the top of the placement plate 4 to cover the detection drone 8, thereby preventing the detection drone 8 from being affected by the outside world during the correction and rest process.

[0019] The placement plate 4 is fixedly connected with a charging plate 7 electrically connected to the battery 3 . The charging plate 7 charges the detection drone 8 in a wireless charging manner, so that the detection drone 8 can be charged autonomously.

[0020] See also Figure 3 - Figure 5 As shown, a first motor 12 is fixedly connected to the mounting frame 9, a first sprocket 13 is fixedly connected to the end of the first motor 12, a chain 14 is movably connected to the first sprocket 13, and both ends of the chain 14 are respectively fixedly connected to the rotating frame 10. When the sun is offset, in order to increase the amount of light collected by the photovoltaic panel 11, the first motor 12 can be controlled to drive the first sprocket 13 to rotate, the rotating first sprocket 13 drives the chain 14 to rotate, and the rotating chain 14 drives the rotating frame 10 and the photovoltaic panel 11 to rotate, so as to adjust the direction of the photovoltaic panel 11, maintain a high amount of light collected by the photovoltaic panel 11, and facilitate the collection of electrical energy.

[0021] In order to prevent the chain 14 from being unable to rotate due to length limitation during the rotation process, the length of the chain 14 can be extended, and a second electric telescopic rod 15 is fixedly connected to the mounting frame 9, and the end of the second electric telescopic rod 15 is rotatably connected to a second sprocket 16 abutting against the chain 14. A sensor that can sense the pressure of the second sprocket 16 can be installed at the end of the electric telescopic rod 15 to control the pressure of the second sprocket 16 within a certain range. When the rotating frame 10 rotates to cause the chain 14 to rotate, the pressure of the chain 14 on the second sprocket 16 will change. At this time, the second electric telescopic rod 15 contracts and extends, ensuring that the chain 14 can be stably fitted on the first sprocket 13 and the second sprocket 16, while also avoiding excessive tension of the chain 14, which helps the first sprocket 13 control the rotation of the rotating frame 10 through the chain 14.

[0022] See also Figure 3 - Figure 6 As shown, the cleaning assembly includes a second motor 17 slidably connected to the rotating frame 10, a cleaning rod fixedly mounted on the second motor 17, and a butt plate 26 fixedly mounted on the rotating frame 10 and abutting against the cleaning rod, the cleaning rod includes an outer cylinder 22 fixedly mounted on the second motor 17, an inner rod 23 slidably inserted into the outer cylinder 22, and a cleaning strip 24 fixedly mounted on the inner rod 23, the lower end of the cleaning strip 24 protrudes out of the lower wall of the outer cylinder 22, a spring 25 is provided inside the outer cylinder 22, and its two ends abut against the outer cylinder 22 and the inner rod 23 respectively, and the end of the inner rod 23 abuts against the wavy surface on the side of the butt plate 26.

[0023] As can be seen from the above, dew, dust and other debris that affect the collection of light energy often appear on the photovoltaic panels 11 set in the field. In order to remove these debris, the second motor 17 can be controlled to slide on the rotating frame 10, and the second motor 17 will drive the outer cylinder 22 and the inner rod 23 to move together. Under the action of the spring 25, the end of the inner rod 23 abuts against the wave surface of the abutment plate 26. As the inner rod 23 moves, the abutment plate 26 forces the inner rod 23 to move inside the outer cylinder 22 to intermittently compress the spring 25, and then the compressed spring 25 resets to push back the inner rod 23, thereby realizing the reciprocating movement of the inner rod 23 inside the outer cylinder 22. The inner rod 23 will drive the cleaning strip 24 to repeatedly move and scrub the photovoltaic panel 11, keeping the surface of the photovoltaic panel 11 clean, which is beneficial to the long-term photovoltaic effect of the photovoltaic panel 11.

[0024] A slide rail 18 is fixedly connected to the rotating frame 10, and a slider 19 fixedly connected to the second motor 17 is slidably connected to the slide rail 18. The slider 19 is fixedly connected to the outer cylinder 22. A rack 21 is fixedly connected to the rotating frame 10, and a gear 20 meshing with the rack 21 is fixedly connected to the output shaft of the second motor 17. After the second motor 17 is started, it can drive the gear 20 to rotate, and the rotating gear 20 will roll on the rack 21. At this time, the gear 20 will drag the second motor 17 to move. Since the slider 19 is fixedly connected to the second motor 17, the slide rail 18 limits the moving direction of the slider 19, thereby limiting the moving direction of the second motor 17, so that the second motor 17 can move along the direction of the slide rail 18.

[0025] The communication controller 2 is respectively connected to the first electric telescopic rod 6 , the detection drone 8 , the first motor 12 , the second electric telescopic rod 15 and the second motor 17 for communication.

[0026] Reference Figure 7-8 As shown, the data processing and analysis system includes: The data preprocessing unit is used to clean and standardize the agricultural information data to obtain standardized complete agricultural information data. The cleaning includes using a filter, a moving average method or a statistical method to remove noise data in the agricultural information data. The calculation formulas of filters of different models are also different. The calculation formula of the low-pass filter is: , is the input data at the current moment, is the output data at the current moment, is the output data of the previous moment, is the filter coefficient , controls the smoothness of the filter; the calculation formula of the moving average method can be expressed as ,in is the smoothed value at the current moment, is the original data of the past N-1 moments, N is the window size of the moving average; the statistical method can use the standard deviation method, and the formula is expressed as threshold = ,in is the mean of the data, is the standard deviation of the data, k is a constant (usually 2 or 3), data beyond the threshold range is regarded as noise, interpolation, regression and deletion methods are used to remove missing data in the agricultural information data, and the box plot method is used to detect and correct outliers in the noise-free agricultural information data. The standardization includes using normalization and Z-score standardization methods to convert data with different characteristics in the agricultural information data into noise-free agricultural information data of the same dimension. The formula of Z-score standardization method is expressed as follows: , x is the original data, is the mean of the data, is the standard deviation of the data, It is the standardized data; The data analysis unit uses crop pest and disease prediction models to process noise-free agricultural information data of the same dimension to predict the risk of farmland pest and disease outbreaks; The crop pest and disease prediction model establishment method comprises: Collect multiple crop images of different climatic conditions, growth stages, and varieties, and mark the location and type of pests and diseases in the crop images; Preprocess the crop images to remove the background noise of the crop photos to obtain noise-free crop images, and use rotation, mirroring, and flipping to perform data enhancement to obtain a crop image dataset; The crop image dataset was divided into a training set and a test set in a ratio of 8:2, and the convolutional neural network model was trained using the training set to obtain a pest and disease prediction model. The test set was used to evaluate the pest and disease prediction model. The pest and disease prediction model was evaluated by accuracy, precision, recall and F1-score. The learning rate, number of network layers and regularization parameters of the pest and disease prediction model were adjusted to optimize the pest and disease prediction model and obtain the final pest and disease prediction model.

[0027] A method for monitoring agricultural information based on big data, applied to an agricultural information monitoring institution based on big data, comprising: The communication controller 2 controls the rotating frame 10 to rotate so that the photovoltaic panel 11 faces the sun, absorbs light energy and converts it into electrical energy to transmit to the storage battery 3, and controls the cleaning component to clean the photovoltaic panel 11; The communication controller 2 controls the battery 3 to supply power to the detection drone 8. The communication controller 2 controls the detection drone 8 to fly over the agricultural land to obtain monitoring image data of the agricultural land. The detection drone 8 transmits the monitoring image data to the communication controller 2 and transmits it to the remote monitoring center via the communication controller 2.

[0028] The standard parts used in the present invention can all be purchased from the market, and the special-shaped parts can be customized according to the description and the drawings. The specific connection methods of each part adopt conventional means such as mature bolts, rivets, welding, etc. in the prior art. The machinery, parts and equipment all adopt conventional models in the prior art, and the circuit connection adopts the conventional connection method in the prior art, which will not be described in detail here. The contents not described in detail in this specification belong to the prior art known to professional and technical personnel in this field.

[0029] In the description of the present invention, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. "Multiple" means two or more, unless otherwise clearly and specifically defined.

[0030] In the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like 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 a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0031] In the present invention, unless otherwise clearly specified and limited, a first feature being "above" or "below" a second feature may mean that the first and second features are in direct contact, or the first and second features are in indirect contact through an intermediate medium. Moreover, a first feature being "above", "above" or "above" a second feature may mean that the first feature is directly above or obliquely above the second feature, or simply means that the first feature is higher in level than the second feature. A first feature being "below", "below" or "below" a second feature may mean that the first feature is directly below or obliquely below the second feature, or simply means that the first feature is lower in level than the second feature.

[0032] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example" or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, unless they are contradictory.

[0033] In the drawings of the embodiments disclosed in the present invention, only the structures related to the embodiments disclosed in the present invention are involved, and other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of the present invention can be combined with each other.

Claims

1. An agricultural information monitoring mechanism based on big data, characterized in that: include: A column (1), the column (1) being connected to a communication controller (2) for communication and a storage battery (3) for function, the communication controller (2) being equipped with a data processing and analysis system for processing collected agricultural information, and the storage battery (3) being connected to a placement board (4) used as a take-off platform; A detection drone (8), the detection drone (8) is placed on the placement board (4) and is used to detect and collect agricultural information data, the agricultural information data including air temperature and humidity, carbon dioxide concentration, oxygen concentration, light intensity and farmland images; A mounting frame (9) is arranged on one side of the column (1); a rotating frame (10) is rotatably connected to the mounting frame (9); a photovoltaic panel (11) electrically connected to the storage battery (3) is fixedly connected to the inner wall of the rotating frame (10); and a cleaning component for cleaning the photovoltaic panel (11) is arranged on the rotating frame (10).

2. The agricultural information monitoring mechanism based on big data according to claim 1, characterized in that: A sealing cover (5) that covers the detection drone (8) is hingedly connected to the placement plate (4), and a first electric telescopic rod (6) is hingedly connected between the sealing cover (5) and the placement plate (4).

3. The agricultural information monitoring mechanism based on big data according to claim 2 is characterized in that: A charging plate (7) electrically connected to the storage battery (3) is fixedly connected to the placement plate (4), a first motor (12) is fixedly connected to the mounting frame (9), a first sprocket (13) is fixedly connected to the end of the first motor (12), a chain (14) is movably connected to the first sprocket (13), and both ends of the chain (14) are respectively fixedly connected to the rotating frame (10).

4. The agricultural information monitoring mechanism based on big data according to claim 3 is characterized by: A second electric telescopic rod (15) is fixedly connected to the mounting frame (9), and an end of the second electric telescopic rod (15) is rotatably connected to a second sprocket (16) abutting against the chain (14).

5. The agricultural information monitoring mechanism based on big data according to claim 4 is characterized in that: The cleaning assembly comprises a second motor (17) slidably connected to the rotating frame (10), a cleaning rod fixedly mounted on the second motor (17), and a butt plate (26) fixedly mounted on the rotating frame (10) and abutting against the cleaning rod. The cleaning rod comprises an outer cylinder (22) fixedly mounted on the second motor (17), an inner rod (23) slidably inserted into the inner part of the outer cylinder (22), and a cleaning rod (24) fixedly mounted on the inner rod (23), the lower end of the cleaning rod (24) protruding out of the lower wall of the outer cylinder (22), the inner part of the outer cylinder (22) is provided with a spring (25) whose two ends respectively abut against the outer cylinder (22) and the inner rod (23), and the end of the inner rod (23) abuts against the wavy surface on the side of the butt plate (26).

6. The agricultural information monitoring mechanism based on big data according to claim 5, characterized in that: The rotating frame (10) is fixedly connected to a slide rail (18), the slide rail (18) is slidably connected to a slider (19) fixedly connected to the second motor (17), the slider (19) is fixedly connected to the outer cylinder (22), the rotating frame (10) is fixedly connected to a rack (21), and the output shaft of the second motor (17) is fixedly connected to a gear (20) meshing with the rack (21).

7. The agricultural information monitoring mechanism based on big data according to claim 1, characterized in that: The data processing and analysis system comprises: A data preprocessing unit, used for cleaning and standardizing the agricultural information data to obtain standardized complete agricultural information data; The data analysis unit uses crop pest and disease prediction models to process standardized complete agricultural information data and predict the risk of farmland pest and disease outbreaks; The crop pest and disease prediction model establishment method comprises: Collect multiple crop images of different climatic conditions, growth stages, and varieties, and mark the location and type of pests and diseases in the crop images; Preprocess the crop images to remove the background noise of the crop photos to obtain noise-free crop images, and use rotation, mirroring, and flipping to perform data enhancement to obtain a crop image dataset; The crop image dataset was divided into a training set and a test set in a ratio of 8:2, and the convolutional neural network model was trained using the training set to obtain a pest and disease prediction model. The test set was used to evaluate the pest and disease prediction model. The pest and disease prediction model was evaluated by accuracy, precision, recall and F1-score. The learning rate, number of network layers and regularization parameters of the pest and disease prediction model were adjusted to optimize the pest and disease prediction model and obtain the final pest and disease prediction model.

8. A method for monitoring agricultural information based on big data, characterized in that: An agricultural information monitoring mechanism based on big data applied to any one of claims 1 to 7, comprising: The communication controller (2) controls the rotation of the rotating frame (10) so that the photovoltaic panel (11) faces the sun, absorbs light energy and converts it into electrical energy to transmit to the storage battery (3), and at the same time controls the cleaning component to clean the photovoltaic panel (11); The communication controller (2) controls the storage battery (3) to supply power to the detection drone (8). The communication controller (2) controls the detection drone (8) to fly over agricultural land to obtain monitoring image data of the agricultural land. The detection drone (8) transmits the monitoring image data to the communication controller (2), and determines whether there is a risk of pests and diseases in the agricultural land based on analysis of the acquired monitoring image data. The communication controller (2) transmits the acquired data and the analysis results to a remote monitoring center.

Images