Field agricultural condition monitoring system based on big data

Abstract

The invention discloses a field agricultural condition monitoring system based on big data. The system is composed of a solar cell panel, a central processing unit, a cloud server, a communication module, a soil monitoring module, a climate monitoring module, a seedling condition monitoring module, an insect condition monitoring module, a water and fertilizer adjusting module, a pesticide applying module and a bird repelling module. The central processing unit obtains field agricultural condition data collected by the monitoring modules, sends the field agricultural condition data to the cloud server through the communication module for analysis and calculation, generates a visual special column and sends the visual special column to user mobile equipment, so that a user can remotely monitor a farmland conveniently. And in case of disasters, early warning and decisions are sent to mobile equipment of a user to assist the user in managing farmland. Compared with a traditional agricultural condition monitoring system, the system employs the cloud server to analyze and calculate the agricultural condition information, reduces the maintenance cost, and improves the interactivity. Through multi-element monitoring, the accuracy and comprehensiveness of agricultural condition monitoring are improved; fertilization is controlled through the central processing unit, agricultural automation is further promoted, and the purpose of water-saving fertilization is achieved.

Description

Technical Field

[0001] The present invention relates to a large-field agricultural situation monitoring system based on big data, and in particular to realizing the adjustment of the optimal water and fertilizer concentration through a cloud server and sending disaster warnings to mobile devices. Background Art

[0002] At present, the production mode of agriculture in China is still mainly traditional agriculture. The main characteristics of traditional agriculture are intensive cultivation, and it is difficult to resist natural disasters. And agricultural situation monitoring can effectively improve this problem. The acquisition of traditional agricultural situation information generally adopts the method of manual investigation and measurement. Obtaining agricultural situation information in this way not only takes time and effort, but also the accuracy is affected by the subjective factors of the operators. With the advent of the agricultural 4.0 era, various smart agriculture solutions have emerged like mushrooms after a spring rain. The existing agricultural situation monitoring solutions mainly have the following disadvantages:

[0003] (1) The growth of crops is generally monitored by optical cameras, which require high light in the fields and are difficult to monitor under conditions such as night and cloudy days.

[0004] (2) The monitoring of insect pests is also generally carried out by optical cameras. The traces of insect disasters on the leaves are similar to the colors of normal crops, and it is difficult for ordinary cameras to distinguish them. It is difficult to analyze the leaf pests by algorithms.

[0005] (3) A large-field agricultural situation monitoring system that uses drones to collect information can achieve large-area farmland coverage, strong timeliness and save manpower. However, relatively speaking, the cost is high and it is easily affected by the weather.

[0006] (4) The collection of soil information is generally realized by sensors. For large-scale planting in regions such as Xinjiang, it is necessary to adjust the soil moisture in real time according to the monitoring information.

[0007] (5) A large-field agricultural situation monitoring system that uses traditional servers to calculate and analyze data has its advantages in terms of resource quantity, performance and security, but the disadvantages are also obvious. There are problems in terms of maintenance, cost and convenience. The collection of agricultural situation information is different from the collection of commercial information. It does not require high security and performance, and is more inclined to low cost, simple maintenance and operation convenience.

[0008] (6) There is a lack of information interaction channels between the server and farmers, and there is no warning for special situations. Summary of the Invention

[0009] In order to solve the above problems, the purpose of the present invention is to provide a large-field agricultural situation monitoring system based on big data and its working method, which can monitor the large-field agricultural situation in real time through an infrared thermal imaging device, calculate and control the adjustment of the soil moisture in real time through a cloud server, and send warning signals to the user's mobile device in scenarios such as insect disasters and droughts to ensure the normal growth of crops.

[0010] To achieve the above object, the present invention provides the following technical solutions:

[0011] A large-field agricultural situation monitoring system based on big data, comprising a monitoring module, an execution module, a communication module, a cloud server, a central processor, and a solar panel. The acquisition end connected to the central processor includes four sub-modules: soil monitoring, climate monitoring, crop growth monitoring, and disaster monitoring, and the execution end includes a water and fertilizer regulation module, a pesticide application module, and a bird repelling module. The entire system is powered by a solar panel. The central processor is connected to the cloud server through the communication module. The cloud server calculates the collected data, controls the water and fertilizer regulation, analyzes the large-field agricultural situation information, and sends disaster and crop growth warnings to the user's mobile device when necessary by comparing with the database.

[0012] Further, the soil monitoring sub-module includes an EC sensor, a pH detector, and a soil temperature and humidity sensor, and is connected to the central processor.

[0013] Further, the climate monitoring sub-module includes an air temperature and humidity sensor, a light intensity sensor, a wind speed and direction sensor, and a rainfall sensor, and is connected to the central processor.

[0014] Further, the seedling situation monitoring sub-module includes an infrared thermal imaging device and is connected to the central processor. Users can observe the crop growth at any time through the thermal imaging without being limited by light.

[0015] Further, the pest monitoring sub-module includes an automatic pest forecasting lamp and is connected to the central processor.

[0016] Further, the water and fertilizer regulation sub-module and the pesticide application sub-module include a plurality of fertilizer storage tanks, pumps, solenoid valves, etc., and are connected to the central processor.

[0017] Further, the communication device includes at least one of a LoRa communication module, an NB-IoT communication module, and a ZigBee communication module.

[0018] Further, the bird repelling sub-module includes an intelligent bird repelling device and is connected to the central processor.

[0019] The beneficial effects of the present invention are:

[0020] (1) By using the cloud server to analyze and calculate the agricultural situation information, the maintenance cost is reduced.

[0021] (2) By connecting to the user's mobile device through the communication module, warnings and visual column analysis can be sent to the user, improving the operation convenience of the user.

[0022] (3) The crop growth monitoring module uses an infrared thermal imaging device, which is no longer limited in monitoring under cloudy and night environments, improving the accuracy and comprehensiveness of agricultural situation monitoring.

[0023] (4) For pest monitoring, an automatic insect situation forecasting lamp is used. It automatically kills insects and uploads the records to the cloud server. When the pest data is abnormal, it automatically sends a warning to the user's mobile device, simplifying the user's operation.

[0024] (5) The soil moisture information is uploaded to the cloud server, and the optimal ratio of water and fertilizer concentration is calculated in real time. Fertilization is controlled through the central processing unit, further promoting agricultural automation and achieving the purpose of water-saving fertilization. Description of the Drawings

[0025] The present invention will be further described below in conjunction with the drawings and embodiments.

[0026] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments recorded in the present invention. For those of ordinary skill in the art, other drawings can also be obtained based on these drawings.

[0027] Figure 1 It is the structural module diagram of the present invention.

[0028] Figure 2 It is the functional module diagram of the cloud server.

[0029] Figure 3 It is the schematic diagram of the execution module of the present invention.

[0030] Figure 4 It is the schematic diagram of the monitoring module of the present invention.

[0031] Figure 5 It is the schematic diagram of the solar power supply module of the present invention.

[0032] Figure 6 It is the structure diagram of the integrated water and fertilizer intelligent control system.

[0033] In the figure: 1. water storage tank, 2. filter, 3. water pump, 4. solenoid valve, 5. check valve, 6. voltage regulator, 7. irrigation solenoid valve, 8. flow meter, 9. solenoid valve, 10. mother liquid tank, 11. pressure gauge, 12. filter, 13. mother liquid tank solenoid valve, 14. Venturi fertilizer injector, 15. acid liquid tank, 16. liquid medicine tank, 17. mixing tank, 18. liquid level gauge, 19. EC sensor, 20. pH sensor, 21. control cabinet, 22. fertilizer pump, 23. fertilizer application solenoid valve, 24. main valve, 25. branch valve, 26. drip irrigation tape.

[0034] Figure 7It is a schematic diagram of the acquisition control pile structure.

[0035] In the figure, 1. vertical pole, 2. central control box, 3. automatic insect situation forecasting lamp, 4. air temperature and humidity sensor, 5. light intensity sensor, 6. solar panel, 7. anemometer, 8. wind vane, 9. infrared thermal imaging device, 10. rain sensor, 11. bird repeller, 12. soil monitoring power supply line, 13. water and fertilizer regulation power supply line. Specific implementation mode

[0036] In Figure 1 , the central processor sends the field agricultural situation data collected by the monitoring module to the cloud server through the communication module for storage, analysis and calculation, generates a visual column analysis and sends it to the user's mobile device. After receiving the disaster warning, the user can also control the cloud server to send a signal to the central processor through the mobile device to control the execution module to take measures.

[0037] In Figure 2 In the illustrated embodiment, the functions included in the cloud server are disaster warning, crop growth warning, and calculation of the best water and fertilizer concentration. Among them, the disaster warning includes disasters such as insect disasters, bird disasters, and droughts. The insect disaster situation can be obtained through the data uploaded by the automatic insect situation forecasting lamp every day; the bird disaster and crop growth can both obtain corresponding image data through the infrared thermal imaging device; the drought can obtain the soil moisture data through the soil monitoring module; all the crop growth and water and fertilizer concentration data are stored in the cloud server, and the cloud server deeply analyzes these data, establishes correlation conditions for prediction, and sends a signal to the user when it is lower than the preset value.

[0038] In Figure 3 In the illustrated embodiment, the execution module includes three aspects: water and fertilizer regulation, pesticide application, and bird repelling. The bird repelling function is realized by the bird repelling device. The system defaults to turn on detection. When it detects that birds are approaching, the system is enabled to emit ultrasonic waves to stimulate the nervous system of the birds, and at the same time, it scares away the birds by simulating the sound source of eagles, etc. In the case of flying birds approaching at night, according to the habit that birds are afraid of flashes, the system is enabled to use stroboscopic strong light to stimulate the visual system of the birds and destroy the living environment of the birds, so as to drive the birds away from the defense area, so as to achieve the purpose of preventing bird damage and ensuring the safety of crops.

[0039] In Figure 4In the illustrated embodiment, the monitoring module includes a soil monitoring sub-module, a climate monitoring sub-module, a seedling condition monitoring sub-module, and a pest condition monitoring sub-module. The soil monitoring sub-module includes an EC sensor, a pH detector, and a soil temperature and humidity sensor. Among them, the EC sensor is used to monitor the water and fertilizer concentration, the pH detector is used to monitor the soil acidity and alkalinity, and the soil temperature and humidity sensor is used to monitor the soil temperature and humidity. The climate monitoring sub-module includes an air temperature and humidity sensor, a light intensity sensor, a wind speed and direction sensor, and a rainfall sensor. The data of the climate monitoring module is transmitted to the cloud server through the central processor, and by analyzing and calculating, it is judged whether the current field crops need irrigation. The seedling condition monitoring sub-module has an infrared thermal imaging device, and users can observe the growth of crops at any time through thermal imaging. The pest monitoring sub-module includes an automatic pest forecasting lamp, which uses modern light, electricity, and numerical control technologies to automatically complete system operations such as attracting insects, killing insects, collecting, and packaging under unattended supervision, and is automatically uploaded to the cloud server through the central processor. The server automatically records the collected data every day to form a pest database.

[0040] In Figure 5 In the illustrated embodiment, a solar + lithium battery power supply method is adopted. The lithium battery mainly has the characteristics of large energy storage, no memory effect, low loss, and recyclability. The photovoltaic panel converts solar energy into electrical energy, stores the energy in the lithium battery through the charging circuit and the voltage stabilizing circuit, and supplies power to the execution module, such as solenoid valves, bird repellers, etc. through the boost circuit. In addition, the lithium battery also supplies power to the monitoring module through the buck circuit, such as the soil temperature and humidity sensor, the light intensity sensor, etc. It should be noted that the power supply of the wireless communication module is supplied by the lithium battery through the buck circuit. The power supply is the foundation for the system to run and maintain a connected state for a long time. When selecting the entire power supply module, characteristics such as high conversion efficiency and reverse current protection need to be considered to be applicable to various complex environments and ensure the stable operation of each electronic device.

[0041] In Figure 6 In the illustrated embodiment, the water and fertilizer regulation is realized by the central processor controlling the opening and closing of solenoid valves for different types of fertilizer solutions. The real-time regulation of nitrogen, phosphorus, potassium fertilizer solutions, acid-base solutions, and liquid medicines can provide the best environment for crops. The overall realization is through the drip irrigation method, and the purpose of water-saving irrigation and fertilization can also be achieved. The calculation of the optimal water and fertilizer concentration at each stage of the crop is realized by the cloud server.

[0042] In Figure 7 In the illustrated embodiment, the power supply module, the central processor, the monitoring module, the control module, and the wireless communication module are integrated on a vertical pole, which improves the stability, reduces the cost, and is convenient for maintenance compared with some current drone monitoring systems.

Claims

1. A field agricultural monitoring system based on big data, in which the monitoring module, the central processing unit, and the execution module are connected in sequence, and the central processing unit is powered by a solar panel. Its characteristics are: The central processor is connected to the cloud server and the mobile device in sequence through the communication module, and the central processor is controlled by the cloud server. The cloud server has data storage, data analysis and data calculation functions. Specifically, it stores sampling point data and image data, performs in-depth analysis on these data, establishes related condition prediction, and automatically monitors the seedling condition, insect condition and disaster condition in the field, so that managers can remotely monitor the growth of crops, issue early warnings for pests and diseases, and crop growth, and generate visual thematic analysis reports and send them to users' mobile devices. The monitoring module comprises a soil monitoring submodule, a climate monitoring submodule, a seedling monitoring submodule and an insect pest monitoring submodule, which are used to monitor the agricultural conditions in the field in real time. The execution module includes a water and fertilizer regulation submodule, a pesticide application submodule and a bird-repelling submodule.

2. The field agricultural condition monitoring system according to claim 1 is characterized in that: The soil monitoring submodule includes an EC sensor, a pH detector and a soil temperature and humidity sensor. The EC sensor is used to monitor water and fertilizer concentration, the pH detector is used to monitor soil acidity and alkalinity, and the soil temperature and humidity sensor is used to monitor soil temperature and humidity.

3. The field agricultural condition monitoring system according to claim 1 is characterized in that: The climate monitoring submodule includes an air temperature and humidity sensor, a light intensity sensor, a wind speed and direction sensor, and a rainfall sensor. The data of the climate monitoring module is transmitted to the cloud server through the central processor, and through analysis and calculation, it is determined whether the current field crops need irrigation.

4. The field agricultural condition monitoring system according to claim 1 is characterized in that: The seedling monitoring submodule includes an infrared thermal imaging device, and the user can observe the growth of crops at any time through thermal imaging.

5. The field agricultural condition monitoring system according to claim 1 is characterized in that: The pest monitoring submodule includes an automatic insect monitoring light, which uses modern optical, electrical and numerical control technologies to automatically complete system operations such as insect luring, insect killing, collection and packaging without human supervision. The data is automatically uploaded to the cloud server through the central processing unit, and the server automatically records and collects data every day to form a pest database.

6. The field agricultural condition monitoring system according to claim 1 is characterized in that: The water-fertilizer regulation submodule includes five fertilizer storage tanks, which are respectively filled with nitrogen, phosphorus, potassium fertilizer and acid-base solution. They are mixed with water in the mixing tank through pump and solenoid valve control, and then flow to the drip irrigation belt. Combined with the sampling point data of the soil monitoring submodule and the climate monitoring submodule, the concentration of fertilizer solution and acid-base solution is adjusted in real time through calculation and control of the cloud server to achieve the optimal water-fertilizer concentration and the optimal pH environment for crops, realizing intelligent irrigation.

7. The field agricultural condition monitoring system according to claim 1 is characterized in that: The pesticide application submodule adds a liquid medicine tank based on the water and fertilizer regulation submodule. After the cloud server combines with the pest database to send a pest warning to the user's mobile device, the user can select the corresponding liquid medicine type according to the visualized thematic analysis and add it to the liquid medicine tank. The liquid medicine flows into the mixing tank through the pump and solenoid valve.

8. The field agricultural condition monitoring system according to claim 1 is characterized in that: The communication device includes at least one of a LoRa communication module, a NB-IoT communication module and a ZigBee communication module.

9. The field agricultural condition monitoring system according to claim 1 is characterized in that: The bird-repellent submodule includes an intelligent bird-repellent device. The system turns on detection by default. When a bird is detected approaching, the system is enabled to emit ultrasonic waves to stimulate the bird's nervous system, and at the same time simulate the sound source of an eagle to scare the bird away. When a flying bird approaches at night, based on the bird's fear of flashes, a strong strobe light is enabled to stimulate the bird's visual system, destroying the bird's living environment, thereby driving the bird away from the defense area, so as to achieve the purpose of eliminating bird damage and ensuring crop safety.

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