Water and fertilizer ratio control system based on artificial intelligence

Abstract

The invention relates to the technical field of agricultural irrigation, in particular to a water and fertilizer ratio control system based on artificial intelligence. The farmland quality monitoring module monitors environmental factors in the N areas, and then calculates N farmland health indexes according to the environmental factors in the N areas and a preset weight coefficient; after traversing and judging that the N farmland health indexes comprise farmland health indexes lower than a preset farmland health index threshold value, turning on the corresponding warning light board; the visual decision support module converts the N farmland health indexes into a health index matrix, and then maps a thermodynamic diagram according to the health index matrix; the calculation module is used for calculating suggested water quantity and suggested fertilizer quantity of the N areas, then graphically displaying the suggested water quantity and the suggested fertilizer quantity of the N areas respectively, and then calculating a suggested water-fertilizer ratio; the water and fertilizer ratio control module controls the water and fertilizer delivery speed of the irrigation devices in the N areas according to the water and fertilizer delivery speed of the N areas.

Description

Technical Field

[0001] The invention belongs to the technical field of agricultural irrigation, and in particular relates to a water-fertilizer ratio control system based on artificial intelligence. Background Art

[0002] With the scale and intensification of agricultural production, the changes in farmland environment are becoming more and more complex. Factors such as soil moisture and temperature directly affect crop growth. Traditional monitoring methods often rely on manual inspections, which makes it difficult to obtain and analyze data in real time, resulting in managers being unable to respond to potential problems in a timely manner. At the same time, farmland management requires processing a large amount of data. How to transform complex information into an intuitive and easy-to-understand form has become the key to improving decision-making efficiency. In the past, managers often faced problems of asymmetric and incomplete information when making decisions such as watering and fertilizing. In addition, water and fertilizer management occupies an important position in modern agriculture, and a reasonable water-fertilizer ratio can significantly improve crop yield and quality. However, the influence of climate change, environmental conditions and crop demand makes traditional water and fertilizer management methods often inflexible and inefficient. Therefore, a water-fertilizer ratio control system based on artificial intelligence is proposed. Summary of the invention

[0003] The present invention aims to solve the technical problems of inaccurate control of large tracts of farmland, inability to reduce the cost of human inspections, insufficient visualization to make better decisions, and over-irrigation caused by climate change and soil conditions, and provides a water-fertilizer ratio control system based on artificial intelligence.

[0004] The technical solution adopted by the present invention to solve the technical problem is: a water-fertilizer ratio control system based on artificial intelligence, including a visual decision support module, a water-fertilizer ratio control module, and a farmland quality monitoring module.

[0005] The farmland quality monitoring module is electrically connected to the warning light board, which is set in N areas for managers to store the overall farmland model. It is also used for managers to divide the overall farmland model into N areas, and then monitor the environmental factors in the N areas, and then send them to the visualization decision support module. After monitoring the environmental factors in the N areas, N farmland health indexes are calculated according to the environmental factors in the N areas and the preset weight coefficients, and then sent to the visualization decision support module. It is also used to turn on the warning light board corresponding to the farmland health index that is lower than the preset farmland health index threshold after traversing and judging that the N farmland health indexes contain a farmland health index that is lower than the preset farmland health index threshold.

[0006] The visualization decision support module is connected to the farmland quality monitoring module network, and is used to convert N farmland health indexes into health index matrices after receiving them, and then map out a heat map based on them. It is used to calculate the recommended water volume and fertilizer volume of N regions according to the N farmland health indexes and environmental factors in N regions after receiving them, and then graphically display the recommended water volume and fertilizer volume of N regions, and then calculate the recommended water-fertilizer ratio according to the recommended water volume and fertilizer volume of N regions, and then send the recommended water-fertilizer ratio of N regions, the recommended water volume and fertilizer volume of N regions to the water-fertilizer ratio control module.

[0007] The water-fertilizer ratio control module is connected to the visualization decision support module, the National Meteorological Bureau meteorological data source, and the N-region irrigation equipment network, which is used for managers to set the farmland location, and then obtain the environmental humidity, ambient temperature, and ambient wind speed of the farmland location in the National Meteorological Bureau meteorological data source. It is used to measure the environmental radiation. It is used to obtain the saturated vapor pressure according to the ambient temperature, and then obtain the saturated vapor pressure slope according to the saturated vapor pressure to temperature, and then obtain the actual vapor pressure according to the ambient humidity and the saturated vapor pressure, and then calculate the plant water evaporation rate according to the environmental radiation, ambient wind speed, saturated vapor pressure, actual vapor pressure, and saturated vapor pressure slope. It is used to calculate the water and fertilizer delivery speed of N regions according to the plant water evaporation rate, the recommended water and fertilizer ratio, the recommended water and fertilizer amount of N regions, and then control the water and fertilizer delivery speed of N regional irrigation equipment according to the water and fertilizer delivery speed of N regions.

[0008] Furthermore, the farmland quality monitoring module includes a region division unit, a data monitoring unit, a warning unit, and a first edge computing device.

[0009] The area division unit is used for the manager to store the overall farmland model and to divide the overall farmland model into N areas, and then transmit the N areas to the data monitoring unit.

[0010] The data monitoring unit is connected to the regional division unit and the visualization decision support module network and is set in N areas. After receiving the N areas, it is used to monitor the soil moisture, soil nutrients and vegetation index in the N areas, and then send them to the visualization decision support module, and then calculate N farmland health indexes according to the soil moisture, soil nutrients, vegetation index and preset weight coefficients in the N areas, and then send the N farmland health indexes to the first edge computing device and the visualization decision support module.

[0011] The first edge computing device is connected to the data monitoring unit network, and is used for the manager to store the data monitoring unit and the warning unit corresponding to the data monitoring unit. After receiving N farmland health indexes, it is used to traverse and determine whether the N farmland health indexes contain a farmland health index that is lower than the preset farmland health index threshold. And after traversing and determining that the N farmland health indexes contain a farmland health index that is lower than the preset farmland health index threshold, it is used to query the data monitoring unit corresponding to the farmland health index that is lower than the preset farmland health index threshold, and then query the corresponding stored warning unit based on the corresponding data monitoring unit, and then generate a warning signal, and then send the warning signal to the corresponding warning unit.

[0012] The warning units are arranged in N areas, electrically connected to the warning light signs, and respectively electrically connected to the data monitoring units in the corresponding areas, and are used to turn on the corresponding warning light signs after receiving the early warning signal.

[0013] Furthermore, the data monitoring unit includes a soil moisture sensor, a soil nutrient sensor, a remote sensing image satellite, and a first microprocessor.

[0014] Soil moisture sensors are arranged in N areas and connected to the visualization decision support module network for monitoring soil moisture in the N areas, and then sending the soil moisture in the N areas to the visualization decision support module and the first microprocessor.

[0015] Soil nutrient sensors are arranged in N areas and connected to the visualization decision support module network for monitoring soil nutrients in the N areas, and then sending the soil nutrients in the N areas to the visualization decision support module and the first microprocessor.

[0016] The remote sensing image satellite is connected to the visualization decision support module network, and is used for collecting the reflectance of plants in the N areas to the infrared band and the near-infrared band after receiving N areas, and then calculating the vegetation index of the N areas respectively by the reflectance of the infrared band and the near-infrared band, and then sending the vegetation index of the N areas to the visualization decision support module and the first microprocessor.

[0017] The first microprocessor is connected to the network of the soil moisture sensor, the soil nutrient sensor, the remote sensing image satellite, the first edge computing device, and the visualization decision support module, and is used to receive soil moisture, soil nutrients, and vegetation index in N areas, and then calculate N farmland health indexes according to the soil moisture, soil nutrients, and vegetation index in the N areas and preset weight coefficients, and then send the N farmland health indexes to the first edge computing device and the visualization decision support module.

[0018] Furthermore, the remote sensing satellite calculates the vegetation index of N regions by the reflectivity of the infrared band and the near-infrared band.

[0019] The vegetation index calculation formula is:

[0020] Among them, NDVI i is the vegetation index of the i-th region, i is the region number, i∈[0,N], NIR i is the reflectivity of the near-infrared band of the i-th region, RED i The reflectivity of the infrared band of the i-th region.

[0021] Furthermore, the first microprocessor calculates the formula of N farmland health indexes according to the soil moisture, soil nutrients, vegetation index and preset weight coefficients in the N regions: i =ω SM SM i +ω N N i +ω NDVI NDVI i ,

[0022] Among them, HI i is the farmland health index of the ith region, N i is the soil nutrient of the ith area, in g / kg, NDVI i is the vegetation index of the ith region, SM i is the soil moisture in the ith region, expressed in percentage, ω SM ,ω N ,ω NDVI is the preset weight coefficient, satisfying ω SM +ω N +ω NDVI =1.

[0023] Furthermore, the visualization decision support module includes a second edge computing device and a visualization unit.

[0024] The visualization unit is connected to the first microprocessor network, and is used to convert the N farmland health indexes into a health index matrix after receiving them, and then map a heat map according to the health index matrix. It is also used to graphically display the recommended water and fertilizer amounts for the N farmlands after receiving them.

[0025] The second edge computing device is connected to the first microprocessor, remote sensing image satellite, soil nutrient sensor, soil moisture sensor, visualization unit, and water-fertilizer ratio control module network, and is used to calculate the recommended water volume and recommended fertilizer volume of the N regions according to the N farmland health indexes, soil moisture, soil nutrients, vegetation index in the N regions and the preset basic water volume of crops, basic fertilizer volume of crops, maximum water volume of crops, and maximum fertilizer volume of crops after receiving N farmland health indexes, soil moisture, soil nutrients, and vegetation index in the N regions, and then send the recommended water volume and recommended fertilizer volume of the N regions to the visualization unit and the water-fertilizer ratio control module respectively, and then calculate the recommended water-fertilizer ratio according to the recommended water volume and recommended fertilizer volume of the N regions, and then send the recommended water-fertilizer ratio of the N regions to the water-fertilizer ratio control module respectively.

[0026] Furthermore, the second edge computing device calculates the recommended water amount and recommended fertilizer amount for the N areas according to the N farmland health indexes, soil moisture, soil nutrients, vegetation index, and preset basic water amount for crops, basic fertilizer amount for crops, maximum water amount for crops, and maximum fertilizer amount for crops.

[0027] The formula for the recommended water volume for the ith area is: W i =W0 +k1·(1-HI i )·W max ,

[0028] Among them, W i is the recommended water volume for the ith area, in L / ha, W0 is the preset basic water volume, in L / ha, k1 is the weight coefficient, HI i is the farmland health index of the ith region, W max It is the preset maximum water volume for crops, in L / ha.

[0029] The formula for the recommended water volume for the ith area is: F i =F0 +k2·(1-HI i )·F max ,

[0030] Among them, F i is the recommended fertilizer amount for the ith area, in kg / ha, F0 is the preset basic fertilizer amount, in kg / ha, F max It is the preset maximum fertilizer amount for crops, in kg / ha, and k2 is the weight coefficient.

[0031] The second edge computing device calculates the recommended water-fertilizer ratio according to the recommended water and fertilizer amounts of the N regions:

[0032]

[0033] Among them, R i is the recommended water-fertilizer ratio for the ith area, in L / kg.

[0034] Furthermore, the water-fertilizer ratio control module includes a water-fertilizer irrigation control module, a second microprocessor, a meteorological data interface, a radiation sensor, and a wind speed sensor.

[0035] The meteorological data program interface is connected to the National Meteorological Bureau meteorological data source network for the manager to set the farmland location, and then obtain the ambient humidity, ambient temperature, and ambient wind speed of the farmland location from the National Meteorological Bureau meteorological data source, and then send the ambient humidity, ambient temperature, and ambient wind speed to the second microprocessor.

[0036] The radiation sensor is used to measure the amount of ambient radiation and then send it to the second microprocessor.

[0037] The wind speed sensor is used to measure the ambient wind speed and then send it to the second microprocessor.

[0038] The second microprocessor is connected to the meteorological data program interface, the radiation sensor, the wind speed sensor, and the second edge computing device network, and is used to obtain the saturated vapor pressure according to the ambient temperature after receiving the ambient temperature, and then obtain the saturated vapor pressure slope according to the saturated vapor pressure to the temperature. And after receiving the ambient humidity, it is used to obtain the actual vapor pressure according to the ambient humidity and the saturated vapor pressure. And after receiving the ambient radiation and ambient wind speed, it is used to calculate the plant water evaporation rate according to the ambient radiation, ambient wind speed, saturated vapor pressure, actual vapor pressure, and saturated vapor pressure slope, and then send the plant water evaporation rate to the water and fertilizer irrigation control module.

[0039] The water-fertilizer irrigation control module is connected to the second microprocessor and the N-area irrigation equipment network, and is used to calculate the water-fertilizer delivery speed of the N areas according to the plant water evaporation rate, the recommended water-fertilizer ratio, the recommended water volume, and the recommended fertilizer volume of the N areas after receiving the recommended water-fertilizer ratio, the recommended water volume, and the recommended fertilizer volume of the N areas respectively, and then control the water-fertilizer delivery speed of the N-area irrigation equipment respectively according to the water-fertilizer delivery speed of the N areas.

[0040] Further, the second microprocessor obtains the formula of saturated vapor pressure according to the ambient temperature:

[0041] Among them, e s is the saturated vapor pressure in kPa, and T is the ambient temperature in degrees Celsius.

[0042] And the formula for obtaining the actual vapor pressure based on the ambient humidity and saturated vapor pressure is:

[0043] Among them, e a is the actual vapor pressure in kPa, and RH is the ambient humidity in percentage.

[0044] And the formula for the saturated vapor pressure slope is obtained based on the saturated vapor pressure versus temperature:

[0045] Where Δ is the saturated vapor pressure slope, in kPa / ℃, e s is the saturated vapor pressure, in kPa.

[0046] The formula for calculating the plant water evaporation rate based on environmental radiation, environmental wind speed, saturated vapor pressure, actual vapor pressure, and saturated vapor pressure slope is:

[0047]

[0048] Among them, ET is the evapotranspiration rate of plant water, in mm / day, R n is the environmental radiation, in MJ / m 2 / day, γ is the psychological constant, u2 is the ambient wind speed, the unit is m / s, Δ is the saturated vapor pressure slope, the unit is kPa / ℃, e s is the saturated vapor pressure, in kPa, e a is the actual vapor pressure in kPa, and λ is the latent heat of evaporation of water, which is 2.45 MJ / kg.

[0049] Furthermore, the water and fertilizer irrigation control module calculates the formula for the water and fertilizer delivery speed of N areas based on the plant water evaporation rate, the recommended water-fertilizer ratio, the recommended water volume, and the recommended fertilizer volume of N areas:

[0050] Among them, V i It is the water and fertilizer delivery rate, and the unit is L / ha / day.

[0051] Beneficial effects of the present invention:

[0052] 1. The farmland quality monitoring module can monitor the environmental factors in N areas in real time, such as soil moisture, temperature, etc., which helps managers to grasp the farmland conditions in time and then calculate the farmland health index through environmental factors and preset weight coefficients, providing a scientific basis for farmland management and ensuring the healthy growth of crops. When the farmland health index is lower than the preset threshold, it can automatically trigger the warning light to remind managers to take measures in time to prevent potential farmland losses.

[0053] 2. The visual decision support module converts the farmland health index into a health index matrix and maps out a heat map, so that managers can intuitively understand the health status of different areas. Then, based on the calculation of the health index and environmental factors, it provides recommended water and fertilizer amounts to help managers make scientific and reasonable decisions and improve the efficiency of farmland management. Then, by calculating the recommended water-fertilizer ratio, it promotes the rational use of water resources and fertilizers, increases crop yields, and reduces costs and environmental burdens.

[0054] 3. The water-fertilizer ratio control module can accurately control the water-fertilizer delivery speed according to real-time environmental data and plant evaporation rate, optimize irrigation effects, and prevent over-irrigation or fertilizer waste. By obtaining real-time meteorological data from the National Meteorological Administration, it can adjust irrigation strategies to adapt to different climatic conditions, improve the resistance of farmland, realize automatic monitoring and control, improve management efficiency, reduce labor costs, and reduce the risk of human operational errors. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 It is a schematic diagram of the system module of the present invention;

[0056] Figure 2 It is a schematic diagram of a data monitoring unit of the present invention. DETAILED DESCRIPTION

[0057] The following will clearly and completely describe the concept and technical effects of the present invention in combination with the embodiments, so as to fully understand the purpose, features and effects of the present invention. Figure 1 , Figure 2 .

[0058] An artificial intelligence-based water-fertilizer ratio control system includes a visual decision support module, a water-fertilizer ratio control module, and a farmland quality monitoring module.

[0059] The farmland quality monitoring module is electrically connected to the warning light board, which is set in N areas for managers to store the overall farmland model. It is also used for managers to divide the overall farmland model into N areas, and then monitor the environmental factors in the N areas, and then send them to the visualization decision support module. After monitoring the environmental factors in the N areas, N farmland health indexes are calculated according to the environmental factors in the N areas and the preset weight coefficients, and then sent to the visualization decision support module. It is also used to turn on the warning light board corresponding to the farmland health index that is lower than the preset farmland health index threshold after traversing and judging that the N farmland health indexes contain a farmland health index that is lower than the preset farmland health index threshold.

[0060] The visualization decision support module is connected to the farmland quality monitoring module network, and is used to convert N farmland health indexes into health index matrices after receiving them, and then map out a heat map based on them. It is used to calculate the recommended water volume and fertilizer volume of N regions according to the N farmland health indexes and environmental factors in N regions after receiving them, and then graphically display the recommended water volume and fertilizer volume of N regions, and then calculate the recommended water-fertilizer ratio according to the recommended water volume and fertilizer volume of N regions, and then send the recommended water-fertilizer ratio of N regions, the recommended water volume and fertilizer volume of N regions to the water-fertilizer ratio control module.

[0061] The water-fertilizer ratio control module is connected to the visualization decision support module, the National Meteorological Bureau meteorological data source, and the N-region irrigation equipment network, which is used for managers to set the farmland location, and then obtain the environmental humidity, ambient temperature, and ambient wind speed of the farmland location in the National Meteorological Bureau meteorological data source. It is used to measure the environmental radiation. It is used to obtain the saturated vapor pressure according to the ambient temperature, and then obtain the saturated vapor pressure slope according to the saturated vapor pressure to temperature, and then obtain the actual vapor pressure according to the ambient humidity and the saturated vapor pressure, and then calculate the plant water evaporation rate according to the environmental radiation, ambient wind speed, saturated vapor pressure, actual vapor pressure, and saturated vapor pressure slope. It is used to calculate the water and fertilizer delivery speed of N regions according to the plant water evaporation rate, the recommended water and fertilizer ratio, the recommended water and fertilizer amount of N regions, and then control the water and fertilizer delivery speed of N regional irrigation equipment according to the water and fertilizer delivery speed of N regions.

[0062] In this embodiment, the farmland quality monitoring module includes a region division unit, a data monitoring unit, a warning unit, and a first edge computing device.

[0063] The area division unit is used for the manager to store the overall farmland model and to divide the overall farmland model into N areas, and then transmit the N areas to the data monitoring unit.

[0064] The data monitoring unit is connected to the regional division unit and the visualization decision support module network and is set in N areas. After receiving the N areas, it is used to monitor the soil moisture, soil nutrients and vegetation index in the N areas, and then send them to the visualization decision support module, and then calculate N farmland health indexes according to the soil moisture, soil nutrients, vegetation index and preset weight coefficients in the N areas, and then send the N farmland health indexes to the first edge computing device and the visualization decision support module.

[0065] The first edge computing device is connected to the data monitoring unit network, and is used for the manager to store the data monitoring unit and the warning unit corresponding to the data monitoring unit. After receiving N farmland health indexes, it is used to traverse and determine whether the N farmland health indexes contain a farmland health index that is lower than the preset farmland health index threshold. And after traversing and determining that the N farmland health indexes contain a farmland health index that is lower than the preset farmland health index threshold, it is used to query the data monitoring unit corresponding to the farmland health index that is lower than the preset farmland health index threshold, and then query the corresponding stored warning unit based on the corresponding data monitoring unit, and then generate a warning signal, and then send the warning signal to the corresponding warning unit.

[0066] The warning units are arranged in N areas, electrically connected to the warning light signs, and respectively electrically connected to the data monitoring units in the corresponding areas, and are used to turn on the corresponding warning light signs after receiving the early warning signal.

[0067] In this embodiment, by dividing the farmland into N areas of equal area and setting a data monitoring unit in each area, accurate monitoring of information such as soil moisture, soil nutrients, and vegetation index in different areas can be achieved. This refined monitoring method improves the accuracy of farmland management, helps managers better understand the health status of each area, and makes refined decisions. The farmland health index is calculated based on data such as soil moisture, soil nutrients, and vegetation index in each area, and compared with the preset health threshold. Once the health index of a certain area is lower than the threshold, the system will automatically trigger an early warning signal. This mechanism can detect farmland problems in a timely manner, such as drought, and immediately notify managers by turning on the warning light sign through the warning unit, effectively avoiding potential farmland damage and ensuring the healthy growth of crops. This automated response not only reduces the burden of manual monitoring, but also realizes real-time monitoring and timely feedback, greatly improving the efficiency and response speed of farmland management. The introduction of edge computing devices can process and store massive data from the data monitoring unit locally, reduce dependence on the central server, and speed up data processing. This not only improves the response efficiency of the system, but also ensures the normal operation of monitoring data and early warning mechanisms when the network is unstable.

[0068] In this embodiment, the data monitoring unit includes a soil moisture sensor, a soil nutrient sensor, a remote sensing image satellite, and a first microprocessor.

[0069] Soil moisture sensors are arranged in N areas and connected to the visualization decision support module network for monitoring soil moisture in the N areas, and then sending the soil moisture in the N areas to the visualization decision support module and the first microprocessor.

[0070] Soil nutrient sensors are arranged in N areas and connected to the visualization decision support module network for monitoring soil nutrients in the N areas, and then sending the soil nutrients in the N areas to the visualization decision support module and the first microprocessor.

[0071] The remote sensing image satellite is connected to the visualization decision support module network, and is used for collecting the reflectance of plants in the N areas to the infrared band and the near-infrared band after receiving N areas, and then calculating the vegetation index of the N areas respectively by the reflectance of the infrared band and the near-infrared band, and then sending the vegetation index of the N areas to the visualization decision support module and the first microprocessor.

[0072] The first microprocessor is connected to the network of the soil moisture sensor, the soil nutrient sensor, the remote sensing image satellite, the first edge computing device, and the visualization decision support module, and is used to receive soil moisture, soil nutrients, and vegetation index in N areas, and then calculate N farmland health indexes according to the soil moisture, soil nutrients, and vegetation index in the N areas and preset weight coefficients, and then send the N farmland health indexes to the first edge computing device and the visualization decision support module.

[0073] In this embodiment, the remote sensing image satellite calculates the vegetation index of N regions by the reflectivity of the infrared band and the near-infrared band.

[0074] The vegetation index calculation formula is:

[0075] Among them, NDVI i is the vegetation index of the i-th region, i is the region number, i∈[0,N], NIR i is the reflectivity of the near-infrared band of the i-th region, RED i The reflectivity of the infrared band of the i-th region,

[0076] For example, the reflectivity of the near-infrared band of the i-th region is 0.7, the reflectivity of the infrared band of the i-th region is 0.3, and the vegetation index of the i-th region is 0.4.

[0077] In this embodiment, the first microprocessor calculates the N farmland health indexes according to the soil moisture, soil nutrients, vegetation index and preset weight coefficients in the N regions: i =ω SM SM i +ω N N i +ω NDVI NDVI i ,

[0078] Among them, HI iis the farmland health index of the ith region, HI i ∈[0,1],N i is the soil nutrient of the ith area, in g / kg, NDVI i is the vegetation index of the ith region, SM i is the soil moisture in the ith region, expressed in percentage, ω SM ,ω N ,ω NDVI is the preset weight coefficient, satisfying ω SM +ω N +ω NDVI =1, the preset weight coefficient ω SM ,ω N ,ω NDVI After experts evaluate and analyze the local soil, weather environment, and crops grown, the preset weight coefficient ω SM ,ω N ,ω NDVI It is a fixed value used for evaluation and analysis and does not change due to the difference in N regions.

[0079] For example, the soil moisture in the i-th area is 35%, the soil nutrient in the i-th area is 0.5 g / kg, the vegetation index in the i-th area is 0.4, the preset weight coefficients are 0.3, 0.4, and 0.3 in the order of the formula, and the farmland health index in the i-th area is 0.425.

[0080] In this embodiment, the visualization decision support module includes a second edge computing device and a visualization unit.

[0081] The visualization unit is connected to the first microprocessor network, and is used to convert the N farmland health indexes into a health index matrix after receiving them, and then map a heat map according to the health index matrix. It is also used to graphically display the recommended water and fertilizer amounts for the N farmlands after receiving them.

[0082] In this embodiment, a heat map is mapped out according to the health index matrix, by grading the farmland health index and then rendering the health index matrix into different colors.

[0083] For example, the farmland health index ∈ [0, 0.5) is red, the farmland health index ∈ [0.5, 0.7) is blue, and the farmland health index ∈ [0.7, 1] is green. The farmland health indexes in the health index matrix are graded one by one, and then the health index matrix is ​​rendered in different colors.

[0084] The second edge computing device is connected to the first microprocessor, remote sensing image satellite, soil nutrient sensor, soil moisture sensor, visualization unit, and water-fertilizer ratio control module network, and is used to calculate the recommended water volume and recommended fertilizer volume of the N regions according to the N farmland health indexes, soil moisture, soil nutrients, vegetation index in the N regions and the preset basic water volume of crops, basic fertilizer volume of crops, maximum water volume of crops, and maximum fertilizer volume of crops after receiving N farmland health indexes, soil moisture, soil nutrients, and vegetation index in the N regions, and then send the recommended water volume and recommended fertilizer volume of the N regions to the visualization unit and the water-fertilizer ratio control module respectively, and then calculate the recommended water-fertilizer ratio according to the recommended water volume and recommended fertilizer volume of the N regions, and then send the recommended water-fertilizer ratio of the N regions to the water-fertilizer ratio control module respectively.

[0085] In this embodiment, through the visualization decision support module, managers can quickly obtain the health status of N farmlands and their recommended water and fertilizer amounts, thereby improving the efficiency and scientificity of agricultural management. The application of heat maps makes the health status of farmlands clear at a glance, which is convenient for quick judgment and decision-making. The second edge computing device accurately calculates the recommended water and fertilizer amounts for each area based on the actual soil moisture, nutrients and vegetation index, combined with the basic and maximum water and fertilizer amounts of crops. This refined management reduces resource waste, improves water and fertilizer utilization efficiency, and promotes sustainable agricultural development. By linking with the data monitoring unit, the farmland health index is obtained in real time, and potential problems can be discovered and warned in time. This intelligent monitoring and response mechanism can reduce crop losses and ensure the yield and quality of farmland. Through the generation of health index matrix and heat map, complex data can be visualized, managers can intuitively understand the health status and resource requirements of different regions, and support rapid decision-making. According to real-time monitoring data and calculation results, the water and fertilizer application strategy can be dynamically adjusted to achieve adaptation to different growth stages and environmental conditions. This flexibility makes agricultural production more efficient and adaptable.

[0086] In this embodiment, the second edge computing device calculates the recommended water amount and recommended fertilizer amount of the N areas according to the N farmland health indexes, soil moisture, soil nutrients, vegetation index in the N areas, and the preset basic water amount of crops, basic fertilizer amount of crops, maximum water amount of crops, and maximum fertilizer amount of crops.

[0087] The formula for the recommended water volume for the ith area is: W i =W0 +k1·(1-HI i )·W max ,

[0088] Among them, W iis the recommended water volume for the ith area, in L / ha, W0 is the preset basic water volume, in L / ha, k1 is the weight coefficient, HI i is the farmland health index of the ith region, W max It is the preset maximum water volume for crops, in L / ha.

[0089] For example, the preset basic water volume is 300 L / ha, the weight coefficient k1 is 0.5, the farmland health index of the i-th area is 0.425, the preset basic water volume is 300 L / ha, the preset maximum water volume for crops is 600 L / ha, and the recommended water volume for the i-th area is 472.5 L / ha.

[0090] The formula for the recommended water volume for the ith area is: F i =F0 +k2·(1-HI i )·F max ,

[0091] Among them, F i is the recommended fertilizer amount for the ith area, in kg / ha, F0 is the preset basic fertilizer amount, in kg / ha, F max It is the preset maximum fertilizer amount for crops, in kg / ha, and k2 is the weight coefficient.

[0092] For example, the preset basic fertilizer amount is 200 kg / ha, the weight coefficient k2 is 0.4, the farmland health index of the i-th area is 0.425, the preset maximum fertilizer amount for crops is 500 kg / ha, and the recommended fertilizer amount for the i-th area is 315 kg / ha.

[0093] The second edge computing device calculates the recommended water-fertilizer ratio according to the recommended water and fertilizer amounts of the N regions:

[0094]

[0095] Among them, R i is the recommended water-fertilizer ratio for the ith area, in L / kg.

[0096] For example: the recommended fertilizer amount for the ith area is 315 kg / ha, the recommended water amount for the ith area is 472.5 L / ha, and the recommended water-fertilizer ratio for the ith area is 1.5 L / kg.

[0097] In this embodiment, the water-fertilizer ratio control module includes a water-fertilizer irrigation control module, a second microprocessor, a meteorological data interface, a radiation sensor, and a wind speed sensor.

[0098] The meteorological data program interface is connected to the National Meteorological Bureau meteorological data source network for the manager to set the farmland location, and then obtain the ambient humidity, ambient temperature, and ambient wind speed of the farmland location from the National Meteorological Bureau meteorological data source, and then send the ambient humidity, ambient temperature, and ambient wind speed to the second microprocessor.

[0099] The radiation sensor is used to measure the amount of ambient radiation and then send it to the second microprocessor.

[0100] The wind speed sensor is used to measure the ambient wind speed and then send it to the second microprocessor.

[0101] The second microprocessor is connected to the meteorological data program interface, the radiation sensor, the wind speed sensor, and the second edge computing device network, and is used to obtain the saturated vapor pressure according to the ambient temperature after receiving the ambient temperature, and then obtain the saturated vapor pressure slope according to the saturated vapor pressure to the temperature. And after receiving the ambient humidity, it is used to obtain the actual vapor pressure according to the ambient humidity and the saturated vapor pressure. And after receiving the ambient radiation and ambient wind speed, it is used to calculate the plant water evaporation rate according to the ambient radiation, ambient wind speed, saturated vapor pressure, actual vapor pressure, and saturated vapor pressure slope, and then send the plant water evaporation rate to the water and fertilizer irrigation control module.

[0102] The water-fertilizer irrigation control module is connected to the second microprocessor and the N-area irrigation equipment network, and is used to calculate the water-fertilizer delivery speed of the N areas according to the plant water evaporation rate, the recommended water-fertilizer ratio, the recommended water volume, and the recommended fertilizer volume of the N areas after receiving the recommended water-fertilizer ratio, the recommended water volume, and the recommended fertilizer volume of the N areas respectively, and then control the water-fertilizer delivery speed of the N-area irrigation equipment respectively according to the water-fertilizer delivery speed of the N areas.

[0103] In this embodiment, the module can obtain the environmental humidity, temperature and wind speed of the farmland in real time through the network connection of the meteorological data interface and the National Meteorological Administration. This provides a scientific basis for subsequent water and fertilizer management, enabling managers to make more accurate decisions based on real-time meteorological data. The second microprocessor can effectively reflect the impact of environmental conditions on plant evapotranspiration by calculating the saturated vapor pressure and its slope. Combined with data such as environmental humidity, radiation and wind speed, the module can calculate the accurate plant water evapotranspiration rate. This process reduces the error caused by environmental changes and provides a reliable basis for subsequent water and fertilizer delivery. After receiving the recommended water-fertilizer ratio, recommended water volume, recommended fertilizer volume and plant water evapotranspiration rate of N areas, the water and fertilizer irrigation control module can obtain the water and fertilizer delivery speed of N areas based on comprehensive calculation. This intelligent control method can effectively improve the utilization rate of water and fertilizer and reduce resource waste. By automatically controlling the irrigation equipment, the application amount of water and fertilizer can be accurately adjusted according to real-time environmental data and the calculated water and fertilizer delivery speed, which greatly improves the management efficiency of farmland, ensures that crops obtain the best water and fertilizer supply during the growth process, and improves crop yield and quality.

[0104] In this embodiment, the second microprocessor obtains the formula of saturated vapor pressure according to the ambient temperature:

[0105] Among them, e s is the saturated vapor pressure in kPa, and T is the ambient temperature in degrees Celsius.

[0106] For example, when the ambient temperature is 25°C, the saturated vapor pressure is calculated to be 3.17 kPa.

[0107] And the formula for obtaining the actual vapor pressure based on the ambient humidity and saturated vapor pressure is:

[0108] Among them, e a is the actual vapor pressure in kPa, and RH is the ambient humidity in percentage.

[0109] For example, the ambient humidity is 60%, the saturated vapor pressure is 3.17 kPa, and the actual vapor pressure is calculated to be 1.90 kPa.

[0110] And the formula for the saturated vapor pressure slope is obtained based on the saturated vapor pressure versus temperature:

[0111] Where Δ is the saturated vapor pressure slope, in kPa / ℃, e s is the saturated vapor pressure, in kPa.

[0112] For example: when the saturated vapor pressure is 3.17 kPa and the ambient temperature is 25°C, the saturated vapor pressure slope is 0.189 kPa / °C.

[0113] The formula for calculating the plant water evaporation rate based on environmental radiation, environmental wind speed, saturated vapor pressure, actual vapor pressure, and saturated vapor pressure slope is:

[0114]

[0115] Among them, ET is the evapotranspiration rate of plant water, in mm / day, R n is the environmental radiation, in MJ / m 2 / day, γ is the psychological constant, u2 is the ambient wind speed, the unit is m / s, Δ is the saturated vapor pressure slope, the unit is kPa / ℃, e s is the saturated vapor pressure, in kPa, e a is the actual vapor pressure in kPa, and λ is the latent heat of evaporation of water, which is 2.45 MJ / kg.

[0116] For example, the ambient temperature is 25°C and the ambient radiation is 15MJ / m 2 / day, the ambient wind speed is 3m / s, the saturated vapor pressure slope is 0.189kPa / ℃, the latent heat of evaporation of water is 2.45MJ / kg, the psychological constant is 0.066, and the calculated plant water evaporation rate is 5.95mm / day.

[0117] In this embodiment, the water and fertilizer irrigation control module calculates the water and fertilizer delivery speed of N areas according to the plant water evaporation rate, the recommended water-fertilizer ratio of N areas, the recommended water volume, and the recommended fertilizer volume. The formula is:

[0118] Among them, V i It is the water and fertilizer delivery rate, and the unit is L / ha / day.

[0119] For example, the plant water evaporation rate is 5.95 mm / day, the recommended water-fertilizer ratio is 1.5 L / kg, the recommended fertilizer amount is 315 kg / ha, the recommended water amount is 472.5 L / ha, and the water-fertilizer delivery rate is 91.2 L / ha / day.

[0120] The above embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, other embodiments obtained by those skilled in the art without creative work shall all fall within the scope of protection of the present invention.

Claims

1. A water-fertilizer ratio control system based on artificial intelligence, characterized by: Including visual decision support module, water-fertilizer ratio control module, farmland quality monitoring module, The farmland quality monitoring module is electrically connected to the warning light board, and is arranged in N areas, for the manager to store the overall farmland model; and for the manager to divide the overall farmland model into N areas, and then monitor the environmental factors in the N areas, and then send them to the visualization decision support module; and after monitoring the environmental factors in the N areas, N farmland health indexes are calculated according to the environmental factors in the N areas and the preset weight coefficients, and then sent to the visualization decision support module; and after traversing and judging that the N farmland health indexes include a farmland health index lower than the preset farmland health index threshold, turn on the warning light board corresponding to the farmland health index lower than the preset farmland health index threshold; The visualization decision support module is connected to the farmland quality monitoring module network, and is used for converting N farmland health indexes into a health index matrix after receiving them, and then mapping a heat map based on them; after receiving N farmland health indexes and environmental factors in N areas, respectively calculating the recommended water volume and recommended fertilizer volume of the N areas according to the N farmland health indexes and environmental factors in the N areas, and then graphically displaying the recommended water volume and recommended fertilizer volume of the N areas, respectively, and then calculating the recommended water-fertilizer ratio according to the recommended water volume and recommended fertilizer volume of the N areas, and then sending the recommended water-fertilizer ratio of the N areas, the recommended water volume and recommended fertilizer volume of the N areas to the water-fertilizer ratio control module; The water-fertilizer ratio control module is connected to the visualization decision support module, the meteorological data source of the National Meteorological Bureau, and the network of N regional irrigation equipment, and is used for the manager to set the location of the farmland, and then obtain the environmental humidity, ambient temperature, and ambient wind speed of the farmland location in the meteorological data source of the National Meteorological Bureau; it is used to measure the environmental radiation; it is used to obtain the saturated vapor pressure according to the ambient temperature, and then obtain the saturated vapor pressure slope according to the saturated vapor pressure to temperature, and then obtain the actual vapor pressure according to the ambient humidity and the saturated vapor pressure, and then calculate the plant water evaporation rate according to the environmental radiation, ambient wind speed, saturated vapor pressure, actual vapor pressure, and saturated vapor pressure slope; it is used to calculate the water and fertilizer delivery speed of the N areas according to the plant water evaporation rate, the recommended water and fertilizer ratio, the recommended water volume, and the recommended fertilizer volume of the N areas after receiving the recommended water-fertilizer ratio, the recommended water volume, and the recommended fertilizer volume of the N areas respectively, and then control the water and fertilizer delivery speed of the irrigation equipment in the N areas according to the water and fertilizer delivery speed of the N areas.

2. The water-fertilizer ratio control system based on artificial intelligence according to claim 1 is characterized in that: The farmland quality monitoring module includes a region division unit, a data monitoring unit, a warning unit, and a first edge computing device. The area division unit is used for the manager to store the overall farmland model; and is used for the manager to divide the overall farmland model into N areas, and then transmit the N areas to the data monitoring unit; The data monitoring unit is connected to the area division unit and the visualization decision support module network, and is set in N areas. After receiving the N areas, the data monitoring unit is used to monitor the soil moisture, soil nutrients, and vegetation index in the N areas, and then send them to the visualization decision support module, and then calculate N farmland health indexes according to the soil moisture, soil nutrients, and vegetation index in the N areas and the preset weight coefficients, and then send the N farmland health indexes to the first edge computing device and the visualization decision support module; The first edge computing device is connected to the data monitoring unit network, and is used for the administrator to store the data monitoring unit and the warning unit corresponding to the data monitoring unit; Used to, after receiving N farmland health indexes, traverse and determine whether the N farmland health indexes include a farmland health index that is lower than a preset farmland health index threshold; and used to, after traversing and determining that the N farmland health indexes include a farmland health index that is lower than the preset farmland health index threshold, query the data monitoring unit corresponding to the farmland health index that is lower than the preset farmland health index threshold, then query the corresponding stored warning unit based on the corresponding data monitoring unit, then generate a warning signal, and then send the warning signal to the corresponding warning unit; The warning units are arranged in N areas, electrically connected to the warning light signs, and respectively electrically connected to the data monitoring units in the corresponding areas, and are used to turn on the corresponding warning light signs after receiving the early warning signal.

3. The water-fertilizer ratio control system based on artificial intelligence according to claim 2 is characterized in that: The data monitoring unit includes a soil moisture sensor, a soil nutrient sensor, a remote sensing image satellite, a first microprocessor, and a second microprocessor. The soil moisture sensors are arranged in N areas and are connected to the visualization decision support module network to monitor the soil moisture in the N areas, and then send the soil moisture in the N areas to the visualization decision support module and the first microprocessor; The soil nutrient sensors are arranged in N areas and are connected to the visualization decision support module network to monitor the soil nutrients in the N areas, and then send the soil nutrients in the N areas to the visualization decision support module and the first microprocessor; The remote sensing image satellite is connected to the visualization decision support module network, and is used to collect the reflectance of the plants in the N areas to the infrared band and the near-infrared band after receiving N areas, and then calculate the vegetation index of the N areas respectively by the reflectance of the infrared band and the near-infrared band, and then send the vegetation index of the N areas to the visualization decision support module and the first microprocessor; The first microprocessor is connected to the soil moisture sensor, the soil nutrient sensor, the remote sensing image satellite, the first edge computing device, and the visualization decision support module network, and is used to calculate N farmland health indexes according to the soil moisture, soil nutrients, and vegetation index in the N regions and preset weight coefficients after receiving the soil moisture, soil nutrients, and vegetation index in the N regions, and then send the N farmland health indexes to the first edge computing device and the visualization decision support module.

4. The water-fertilizer ratio control system based on artificial intelligence according to claim 3 is characterized in that: The remote sensing image satellite calculates the vegetation index of N regions by the reflectivity of the infrared band and the near-infrared band. The vegetation index calculation formula is: Among them, NDVI i is the vegetation index of the i-th region, i is the region number, i∈[0,N], NIR i is the reflectivity of the near-infrared band of the i-th region, RED i The reflectivity of the infrared band of the i-th region.

5. The water-fertilizer ratio control system based on artificial intelligence according to claim 4 is characterized in that: The first microprocessor calculates the N farmland health indexes according to the soil moisture, soil nutrients, vegetation index and preset weight coefficients in the N regions: i =ω SM SM i +ω N N i +ω NDVI NDVI i , Among them, HI i is the farmland health index of the ith region, N i is the soil nutrient of the ith area, in g / kg, NDVI i is the vegetation index of the ith region, SM i is the soil moisture in the ith region, expressed in percentage, ω SM ,ω N ,ω NDVI is the preset weight coefficient, satisfying ω SM +ω N +ω NDVI =1.

6. The water-fertilizer ratio control system based on artificial intelligence according to claim 5 is characterized in that: The visualization decision support module includes a second edge computing device and a visualization unit. The visualization unit is connected to the first microprocessor network, and is used to convert N farmland health indexes into a health index matrix after receiving them, and then map a heat map according to the health index matrix; and for graphically displaying the recommended water and fertilizer amounts for N farmlands after receiving them; The second edge computing device is connected to the network of the first microprocessor, the remote sensing image satellite, the soil nutrient sensor, the soil moisture sensor, the visualization unit, and the water-fertilizer ratio control module, and is used to calculate the recommended water amount and recommended fertilizer amount of the N areas according to the N farmland health indexes, the soil moisture, soil nutrients, and vegetation index in the N areas and the preset basic water amount of crops, basic fertilizer amount of crops, maximum water amount of crops, and maximum fertilizer amount of crops after receiving N farmland health indexes, soil moisture, soil nutrients, and vegetation index in the N areas, and then send the recommended water amount and recommended fertilizer amount of the N areas to the visualization unit and the water-fertilizer ratio control module respectively, and then calculate the recommended water-fertilizer ratio according to the recommended water amount and recommended fertilizer amount of the N areas, and then send the recommended water-fertilizer ratio of the N areas to the water-fertilizer ratio control module respectively.

7. The water-fertilizer ratio control system based on artificial intelligence according to claim 6 is characterized in that: The second edge computing device calculates the recommended water amount and recommended fertilizer amount of the N areas according to the N farmland health indexes, soil moisture, soil nutrients, vegetation index and preset basic water amount of crops, basic fertilizer amount of crops, maximum water amount of crops and maximum fertilizer amount of crops. The formula for the recommended water volume for the ith area is: W i =W0 +k1·(1-HI i )·W max , Among them, W i is the recommended water volume for the ith area, in L / ha, W0 is the preset basic water volume, in L / ha, k1 is the weight coefficient, HI i is the farmland health index of the ith region, W max It is the preset maximum water volume for crops, in L / ha; The formula for the recommended water volume for the ith area is: F i =F0 +k2·(1-HI i )·F max , Among them, F i is the recommended fertilizer amount for the ith area, in kg / ha, F0 is the preset basic fertilizer amount, in kg / ha, F max is the preset maximum fertilizer amount for crops, in kg / ha, and k2 is the weight coefficient; The second edge computing device calculates the recommended water-fertilizer ratio according to the recommended water amount and recommended fertilizer amount of the N areas: Among them, R i is the recommended water-fertilizer ratio for the ith area, in L / kg.

8. The water-fertilizer ratio control system based on artificial intelligence according to claim 5 is characterized in that: The water-fertilizer ratio control module includes a water-fertilizer irrigation control module, a second microprocessor, a meteorological data interface, a radiation sensor, and a wind speed sensor. The meteorological data program interface is connected to the meteorological data source network of the National Meteorological Bureau, and is used for the manager to set the location of the farmland, and then obtain the ambient humidity, ambient temperature, and ambient wind speed of the farmland location in the meteorological data source of the National Meteorological Bureau, and then send the ambient humidity, ambient temperature, and ambient wind speed to the second microprocessor; The radiation sensor is used to measure the amount of environmental radiation and then send it to the second microprocessor; The wind speed sensor is used to measure the ambient wind speed and then send it to the second microprocessor; The second microprocessor is connected to the meteorological data program interface, the radiation sensor, the wind speed sensor, and the second edge computing device network, and is used to obtain the saturated vapor pressure according to the ambient temperature after receiving the ambient temperature, and then obtain the saturated vapor pressure slope according to the saturated vapor pressure to the temperature; and is used to obtain the actual vapor pressure according to the ambient humidity and the saturated vapor pressure after receiving the ambient humidity; and is used to calculate the plant water evaporation rate according to the ambient radiation, the ambient wind speed, the saturated vapor pressure, the actual vapor pressure, and the saturated vapor pressure slope after receiving the ambient radiation and the ambient wind speed, and then send the plant water evaporation rate to the water and fertilizer irrigation control module; The water-fertilizer irrigation control module is connected to the second microprocessor and the N-region irrigation equipment network, and is used to calculate the water-fertilizer delivery speed of the N regions according to the plant water evaporation rate, the recommended water-fertilizer ratio, the recommended water volume, and the recommended fertilizer volume of the N regions after receiving the recommended water-fertilizer ratio, the recommended water volume, and the recommended fertilizer volume of the N regions respectively, and then control the water-fertilizer delivery speed of the N-region irrigation equipment respectively according to the water-fertilizer delivery speed of the N regions.

9. The water-fertilizer ratio control system based on artificial intelligence according to claim 7 is characterized in that: The formula for obtaining the saturated vapor pressure according to the ambient temperature by the second microprocessor is: Among them, e s is the saturated vapor pressure in kPa, T is the ambient temperature in degrees Celsius; And the formula for obtaining the actual vapor pressure based on the ambient humidity and saturated vapor pressure is: Among them, e a is the actual vapor pressure in kPa, RH is the ambient humidity in percentage; And the formula for the saturated vapor pressure slope is obtained based on the saturated vapor pressure versus temperature: Where Δ is the saturated vapor pressure slope, in kPa / ℃, e s is the saturated vapor pressure, in kPa; The formula for calculating the plant water evaporation rate based on environmental radiation, environmental wind speed, saturated vapor pressure, actual vapor pressure, and saturated vapor pressure slope is: Among them, ET is the evapotranspiration rate of plant water, in mm / day, R n is the environmental radiation, in MJ / m 2 / day, γ is the psychological constant, u2 is the ambient wind speed, the unit is m / s, Δ is the saturated vapor pressure slope, the unit is kPa / ℃, e s is the saturated vapor pressure, in kPa, e a is the actual vapor pressure in kPa, and λ is the latent heat of evaporation of water, which is 2.45 MJ / kg.

10. The water-fertilizer ratio control system based on artificial intelligence according to claim 9, characterized in that: The water and fertilizer irrigation control module calculates the water and fertilizer delivery speed of N areas according to the plant water evaporation rate, the recommended water-fertilizer ratio of N areas, the recommended water volume, and the recommended fertilizer volume: Among them, V i It is the water and fertilizer delivery rate, and the unit is L / ha / day.

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