11833results about "Watering devices" patented technology

The invention relates to the technical field of intelligent agriculture and ecological internet of things, in particular to an ecological irrigation decision dynamic optimization method and related equipment. Comprising the following steps: acquiring multi-source environment data, acquiring a soil profile humidity gradient in real time through a soil humidity sensor array, acquiring future rainfall probability distribution, a temperature change rate and a wind speed predicted value in combination with a weather forecast interface, and synchronously accessing a geographic information system to acquire terrain elevation and crop distribution data. The three technical bottlenecks of model dimension collapse, parameter estimation instability and optimization response lag in a traditional irrigation decision-making system are systematically solved by constructing a space-time coupling analysis framework and a closed-loop optimization mechanism of multi-source heterogeneous data.

The invention discloses an urban greening system based on big data and an optimization method thereof, relates to the technical field of artificial intelligence, and solves the problems of difficulty in heterogeneous data integration, insufficient real-time analysis capability of dynamic data and low management efficiency in an existing urban greening system. Multi-source heterogeneous data are collected through an API interface and Internet of Things communication, and are cleaned, aligned, converted and fused through a distributed real-time data stream processing platform; image recognition and a machine learning algorithm are used for monitoring diseases and insect pests in real time, and a growth prediction model is trained in combination with an LSTM network, so that the quick response capability of the system to environmental changes is enhanced; according to the method, target weights are dynamically adjusted and optimized through the deep Q network, a multi-target optimization model is constructed in combination with mixed integer linear programming, context awareness and a genetic algorithm, intelligent optimization of irrigation, fertilization, pest control and greening layout is achieved, and the management efficiency and the resource utilization rate of an urban greening system are remarkably improved.

The invention relates to the technical field of agricultural intelligent irrigation, and discloses a meteorological data fused water-saving irrigation control method, device and equipment and a medium. According to the method, a historical meteorological data set is constructed through multi-source meteorological data fusion, a dynamic water demand table is generated in combination with a crop water demand characteristic database, and a crop water demand model is established based on soil moisture content data. A grid irrigation unit division and growth period coupling soil moisture content response matrix construction technology is adopted, a cooperative constraint is established between a water demand threshold value and a water saving benefit through a multi-objective optimization learning algorithm, and a personalized irrigation scheme is generated. A soil moisture content dynamic evaluation matrix containing a dynamic time warping operator is designed, and dynamic matching of the soil layered soil moisture content and a standard template is achieved. The contradiction between meteorological response lag and low water resource utilization rate in traditional irrigation is effectively solved, accurate irrigation decision is realized through multi-dimensional data fusion and an intelligent optimization algorithm, and the water-saving benefit and the agricultural water resource utilization efficiency are improved.

Provided is an intelligent irrigation control method for rice fields based on a cloud service platform and a system thereof. Constructing a planting condition data set and a condition coefficient, monitoring the current water supply environment of crops, and constructing a water supply coefficient. If the water supply coefficient is lower than the water supply threshold, based on the current growth data of crops, a plurality of corresponding irrigation strategies are matched from the pre-constructed crop irrigation knowledge graph, and the target strategy is selected from a plurality of irrigation strategies; constructing an irrigation observation coefficient set, and constructing irrigation coefficient. If the irrigation coefficient is lower than the efficiency threshold, use the trained strategy optimization model to optimize the target strategy, and control the irrigation coefficient based on the optimized target strategy to complete the irrigation of crops in the irrigation area.

The invention discloses a water-saving control method for agricultural irrigation, a cloud platform and equipment, and relates to the technical field of irrigation water-saving control, and the method comprises the steps: determining the historical rainfall of the geographic position of a target farmland and the historical soil moisture content parameter of the target farmland; determining farmland water demand rule characteristics of the target farmland based on the historical rainfall and the historical soil moisture content parameters; constructing a farmland water-saving control model according to the farmland water demand rule characteristics; dividing a water demand area of the target farmland based on the crop information; based on the farmland water-saving control model and the soil moisture content parameter of each water demand area, obtaining a predicted irrigation value of each water demand area; acquiring a real-time irrigation value of each water demand area; and based on the predicted irrigation value and the real-time irrigation value, performing real-time regulation and control on a preset intelligent irrigation water valve in each water demand area. The problem that the utilization rate of water resources is low can be effectively solved.

The invention provides a crop accurate management method and system based on a crop growth model. The method comprises the following steps: collecting environment data of a crop growth period by integrating a remote sensing technology, a field intelligent sensor and an unmanned aerial vehicle, and carrying out space-time alignment to form a comprehensive environment data set; and dynamically adjusting parameters of the crop growth model by using a Bayesian rule, evaluating the influence of environmental uncertainty on crops in combination with Monte Carlo simulation, and providing yield prediction with a confidence interval. Based on the prediction, a particle swarm optimization algorithm is applied to formulate management schemes such as irrigation, fertilization, pest control and harvesting opportunities, and meanwhile, a multi-objective optimization strategy is adopted to balance economic benefits and environmental protection. After the scheme is implemented, the crop growth response is monitored in real time so as to reinforce learning and automatically adjust management measures, and precise agricultural management is realized. According to the technical scheme provided by the embodiment of the invention, the crop management precision and efficiency are improved.

The invention relates to the technical field of automatic irrigation control, in particular to a multi-sensor fusion agricultural precise irrigation system which comprises a leaf area analysis module, an environment evaluation module, a task arrangement module, an execution regulation and control module and a feedback regulation module. According to the method, the crop leaf area index is introduced to be compared with the growth stage target value, the dynamic expression of the group moisture demand is realized, the environmental evapotranspiration influence factor is generated in combination with illumination and temperature disturbance parameters, the timeliness of water demand driving force identification is enhanced, and the task execution sequence is judged by adopting regional water pressure disturbance data; a multi-region irrigation resource allocation process is optimized, a water quantity and pressure difference double-factor adjustment mechanism is utilized, the rationality and response accuracy of time length allocation are improved, water supply state analysis and task target deviation comparison are performed, dynamic supplementary irrigation regulation and control are realized, the closed-loop capability and supplementary irrigation accuracy of irrigation period control are improved, and the irrigation period control efficiency is improved. And the stable allocation capability and the irrigation response efficiency of the irrigation system under the influence of multiple variables are enhanced.

The invention relates to the technical field of soil monitoring, in particular to a farmland irrigation management and control system based on the Internet of Things, and the system comprises a soil monitoring module, a crop water demand analysis module, an irrigation strategy making module, an irrigation execution control module, a water source management module, a fertilizer distribution module, an irrigation effect evaluation module and an adaptability adjustment module. According to the method, the crop water demand is analyzed by combining the decision tree, the water consumption is accurately calculated, the irrigation strategy optimizes the time and frequency based on the linear programming and simulated annealing method, the scheme adaptation degree is improved, the irrigation link adopts an automatic control and dynamic adjustment mechanism, the environment and crop demand changes are adapted in real time, and the irrigation efficiency is improved. Water source allocation ensures efficient distribution of multiple water sources on the basis of dynamic optimization, the type and quantity of fertilizer feeding are accurately controlled according to crop requirements, the irrigation effect is subjected to self-adaptive optimization of an irrigation plan after crop data evaluation, and accurate, flexible and efficient farmland resource management is integrally achieved.

The invention discloses an ecological garden intelligent management method and system, and belongs to the technical field of landscaping management, and the method specifically comprises the steps: monitoring environmental parameters in real time through multiple sensors, and uploading the environmental parameters to a cloud server; at the cloud end, a dynamic data analysis model is constructed by utilizing historical irrigation data, a plant growth model and real-time monitoring parameters, the water demand of plants is predicted, and an irrigation decision is made; an irrigation threshold value is set according to the decision, and an irrigation program is automatically started and executed through remote control equipment; after irrigation, detailed information is recorded and fed back to the data analysis model, the irrigation effect is evaluated by adopting a data analysis method, and an irrigation decision is finely adjusted accordingly; intelligent and precise irrigation management is realized, and the utilization efficiency of water resources and the growth quality of plants are improved.

The invention discloses a drip irrigation parameter dynamic regulation and control method combined with multi-point sensor monitoring, and relates to the technical field of irrigation regulation and control, the method comprises the following steps: monitoring a multi-point sensor arranged in a target area to obtain target monitoring data; performing actual demand analysis on the target crop to obtain actual demand data; analyzing the target soil permeability of the target area to obtain a target irrigation period; and performing irrigation processing according to the actual demand data and the target irrigation period to obtain irrigation data. The technical problems that in the prior art, real-time requirements of crops cannot be accurately obtained, irrigation is difficult to implement according to soil characteristics, and the agricultural production efficiency and sustainability are limited are solved. The effects that multiple types of monitoring data are obtained by arranging the multi-point sensors in the target area, precise irrigation is achieved, the crop growth environment is optimized, good physicochemical properties of soil are maintained, and the technical effects of high efficiency and sustainability of agricultural production are improved are achieved.

The invention relates to the technical field of plant monitoring, in particular to a plant growth monitoring and maintenance system. The system comprises the following modules: a data collection module used for acquiring a plant image and environment data; judging the health condition of the plant based on the plant image; performing plant irrigation and maintenance demand analysis on the health condition according to the environmental data to generate plant irrigation and maintenance demand data; the data processing module is used for performing region segmentation on the plant image through the plant irrigation and maintenance demand data to generate a plant irrigation region; and setting a regional environment anomaly threshold value based on the plant irrigation region, and performing distributed early warning on the plant irrigation region according to the regional environment anomaly threshold value to generate a distributed early warning signal. Through intelligent data collection, environment monitoring, automatic control and precise irrigation optimization, plant health condition evaluation, irrigation demand analysis and efficient water conveying are achieved, and the efficiency and the intelligent level of plant growth and maintenance are improved.

The invention relates to the technical field of environment regulation, in particular to a corn cultivation environment intelligent regulation method based on multi-sensor control, which comprises the following steps: S1, generating a soil moisture three-dimensional distribution diagram in real time through humidity sensor arrays arranged at different depths of a corn root zone; s2, combining infrared temperature data of the canopy and the three-dimensional distribution diagram of the soil moisture, and calculating a moisture motion mismatch degree through transpiration-permeation conduction collaborative analysis; s3, generating a user-defined irrigation mode based on the water movement mismatch degree, and controlling the irrigation duration, the stop interval and the water flow rate. According to the method, coupling modeling is carried out on the plant physiological water demand behavior and the soil moisture supply characteristic, the limitation that a traditional irrigation system only depends on a soil humidity threshold value or meteorological index judgment is broken through, and the biological adaptability and the aging responsiveness of field moisture regulation and control are improved.

The invention relates to the technical field of agricultural intelligent irrigation, and discloses a high-standard farmland intelligent irrigation system based on Internet of Things and data analysis, and the system comprises a soil moisture content sensing module which collects data through a multi-source sensor to construct a three-dimensional soil moisture content distribution model, and generates a soil moisture content characteristic spectrum; the soil moisture content prediction module generates water demand prediction data based on the soil moisture content characteristic spectrum, the meteorological data and the crop growth stage; the irrigation strategy module fuses terrain elevation and pipe network pressure parameters to generate an irrigation control map; the equipment state monitoring module collects water pump current waveform and other data to generate equipment health degree parameters; the pipe network optimization module optimizes pipe network topology and generates an adjusting instruction; the multi-source data fusion module generates fusion evaluation indexes by using an evidence theory, an entropy weight method and the like; and the intelligent execution module generates an execution control instruction accordingly. All the modules cooperate to achieve precise irrigation, and the utilization efficiency of water resources and the intelligent level of farmland management are improved.

The invention discloses a strip-shaped compound planting mode water and fertilizer zoning management method and system, and relates to the technical field of modern agriculture, and the method comprises the following steps: installing a sensor network in a field, collecting data through a soil moisture sensor, an intelligent water meter and an unmanned aerial vehicle multispectral camera, threshold values are set according to the water demand and the fertilizer demand in the crop growth cycle to judge fertigation, crop demands are predicted by applying multiple linear regression and a random forest algorithm, a fertigation plan is optimized, the growth trend is analyzed, the yield potential is evaluated, the influence of the irrigation level is researched, and an irrigation strategy adjustment suggestion is provided. The system collects field data through an integrated sensor network, accurately sets an irrigation and fertilization threshold value, predicts crop demands by using an advanced algorithm, optimizes a water and fertilizer management plan, effectively analyzes a growth trend and evaluates yield potential, provides a scientific basis for irrigation strategy adjustment, and significantly improves modern agricultural production efficiency and resource utilization efficiency.

The invention discloses an intelligent irrigation control method and system based on meteorological information, and relates to the technical field of irrigation control, an area to be irrigated is divided into a plurality of sub-areas, and future rainfall (first rainfall) is predicted through a preset meteorological early warning model; acquiring water absorption data of each sub-region, calculating a water absorption coefficient, and determining absorbable rainfall (second rainfall) in combination with the first rainfall; and judging the water consumption of each sub-region according to the crop growth data and the historical data, and comparing the water consumption with the second rainfall. If the water consumption is greater than the second rainfall, the sub-region needs to be irrigated; according to the method, the soil water content of each sub-region can be finely judged, and whether rainfall meets the water demand or not is evaluated, so that whether irrigation is needed or not is judged, excessive irrigation and water resource waste are avoided, meanwhile, it is ensured that crops obtain enough water, water resource management is optimized, and the crop growth effect and agricultural production efficiency are improved.

The invention relates to a supply and demand multi-source data fusion farmland water-saving irrigation water system design and dynamic water distribution optimization method, which is characterized by comprising the following steps: S1, crop-soil-weather multi-source data coupling modeling, S2, water-saving water system design optimization, S3, dynamic water-saving water distribution strategy, and S4, intelligent terminal control system control. According to the scheme, accurate configuration of water resources is achieved through the artificial intelligence technology, the irrigation water consumption is reduced to the maximum extent, and meanwhile the crop growth requirement is met.

An automated method of classifying irrigation status of fields within a geographical region includes identifying a plurality of field areas delineated by field boundaries within the geographical region. Seasonal normalised difference vegetation index (NDVI) time series data are processed to generate a plurality of aggregate field NDVI feature values for each identified field area. Irrigation status of each identified field area is classified by executing a decision tree classifier that is configured to determine a classification as either ‘irrigated’ or ‘non-irrigated’ based upon the corresponding plurality of aggregate field NDVI feature values.

The invention relates to the field of power system supply and demand interaction, and discloses an intelligent greening irrigation system and a water-saving control method, the system comprises a multi-source data acquisition module, a space-time tensor modeling module, a dynamic decision generation module, an edge calculation acceleration module, a distributed execution control module and a drip irrigation module; the method comprises the following steps: collecting multispectral, meteorological and soil moisture data of a plant canopy in real time to generate an original data set; a fusion data set is obtained through space-time alignment and normalization preprocessing; the water demand is predicted based on an LSTM-Transform model, and an irrigation safety interval is screened; the irrigation uniformity and water pressure distribution are simulated and evaluated through multi-physics field coupling; a double-delay DDPG algorithm is used for optimizing valve opening parameters; the model and the execution error are corrected through Bayesian modeling, and an NDVI feedback optimization strategy is combined. According to the invention, a double-delay depth deterministic strategy gradient algorithm is introduced for dynamic optimization of an irrigation strategy, so that the capability of quickly adapting to environmental changes is achieved.

The invention relates to the field of intelligent agriculture, and discloses an intelligent drip irrigation control method, system and device and a storage medium, and the method comprises the following steps: data collection: obtaining soil humidity data, environmental meteorological data and crop growth state data of a target area through a plurality of sensors, and transmitting the data to a data processing module; the system comprises a data acquisition module used for acquiring soil humidity data, environmental meteorological data and crop growth state data and transmitting the acquired data to a data processing and storage module; the device comprises a machine case shell, and an intelligent control chip, a wireless communication module, an electromagnetic valve and a water flow meter are installed in the machine case shell. By integrating a sensor network, intelligent analysis and a real-time feedback mechanism, the water demand of crops is accurately calculated, irrigation is automatically adjusted, and water resource utilization is optimized; a personalized irrigation plan is made by combining a deep neural network and time sequence analysis, and the water requirements of crops in different growth stages are ensured.

The invention relates to the technical field of saline-alkali soil improvement, in particular to an intelligent irrigation and soil conditioning system for saline-alkali soil improvement, which comprises a climate prediction module, a soil detection module, an electrochemical salt migration prediction module, a data analysis module, an irrigation execution module and a data feedback module, the climate prediction module predicts future climate conditions; the soil detection module monitors soil parameters of the saline-alkali land in real time; the electrochemical salt migration prediction module is used for predicting the migration behavior of salt in soil; the data analysis module formulates irrigation and soil conditioning strategies; the irrigation execution module controls operation of irrigation equipment; and the data feedback module feeds back the irrigation execution result and the actual soil improvement effect, and continuously optimizes irrigation and soil conditioning strategies. According to the method, efficient utilization of resources is achieved, and the accuracy and scientificity of saline-alkali soil improvement are ensured.

The invention discloses an agricultural water-saving irrigation system and a water-saving irrigation method thereof. Relates to the technical field of agricultural irrigation. The height adjusting device comprises clamping assemblies and a plurality of lifting air cylinders, and the top of each lifting air cylinder is provided with the corresponding clamping assembly; and the two water supply pipelines are correspondingly arranged at intervals, each water supply pipeline is fixed to the lifting air cylinder through a clamping assembly, a plurality of irrigation pipelines are arranged between the two water supply pipelines at intervals, and each irrigation pipeline is provided with an irrigation spray head assembly. The agricultural water-saving irrigation method comprises the following steps: step 1, height adjustment; 2, adjusting the irrigation water flow; step 3, carrying out drip irrigation; 4, sprinkling irrigation is carried out; and 5, pressure adjustment. According to different irrigation requirements, switching between spray irrigation and drip irrigation can be achieved through the irrigation spray head assembly, so that more accurate moisture control is achieved, and the irrigation process is simple, direct and practical.

The invention relates to the technical field of irrigation, and discloses an intelligent energy-saving irrigation management system and method based on environmental monitoring, and the method comprises the steps: obtaining the daily water demand of crops in a farmland through a crop growth monitoring module, setting the water flow of irrigation according to the daily water demand, then dividing the farmland into a plurality of regions, then environment parameters of soil humidity, temperature and illumination intensity of each area are monitored in real time through an environment monitoring module, and then the environment parameters are processed and analyzed through a data processing module to obtain current irrigation indexes of each area; whether the set irrigation water flow meets the irrigation requirements of all the areas or not is judged based on the current irrigation indexes of all the areas, if the areas do not meet the irrigation requirements, water supplementing is conducted on the areas in a sprinkling irrigation mode, then the water supplementing water flow is calculated based on the environment parameters, and it is guaranteed that the water content of all the areas of the farmland is consistent; therefore, the growth vigor of crops in each area is consistent.

The invention discloses an intelligent soil moisture content monitoring and precise irrigation linkage system, and relates to the technical field of irrigation. Key parameters such as moisture content, temperature, humidity and conductivity of soil are obtained in real time through a soil moisture content monitoring module, processed by a data acquisition and transmission module and transmitted to a control center; the control center carries out deep analysis and evaluation on the soil moisture condition through the edge computing gateway and the cloud decision controller, an accurate irrigation control instruction is generated, the irrigation control execution module carries out accurate regulation and control on irrigation equipment according to the instruction, and reasonable irrigation of a farmland is achieved. The system can comprehensively master the moisture condition of farmland soil, provides data support for precise irrigation, improves the precision and efficiency of irrigation, saves water resources, is intelligent and high in automation degree, can reduce manual intervention, reduces the labor cost, and improves the stability and reliability of irrigation at the same time.

The invention provides a high-standard farmland water and fertilizer integrated intelligent regulation and control method and system, and the method comprises the steps: obtaining terrain point cloud data and crop canopy water stress data of a high-standard farmland, generating an elevation gradient distribution feature set, and generating an elevation model according to the set; analyzing the crop canopy moisture stress data, and calculating a moisture stress index; performing spatial position matching on the terrain difference parameters and the micro-terrain difference parameters to generate a terrain compensation parameter set; establishing a time sequence optimization correlation model in the 5G edge computing node, and optimizing a pulse irrigation time sequence factor and a flow distribution weight by using the time sequence optimization correlation model according to the terrain compensation parameter set and the historical irrigation record so as to generate a multi-target irrigation control instruction; performing high-standard farmland water and fertilizer integrated intelligent regulation and control according to the multi-target irrigation control instruction and the water and fertilizer migration rate parameter corresponding to the microtopography difference parameter; water and fertilizer are accurately distributed according to needs, and the irrigation uniformity, the resource utilization efficiency and the crop yield are improved.

The present invention discloses a direct-seeding machine for dry paddy fields with film covering and synchronous hole seeding for rice, which includes a frame, a rotary tillage device, a fertilizing device, a drip irrigation belt laying device, a film laying device, a soil covering device, a laser film cutting device, a seeding device, and an irrigation device provided on the frame. A depth limit assembly is attached to the front end of the frame, and a tractor support is attached to the top of the frame. The frame is connected to an agricultural machine via the tractor support. 【Effect】 The present invention has multiple functions, improves the stability, accuracy, and adaptability of the machine, improves the seeding quality of direct seeding in dry paddy fields with film covering for rice, and truly realizes the cultivation of direct seeding in dry paddy fields with film covering for rice. It solves the problem of difficult water injection during the process of direct seeding with film covering and hole opening in dry paddy fields, realizes water injection into the holes at the same time of seeding, greatly improves the seedling emergence rate of direct seeding with film covering and hole opening in dry paddy fields for rice, and can obtain complete and strong seedlings that are uniform.

The invention discloses an integrated control system for potato breeder's seed production, and relates to the technical field of potato breeding, the integrated control system for potato breeder's seed production comprises an environment monitoring module, a crop growth monitoring module, a fertilization demand module, a water and fertilizer supply control module, an equipment state monitoring module and a feedback correction module; the environment monitoring module collects environment parameters of a crop growth environment through a deployed sensor, and the environment parameters comprise temperature, soil humidity and illumination intensity. Through water and fertilizer supply and real-time monitoring, it is ensured that crops can obtain sufficient water and nutrients in all growth stages, irrigation and fertilization strategies are dynamically adjusted according to environmental conditions and plant growth states, the problem of poor growth caused by excessive or insufficient fertilization is avoided, the overall yield of the crops is increased through accurate regulation, and the yield of the crops is increased. The quality of the potatoes is improved, so that the goals of high quality and high yield are achieved.

An agricultural automatic irrigation device, comprising a base (1), wherein an outer frame (2) is fixedly mounted at the top end of the base (1), a stirring tank (3) is fixedly mounted on the outer frame (2), an indirect discharging mechanism (5) is fixedly mounted on the stirring tank (3), a mixing frame (4) is fixedly mounted at the top end of the stirring tank (3), a mixing and stirring mechanism (6) is fixedly mounted on the mixing frame (4), a feeding mechanism (8) is fixedly mounted on one side of the top end of the base (1), a connecting channel (7) is fixedly mounted on the side of the feeding mechanism (8) that is close to the outer frame (2), and a fixed stirring mechanism (9) is fixedly mounted in the stirring tank (3). By providing the feeding mechanism (8), the indirect discharging mechanism (5), the mixing and stirring mechanism (6) and the fixed stirring mechanism (9), various solid agents needing to be mixed and required for crop growth are conveyed into the mixing frame (4) by means of the feeding mechanism (8), and the solid agents required for the growth of various solid crops are stirred and mixed by means of the mixing and stirring mechanism (6).

The invention provides a photovoltaic field rainwater collection and intelligent distribution irrigation system, and relates to the water resource management and utilization technology, the photovoltaic field rainwater collection and intelligent distribution irrigation system comprises a photovoltaic panel body, and one side of the photovoltaic panel body is provided with a distribution irrigation mechanism. According to the application, the integrated sensor module, the control module and the execution module are arranged in the distribution irrigation mechanism, so that real-time monitoring and analysis of soil humidity, crop states and meteorological data are realized, and water is accurately distributed to the target area according to irrigation requirements of different areas. The drip irrigation unit, the spray irrigation unit and the micro-spray irrigation unit are utilized to meet irrigation requirements of different land parcels, and the problems that in the prior art, the irrigation mode is single, resource waste is serious, and the irrigation amount cannot be adjusted according to dynamic requirements are solved. According to the design, through intelligent control and partition management, accurate irrigation and efficient utilization of water resources are achieved.

The invention relates to the technical field of self-adaptive control, in particular to a tobacco field variable fertilization control system and method, and the system comprises a sensing data collection module which collects soil humidity data through a soil humidity sensor, monitors the growth data of crops at the same time, and carries out the synthesis to obtain real-time soil and growth data; and performing time sequence analysis on the real-time soil and growth data, identifying a data trend and an abnormal point, and generating a trend analysis result. According to the method, the soil humidity and the crop growth data are collected, and the time sequence analysis is combined, so that the trend and the abnormality are quickly identified, and the prediction accuracy is improved. The convolutional neural network is used for carrying out recognition and probability evaluation on diseases and insect pests, so that disease and insect pest management is more accurate, and response is quicker. Through the technologies, the system can dynamically adjust irrigation parameters based on real-time data, optimize water distribution, and ensure that an irrigation strategy is perfectly matched with crop requirements and potential risks.

The invention discloses an artificial intelligence rice water and fertilizer real-time monitoring method and system, and relates to the technical field of agricultural intelligent decision making, and the method comprises the steps: inputting a farmland feature data set into a soil thermodynamic diagram generation model, carrying out the high-resolution reconstruction of the farmland feature data set through a GAN adversarial network, and generating a whole-field high-precision soil thermodynamic diagram; based on the whole-field high-precision soil thermodynamic diagram, a collision relation between the fertilization amount and historical farming data is detected according to an FCL causal algorithm, a preliminary causal diagram is generated, and a causal diagram structure of the fertilization amount and the historical farming data is constructed by adopting a multiple linear regression method; based on a causal diagram structure, the multi-order causal effect of the fertilization amount, the soil parameters and the historical yield is analyzed through a dynamic allocation algorithm, and a water and fertilizer regulation and control strategy is formulated in combination with a multi-objective optimization algorithm. According to the method, the soil thermodynamic diagram generation model is constructed, so that the fuzzy problem of the edge of the field and the salinization area is solved, a high-fidelity soil space state substrate is provided for water and fertilizer regulation and control, and invalid irrigation is reduced.