322 results about "Irrigation control" patented technology

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 specifically relates to the technical field of intelligent irrigation, and discloses a meteorological prediction-based irrigation dynamic regulation and control system, which comprises a data acquisition module, a data analysis module, a strategy generation module, a strategy execution module, a feedback regulation module and a man-machine interaction module, the data acquisition module integrates a water quantity acquisition terminal, a crop state acquisition terminal and a meteorological monitoring terminal, acquires multi-source irrigation decision data of a target irrigation farmland in real time, judges a water shortage risk level of the target irrigation farmland through the data analysis module, and generates an irrigation strategy through the strategy generation module; the strategy execution module executes an irrigation strategy through an electrically-driven intelligent water-saving valve, the feedback adjustment module dynamically adjusts the irrigation strategy based on sensor feedback data, and the man-machine interaction module provides a data visual interface, dynamically optimizes the irrigation strategy in combination with real-time meteorological changes and irrigation feedback, divides water shortage risk levels, and provides a water-saving management system. The utilization efficiency of water resources is effectively improved, and the applicability and reliability of the system are improved.

The invention relates to the technical field of agricultural irrigation, and particularly discloses a farmland irrigation control method and system, and the method comprises the steps: constructing a multi-sensor fusion monitoring network, and collecting soil, weather and plant physiological data in real time; transmitting data to an edge computing node through LoRa wireless communication; utilizing a lightweight neural network model deployed by edge computing nodes to calculate and predict crop water demand and accurate irrigation volume in combination with evapotranspiration; the irrigation strategy is executed through the intelligent irrigation execution system; and remote monitoring and abnormity alarm are realized by means of a remote monitoring and management platform based on WebGIS. Precise and intelligent management of farmland irrigation is realized, the utilization rate of water resources and fertilizers can be effectively improved, irrigation abnormity can be timely handled, the labor management cost is reduced, and the growth requirements of crops are guaranteed.

The invention discloses an intelligent water and fertilizer integrated irrigation system based on an Internet of Things sensor and a large language model, and relates to the technical field of intelligent agriculture. The system obtains soil, weather and plant growth state data in real time through Internet of Things sensors, including a soil sensor, a weather sensor and a multispectral sensor, deployed in a farmland; the method comprises the following steps: based on a large language model architecture, integrating preset agricultural field knowledge base data, performing field adaptive fine tuning on model parameters by adopting a data migration technology, and constructing an intelligent irrigation control model with a dynamic decision-making function; the control model analyzes sensor data and crop growth requirements, generates a water and fertilizer supply strategy, calls an internet-of-things control interface of the water and fertilizer all-in-one machine, and automatically adjusts irrigation water quantity and proportional supply of nutrient elements such as nitrogen, phosphorus and potassium. According to the invention, Internet of Things perception and large model decision are fused, and different environments are adapted through fine adjustment, so that closed-loop precise control is realized, and the water and fertilizer utilization rate and the crop yield are remarkably improved. Actual measurement shows that the system can improve the water and fertilizer utilization rate by 30% or above, and the crop yield is increased by 15-20%.

The invention discloses a high-water-saving accurate drip irrigation optimization method based on a population algorithm. The method comprises the following steps: S1, constructing a comprehensive input data set; s2, forming a multi-dimensional collaborative vector coding set; s3, constructing a multi-objective optimization model; s4, generating an initial improved shark search algorithm population; s5, in a global exploration stage, forming an evaluation result data set; s6, in a local development stage, recording a current optimal multi-target solution; s7, decoding the multi-dimensional collaborative vector code corresponding to the current optimal multi-target solution into a drip irrigation pipe network implementation data set and an irrigation scheduling implementation data set; and S8, generating an irrigation control instruction set based on the drip irrigation pipe network implementation data set and the irrigation scheduling implementation data set, and executing partition irrigation operation. According to the method, the pipe arrangement rationality and the water resource utilization efficiency can be optimized at the same time, and higher convergence and generalization ability are shown in complex terrains and heterogeneous crop distribution environments.

The invention provides an integrated intelligent irrigation self-adaptive control system and method, and relates to the technical field of intelligent irrigation. Comprising the steps of collecting historical irrigation data and real-time irrigation data; preprocessing the irrigation data to obtain preprocessed irrigation data; an irrigation decision model is constructed through BiLSTM-CNN-Attention, and the irrigation demand change trend in a short time in the future is predicted; according to the irrigation demand change trend in a short time in the future, the irrigation amount needed by plants is calculated, and a self-adaptive irrigation control strategy is generated; and evaluating the irrigation decision model by using the model evaluation index, and dynamically adjusting hyper-parameters of the irrigation decision model according to feedback. According to the method, the irrigation decision model is constructed, the change trend of the irrigation demand in a short time in the future is predicted, the irrigation amount required by plants is calculated, and the self-adaptive irrigation control strategy is generated, so that the overall utilization efficiency of water resources is improved, and the irrigation work is ensured to be efficiently and continuously propelled.

The invention relates to the technical field of water conservancy irrigation control, and particularly discloses an energy-saving and environment-friendly water conservancy irrigation system informatization control method which comprises the following steps: S1, acquiring key environment parameters influencing irrigation operation in real time through a wind power detector deployed near a sprinkling irrigation opening, synchronously acquiring a reference working state and a target area of the sprinkling irrigation port; s2, abstracting natural wind into a computable wind vector by establishing a spatial reference coordinate system, and constructing a water drop kinematics model based on a physical law; with the aim of achieving accurate falling of water drops to a target area, model reverse solution is carried out, and the spray irrigation opening angle and the water pressure compensation amount needed for counteracting the wind power influence are accurately calculated; and S3, according to the solved compensation amount, the initial working parameters of the sprinkling irrigation opening are adjusted in real time, so that water drop drifting and evaporation caused by wind power are effectively inhibited, the water resource utilization rate is remarkably increased, and the purposes of energy conservation and environmental protection are achieved.

The invention relates to the technical field of agricultural engineering and ecological environment protection, in particular to a saline-alkali soil desalination improvement system and method based on brackish water recycling. The system comprises a data collection module which collects soil salinity data, meteorological data and crop growth data of the saline-alkali land in real time; the data processing and analyzing module is used for receiving and preprocessing the soil salinity data, the meteorological data and the crop growth data of the saline-alkali land, constructing a soil salinity prediction model and outputting a soil salinity prediction result; the irrigation strategy decision module is used for generating an optimal irrigation strategy by adopting a reinforcement learning algorithm according to the soil salinity prediction result and the preprocessed crop growth data; and the irrigation control system is used for performing brackish water irrigation operation on the saline-alkali soil according to the optimal irrigation strategy. Precise regulation and control of saline-alkali soil salinity can be achieved, brackish water is adopted as irrigation water, water resources are saved to a certain degree, and therefore the improvement cost of saline-alkali soil is reduced.

The invention relates to a drip irrigation pipe network zoning irrigation control method and system based on multi-objective optimization, and belongs to the technical field of artificial intelligence. The method comprises the following steps of collecting multi-source heterogeneous data and sampling point space coordinates, after abnormal value elimination and normalization processing, splicing features and normalized coordinates to form a joint feature vector, and obtaining irrigation partitions with continuous space and similar features through K-means clustering; constructing a multi-objective optimization model taking the zoning irrigation duration and the inlet target flow as decision variables; solving by adopting a hybrid strategy multi-objective evolutionary algorithm of chaotic mapping initialization and adaptive hybrid variation to obtain a Pareto optimal solution set; and finally, combining an entropy weight method and decision maker preference, determining an optimal irrigation parameter through a superior and inferior solution distance method, and introducing a real-time soil moisture monitoring feedback correction parameter. Partitioned precise irrigation of the drip irrigation pipe network can be achieved, multiple optimization objectives are balanced, the irrigation effect and the resource utilization efficiency are improved, and system energy consumption is reduced.

The invention belongs to the technical field of agricultural irrigation, and discloses a precision agriculture water and fertilizer integrated distribution method, which comprises the following steps: S1, data acquisition; s2, data processing and analysis; s3, formulating a water and fertilizer formula; s4, water and fertilizer distribution and conveying The method has the beneficial effects that by comprehensively collecting farmland soil, weather and crop growth data, a crop growth and water and fertilizer demand model is constructed, and accurate prediction and scientific formula making of water and fertilizer demands are achieved; by utilizing a drip irrigation and intelligent irrigation control system, water and fertilizer distribution is accurately regulated and controlled, the resource utilization efficiency is remarkably improved, waste is reduced, healthy growth of crops is promoted, and the yield and quality are improved; in addition, due to precise management, use of chemical fertilizers is reduced, environmental pollution is relieved, the ecological environment is protected, the labor intensity of farmers is reduced due to the intelligent management characteristic, and the production efficiency and flexibility are improved.

The invention discloses a rice growth period distinguishing method and an intelligent irrigation control device. Belongs to the technical field of crossing of intelligent agriculture and irrigation and water conservancy engineering and particularly relates to the technical field of rice growth period judgment and intelligent irrigation. The technical problem that an accurate and effective rice growth period judgment method for guiding intelligent rice irrigation is lacked at present is solved. The method specifically comprises the following steps: calculating a rice growth process index through an improved accumulated temperature model; and constructing a multi-factor coupling growth period judgment method, and judging the current rice growth period through the rice growth process index. The system comprises a sensing unit, a judgment and decision-making unit, an electric execution unit and an input and power supply unit, the judgment and decision-making unit receives the environment data of the rice field and the water layer depth data of the rice field, judges the current growth period of the rice according to a rice growth period judgment method, calculates the current water layer deviation and generates a control instruction to the electric execution unit.

The present disclosure relates to an intelligent water precise irrigation control system and method for cultivation of fruit vegetables in solar greenhouses. The system includes: an information acquisition module for acquiring information by means of sensors, the acquired information including at least one of soil information, ground environment information, irrigation device use process information, and crop information; a water demand prediction module for inputting the acquired information into a deep neural network to predict water demand of fruit vegetables; and an irrigation control module for forming a control instruction according to the predicted water demand, so as to irrigate periodically and quantitatively. In this way, irrigation time and irrigation amount can be decided automatically according to growth conditions and environmental parameters in the whole process. Intelligent irrigation can be achieved with high working efficiency and accuracy, and the water-saving, quality-improved and efficiency-improved production of fruit vegetables can be achieved.

The invention discloses an ecological bank protection intelligent irrigation control system and method based on multi-source data fusion, and relates to the field of irrigation control. Soil moisture content data is collected in real time, meteorological and vegetation growth information is combined, an irrigation strategy is dynamically adjusted through a prediction model, and accurate matching of vegetation water demand and water supply is ensured; meanwhile, sonar echoes are used for constructing underwater digital twin bodies, the state of a fish nest channel is monitored in real time through image recognition, when blockage is detected, the system immediately triggers a cleaning mechanism and synchronously optimizes an irrigation threshold value, and it is avoided that vegetation irrigation is affected due to the fact that water quality is affected by blockage; in the cleaning process, the main operation machine efficiently dredges the channel through rotary cleaning and water flow scouring, and the cleaning effect is verified in real time by means of digital twin bodies; in addition, the system further guarantees the irrigation continuity by presetting the cleaning time limit and a standby water source switching mechanism, effectively prevents the risk of bank slope instability, and remarkably improves the durability and ecological stability of the bank protection structure.

The invention belongs to the technical field of intelligent irrigation, and particularly relates to a dry land terrace intelligent irrigation control system based on multi-modal data, which comprises a data acquisition module, a data analysis and processing module, a water source and water delivery module, an irrigation execution module and a user interface and monitoring module. According to the invention, sudden water deficit (such as late spring coldness) is dealt with through path re-planning by the mobile irrigation unit, the emergency response speed is increased by 70%, and the drought loss rate is reduced by 54% by a synchronous digital twinning alarm strategy. The core breakthrough is that a closed-loop dynamic optimization mechanism of multi-source data acquisition-edge cloud collaboration-execution feedback is formed, and the problem of resource mismatching caused by data splitting of a traditional system is thoroughly solved, so that the emergency capability is improved; through collaborative optimization of an edge calculation layer (for example, more than 50% humidity data is removed in real time in continuous 3 hours) and a cloud decision layer (three-dimensional control matrix output), a valve is dynamically adjusted in combination with gravitational potential energy, so that the irrigation misjudgment rate is reduced.

The invention relates to the technical field of intelligent agricultural intelligent irrigation control, and discloses an intelligent irrigation analysis control system based on a crop growth period. The system comprises a crop image sequence, soil humidity profile data and a regional meteorological sequence. And the data analysis module is used for performing multi-stage growth state interpretation on the image sequence, generating a crop structure state profile in each growth period, performing vertical moisture exchange identification on the soil humidity data, and generating a root zone moisture dynamic map. And the habitat mapping and stress evaluation module synchronously executes habitat adaptability mapping and moisture stress risk mapping. And the irrigation decision module corrects the habitat mapping result according to the stress evaluation result and generates an irrigation decision profile. And the control instruction generation module generates a partition valve control instruction in combination with the decision profile and the alternate irrigation rule. According to the invention, deep fusion analysis of the crop growth state, the root zone moisture and the meteorological environment is realized, and the irrigation decision accuracy and the water resource utilization efficiency are improved.

The invention provides a water and fertilizer on-line accurate detection and irrigation control system which is used for irrigation of hardened water channels in low-latitude plateau areas. Comprising a cloud box, a data acquisition module, an image recognition module, a system PLC controller and a remote control and system alarm. The cloud box establishes a real-time and historical database based on the data acquired by the data acquisition module, further comprises an irrigation volume model and a crop growth period moisture management model, and makes and outputs an irrigation decision based on the irrigation volume and moisture management model; the data acquisition module is used for acquiring soil or matrix data and field water level; the image recognition module collects crop growth images to enter different period schemes; and the PLC receives an irrigation decision or controls a lifting telescopic rod or a water gate decision. According to the system, large-scale intelligent planting of crops is achieved, a large amount of manpower is saved, the problem that the low-latitude plateau green efficient water-saving irrigation technology lacks is solved, and the crop production amount is greatly increased.

To provide a suction and irrigation system for maintaining in situ pressure of an anatomical environment at an anatomical site under control during an endoscopic procedure.SOLUTION: Systems and methods for providing in situ pressure control in an anatomical environment during a procedure are disclosed. The exemplary irrigation and aspiration system includes a user input configured to receive from a user a desired pressure to be applied to the anatomical environment or a desired flow condition corresponding to the desired pressure. The system includes a pressure sensor for sensing pressure in or near an anatomical environment during a procedure, and a pressure sensor for sensing a pressure in the anatomical environment during the procedure, or a control module for adjusting one or more of an irrigation flow rate or an aspiration flow rate of at least one working channel of the medical device to maintain a desired flow condition in the working channel.SELECTED DRAWING: Figure 1

The invention provides a garden plant irrigation control method and system, and relates to the technical field of garden plant irrigation control, and the method comprises the steps: periodically collecting a canopy image of a target plant in a garden scene through a visual perception device, carrying out the preprocessing and feature extraction of the image, and obtaining the plant visual features of the target plant; then, according to the visual features and water shortage judgment standards preset for different plant types, whether the target plant is in an acute water stress state or not is judged. Once it is confirmed that the plant is in an acute water stress state, the system immediately triggers emergency irrigation of the area where the target plant is located, and the problem that in the prior art, an automatic irrigation system excessively depends on environmental parameter measurement and weather prediction when facing sudden extreme weather, and the irrigation efficiency is high is effectively solved. The acute water stress of the plant cannot be found and responded in time.

The invention relates to the technical field of garden irrigation, in particular to a landscaping irrigation intelligent management system based on the Internet of Things, and the system comprises an environment monitoring module which is used for obtaining the real-time environment monitoring data, the real-time irrigation amount and the historical irrigation amount of a landscaping area; the data storage module is used for storing information of different vegetation units in the landscaping area and plant identity information corresponding to the vegetation units, the vegetation unit information comprises water and soil loss amount and soil water storage change amount, and the plant identity information comprises plant species and water amount required by plants; the irrigation prediction module is used for combining the real-time environment monitoring data, the real-time irrigation amount, the historical irrigation amount and the plant identity information through a prediction model to generate a predicted irrigation amount, adjusting the real-time irrigation amount based on the predicted irrigation amount, and generating an irrigation control instruction; the irrigation control module is used for issuing the irrigation control instruction to the corresponding irrigation equipment; and the self-maintenance diagnosis module is used for identifying the execution condition of the irrigation equipment according to the control instruction.

The invention discloses a farmland irrigation control system, and the system comprises an acquisition module which records a crop image of a target crop, introduces the image into a database, and obtains a humidity threshold value of the target crop and soil data of target soil; the analysis module is used for extracting a first shape feature and a color feature of the crop image, analyzing the first shape feature and the color feature to obtain the rhizome depth of the target crop, and analyzing the soil data to obtain the threshold level of the target soil; the decision-making module analyzes the depth of the rhizome to obtain a humidity monitoring range, the acquisition module detects humidity data of the humidity monitoring range, adjusts a humidity threshold value in combination with a threshold value level, generates a first difference value and makes an irrigation decision; according to the method, a double analysis strategy of appearance features and color features is adopted, the growth cycle is accurately identified, the problem of irrigation depth misalignment caused by erroneous judgment in the growth stage in a traditional method is thoroughly solved, and the effect of improving the irrigation depth matching degree is achieved.

The invention relates to the technical field of irrigation saline-alkali soil improvement, in particular to an irrigation saline-alkali soil improvement method based on straw adsorption and water conservancy regulation, which comprises the following steps: acquiring multi-depth soil parameters and surface meteorological data of an irrigation area, and establishing a soil water-salt dynamic migration coupling model; calculating a vertical moisture flux and a plowing layer net salt flux by using the model; calculating an accumulated salt return risk index to obtain a salt return risk grade; building a straw decomposition index by using multi-depth soil parameters; on the basis of the straw decomposition index, updating the soil water and salt dynamic migration coupling model; in response to the fact that the salt return risk level is a high risk, constructing an optimization objective function; resolving and optimizing the objective function to obtain an optimal irrigation strategy; outputting an optimal irrigation strategy to an irrigation control system, and feeding back the optimal irrigation strategy to the model as an irrigation rate; according to the invention, threats can be identified before a high-risk salt return event occurs, the timeliness and initiative of regulation and control are improved, and the balance between treatment benefits and economic cost is realized.

The application relates to the field of garden greening management automation, and discloses a garden greening intelligent irrigation method, system, controller and spray head, the method comprising: collecting environmental information; constructing a soil moisture dynamic equation and a plant growth model according to plant information and environmental information; calculating a spray head opening time based on the dynamic equation and the growth model; controlling the spray head to open and close according to the opening time; and dynamically adjusting the spray head opening time based on the environmental information after the spray head is opened. The application constructs a soil moisture dynamic equation based on soil humidity and weather changes, and calculates a spray head opening time based on the dynamic equation and the growth model, so that efficient and intelligent irrigation control is realized. Compared with an existing timing automatic irrigation system, the application effectively avoids water resource waste caused by fixed cycle watering, while ensuring the accuracy and timeliness of water supply, meets the needs of modern water saving and accurate maintenance, and has remarkable environmental and economic benefits.

The invention discloses a fruit tomato precise irrigation control system and method, and relates to the technical field of agricultural irrigation, and the method comprises the following steps: collecting environment data, soil data and crop growth state data according to a preset frequency, and generating a sample data set; preprocessing original data in the sample data set to obtain a training data set; building an initial model based on a deep learning method, training the initial model by using the training data set until the model converges, and obtaining a trained water demand prediction model; using the trained water demand prediction model to obtain a water demand prediction result of the fruit tomatoes in the current growth state; operation of irrigation equipment is automatically controlled by combining a water demand prediction result and the current soil humidity condition, and various parameters in the irrigation process are monitored in real time. According to the method, the prediction precision of the water demand of the fruit tomatoes can be improved, a suitable moisture environment is provided for the fruit tomatoes, and efficient utilization of water resources and improvement of fruit quality are realized.

The invention relates to the technical field of intelligent agriculture, in particular to an intelligent agricultural water-saving irrigation control system based on a wireless sensor network, which comprises the steps of acquiring crop information, judging an irrigation regulation and control stage, marking land parcels, reading marks, extracting serial numbers of associated acquisition points to divide data transmission priorities, humidity measurement values of different depths are extracted based on the priority list and compared with a crop root layer demand threshold value to identify a water layer needing to be supplemented, root layer types are distinguished according to the soil layer depth, intervals or continuous irrigation periods are set, and the water supply rhythm is arranged; water supply arrangement is read, and instruction contents such as plot numbers, starting and ending time and water supply depth are generated and combined into tasks capable of being continuously called. By monitoring the crop growth and the soil humidity in real time, the irrigation strategy can be accurately judged and dynamically adjusted to meet the water requirement of each stage, the crop root depth and the soil humidity are accurately matched, the irrigation periods of deep and shallow soil layers are optimized, and a flexible scheme is provided to improve the water resource utilization efficiency.

The invention discloses a mechanical arm spraying parameter regulation and control system for artificial rainfall simulation, particularly relates to the technical field of agricultural irrigation control, and is used for solving the technical problems of water pressure self-adaption lagging and spraying parameter instability during alternate irrigation mode switching caused by pipeline extension and retraction of existing mechanical arm irrigation equipment. According to the system, by detecting the length variation of a telescopic water pipe of the mechanical arm and the real-time water pressure value of a water pipe inlet, the flow entropy yield space gradient and the turbulent flow energy dissipation rate are calculated to generate the water pressure compensation amount; regulating and controlling the water pump pressure based on the water pressure compensation amount, and synchronously analyzing a target spraying parameter combination of the alternate irrigation instruction; pressure compensation and parameter adjustment are executed in a linkage mode in the moving process of the mechanical arm, and kinetic energy distribution is collected through a water drop impact sensor array; when the kinetic energy distribution uniformity does not reach the standard, the entropy production and turbulence calculation logic is reversely corrected; precise and stable control over spraying parameters under dynamic operation is achieved, and the multi-area and multi-mode switching requirement is met.

The invention discloses a smart agricultural irrigation visual control method and system based on AI voice control, and relates to the technical field of smart agricultural irrigation control, and the method comprises a monitoring system construction stage and a smart irrigation control stage based on AI voice. A digital twinborn model of the farmland to be irrigated is constructed, and the digital twinborn model is provided with a digital twinborn layer; a ground monitoring point, a soil monitoring point, a crop growth monitoring point and an irrigation point are arranged in a farmland to be irrigated, an environment data monitoring device is arranged at the ground monitoring point, a soil monitoring device is arranged at the soil monitoring point, a crop growth state monitoring device is arranged at the crop growth monitoring point, and an irrigation device is arranged at the irrigation point. Through deep fusion of digital twinborn and multi-modal monitoring and AI voice control, precision, convenience and visualization of intelligent agricultural irrigation are realized, multi-modal data acquisition covers full dimensions of farmland environment soil crops, decision deviation caused by single data is avoided, and comprehensive data support is provided for irrigation decision.

The invention discloses an intelligent garden irrigation control method, and relates to the technical field of garden irrigation, and the technical scheme is characterized in that the method comprises the following steps: collecting soil humidity, temperature and net radiation through a soil parameter detection module; acquiring wind speed, illumination intensity and future rainfall prediction through a meteorological data acquisition module; calculating and outputting a dynamic irrigation demand index based on an edge analysis module; the pressure compensation module generates a valve control instruction based on pipe network position analysis. According to the system, the dynamic irrigation demand index is calculated and output through diversified collection and the edge analysis module, so that precise irrigation can be carried out on the garden according to the actual demand; by arranging the pressure compensation module, the actual flow of each position of the pipe network can be dynamically calculated, and the flow of the pipe network is adjusted, so that the flow difference of each position of the pipe network can be reduced, and irrigation of each position of the garden is more comprehensive and accurate.

The invention provides a saline-alkali soil crop multi-water-source irrigation control method and system, and belongs to the technical field of agriculture, and the method comprises the steps: determining an irrigation water salinity target threshold value and a target total irrigation amount according to soil salinity data and crop physiological parameters; determining a water distribution strategy based on the salinity concentration data, wherein the water distribution strategy at least comprises irrigation priorities and collocation of different types of water sources; based on the target irrigation total amount, the irrigation water salinity target threshold value and the water distribution strategy, the target water taking amount of each type of water source is determined; and generating an irrigation control instruction according to the target water intake amount. According to soil salinity, crop types, crop physiological parameters and salinity concentration of multiple water sources, the irrigation water salinity target threshold value and the irrigation water total amount are dynamically and accurately determined; and meanwhile, a priority water distribution strategy is formulated, so that flexible allocation of irrigation among multiple water sources and fine management of the salinity concentration of crop irrigation water can be realized, and soil salinization and crop salinity stress are effectively avoided.

The invention relates to the technical field of edge calculation, in particular to a precise irrigation system and method based on a plant growth model and edge calculation, and the system comprises an environment perception fusion module, a growth state matching module, an edge water volume calculation module, an equipment instruction issuing module and a feedback cycle recognition module. According to the invention, continuous detection and unified processing are carried out on environmental data through edge nodes, data integrity and space mapping efficiency are improved, moisture absorption capability and root distribution are matched according to crop growth stage parameters, an area to be irrigated is accurately calibrated, and target water volume calculation is locally completed in combination with a real-time soil state. A time and flow matching structure is constructed, pertinence of irrigation control is improved, control instructions are executed through distributed control equipment, response behaviors are recorded, equipment state traceability is achieved, continuous feedback recognition is conducted on soil moisture changes after irrigation, dynamic adjustment of a closed loop is promoted, the system response speed and irrigation precision are improved, and the risk of resource waste is reduced.

The invention belongs to the technical field of crop irrigation control, and particularly discloses a multi-modal water-saving sprinkling irrigation system based on the Internet of Things, which comprises a data acquisition module, a stress analysis module connected with the data acquisition module, a sprinkling irrigation control module connected with the stress analysis module and a fault processing module connected with the sprinkling irrigation control module, the embedded stem micro-change sensor and the thermal infrared imager are cooperated to monitor the physiological dynamic state of crops in a multi-mode manner, the occurrence of water stress can be accurately identified in an early stage, a capillary pulse spray irrigation mode is automatically started when the water stress is identified, and on-demand, accurate, small-flow and high-frequency water supply is realized; the timeliness and physiological suitability of irrigation response are remarkably improved, the appropriate water potential of the root zone can be effectively maintained, efficient absorption and utilization of water are promoted, waste of water resources is reduced, and meanwhile normal physiological metabolism of crops is guaranteed.