233 results about "Soil temperature" patented technology

The invention discloses a buried pipe heat pump system optimization method and device, electronic equipment and a storage medium. The method comprises the steps of obtaining soil temperature data of a current buried pipe heat pump system in an operation cycle; dynamically correcting the heat exchange capacity of the current buried pipe heat pump system according to the soil temperature data to obtain actual heat exchange capacity data; the buried pipe distribution of the current buried pipe heat pump system is optimized and adjusted based on the actual heat exchange capacity data until a target buried pipe layout scheme capable of meeting the real-time heat exchange requirement is obtained; real environment parameter support is provided for dynamically correcting the heat exchange capacity by obtaining soil temperature data of an operation cycle; actual heat exchange capacity data are obtained through correction, and the problem that traditional fixed value evaluation is inaccurate is solved; and then the distribution of the buried pipes is optimized on the basis of the actual heat exchange capacity, so that the layout is accurately matched with the real-time heat exchange requirement, and finally the heat exchange efficiency of the system and the dynamic adaptability to the real-time requirement are improved.

The invention discloses a frozen soil temperature feature recognition algorithm and a moisture and electric field state prediction model, and the method comprises the steps: synchronously collecting temperature, moisture, resistivity and meteorological data through arranging a multi-depth sensor array, and constructing a multi-source data set with time-space alignment; utilizing continuous wavelet transform and cross-modal coherence analysis, and combining a hidden semi-Markov model to extract a depth-periodic characteristic profile; a time domain fusion Transform model embedded with physical constraints is adopted to realize frozen soil multi-parameter physical consistency prediction and uncertainty quantification; and finally, outputting a prediction result through a visual interface and setting an automatic alarm. The problem of cycle identification caused by weak and non-stable deep frozen soil signals is solved, the prediction accuracy and the physical rationality are remarkably improved, an end-to-end solution from data quality control to early warning is formed, and the reliability and the practicability of frozen soil engineering monitoring are greatly enhanced.

The invention discloses a dynamic prediction method for a deformation joint of an underground comprehensive pipe gallery. The method comprises the following steps: S1, collecting and fusing multi-source monitoring data; s2, data preprocessing and feature engineering; s3, constructing a dynamic prediction model; s4, dynamic prediction and performance evaluation; s5, early warning and decision support are carried out, in the step S1, temperature field data including the air temperature in the pipe gallery, the concrete temperature (inner and outer surfaces) of the pipe gallery structure and the soil temperature outside the pipe gallery are acquired, and the measuring range ranges from-40 DEG C to 80 DEG C; according to the method, a multi-source monitoring data acquisition and dynamic prediction model system is established, continuous monitoring and trend prediction of the deformation joint of the underground comprehensive pipe gallery are achieved, multi-dimensional data such as the temperature field, the soil pressure and the underground water level are integrated, time sequence analysis is combined, and the deformation joint of the underground comprehensive pipe gallery is obtained. The development rule of the deformation joint can be accurately captured, and a prospective evaluation basis is provided for the safety of a pipe gallery structure.

The invention discloses an optimization method of a ground source heat pump, electronic equipment and a program product, and the method comprises the steps: collecting the operation data and environment data of a ground source heat pump system in real time through an edge computing gateway deployed on site; constructing a multi-objective optimization model of the ground source heat pump system on the cloud server; solving the optimization model by adopting a self-adaptive multi-target genetic algorithm, and outputting a Pareto optimal solution set; selecting a final execution scheme from the Pareto optimal solution set according to a preset decision preference weight, generating a control instruction, and issuing the control instruction to the field executor through the edge computing gateway; the soil temperature field evolution is predicted through the buried pipe heat transfer model, and a prediction result is fed back to the optimization model and used for correcting the soil heat balance objective function, and long-term dynamic optimization is achieved. According to the method, collaborative optimization of economy, environmental protection and sustainability can be realized by constructing the multi-objective optimization model fusing the operation cost, the soil heat balance and the carbon emission.

The invention discloses a grounding resistance thermal-electric coupling prediction method and system suitable for various soil scenes. The method comprises the following steps: acquiring an electrode parameter, a soil parameter, a grounding fault parameter and initial temperatures of an electrode and soil; calculating an electrode current and a soil leakage current of the time step based on the electrode and soil resistivity of the time step; based on the electrode current and the soil leakage current of the time step, calculating the electrode temperature, the soil radial temperature distribution and the grounding potential rise of the time step by adopting a finite difference method; based on the electrode temperature and soil radial temperature distribution of the time step, updating the electrode resistivity and the soil resistivity of the time step + 1; if the end of the fault time is not reached, returning to continuously calculate the temperature of the electrode and the soil at the time step + 1; otherwise, outputting the electrode temperature and soil radial temperature distribution of each time step. According to the invention, thermal-electric dynamic coupling is considered, and accurate evaluation of the performance of the grounding system is realized.

The invention relates to the technical field of environmental remediation, in particular to an in-situ soil perfluorinated compound remediation method and system.The method comprises the following steps that electrochemical targeted enrichment is conducted, applying a pulse type direct-current electric field to the anode and the cathode to drive anionic PFAS in the soil to migrate and enrich towards an anode area; in the anode area, the temperature of anode soil is increased, composite peroxide and a chemical activator are continuously injected, and perfluorinated compounds enriched in the anode are oxidized and degraded; and microbial polishing and ecological restoration: stopping the electric field, carrying out post-treatment on the anode region, adding a microbial agent and a nutritional agent into the anode region, and carrying out biodegradation on residual perfluorinated compounds or degradation intermediate products thereof. Through systematic design of physical field guidance, targeted energy injection, multiple catalytic oxidation and ecological function reconstruction, in-situ soil treatment is achieved, and the core problem in PFAS in-situ remediation is precisely solved.

The embodiment of the invention discloses a soil nutrient classification method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring soil attribute information of a target area within a preset duration; the soil attribute information comprises soil conductivity, soil temperature and spectral reflectivity; performing data preprocessing on the soil attribute information to obtain preprocessed multi-channel time sequence data; performing feature extraction and fusion on the multi-channel time sequence data based on a target feature extraction model to obtain hidden state features; the target feature extraction model is obtained by performing semi-supervised mutual learning on a preset feature extraction model by using different enhanced samples obtained by performing different data enhancement processing on unlabeled samples; and determining a soil nutrient classification result of the target region based on the target classification model and the hidden state features. Through the technical scheme of the embodiment of the invention, the soil nutrients can be accurately and conveniently analyzed, and efficient soil nutrient classification in a few-sample environment is realized.

The invention provides a cold region greenhouse irrigation method and system, and belongs to the technical field of environment control. The method comprises the steps that soil temperature data and humidity data of different depths in all partitions of a greenhouse are acquired in real time; carrying out preprocessing and spatial-temporal feature enhancement on the collected data, inputting the data into a soil temperature-humidity dynamic coupling monitoring model, and calculating to obtain a root retting risk index of the current soil environment; if the root retting risk index exceeds a dynamic risk threshold, generating an irrigation strategy for inhibiting the root retting risk; if the root retting risk index does not exceed a dynamic risk threshold, generating a conventional irrigation strategy based on a multi-objective optimization algorithm; according to the generated irrigation strategy, driving the irrigation execution mechanism of the corresponding subarea to perform independent action, and realizing subarea accurate irrigation; the problem of root retting caused by low temperature and high humidity in a cold region greenhouse environment is solved, and precision, intelligence and high efficiency of irrigation management are achieved.

The application relates to the technical field of building construction, in particular to a building foundation construction method based on digital twinning, which comprises the following steps: constructing a digital twin based on BIM technology; collecting the stress of a supporting structure and the soil temperature at a preset detection frequency during the overwintering period of a foundation pit, and synchronizing the stress and the soil temperature to the digital twin; calculating a freeze-thaw damage characteristic value of the supporting structure according to the area of a hysteresis loop surrounded by a stress-temperature curve in a preset temperature period, and determining the construction risk grade of the deep foundation pit according to the freeze-thaw damage characteristic value; when the construction risk grade is determined as the third type, collecting the displacement of the supporting structure at a key depth, obtaining a deformation recovery characteristic value, determining an adjustment strategy when the deformation recovery characteristic value does not meet the requirements, feeding back the adjustment strategy to a physical construction site for execution, and recording the data and the treatment result of this time to a case library to optimize the digital twin model. The application improves the intelligent level of building foundation construction.

The invention relates to the technical field of corrosion tests, in particular to a deep soil environment simulation corrosion test device and method.The deep soil environment simulation corrosion test device comprises a test box, a plurality of opening air channels vertically distributed in soil in a penetrating mode and a heating unit composed of a circumferential heating part and an internal heating part vertically inserted into the soil. Gas is directly introduced into the soil through the perforated gas channel to adjust the oxygen content, the humidity and the chemical environment, the soil temperature is cooperatively adjusted through the heating unit, and dynamic closed-loop control is carried out based on feedback of the sensor. The environment regulation and control actuator is directly implanted into the soil, so that the problems of slow response, large gradient and incapability of simulating the deep low-oxygen compact soil environment caused by external regulation and control in the traditional method are solved, and accurate, rapid and uniform simulation and accelerated experiment on the deep soil corrosion environment are realized.

The invention provides a simulation method and system for a solar ground source heat pump system, and relates to the technical field of solar ground source heat pump system simulation, and the method comprises the steps: firstly obtaining a soil initial temperature field, and calculating the soil temperature cumulative variation in a future time period through a one-dimensional radial simplified heat transfer model in combination with a predicted load; defining as a soil thermal imbalance risk index; according to comparison between the index and a preset threshold value, selecting an efficiency priority strategy with solar energy immediate utilization as priority or a heat balance priority strategy with soil temperature field adjustment as priority; linkage rules of all subsystems are determined according to a selected strategy, the net heat exchange amount of a geographical pipe heat exchanger and the net heat storage / release amount of a heat storage device are calculated by jointly solving a dynamic model, and then the soil temperature field and the state of the heat storage device are updated; and the simulation step length is iteratively propelled until the period is ended, and finally, the system energy efficiency coefficient, the soil heat balance degree and the time-varying curve of the key parameters are output.

The utility model relates to the technical field of soil detection, and discloses a direct insertion type soil nutrient detector which comprises an upper shell and a lower shell, the upper shell is fixedly connected with the lower shell, and the bottom of the lower shell is fixedly connected with a guide head; the display assembly is mounted on the upper shell; the detection probe is installed in the lower shell, a light emitting diode is fixed to the detection probe and used for emitting near-infrared light with the specific wavelength to soil, the photodiode is used for receiving the near-infrared light reflected by the soil and converting the near-infrared light into an electric signal, and the temperature sensor is used for monitoring the soil temperature in real time; the optical glass is fixedly connected with the detection probe, covers the outer sides of the light emitting diode, the photodiode and the temperature sensor, and is in direct contact with soil; and the mainboard is arranged in the clamping groove of the lower shell. The rapid and accurate detection of the contents of nitrogen, phosphorus, potassium and organic matters in the soil can be realized.

The application discloses a self-powered temperature sensor based on thermoelectric effect and a preparation method and application thereof, and aims to provide a temperature sensor based on high-performance bismuth telluride-based thin film thermoelectric material, which has high sensitivity and strong flexibility, and a preparation method and application thereof in monitoring soil temperature of a greenhouse. The temperature sensor comprises a thermoelectric module, the thermoelectric module comprises a base plate, the base plate is provided with N-type bismuth telluride thin films and P-type antimony telluride thin films which are distributed in a scattering mode, the N-type bismuth telluride thin films and the P-type antimony telluride thin films are arranged at intervals, the N-type bismuth telluride thin films and the P-type antimony telluride thin films are integrated into multiple pairs of P-N junction thermoelectric legs by being connected in series through thin film electrodes, a center hollow hole is arranged on an inner ring formed by the thin film electrodes on the base plate, the hollow position at the center hollow hole and the thin film electrodes of the inner ring are encapsulated by high-thermal-conductivity material, and a thermal-conductivity encapsulation layer is formed in a middle region. The sensor has high sensitivity, strong flexibility and the ability of accurate monitoring.

The invention relates to application of a dazomet liquid preparation in soil treatment in the field of pesticides. The liquid preparation can be used for preventing and treating true and bacterial diseases, nematodes and weeds of crops, and has a remarkable synergistic effect on soil-borne bacteria, fungal diseases, root-knot nematodes and field weeds. The pesticide application mode can be selected from one or more of drip irrigation, flushing application, mist spraying and soil layer treatment, and the pesticide can be directly used or used after being diluted for multiple times during pesticide application. Besides, the core advantage of the application is that the application limitation of the traditional dazomet preparation is broken through, and the dazomet preparation is suitable for wide regions, especially suitable for low-temperature regions and environments with the soil temperature being lower than 10 DEG C, and is especially preferably applied to rice seedling raising fields in low-temperature regions; multiple operation modes such as soil mixing, pulping and rice hull mixing can be adopted in a low-temperature scene, the operation is convenient and fast, the actual field requirements are met, and the environmental adaptability and the application flexibility of the dazomet preparation are remarkably improved.

The invention relates to the technical field of meteorological short-term climate prediction, and discloses a temperature prediction method based on hybrid space-time neural network and multi-scale feature fusion. The method comprises the following steps: acquiring a historical temperature data sequence and a multi-source meteorological data sequence, wherein the multi-source meteorological data sequence comprises wind speed data, soil temperature data, snow cover data and sea temperature data; strict time sequence feature extraction is conducted on the historical temperature data sequence, a temperature short-term fluctuation feature set and a temperature long-term trend feature set are obtained, and it is ensured that only historical information is used without data leakage through strict time sequence feature extraction; and on the basis of the multi-source meteorological data sequence, the temperature short-term fluctuation feature group and the temperature long-term trend feature group, predicating through an improved LSTM neural network to obtain predicated temperature data of a preset number of days in the future. The accuracy of temperature prediction is improved by constructing a temperature short-term fluctuation feature group and a temperature long-term trend feature group during temperature prediction.

The application discloses a kind of tread-resistant organic covering garden roads and its manufacturing method, by composite organic covering layer, leveling layer, cushion layer, waterproof layer, waterproof protective layer and drainage ditch composition;The prepared organic covering garden road has higher compactness and tread-resistant ability, increases the mildew-proof, fireproof, windproof ability of organic covering garden road, greatly improves the service life and safety of organic covering garden road, also has the effect of keeping moisture, adsorbing dust, adjusting soil temperature, increasing soil fertility, inhibiting weeds, promoting planting growth, reducing soil erosion and decoration beauty etc.

The utility model relates to the field of infrared detection systems, in particular to an infrared detection system with stable moving performance, which comprises a bottom plate. A moving mechanism is placed at the upper end of the bottom plate, and a vertical frame is fixedly connected to the upper end of the moving mechanism. According to the device, the first motor is started to enable one first roller to rotate, the moving mechanism can move along the guide mechanism, then the angle adjusting mechanism is started to adjust the angle of the infrared thermal imaging machine, the infrared thermal imaging machine is started to collect the soil temperature change at the damaged position of the HDPE film, and the damage degree of the HDPE film is improved. When the low-electric-quantity detection warning mechanism detects that the electric power of the storage battery is insufficient, the low-electric-quantity detection warning mechanism gives an alarm, a user can conveniently recall the storage battery, intelligent inspection is achieved, and the problems that in the prior art, when an infrared detection system is used, intelligent inspection is usually difficult, the detection efficiency cannot be improved, and the detection cost is high are solved. And the soil temperature change at the damaged part of the HDPE film is difficult to collect in real time.

The invention relates to the technical field of agricultural informatization and intelligent monitoring, in particular to agricultural environment all-in-one sensor equipment capable of wirelessly transmitting data, which comprises a fixed seat, two rotating rods are rotatably connected to the fixed seat through bearings, and two ends of the two rotating rods extend out of the fixed seat and are fixedly connected with a fixed frame. Walking wheels are fixedly installed on the fixing frame, soil temperature and humidity sensing assemblies are fixedly installed on the outer side walls of the walking wheels, a driving assembly is arranged between the fixing base and the rotating rod, autonomous movement of the equipment in a field and a greenhouse is achieved through the walking wheels, and large-range inspection and fixed-point accurate detection can be flexibly completed; three core parameter data of air temperature and humidity, concentration and illumination intensity can be collected during inspection, two core parameter data of soil temperature and humidity and pH value can be collected at a fixed position, and a field environment or a greenhouse environment can be adjusted in a targeted manner according to the data, so that the field environment or the greenhouse environment is adapted to growth of agricultural plants.

The invention discloses a ground source heat pump heat exchanger coupling performance simulation algorithm based on an unsteady-state numerical model, and the algorithm comprises the following steps: S100, designing a triple iteration algorithm, and achieving the simulation of receiving the load of a heat exchanger and calculating the on-way temperature and the pipe wall temperature of a fluid at each time step; step S200, designing a quadruple iterative algorithm to realize simulation of receiving heat pump load, calculating fluid on-way temperature and pipe wall temperature, and calculating backfill and rock-soil temperature; according to the method, the assumption of steady-state heat transfer in the hole is abandoned, and the unstable-state heat transfer models are established in fluid, pipe walls, backfill materials in the hole and rock soil areas outside the hole, so that the method is more in line with physical practical conditions and can accurately accord with measured values even in 30s-level short-time-step simulation.

The invention discloses a cultivated land health state monitoring and evaluating device and method.The cultivated land health state monitoring and evaluating device comprises a machine body, a central information processing module is integrated in the machine body, and an energy supply module, a cultivated land soil monitoring module and a meteorological monitoring module are connected to the exterior of the machine body; the energy supply module is used for providing energy for the whole device, and the cultivated land soil monitoring module comprises a cultivated land soil temperature monitoring module, a cultivated land soil humidity monitoring module, a cultivated land soil PH value monitoring module and a cultivated land soil tension monitoring module. The cultivated land soil monitoring module is used for monitoring and feeding back all data of soil; the meteorological monitoring module comprises an air temperature monitoring module, an illumination duration monitoring module, a precipitation monitoring module and a wind speed and wind direction monitoring module. The meteorological monitoring module is used for monitoring meteorological data and feeding the meteorological data back to the terminal. The cultivated land soil monitoring module and the meteorological monitoring module transmit monitoring data to the central information processing module.

This invention provides a multi-algorithm fusion method for temperature control of vegetated soil in complex disturbance scenarios in high-altitude and cold regions, belonging to the field of intelligent temperature control technology. The method includes: S1: collecting multi-source environmental data and obtaining soil suitability parameters; S2: preprocessing the slope of the target area and deploying intelligent temperature control core components; S3: determining the benchmark value and dynamic adjustment range of the core temperature control index based on multi-source environmental data and soil suitability parameters; S4: constructing a fusion algorithm model and designing a deep interactive fusion mechanism; S5: training the fusion algorithm model, optimizing the algorithm parameters, and then adjusting the algorithm interaction parameters through overall testing to complete model optimization; S6: performing temperature control based on the optimized fusion algorithm model. This invention solves the problems of low temperature control accuracy, poor stability, and high energy consumption caused by multi-source disturbances, insufficient prediction, response lag, and parameter solidification in the process of temperature control of vegetated soil in high-altitude and cold regions.

This invention relates to the field of soil slope monitoring technology, specifically to a method for monitoring cavitation erosion in dispersed soil slopes. The method involves acquiring soil moisture, soil temperature, air temperature, air humidity, current rainfall, slope runoff velocity, and images of the soil slope surface and surface water for a target dispersed soil slope. Based on these data, the method determines the rainfall erosion index and soil cavitation sensitivity index for the target dispersed soil slope. Finally, based on these indices, the method determines the risk level of cavitation erosion development for the target dispersed soil slope. This comprehensive and dynamic assessment of cavitation erosion in dispersed soil slopes improves the targeting and timeliness of slope disaster identification and diagnosis, thereby reducing slope disaster risks.

The application discloses a smart garden-oriented multi-element data sensing terminal device system and processing method. The system is composed of a central server and a group of terminal devices, and the terminal device contains four functional modules, namely, a data capture and image acquisition module, a central control and operation module, a wireless communication module and an independent power supply module. The method collects characteristic data such as soil temperature and humidity locally through sensors. Among them, the soil oxidation-reduction potential sensor adopts a molybdenum electrode to avoid the production of an oxidation film on the electrode surface and the adsorption of other impurities. The central server decides to initiate a federal learning task. Model training invitations are sent to each sensor. The sensor receives the model training information from the central server and decides whether to accept and feedback. After receiving the feedback, the central server distributes the training model to the sensors that agree to participate in the training, and performs the federal learning training process. The application significantly improves the accuracy of soil oxidation-reduction potential measurement and the durability of the electrode.

The application discloses a remote monitoring system based on intelligent agriculture, and relates to the field of intelligent agriculture.The remote monitoring system based on intelligent agriculture comprises a sliding support and a lifting hydraulic cylinder, the bottom of the lifting hydraulic cylinder is provided with a soil temperature and humidity detection probe, the top of the lifting hydraulic cylinder is provided with a self-starting equipment box, the self-starting equipment box comprises a box body and a sliding frame, the inside of the sliding frame is provided with a turnover support, and an air temperature and humidity detection probe and an illumination intensity sensor are fixedly installed in the middle of the two turnover supports respectively.The remote monitoring system based on intelligent agriculture can realize that the soil temperature and humidity detection probe, the air temperature and humidity detection probe and the illumination intensity sensor in the collected state can automatically extend to detect, and can realize automatic resetting and storage after use, so that the equipment is prevented from being damaged due to accidental touch during ploughing and picking, the equipment is prevented from being corroded by watering and soil, and the service life is prolonged.

The invention relates to the technical field of data processing, and discloses a drip irrigation cotton field water, fertilizer and salt migration monitoring method and system based on an intelligent sensor, the water content, conductivity, temperature and drip irrigation flow data of soil are collected in real time through the sensor, and the temperature data is the soil temperature of each soil layer node; cleaning the collected original data, removing abnormal values, complementing missing values, and extracting time features and spatial features through space-time standardization; carrying out feature fusion on the preprocessed data by adopting a Transform model to generate migration features; inputting the migration features into a random forest model, and outputting a monitoring result; according to the method, the time-space relevance of the data is enhanced through the Transform model, the matching precision of the data after migration and the actual soil sampling value is improved, the problem of information loss in migration is solved, dynamic monitoring is achieved, migration rule prediction is optimized, and a basis is provided for precise irrigation and fertilization.

This invention provides a method and system for calculating the liquid water content of permafrost in highland soil. [Solution] The method includes: step S1 acquiring a soil temperature and humidity observation network dataset from the central part of the plateau; step S2 performing texture classification on the soil to obtain soil texture classification results; step S3 combining the soil texture classification results and the soil temperature and humidity observation network dataset to fit the relationship between solid water content and soil temperature for soils with different textures; step S4 determining a formula for calculating the liquid water content of the soil based on the relationship between solid water content and soil temperature; step S5 improving the VIC model based on the formula for calculating the liquid water content; and step S6 calculating the liquid water content of the plateau permafrost using the improved VIC model.

The application discloses a kind of film mulching soil surface layer temperature calculation method.The method comprises the following steps:1, collecting historical meteorological data;2, calculate the soil surface layer temperature of non-mulching film using historical meteorological data;3, calculate the soil surface layer temperature of mulching film using the soil surface layer temperature of non-mulching film.The film mulching soil temperature calculation method provided by the application provides a strong guarantee for accurate estimation of film mulching planting agriculture, more accurately simulates crop planting information and greenhouse gas emissions, and has great agricultural ecological application value.

The invention discloses a photovoltaic vegetation light-supplementing sprinkling irrigation control system for a stony desertification mountain land, and relates to the technical field of agricultural Internet of Things and ecological environment regulation and control. According to the system, vegetation units under a photovoltaic array are finely divided, and an underground root system imaging technology and multi-dimensional root system structure analysis are combined; precise measurement of key parameters such as the horizontal extension length of the sea-buckthorn vegetation root system, the rhizosphere connectivity, the complexity of a fine root net structure, the capillary water effect and the like is achieved, and the transpiration potential and the water supply condition of the vegetation are comprehensively reflected. The first priority regulation and control area and the second priority regulation and control area are scientifically identified by constructing the transpiration cooperation index and combining the local air humidity, the soil temperature and the photovoltaic shielding intensity which are collected in real time, it is ensured that light supplementing spray irrigation regulation and control are accurately focused on the area with the high transpiration capacity and obvious water stress, and the water resource utilization efficiency and the light supplementing effect are greatly improved. Meanwhile, by dynamically matching the sprinkling irrigation time period and the photovoltaic shielding intensity, collaborative optimization of sprinkling irrigation and light supplement is achieved.

This invention relates to the field of intelligent agriculture technology and discloses a method and system for multi-factor synergistic optimization of the strawberry rhizosphere microenvironment. The system includes: a data acquisition module, a data processing module, a correlation analysis module, a strategy generation module, a regulation execution module, a feedback collection module, and an optimization module. By deploying a multi-factor data acquisition mechanism, it collects multi-factor data, including light intensity and soil temperature, in real time. It then uses machine learning algorithms to perform multi-factor correlation analysis, identifying the interactions between key factors. This allows for real-time detection of the coupling effect between light intensity and soil temperature, avoiding light-temperature imbalance, ensuring the stability of strawberry root metabolic activities, and reducing growth and development fluctuations caused by abnormal factor synergy. By constructing a multi-factor synergistic optimization objective function to generate an optimization strategy, it can determine in real time whether the matching degree of water-nutrient synergistic regulation is abnormal, avoiding low rhizosphere water and fertilizer transport efficiency.

The present application relates to the field of agricultural engineering, and discloses a self-adaptive water supply system for corn greenhouse planting, which comprises an environment monitoring module for monitoring air temperature, air humidity, light intensity and concentration in the greenhouse; a growth monitoring module for monitoring corn leaf surface temperature and plant height; a soil monitoring module for monitoring soil temperature, soil moisture content and soil water potential; a root system analysis module for monitoring corn root system distribution depth and root system vigor index; and a control module connected with the environment monitoring module, the crop growth monitoring module, the soil monitoring module and the root system analysis module, for calculating irrigation water requirement according to the corn growth stage, soil moisture condition and root system distribution depth. The present application monitors corn root system distribution depth in real time through the root system analysis module, and introduces a root depth correction coefficient when calculating irrigation water requirement, so as to match water supply with the actual distribution area of root system, thereby improving water use efficiency.