504 results about "Soil temperature" patented technology

The invention discloses a farmland soil quality dynamic diagnosis method based on multi-source remote sensing collaborative inversion, and relates to the technical field of agricultural information, and the method comprises the steps: collecting physical and chemical parameters of soil temperature, humidity, pH value, organic matter content, nitrogen phosphorus and potassium concentration and the like in real time through a multi-source sensor network; removing abnormal values by using a data preprocessing algorithm, performing standardization processing, generating a standardized soil parameter set for subsequent climate and management factor correlation analysis, automatically generating a risk early warning signal, pushing the risk early warning signal to an agricultural management decision platform, and completing full-process analysis from data acquisition to decision support; the farmland soil quality dynamic diagnosis method based on multi-source remote sensing collaborative inversion can provide a scientific basis for agricultural management decision, effectively guide farmland management practice, and improve soil quality and agricultural production efficiency.

The invention discloses a mine reclamation effect evaluation method based on a multi-temporal remote sensing image, and belongs to the field of mine reclamation effect evaluation, and the method comprises the steps: obtaining and preprocessing multi-source remote sensing data, and obtaining a standardized multi-temporal data set; performing image registration and radiation correction on the standardized multi-temporal data set to obtain a correction data set with consistent space and consistent radiation; constructing a multi-dimensional feature data set based on the correction data set, wherein the multi-dimensional feature data set comprises surface morphological features, vegetation health features, soil temperature features and underground water level change features; extracting a surface form feature vector according to the multi-dimensional feature data set, and generating a vegetation health distribution map, a soil temperature feature map and an underground water level change distribution map; and fusing the surface form feature vector, the vegetation health distribution map, the soil temperature feature map and the underground water level change distribution map, constructing a comprehensive index system, and outputting a mine reclamation effect evaluation result. According to the method, the accuracy and comprehensiveness of reclamation effect evaluation are remarkably improved.

An unmanned aerial vehicle (UAV) agent for forming a two-tier hybrid smart agriculture network architecture is provided. The UAV agent is configured to support two communication protocols, a short-range communication protocol and a long-range communication protocol. The agriculture sensor gathers agriculture data such as soil temperature and participates in a first-tier short range wireless communication network to send the collected data to at least one UAV agent. A UAV agent participates in one or more first-tier short-range communication networks to pick up sensor data from agriculture sensors in one or more clusters and also participates in a second-tier long-range communication network to route the collected sensor data to at least one cloud server. The tasks in both tier networks are formulated as optimization problems to achieve optimal data delivery and solved by using multi-agent reinforcement learning (MARL), which is implemented by the invented Focus Coordination Multi-Agent Deep Deterministic Policy Gradient (FC-MADDPG) algorithm.

The invention relates to the technical field of agriculture, and discloses an intelligent fertilization technical measure and method for improving the fertilizer utilization rate, and the intelligent fertilization technical measure comprises a soil sensor module which is used for monitoring various parameters of soil in real time, including but not limited to soil nutrient content, soil humidity, soil acidity and alkalinity, soil temperature and soil texture; the soil sensor module can collect monitored parameter data with high precision and high frequency, and transmit the data to the central control unit through the wireless communication module; the fertilizer storage and conveying module is internally provided with a plurality of independent fertilizer storage bins, and each storage bin can store different types of fertilizers. According to the present invention, the type, the use amount and the application time of the fertilizer can be precisely controlled according to the growth requirements of different crops and the soil state through the precise fertilization mode so as to ensure the efficient absorption of the fertilizer by the crops, such that the fertilizer utilization rate is significantly improved, and compared with the traditional fertilization mode, the fertilizer waste can be reduced, and the agricultural production cost can be reduced.

The invention discloses a landscaping maintenance monitoring and early warning system, and belongs to the technical field of landscaping maintenance monitoring. Comprising a distributed sensor network, an edge computing processing unit, a cloud intelligent decision center and an intelligent execution terminal, the distributed sensing network comprises a soil sensor array which is deployed according to an elastic density grid and is used for dynamically adjusting the distance between sensors according to a plant value coefficient and monitoring the temperature, the humidity, the pH value and the ion concentration of soil in real time; and the autonomous mobile inspection robot carrying a multispectral imaging module executes dynamic path planning based on the abnormal probability thermodynamic diagram.

The invention discloses an alpine grassland no-tillage restoration suitability evaluation method based on a 3S technology, and particularly relates to the technical field of data processing. Through the combination of multi-temporal satellite images and global positioning system data, the spatial dynamic change of the frozen soil layer of the alpine grassland and the long-term influence of the spatial dynamic change on vegetation growth are accurately obtained, and a frozen soil layer depth and distribution dynamic monitoring model is constructed based on multi-source remote sensing data and historical weather and soil temperature and humidity data. Analyzing the influence of freezing and thawing alternation on plant root growth; establishing a vegetation recovery potential index and a soil moisture supply index by combining the vegetation coverage and the dynamic change of the frozen soil layer, and generating a suitability partition map through a GIS spatial analysis and analytic hierarchy process; through field sampling and long-term vegetation growth monitoring data verification and model optimization, the accuracy of no-tillage restoration suitability evaluation is remarkably improved, and scientific and accurate decision support is provided for ecological restoration of alpine grassland.

The invention relates to the field of new-generation information technology and civil engineering, in particular to a frost heaving prevention technology of a roadbed in a seasonal frozen area, and particularly relates to a solar heating frost heaving prevention drainage roadbed in the seasonal frozen area and a construction method of the solar heating frost heaving prevention drainage roadbed. The method comprises the steps that environment sunlight data are obtained based on a solar heat collection device, heat energy is stored through an efficient heat storage material, and a heat energy output sequence is generated; acquiring soil temperature, humidity and frost heaving stress data from an environment sensor, predicting a frost heaving trend in combination with historical frost heaving characteristics, and generating regulation and control parameters; the heat energy output sequence and the frost heaving regulation and control parameters are input into a dynamic temperature control and drainage linkage module, heat distribution and optimization adjustment of a drainage path are carried out, and a linkage control strategy is generated; and performing feedback analysis on the operation condition of each module based on the data, and optimizing the control parameters of the dynamic temperature control and drainage linkage module. The temperature and humidity of the roadbed can be accurately adjusted, the frost heaving phenomenon is prevented, and roadbed drainage is optimized.

The invention discloses a tower grounding grid multi-frequency composite wave electric field imaging and soil environment medium diagnosis method, which comprises the following steps of: generating a composite excitation signal through superposition of a low-frequency sine wave and a high-frequency CHIRP square wave, and collecting multi-dimensional data such as voltage / current response, soil temperature and humidity, electric field intensity and the like in combination with a distributed sensor array; separating signal features by using wavelet transform and extracting impedance information of a target frequency point; a multi-grid homotopy algorithm is adopted to realize grounding grid three-dimensional resistivity distribution reconstruction, corrosion spots and abnormal areas are marked, and high-precision positioning of underground conductors is completed through UWB radar or a capacitance detector; meanwhile, based on the information entropy maximization optimization frequency band combination, the grounding grid state is comprehensively evaluated in combination with a multi-parameter fusion model. The method has the non-contact patrol capability, the unmanned aerial vehicle carries equipment to scan the grounding grid, the detection efficiency and convenience are remarkably improved, and an efficient and accurate solution is provided for guaranteeing safe operation of the power grid.

The invention discloses a rock-soil temperature field rapid solving method suitable for a ground source heat pump system, and the method comprises the steps: firstly building a three-dimensional unsteady-state heat transfer model in consideration of a buried pipe coaxial structure, a porous arrangement form and the characteristics of a multilayer heterogeneous soil body in the ground source heat pump system; then simulating a thermal response process by using the model, constructing a multi-domain coupled thermal conduction augmentation matrix, performing POD on the matrix, extracting a dominant mode function of a temperature field, and constructing a low-dimensional POD-based mode space; and finally, constructing a POD-Galerkin low-order model, simulating a buried pipe group soil temperature field, performing inversion of a heat source function, and outputting stratum thermophysical parameters. According to the method, the calculation efficiency and the simulation precision of the porous coupling and long-period unsteady state heat transfer process are remarkably improved, the problem that traditional finite element and finite difference methods are high in time consumption in porous strong coupling modeling is solved, and rapid prediction of the soil temperature and robust recognition of the heat source function under a complex stratum and a heat exchange structure can be achieved.

The invention provides a temperature control type anti-frost-heaving retaining wall structure and a design method thereof, and belongs to the technical field of infrastructure retaining engineering in cold regions, the temperature control type anti-frost-heaving retaining wall structure comprises a retaining wall body, a ground temperature energy conversion system and an intelligent control system, and the ground temperature energy conversion system is connected with the retaining wall body; the ground temperature energy conversion system is used for absorbing ground temperature energy, converting a gas-state heating medium from a low-pressure state into a high-pressure state, adjusting the flow of a liquid-state heating medium, reducing the pressure of the heating medium and dissipating the ground temperature energy into the retaining wall body, and the intelligent control system is electrically connected with the ground temperature energy conversion system; the controller is used for monitoring the temperature of filling soil on one side of the retaining wall body and controlling the ground temperature energy conversion system to operate according to the filling soil temperature so as to control the retaining wall body temperature and filling soil heat. The technical problems that the retaining wall frost heaving disease control difficulty is large, and the frost damage prevention and control effect is poor are solved, and the technical effects that the retaining wall and the filling temperature can be controlled, frost heaving disease control is easy, and the frost damage prevention and control effect is good are achieved.

The invention discloses an ecological restoration area carbon sink increment real-time prediction method and system based on artificial intelligence, and the method comprises the following steps: multi-source data collection: obtaining a monthly vegetation coverage image through a satellite remote sensing platform, collecting the sensor data of soil temperature and humidity, air CO2 concentration and the like through a laid ground sensor network, and carrying out the real-time prediction of the carbon sink increment of an ecological restoration area; adopting an unmanned aerial vehicle laser radar to obtain vegetation canopy point cloud data according to a preset period, and collecting biomass actual measurement data of a restoration area in a historical preset age limit; preprocessing data, performing radiometric calibration, atmospheric correction and cutting splicing on a monthly vegetation coverage image acquired by a satellite remote sensing platform, and extracting a vegetation coverage and vegetation index time sequence; denoising, ground point separation and single tree canopy segmentation are carried out on vegetation canopy point cloud data acquired by the unmanned aerial vehicle laser radar, and the height and crown breadth of single plant vegetation are calculated. According to the invention, carbon sink increment prediction can be realized more accurately.

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 an accounting method for carbon sequestration and emission reduction of soil. The accounting method comprises the following steps: S1, acquiring the average soil temperature # imgabs0 # average soil humidity # imgabs1 # average soil acidity and alkalinity # imgabs2 # average soil microbe number # imgabs3 # average soil microbe activity # imgabs4 # average environment temperature # imgabs5 # average environment humidity # imgabs6 # S2 of selected type soil from a moment t to a moment t + delta t; inputting the average soil temperature # imgabs7 #, the average soil humidity # imgabs8 #, the average soil acidity and alkalinity # imgabs9 #, the average soil microbe number # imgabs10 #, the average soil microbe activity # imgabs11 #, the average environment temperature # imgabs12 #, the average environment humidity # imgabs13 # and the soil type of the selected type of soil into a trained soil carbon sequestration emission reduction amount accounting model; and obtaining the carbon sequestration amount and greenhouse gas emission reduction amount of the selected type of soil. The method can quickly and accurately reflect the actual carbon sequestration and emission reduction conditions of the soil.

The invention relates to the technical field of ground source heat pump operation control, in particular to an optimal adjustment method of a ground source heat pump system, which comprises the following steps: S1, collecting underground soil temperature and system heat load of the ground source heat pump system; s2, calculating a soil heat balance index based on the underground soil temperature; s3, according to the soil heat balance index and the system heat load, the optimized operation mode of the ground source heat pump system is judged; and S4, according to the optimized operation mode judged in the S3, the operation parameters of the ground source heat pump system are adjusted, and a corresponding execution mechanism is driven. According to the method, the operation mode is judged by introducing the soil heat balance index and combining the system heat load, meanwhile, the flow of the circulating water pump, the frequency of the compressor and the opening degree of the heat exchange valve are subjected to interval adjustment, and unification of energy efficiency optimization and long-term balance of the soil heat environment is achieved.

The invention belongs to the technical field of data transmission processing, and discloses a control system and method for intelligent agriculture multilayer soil temperature and humidity sampling. The system comprises a land data acquisition module, an updated data acquisition module, a data set preprocessing module, a soil humidity prediction module, a decision report generation module and a report transmission module, and is characterized in that a land data set is acquired, an updated data set is acquired, the land data set and the updated data set are preprocessed to obtain comprehensive feature data, and the comprehensive feature data are transmitted to the decision report generation module; analyzing the land data set, the update data set and the comprehensive feature data set to obtain a predicted humidity reference value, analyzing the predicted humidity reference value to obtain a soil decision report, processing the soil decision report, and outputting the processed soil decision report to a terminal. The method has the remarkable advantages of high accuracy of sampled soil data, strong auxiliary decision-making capability and good use economic effect.

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 utility model relates to the technical field of soil in-situ detection, and discloses a portable soil quality multi-parameter in-situ detection device. The device mainly comprises a controller, a connecting wire, an optical probe and a sensor. The controller is provided with a touch screen, a single-chip microcomputer circuit board, a single-chip microcomputer, an SD card, a key switch, a wireless communication control panel and a power source, and power source management, detection system control, real-time data processing, man-machine interaction, data storage and remote transmission can be achieved. The sensor comprises a soil temperature probe, a soil humidity probe, a soil conductivity probe and a soil pH probe, and can realize real-time data acquisition of soil temperature and humidity, conductivity and pH value; an annular lamp holder, a light source, a photoelectric sensor, a plano-convex lens, a light shielding plate, a light shielding boss and a light shielding ring are arranged in the optical probe, and rapid collection of soil organic matter spectrum information can be achieved. The soil in-situ detection device realizes synchronous acquisition of multiple parameters of soil, is reasonable in structural design and convenient to operate, and is suitable for popularization and application in the field of soil in-situ detection.

The invention discloses a fruit tree growth environment intelligent regulation and control system and method, and relates to the technical field of monitoring analysis, and the system comprises a temperature control module which comprises an air temperature control unit and a soil temperature control unit, and is used for carrying out the temperature regulation and control of the air temperature and soil temperature in a target region through a preset device according to a preset mode; the humidity regulation and control module is used for dynamically regulating and controlling the humidity in the target area; the energy recovery module is used for recovering heat energy released by the humidity regulation and control module when the dehumidification unit works, and the heat energy acts on the soil temperature control unit or the air temperature control unit through a heat exchange device; the sensor module is used for collecting corresponding environment data and fruit tree data in a target area in real time; and the control module is used for dynamically controlling the temperature control module, the humidity regulation and control module and the energy recovery module according to the corresponding environment data and fruit tree data in the target area output by the sensor module. The method has the effect of improving the regulation and control efficiency.

The application provides a kind of intelligent temperature-regulated planting field soil temperature control system and method, related to soil temperature control technical field, obtains seedling planting field regional information, extracts all soil temperature monitoring sub-block according to seedling planting field regional information;Obtain the block environment data of soil temperature monitoring sub-block, determine soil temperature stress factor according to block environment data, obtain all soil temperature stress risk areas in seedling planting field based on soil temperature stress factor;Obtain the temperature control resource information in seedling planting field, determine resource area mapping matrix through temperature control resource information, determine temperature control response strategy through resource area mapping matrix and soil temperature stress factor;According to the soil temperature regulation of each soil temperature stress risk area according to temperature control response strategy.This application can realize the risk analysis and resource optimization control of soil temperature, to improve the temperature regulation precision and regulation efficiency of nursery stock cultivation environment.

The invention provides a soil moisture content detection method based on unsteady heat conduction and optical fiber temperature measurement, which comprises the following steps: heating a soil body in a target measurement area based on an active heating method, and measuring the temperature value of the soil body at each moment under different radial distances from a heating source in the heating process; substituting the soil body temperature value at any moment in the heating process and the corresponding radial distance into a predetermined soil body moisture content relation model to obtain the soil body moisture content at the position corresponding to the radial distance from the heating source in the target measurement area at the corresponding moment; and determining the soil mass moisture content of the target measurement area according to the soil mass moisture content at each radial distance position from the heating source in the target measurement area at the corresponding moment. According to the method, the relationship between the soil moisture content and the soil temperature value is established, and in-situ monitoring and long-time monitoring of the large-range soil in the target measuring area are achieved through the soil temperature value obtained through the active heating method.

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 a construction method of an underground heat exchange model of a U-shaped middle-deep layer buried pipe. The construction method comprises the steps of collecting monitoring data of underground heat exchange of a preset buried pipe, preprocessing the monitoring data, and constructing a physical model of the underground heat exchange of the U-shaped middle-deep layer buried pipe based on the monitoring data; soil temperature distribution and wall temperature are obtained based on the physical model according to the heat transfer process outside the drill hole, and the water temperature at the next moment is obtained based on an energy equation of circulating fluid according to the heat transfer process inside the drill hole; performing underground temperature field evolution simulation analysis on the basis of the mathematical model of the soil temperature distribution, the wall temperature and the water temperature at the next moment to obtain simulation data, and constructing a U-shaped medium-deep buried pipe underground heat exchange model on the basis of underground temperature field evolution simulation; time sequence deviation analysis is conducted on the simulation data and the monitoring data to obtain time deviation data, the U-shaped middle-deep layer buried pipe underground heat exchange model is optimized according to the time deviation data, and a target model is output.

The invention discloses a dense-phase carbon dioxide pipeline leakage simulation system and method.The experimental device comprises a carbon dioxide injection device, a pressure-bearing container, a pressure-bearing pipeline, a temperature monitoring device and a temperature collecting device, and the carbon dioxide injection device is provided with a fluid outlet used for outputting dense-phase carbon dioxide; the pressure-bearing container is provided with a pressure-bearing cavity used for being filled with soil, the pressure-bearing pipeline is arranged in the pressure-bearing cavity, the pressure-bearing pipeline is connected with the fluid outlet, the pressure-bearing pipeline is provided with a leakage opening, the temperature monitoring device comprises a plurality of temperature sensors, the temperature sensors are arranged in the pressure-bearing cavity at intervals, and the temperature sensors are all electrically connected with the temperature collecting device. And the temperature acquisition device is used for receiving and processing the soil temperature monitored by the temperature sensor. The experimental device provided by the embodiment of the invention can simulate and verify the influence and diffusion rule of dense-phase carbon dioxide pipeline transportation leakage on soil temperature distribution, and provides a theoretical basis for dense-phase carbon dioxide leakage prevention and control and emergency disposal in practical application.

The invention relates to the technical field of agricultural irrigation, in particular to a precision agricultural drip irrigation system based on intelligent sensing and a control method thereof, and the system comprises an intelligent sensing module which is used for collecting meteorological data, soil humidity data and soil temperature data of different irrigation areas; the model prediction module comprises a moisture diffusion model and a rainfall prediction model which are respectively used for performing soil moisture diffusion prediction and rainfall prediction on different irrigation areas by utilizing the soil humidity data, the environment temperature data and the meteorological data, and outputting prediction results; the drip irrigation control module is used for controlling operation of a drip irrigation pump; the drip irrigation control module is further used for controlling electromagnetic valves in drip irrigation pipes in different irrigation areas to be opened and closed by utilizing an intelligent control mechanism according to the prediction result of the model prediction module so as to adjust the irrigation volumes in the different irrigation areas; the soil moisture diffusion rule can be predicted, repeated irrigation and irrigation blind areas are reduced, and waste of water resources is reduced.

The invention discloses a remote intelligent control system for a drip irrigation head water pump based on the Internet of Things, relates to the technical field of agricultural intelligent irrigation, and is used for solving the problems of low precision and poor management efficiency of a traditional drip irrigation technology. The system comprises a drip irrigation area parameter acquisition module which acquires soil temperature and humidity, equipment operation parameters and meteorological data in a layered manner through a multi-source sensor network; the data processing module performs differential filling, space-time alignment and integration on the data; the intelligent analysis module realizes drip irrigation demand judgment, quantity value calculation, opportunity optimization and equipment health assessment; and the control execution module converts the instruction into equipment operation and supports remote intervention, so that precise management and control of drip irrigation are realized, and the precision and management efficiency of drip irrigation are improved.

The invention provides an intelligent temperature sensing regulation and control planting field soil temperature control system and method, and relates to the technical field of soil temperature control, and the method comprises the steps: obtaining the regional information of a seedling growing planting field, and extracting all soil temperature monitoring sub-blocks according to the regional information of the seedling growing planting field; obtaining block environment data of the soil temperature monitoring sub-block, determining a soil temperature stress factor according to the block environment data, and obtaining all soil temperature stress risk areas in the seedling cultivation field based on the soil temperature stress factor; temperature control resource information in the seedling growing planting field is obtained, a resource area mapping matrix is determined through the temperature control resource information, and a temperature control response strategy is determined through the resource area mapping matrix and the soil temperature stress factor; and performing soil temperature regulation and control on each soil temperature stress risk area according to the temperature control response strategy. According to the invention, risk analysis and resource optimization regulation and control of the soil temperature can be realized, so that the temperature regulation and control precision and regulation and control efficiency of the nursery stock cultivation environment are improved.

The invention discloses an air energy-soil composite heat pump cross-seasonal energy storage and winter combined heating system and an application method, and relates to the technical field of building energy conservation. Comprising the following steps: acquiring quantitative data of heat unbalance; when a heat unbalance phenomenon exists, determining a soil initial temperature and a maximum rising temperature before heat compensation, and calculating a heat compensation amount; determining a heat compensation operation time period and a system type selection of an air source heat pump; determining an initial rising temperature, a heat compensation initial investment and a preset age limit; the operation cost is determined, when the number of times of heat compensation is larger than a preset year limit, the sum of the initial investment of heat compensation and the operation cost within the preset year limit is recorded, and when it is detected that the total soil temperature increasing value is not lower than the maximum temperature increasing value, the air source heat pump system is determined again; and the strategy with the minimum operation cost and the minimum initial heat compensation investment is used as the optimal soil heat compensation strategy. The system obviously improves the utilization rate of renewable energy sources, and has the advantages of high energy efficiency, wide adaptability and low whole life cycle cost.

The invention discloses an alfalfa planting management method based on high-altitude saline-alkali soil, and relates to the technical field of agricultural cultivation, and the method comprises the following steps: S1, an irrigation water preheating step: enabling irrigation water to flow through a deep-color pipeline laid on the ground surface for solar preheating; the preheated irrigation water is used for irrigating the field in a drip irrigation mode, and the irrigation water amount is determined according to the initial salt content of the soil and the target salt leaching depth. According to the alfalfa planting management method based on the high-altitude saline-alkali soil, through combination of irrigation water preheating treatment and precise drip irrigation, the contradiction between salt leaching operation and ground temperature keeping in a high-altitude area is effectively solved. Preheated irrigation water avoids soil temperature sudden drop caused by cold water irrigation, the layered covering technology synergistically inhibits water evaporation and salt upward returning, meanwhile, the soil temperature is kept stable, a proper water temperature and salt environment is created for alfalfa seed germination, and therefore the seedling emergence uniformity and the seedling survival rate are improved.

Various embodiments for an autonomous forest fire detection, alerting and mitigation device includes a subterranean data gatherer having a plurality of soil temperature and soil moisture sensors installed at a plurality of different depths in a soil. A data assimilator that has a configured threshold change depending on the plurality of different depths in the soil of the plurality of soil temperature and soil moisture sensors, the soil properties, the duration of the fire, and a time delay duration. The data assimilator receives a data transmission packet from the subterranean data gatherer and detects a fire and generates a fire alert when the plurality of soil temperature and soil moisture sensors all breach the configured threshold change. A smart water pump is also started to slow the fire or completely stop it. The subterranean data gatherer is installed at the plurality of different depths in the soil.

The invention relates to the technical field of soil detection, in particular to an electronic tag for passive soil temperature and humidity measurement and a use method of the electronic tag. The electronic tag comprises a tag shell, a soil temperature and humidity sensor is arranged in the tag shell, a probe interface is arranged in the tag shell, and a probe body is fixedly installed on the surface of the probe interface. The NFC chip with the model of ST25DV is adopted, 13.56 MHz radio-frequency signals emitted by a mobile phone or a reader-writer are efficiently rectified into 3.3 V direct current, short-time power supply buffering is achieved in combination with a 2.7 V / 10F energy storage capacitor, energy is supplied to an ultra-low power consumption master control MCU 22 and a high-precision soil temperature and humidity sensor, when radio-frequency energy is insufficient, the master control MCU records the current state to an EEPROM of the NFC chip, data are continuously transmitted during next power supply, and the power consumption is reduced. A traditional battery is completely replaced, a large amount of cost generated by battery replacement is avoided, and the technical standard of sustainability and high robustness of the agricultural sensor is redefined.