640 results about "Moisture capacity" patented technology

The invention discloses a loess tunnel surrounding rock deformation monitoring method, and relates to the technical field of civil engineering and geological engineering, and the method comprises the steps: integrating a spiral winding type optical fiber sensor, a double-cavity humidity compensation vibrating wire sensor and a microseismic array, and capturing surrounding rock strain, vibration and geological activities; the vibrating wire sensor suppresses humidity interference through a silicone oil damping medium and self-adaptive excitation frequency, and the optical fiber sensor is fixed through a pre-embedded silica gel sleeve to adapt to surrounding rock deformation; edge computing nodes are deployed on the inner wall of the tunnel, an FPGA chip and a lightweight GRU model are integrated, optical fiber strain, a micro-seismic energy spectrum and laser point cloud displacement field data are fused in real time, the strain gradient is analyzed, and a crack propagation probability cloud picture is generated; redundant optical fiber link switching is combined with a six-degree-of-freedom mechanical arm to realize breakpoint self-repairing, and a self-cleaning air curtain is integrated to inhibit dust adhesion; and constructing a geological parameter library based on a BIM-GIS fusion platform, driving a finite element-discrete element coupling model to dynamically update boundary conditions, and predicting surrounding rock deformation and collapse risks.

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

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

The invention relates to the technical field of intelligent regulation and control, in particular to a method for predicting and adjusting the moisture content of raw materials for shaving board production. According to the method, the raw material drying section disturbance parameter set and the moisture content detection sequence record in the shaving board production process are obtained, symbol matching, amplitude sorting and disturbance direction and influence intensity marking are carried out in combination with the prediction sequence and the disturbance characteristic sequence, so that the raw material moisture content prediction has the dynamic trend judgment capability; tracing correlation can be carried out on a disturbance source, prediction sequence amplitude adjustment is carried out through a disturbance direction and an amplitude mark, prediction correction of disturbance response and trend inversion abnormal point detection are achieved, and meanwhile local residual analysis is introduced to construct a trend residual sorting table; the abnormal inflection point is taken as the core to carry out weight sorting of the correction result and guide scaling and direction adjustment of the moisture content correction trend, and finally, adjustment instructions of the hot air temperature, the heating source power and the drying channel humidity are generated according to the deviation degree of the prediction result and the target set value.

The intelligent control method comprises the steps that a plurality of sensors and frequency converters are installed and used for monitoring the air temperature and humidity, the moisture content and the front-back pressure difference of a fresh air filter in real time; regulating and controlling the rotating speed of an air feeder, the rotating speed of a regeneration fan and the rotating speed of a rotating wheel through a frequency converter, obtaining sensor data under corresponding rotating speeds, and establishing an air supply quantity model, a fresh air quantity model and a rotating wheel dehumidification quantity model; the power of an air feeder, the front-back pressure difference of a fresh air filter and air parameter data are collected in real time, and the current dehumidification load is calculated according to a fan air supply amount model, a fresh air amount model and a preset formula; and selecting a preset control strategy to dynamically adjust the rotating speed of the rotating wheel, the rotating speed of the regeneration fan and the regeneration temperature according to the current dehumidification load and / or the rotating wheel dehumidification amount model so as to realize indoor humidity control. Start and stop can be automatically controlled and the dehumidification amount can be matched according to the actual wet load, excessive dehumidification or idle work is avoided, and the dehumidification efficiency is improved through multi-parameter cooperative control.

The invention relates to the technical field of safety assessment of building construction, and discloses an online simulation analysis method for safety assessment of a foundation pit, which comprises the following steps: S1, data acquisition, cleaning and preprocessing: acquiring soil pressure, underground water level, structural deformation, temperature and humidity information around the foundation pit by deploying a plurality of sensors, the invention further provides an online simulation analysis system for foundation pit safety assessment, online simulation analysis equipment for foundation pit safety assessment and a computer readable storage medium. The deep reinforcement learning algorithm, the intelligent early warning mechanism and the distributed storage and encryption technology are introduced, real-time monitoring, accurate early warning and data safety guarantee of foundation pit safety assessment are achieved, and the safety, efficiency and reliability of the foundation pit construction process are improved.

The invention discloses a near-infrared on-line intelligent detection system and method for material moisture of a conveying belt, and relates to the technical field of material moisture detection.The system comprises a material and environment information acquisition module, a data processing module and a data processing module, meanwhile, temperature, humidity and air pressure sensors are used for monitoring changes of environmental factors in real time, equipment is calibrated and maintained regularly, and parameters are initialized before detection; according to the invention, material characteristic pre-identification and environmental factor real-time sensing functions are integrated, and parameters of the near-infrared detection module are dynamically adjusted by using an intelligent algorithm so as to adapt to changes of different material characteristics and environmental factors, so that the detection system can accurately detect various material characteristics in a complex and changeable industrial field environment. And high-precision and high-stability moisture detection can still be maintained.

The invention relates to the technical field of rainfall type loess side slope instability early warning methods, and discloses a rainfall type loess side slope instability early warning method and system based on multi-source data fusion, and the method comprises the steps: S1, arranging a sensor network on a side slope, and collecting rainfall capacity, surface displacement and soil pressure data in real time; s2, preprocessing the collected multi-source data, including data cleaning, missing value filling and data standardization; and S3, extracting characteristic indexes capable of reflecting the stability state of the slope from the preprocessed data. Environmental data of the loess slope, such as rainfall, evaporation capacity, temperature and humidity, are acquired by using a sensor network; the deformation data comprises earth surface displacement, deep displacement and crack width; the mechanical data comprises soil pressure, pore water pressure and soil moisture content; image data: a slope surface image and a crack development image are collected, an early warning model is constructed based on a machine learning algorithm, and data features can be automatically learned.

The invention relates to the technical field of the Internet of Things, in particular to a landscaping intelligent management method and system based on the Internet of Things, and the method comprises the following steps: obtaining humidity, temperature, pH value and salinity sensors deployed in a landscaping area, collecting the monitoring data of an integral point, synchronizing the values of the four types of sensors, and eliminating change rate abnormal points. And a distributed soil sensing data set is generated after integration and archiving. According to the method, the time consistency is ensured and the monitoring precision is improved through hourly data synchronization and abnormal value elimination, the microenvironment change identification capability is enhanced through comprehensive analysis of salinity, humidity and temperature, the abnormal region discrimination accuracy is improved, and after a plant database is matched, the actual guidance value of plant adaptability assessment is improved, the health risk direction is defined, and the health risk assessment efficiency is improved. Historical irrigation and salinity analysis reveal the structural deviation of irrigation behaviors, the irrigation scheme is adjusted in a partitioned mode, the pertinence of resource allocation and the water-saving efficiency are enhanced, and efficient, accurate and self-adaptive development of landscaping management is promoted.

The invention relates to the technical field of concrete structure maintenance, and discloses an adjustable pier column intelligent water-saving spraying maintenance method and a maintenance device.The method comprises the following steps that a cover body of a pier column is arranged on the periphery of the pier column, and pier column surface humidity data are collected through sensing devices arranged on the periphery and the surface of the pier column; whether the spraying triggering condition is met or not is judged in combination with a preset control strategy, the control strategy is adjusted based on one or more of the environment temperature, the wind speed, the time and the historical spraying data, the spraying system is controlled to execute spraying operation when the spraying triggering condition is met, and the spraying operation is used for a spraying head opening area. Recycled water generated by spraying is collected through the seepage and drainage pipe. The closed or semi-closed spraying space is formed by arranging the cover body module, and the fresh-keeping film or tarpaulin wrapping structure is combined, so that local humidity stable control and evaporation suppression of the spraying environment are realized, and the effects of remarkably improving the spraying maintenance efficiency and reducing the water loss are achieved.

The invention relates to the technical field of industrial control, and discloses a real-time dynamic tuning system for a microwave drying process, which is characterized in that temperature distribution, microwave power intensity, humidity gradient and material deformation parameters in a drying cavity are acquired in real time, and time-space alignment and noise suppression are carried out on data of a multi-source sensor based on a Kalman filtering algorithm; generating a drying state matrix, generating a three-dimensional regulation and control instruction containing microwave emission frequency, power partition and drying time according to the drying state matrix by adopting a mixed algorithm of model predictive control and fuzzy logic, and taking the deviation between a final moisture content detection value of the material and a model predictive value as a loss function through an online error back propagation model. The weight coefficient of the microwave-thermal-mass transfer coupling model is dynamically corrected, the microwave energy ratio is optimized based on the improved particle swarm optimization, and the three-dimensional gradient field intensity distribution matched with the material morphology is generated according to the three-dimensional regulation and control instruction, so that the efficiency of the microwave drying process during real-time dynamic regulation and optimization is improved.

The invention provides a saline-alkali soil underground water regulation and control method and device, electronic equipment and a storage medium, and relates to the technical field of land governance. Inputting the first historical monitoring information into a pre-constructed prediction model to obtain a predicted value of soil salinity in a future time period; the predicted value of the soil salinity is input into the analysis model, and the target water level of underground water in the future time period is obtained; wherein the target water level of the underground water is used for restraining the target value of the soil salinity to be smaller than a preset salinity threshold value and the target value of the soil humidity to be larger than a preset humidity threshold value; generating a water level adjusting strategy based on the target water level of the underground water, and controlling the opening or closing of the water pump based on the water level adjusting strategy. According to the method, the soil salinity in the future time period is predicted by acquiring the saline-alkali soil monitoring information, so that the target water level of the underground water is obtained, the water level regulation strategy is generated, and the perspectiveness, dynamic nature and stability of underground water level regulation are ensured.

The invention relates to the field of material performance detection, and discloses a corrugated paper moisture regain resistance detection method and system, and the method comprises the steps: firstly obtaining a corrugated paper sample storage environment, collecting environment data, carrying out dynamic moisture absorption analysis according to the environment data, and calculating a moisture permeation rate; analyzing the damp state of the structure in combination with the rate, querying a moisture regain index, and then carrying out layered humidity detection to obtain interlayer moisture change data; calculating anti-moisture regaining residual strength based on the data, generating an anti-moisture efficiency index by combining temperature and humidity, and dividing moisture regaining risk grades; and finally, configuring multi-order early warning indexes according to grades, positioning an edge moisture absorption area, calculating a diffusion gradient value, generating a humidity stable signal, sending the humidity stable signal to the terminal, and formulating a moisture regain detection strategy according to feedback. The corrugated paper moisture regaining detection accuracy can be guaranteed.

The present invention discloses a GNSS-R soil moisture inversion method for mountainous areas that integrates a terrain moisture index. The method comprises the following steps: obtaining remote sensing data from target mountainous areas other than water bodies and soil moisture data from each observation station; selecting altitude, slope, aspect, longitude and latitude, vegetation index, clay content, and signal-to-noise ratio as influencing factors for soil moisture inversion in mountainous areas; calculating the corrected signal-to-noise ratio and terrain moisture index; constructing a mountainous area soil moisture inversion model, training it, and validating it; inputting a test set into the trained model to obtain daily soil moisture prediction data with a 1km resolution, taking the monthly average, and obtaining monthly soil moisture prediction data. The present invention's integration of the terrain moisture index with CYGNSS data can fully leverage the advantages of terrain factors and remote sensing technology, further improving the accuracy of soil moisture distribution and the ability to predict spatiotemporal changes, and better revealing the dynamic changes in soil moisture in complex terrain areas such as mountainous areas.

The invention discloses a new energy power generation prediction method based on weather data, and the method comprises the following steps: a, carrying out the characteristic analysis of a raw material, collecting the physical characteristic parameters of a biomass raw material, including the heat value of a dry basis, the moisture content of a wet basis and the mass, and generating an initial power generation prediction through a thermodynamic model; b, a distributed temperature and humidity sensor network is deployed in a raw material storage area, temperature, humidity and rainfall data are collected in real time, and the raw material mildew rate and moisture content change are dynamically predicted in combination with environmental parameters; through multi-dimensional data perception, multi-physical field coupling modeling and an intelligent decision engine, dynamic prediction of the raw material quality and the transportation efficiency in biomass energy power generation is realized, the power generation capacity prediction error is reduced, meanwhile, the raw material loss is reduced, and a key technical support is provided for large-scale efficient utilization of biomass energy power generation in new energy power generation.

The invention relates to a structure anti-seepage waterproof technology, in particular to a concrete structure anti-seepage performance analysis method considering a multi-physics field coupling effect, which comprises the following steps of: establishing a chemical-thermal-mechanical multi-field coupling model in a concrete hydration process by comprehensively considering various influence factors such as hydration heat, temperature, humidity and structure constraint and combining a phase field theory; solving is carried out through refined numerical simulation, and the concrete crack development and evolution process is obtained. The method has the advantages that multiple influence factors such as hydration heat, temperature, humidity and structural constraint are comprehensively considered by constructing the multi-factor coupled phase field model, the cracking risk of the concrete can be accurately estimated, and comprehensiveness and accuracy of impermeability performance evaluation are improved. By combining finite element simulation and based on a high-precision numerical simulation technology, the anti-permeability performance of the concrete structure under different working conditions can be predicted, and a scientific basis is provided for engineering design.

The invention provides a cultural relic ancient building hollow beam body damage quantification and bearing capacity verification method, and relates to the technical field of data processing, and the method comprises the steps: obtaining the original detection data of a hollow beam body; noise filtering processing is carried out on the ultrasonic signal data and the infrared imaging data, and correction is carried out in combination with an environment humidity parameter; in combination with the water content data of the detection points, carrying out space partitioning on the structural area of the hollow beam body; analyzing humidity correction data in each space partition, identifying signal abnormal areas, and extracting damage features in each abnormal area; performing weighted normalization processing on the multi-dimensional damage parameters, establishing mapping in combination with the moisture content of the spatial partitions and statistical data, and generating a damage quantification result of each spatial partition; carrying out mechanical analysis by combining the material type, the geometric dimension and the load information of each space partition, and generating a bearing capacity distribution result of the hollow beam body; the accuracy of the method for quantifying the damage of the hollow beam body of the cultural relic and ancient building and verifying the bearing capacity is improved.

The invention discloses an industrial equipment linkage control system based on dynamic time sequence reconstruction, relates to the technical field of kiln linkage control, solves the technical problems that a multi-system collaborative dynamic time sequence reconstruction capability is lacked and chain reaction caused by disturbance coupling is difficult to solve, and provides an industrial equipment linkage control system based on dynamic time sequence reconstruction by distinguishing humidity abnormal levels and customizing a heating strategy. The method ensures that heat release is completely matched with a wet material transmission rhythm, improves product drying uniformity, accurately calculates retention time and rotation speed according to a kiln type, realizes a'moisture evaporation demand-rotation speed-retention time 'closed loop, reduces energy consumption, integrates real-time material parameters, waste heat recovery and environment heat dissipation, accurately calculates a heat gap, and performs graded response, so that the energy consumption is reduced, and the energy consumption is reduced. And finally, a cooling air volume-pressure correlation model and an induced draft fan compensation-pressure repair model are established, accurate pressure compensation during cooling strengthening is achieved, and the stability of the microenvironment in the kiln is improved.

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.

An illustrative example of a planting machine includes a processing system, a moisture measurement device in communication with the processing system, a seed delivery system in communication with the processing system, and a water dispersion system in communication with the processing system. The processing system is configured to, receive one or more soil moisture measurement signals from the moisture measurement device, determine one or more water dispersion parameters based at least in part on a soil moisture measurement signal from the moisture measurement device, and transmit a control signal to one or more of the seed delivery system and the water dispersion system to disburse a desired amount of water with a commodity based at least in part on the determined water dispersion parameters.

The invention relates to the technical field of data processing, in particular to a water conservancy project construction flying dust control method and system. Comprising the steps of collecting environmental data of a water conservancy project construction site in real time through monitoring points arranged on the water conservancy project construction site; according to the environment data, the spraying intensity of each construction area at the current moment is determined, and then real-time regulation and control are conducted on each spraying head of a spraying system on the construction site; wherein the environment data comprises position coordinates, wind speed, wind direction, humidity and PM2.5 concentration of the monitoring points. According to the method, the PM2.5 concentration is considered, data such as the wind speed, the wind direction, the humidity and the position coordinates of the monitoring points are taken into consideration, and the spraying intensity suitable for the current moment and the environment characteristics of the current construction area is obtained. Therefore, each construction area can adopt different spraying intensities to carry out dust raising control according to self environment characteristics, and the best construction dust raising control effect is achieved with the most appropriate spraying intensity.

The invention discloses an intelligent maintenance system and method for a cement stabilized macadam base. The maintenance system comprises a monitoring module, an intelligent control module, maintenance equipment and a covering material, the monitoring module comprises a temperature and humidity sensor, a moisture evaporation sensor and an environment monitor; the intelligent control module comprises a data collector, a data processing unit and a controller; the maintenance equipment comprises a water tank, a water pump, pipelines and nozzles. The maintenance method adopts the maintenance system and further comprises the maintenance steps of data acquisition, data analysis and processing, maintenance decision and control and real-time monitoring and adjustment. The system has the beneficial effects that by monitoring the temperature, humidity, moisture evaporation rate and environmental parameters of the cement stabilized macadam base in real time and utilizing the data processing and control module to accurately calculate maintenance parameters, accurate maintenance of the base is achieved, uniform development of the strength of the base is ensured, generation of diseases such as cracks is effectively reduced, and the service life of a road is prolonged.

The invention belongs to the technical field of road engineering roadbed nondestructive testing, discloses a roadbed humidity nondestructive testing method based on wireless radio frequency signal multi-parameter inversion, and aims to solve the problems that a traditional roadbed humidity testing method is destructive, low in efficiency and discontinuous in monitoring or detection parameters are easily interfered. The method specifically comprises the following steps of: firstly, embedding an RFID tag and acquiring an on-site received signal strength indication value; then establishing a relation model of the received signal strength indication value and the roadbed moisture content, and extracting characteristic parameters only influenced by the moisture content; then, constructing a neural network model, taking the extracted characteristic parameters as input, and utilizing field data to train the model to invert the roadbed moisture content; and finally, the spatial distribution of the moisture content of the roadbed is obtained by combining the distribution of the test points and the roadbed structure information, so that the efficient, non-contact and continuous monitoring of the humidity state of the roadbed is realized.

The invention discloses an agricultural drought monitoring method for a humid and semi-humid area. The method comprises the following steps: acquiring a day-by-day soil moisture content historical time sequence of a drought generation year of a research site; according to the day-by-day soil moisture content historical time sequence of the research site, estimating the field moisture capacity and the wilting moisture content of various soil textures, and calculating the soil effective moisture content of the various soil textures; according to the crop irrigation water amount and the actual monitoring value of the soil water content in the key growth period of the dry crops, obtaining the soil water content when the dry crops are subjected to water stress; calculating agricultural drought monitoring indexes of the dry crops in the humid and semi-humid areas according to the soil water content when the dry crops are subjected to water stress and the soil effective water content of the corresponding soil texture, and determining agricultural drought severity grade division according to the STAD value for representing the agricultural drought grade of the research area so as to realize drought monitoring. According to the method, the problem that other indexes fail in drought monitoring of a wet or semi-wet area can be solved, and the method has relatively high universality.

The invention relates to the technical field of intelligent environment recognition, and particularly discloses a water and soil conservation measure intelligent query method and system based on multi-dimensional parameterization. Temperature and humidity data are collected in real time through a multi-source sensor deployed in water and soil, and a temperature stability characteristic value is calculated by adopting zero-sequence processing and fast Fourier transform; a humidity change rate characteristic value is extracted by combining first-order difference processing and Haar wavelet transform; the feature values are constructed into a comprehensive environment state feature vector, and the comprehensive environment state feature vector is input into a trained random forest model for environment recognition result evaluation; according to the method, the sensing technology, signal analysis and machine learning prediction are fused, the sensing ability, the regulation and control precision and the self-adaptability of the system are improved, the method is suitable for complex and changeable environment scenes, and the method has the advantages of being high in adaptability, high in adaptability and the like. Good application prospects are realized.

The invention relates to the technical field of watering control, in particular to an intelligent watering control method for alfalfa seed production, which comprises the following steps: collecting humidity data of current soil through a soil humidity sensor, analyzing a soil humidity state and generating a soil humidity result; evaluating the required water quantity according to the soil humidity result, and adjusting the output quantity of a water pump to obtain an adjusted watering plan. The current soil humidity state of the farmland is obtained by monitoring the soil humidity in real time, so that the output quantity of the water pump is dynamically adjusted, intelligent regulation and control of the watering plan are achieved, the irrigation accuracy is improved, and waste and insufficiency of water resources in the watering process are avoided; meanwhile, the watering plan is optimized by means of air temperature and rainfall data, so that the irrigation action is closely combined with the actual weather condition, the irrigation timeliness is improved, and the negative effects caused by adverse weather conditions are reduced.

The invention discloses a moisture-proof corrugated paper generation method and system based on machine vision. Humidity distribution data are obtained through image acquisition equipment, uniformity deviation characteristics are extracted through an image processing algorithm and input into an intelligent analysis model, and if deviation exceeds a threshold value, a coating thickness adjusting signal is output to determine the spraying amount of a moisture-proof agent; then, on the basis of the spraying amount, a structural integrity image in the forming stage is collected, deformation parameters are extracted, a production parameter optimization instruction is generated through a feedback verification unit in combination with the effect mapping relation model, an execution mechanism is driven to adjust the pre-drying temperature and the forming pressure, and meanwhile finished product moisture resistance detection data are obtained; finally, a closed-loop regulation and control cycle is formed through detection data and deviation characteristics, model parameters are optimized, deviation changes are continuously monitored, the mapping model is dynamically adjusted to adapt to different paper types, intelligent real-time optimization is achieved, and the production efficiency and the moisture-proof performance stability are improved.

The invention belongs to the technical field of soil humidity prediction methods, and particularly relates to a soil deep humidity prediction system and method based on near infrared spectrum and federated learning. The system comprises a near infrared spectrum acquisition device, an auxiliary information acquisition module, an edge end data preprocessing module, a federated learning client module, a cloud federated aggregation server and a man-machine interaction and equipment control module. The method comprises the following steps: establishing a surface humidity estimation model by collecting soil surface near-infrared reflectivity and environment auxiliary information; a deep humidity prediction model is constructed in combination with a heat conduction equation and machine learning, and the accuracy is improved by adopting weighted fusion. A federal learning framework is introduced, local training and cloud aggregation of each agricultural machine are realized, data privacy is protected, and the model generalization ability is improved. The system does not need to destroy the soil structure, has the advantages of non-contact, high efficiency, safety and expandability, and is suitable for intelligent prediction of large-range deep humidity in farmland and linkage control of agricultural operation.

A self-watering plant container includes a reservoir in a cavity of an outside wall of the container and having an inner wall that holds soil for plants placed in the plant container, a plurality of openings in a bottom portion of the inner wall, and an automatically actuatable air valve disposed in a top portion of the reservoir. Opening the air valve causes water from the reservoir to flow through the openings to increase a moisture content of the soil and closing the air valve causes negative air pressure to act on the water to prevent the water from flowing through the openings. The self-watering plant container also includes a motherboard with firmware that operates the air valve and a display that displays status information and instructions for a user. A cloud service communicates with the motherboard to provide signals that cause the motherboard to actuate the air valve.

The invention relates to the technical field of permeable material testing, solves the problem that a more complete material selection basis cannot be provided for engineering design in the prior art, and provides a method, a device and equipment for testing the heat dissipation performance of an evaporative cooling material and a storage medium. Acquiring a first mass change value of the to-be-tested sample in the simulated rainfall process; when the instantaneous moisture content meets a preset condition, rainfall simulation is stopped, and a second mass change value of the to-be-tested sample in a preset duration is obtained; placing the to-be-tested sample in the wind tunnel test platform, and obtaining a third mass change value and a surface temperature change value of the to-be-tested sample and an environment temperature change value, a humidity change value and a wind speed change value of the wind tunnel test platform; and obtaining a heat dissipation performance evaluation result of the to-be-tested sample based on the parameters. According to the method, quantitative, comparable and repeatable evaluation of the cooling capacity of the permeable material is realized, and a scientific basis is provided for material performance judgment and application scene selection.