94 results about "Soil wetness" patented technology

The invention relates to the technical field of forestry intelligent management and control, and discloses a forestry optimization management and control method and system based on artificial intelligence. The method comprises the following steps: collecting multi-source environment monitoring data such as soil humidity, illumination intensity and vegetation growth indexes in a forestry area, aligning a time sequence through a dynamic time warping algorithm, and separating steady-state and transient components; detecting anomalies through an isolated forest algorithm and generating a thermodynamic diagram, and obtaining a potential disease and pest outbreak area through causal reasoning in combination with historical records; constructing a dynamic growth reference curve, and identifying a disturbance sensitive area by using a generative adversarial network and a convolutional neural network; and integrating and generating a management and control priority partition map, optimizing resource allocation through deep reinforcement learning, outputting a task sequence, and driving equipment to execute irrigation, fertilization or pest control operation. According to the method, multiple artificial intelligence algorithms are fused, accurate control over the whole forestry process is achieved, and the method adapts to the dynamically-changing forestry environment.

The invention relates to the technical field of water conservancy flood prevention monitoring, and discloses a water conservancy flood prevention monitoring and early warning method and system. The method comprises the following steps: acquiring multi-source hydrological monitoring data including real-time rainfall, riverway water level, soil humidity and weather forecast data, and constructing a comprehensive hydrological information basis; flood risk analysis is carried out based on the data, a flood risk prediction signal and a flood situation evolution signal are synchronously generated, and the flood occurrence probability and the development trend are clarified. And combining the flood risk prediction signal with the multi-source data to determine flood prevention regulation and control parameters and generate an optimized flood prevention signal. Flood prevention facility operation is adjusted according to the optimized flood prevention signal and the flood situation evolution signal, an early warning control signal is output, the two signals are processed at the same time to generate a comprehensive early warning index, and the severity of the flood situation is visually reflected. According to the method, hydrological data multi-dimensional fusion is realized, flood prevention monitoring and early warning are promoted to change from single data dependence to multi-source collaboration, and the flood situation response efficiency is improved.

The invention discloses a rainfall type landslide early warning method based on multi-source environment threshold and nonlinear fusion. The method comprises the following steps: constructing a landslide disaster-inducing factor set; introducing soil humidity, vegetation indexes and evapotranspiration, and calculating a threshold parameter corresponding to the rainfall type landslide event to obtain an environment threshold point set; according to the landslide disaster-inducing factor set, constructing and training a landslide susceptibility model based on progressive learning; adopting a double-layer nonlinear fusion model based on multi-source data fusion and quality perception gating, and combining a landslide susceptibility model to obtain comprehensive risk probability distribution; and performing graded early warning based on the comprehensive risk probability distribution to complete rainfall type landslide early warning. According to the method, on the basis of traditional rainfall parameters, early-stage disaster-pregnant environment factors are introduced, and a multi-source environment threshold value is formed; fuzzy logic reasoning is adopted to realize nonlinear fusion of the threshold information and the landslide susceptibility base map; and dynamically reflecting a regional environmental condition evolution process in combination with an annual iterative updated susceptibility layer, and realizing finer and more adaptive space grading early warning.

The invention provides an agricultural pest correlation analysis and diagnosis method and system based on a knowledge graph, and the method comprises the steps: firstly collecting a multi-source agricultural monitoring data set, including crop growth stage parameters, meteorological fluctuation parameters and the like, of a target region, and then processing meteorological and soil humidity parameters through an environment feature extraction model to generate a multi-dimensional environment feature set; processing disease and pest symptom image data by using a symptom feature extraction model to generate a symptom feature set, calculating dynamic correlation degree parameters of the two based on a knowledge graph topological structure, constructing a disease and pest cause probability distribution diagram, and then performing joint reasoning on crop growth stage parameters and the cause probability distribution diagram by using a pre-trained disease and pest diagnosis model to obtain a disease and pest disease diagnosis result. And finally, matching an optimal control strategy set according to the multi-level disease and insect pest diagnosis results, and inputting the optimal control strategy set into an agricultural decision-making system to trigger control equipment regulation and control operation, thereby realizing scientific and effective disease and insect pest diagnosis and control.

The invention provides a multi-scheme collaborative yield forecasting method based on data assimilation and model parameter optimization, and belongs to the technical field of agricultural information, and the method comprises the steps: obtaining historical and real-time data of a target region and a target crop growth season; constructing a plurality of combined simulation schemes of the WOFOST model; carrying out data assimilation on the leaf area index and the soil humidity by utilizing an ensemble Kalman filter (EnKF) method and combining a Gaussian disturbance strategy; performing sensitivity analysis and optimization on photosynthetic parameters of the WOFOST model, determining an optimal photosynthetic parameter combination and operating the model; improving a water stress function; constructing a rolling updating yield prediction framework, and dynamically optimizing a yield prediction result; and dynamically selecting an optimal simulation strategy to simulate and forecast the yield. According to the method, the yield simulation precision and forecasting stability of the crop model under different moisture years are remarkably improved, and a reference is provided for developing a new meteorological year adaptive dynamic simulation framework of the crop model.

The invention discloses a regional extreme drought and flood event prediction system based on a climate model, and relates to the technical field of climate model prediction and disaster early warning, and the system comprises a data input module which is used for receiving regional multivariable prediction data processed by downscaling of the climate model, and the multivariable prediction data comprises rainfall, soil humidity and evapotranspiration. According to the regional extreme drought and flood event prediction system based on the climate model, equation strong constraint and variational optimization are carried out on key variables such as rainfall, soil humidity and evapotranspiration through the physical constraint dynamic coupler, the physical law of water circulation mass conservation and surface energy balance is forcibly met, the distortion phenomenon is eliminated, and the prediction accuracy is improved. According to the method, physical correction residual errors are converted into weight factors, Copula function parameters are dynamically adjusted, it is ensured that joint probability distribution of extreme drought and flood events strictly follows a physical mechanism, the path of misinformation physical impossible events is blocked from the source, and the problem of prediction distortion caused by multivariate physical inconsistency in downscaling output of a climate model is solved.

The application discloses a UWB navigation system and method based on visual feature fusion, and the system comprises four modules of UWB positioning, visual perception, data fusion processing and navigation control. The UWB positioning module adaptively generates a UWB anchor point layout, and after calculating UWB coordinates in real time, UWB positioning data are obtained by calibration according to the coverage rate of fruit trees and soil humidity. The visual perception module collects orchard images, identifies fruit trees and obstacles, obtains visual coordinates and corrects visual positioning data. The data fusion processing module calculates the weight of UWB positioning data and visual positioning data, fuses UWB positioning data and visual positioning data according to the weight to obtain fusion coordinates, and corrects errors to obtain optimal coordinates. The navigation control module calculates target path points according to the optimal coordinates, obstacle recognition results and weeding operation paths, and controls the weeding robot to travel to the target path points. The application realizes high-precision navigation of the weeding robot in the complex environment of the orchard.

The application relates to the technical field of precision agriculture monitoring, and discloses a precision agriculture monitoring system based on adaptive wireless communication. The system comprises a multi-source environment acquisition module, a communication protocol adaptation module and a crop state evaluation module. The multi-source environment acquisition module obtains soil humidity data, illumination intensity data and meteorological parameter data through wireless sensor nodes arranged in farmland areas, and synchronizes the timestamps of the data to ensure the consistency of the data in the time dimension. The communication protocol adaptation module dynamically selects a wireless transmission frequency band according to the synchronous data volume, allocates communication time slots based on data priority, and generates adaptive transmission channel parameters to cope with the communication requirements under the conditions of data volume fluctuation and complex environment. The crop state evaluation module receives the transmission channel parameters, analyzes real-time environment data streams, and divides the current crop growth state into a growth standard state, a growth lag state or a growth fluctuation state. The system provides support for fine management of agricultural production.

The application provides a wheat wide seedling strip seedbed preparation device and a monitoring system thereof, which comprises a single fixed seat, a front ditch opener fixed seat, a front ditch opener, a fertilizer spreading device, an anti-abrasion plate, a rotary tiller group, a side plate, a soil retaining plate, a rear ditch opener, a soil humidity sensor, a metal water pipe, a profiling mechanism, a spring damper, a transmission box and a motor. The single fixed seat is provided with a through hole, and the single body is fixed to a seeding machine frame through U-shaped bolts. The seeding machine can be installed with multiple single bodies. The spacing between the single bodies is adjusted to adapt to the wide seedling strip seeding operation of different row spacings. The soil disturbance and power consumption during operation are reduced through wide seedling strip rotary tillage. The monitoring system comprises a rotary tiller group power distribution monitoring system and a lower irrigation monitoring system. The rotary tiller group power is automatically adjusted with the change of the forward speed and the working resistance, so that the seedbed preparation operation effect is improved. Through lower irrigation of the seedling strip, the problem of uneven emergence caused by the inconsistent soil moisture content of different plots in the field is solved.

This invention relates to the field of irrigation technology for afforestation in barren mountains, specifically a monitoring and irrigation device for afforestation in barren mountains. It includes an electric six-wheeled chassis and a side-spray water supply structure connected to the chassis. The side-spray water supply structure includes a water tank, with a telescopic water supply unit fixedly connected to the tank, and two symmetrically arranged side-spray units fixedly connected to the tank. A point-based detection irrigation structure is also connected to the chassis. This structure includes a mobile carrier unit connected to a drone, a lifting limit unit connected to the chassis, multiple independent detection units connected to the lifting limit unit, and an aerial sprinkler unit movably connected to the lifting limit unit. Through the combination of the side-spray water supply structure and the point-based detection irrigation structure, this invention is suitable for complex mountainous terrain, accurately monitoring soil moisture and performing irrigation operations, thus improving the applicability and accuracy of irrigation operations in mountainous areas.

This invention discloses a method for improving the accuracy of rice irrigation forecasts in irrigation districts based on digital twins, belonging to the field of agricultural water conservancy engineering technology. Based on digital twin technology, this invention divides the irrigation district into sub-regions using GIS and constructs a digital mapping model; it establishes a dynamic adaptive calculation system with multi-model selection, combining meteorological data completeness, rice growth period, and historical errors, and calculates the appropriate model using a dynamic weighted adaptation algorithm, obtaining the final value from the input data; it introduces soil moisture and field management correction coefficients to construct a dynamic calculation model; combined with the calculation of real-time water requirements for rice, it generates a refined irrigation scheduling plan for the sub-regions and achieves coordinated irrigation; and it corrects parameters using a gradient descent algorithm to ensure forecast accuracy. This method, through its dynamic adaptive calculation system, solves the accuracy problem in scenarios with missing data and has broad application value.

The application provides a multi-scheme cooperative yield prediction method based on data assimilation and model parameter optimization, and belongs to the field of agricultural information technology.The method comprises the following steps: obtaining historical and real-time data of a target region and a target crop growing season; constructing multiple combination simulation schemes of a WOFOST model; using an ensemble Kalman filter (EnKF) method combined with a Gaussian disturbance strategy to perform data assimilation on a leaf area index and soil humidity; performing sensitivity analysis and optimization on photosynthetic parameters of the WOFOST model, determining an optimal photosynthetic parameter combination, and running the model; improving a water stress function; constructing a rolling update yield prediction framework, dynamically optimizing yield prediction results; and dynamically selecting an optimal simulation strategy to perform yield simulation and prediction.The application significantly improves the yield simulation accuracy and prediction stability of the crop model under different water year types, and provides a reference for developing a new framework of crop model meteorological year type self-adaptive dynamic simulation.

This invention discloses an InSAR interferometric network optimization method based on a multi-factor coherence surrogate model. The method includes: constructing a multi-factor feature dataset containing SAR imagery, baseline data, and soil moisture data of the study area; constructing a candidate interferometric pair set, and randomly selecting a subset of sample interferometric pairs from the candidate set; constructing a coherence surrogate prediction model, which uses the multi-factor feature data corresponding to the sample interferometric pair subset and the ground truth values ​​of sample coherence to train the model parameters; inputting the multi-factor feature data corresponding to each interferometric pair in the candidate set into the trained coherence surrogate prediction model and outputting the predicted coherence of each interferometric pair and the optimized interferometric pair network. This invention improves the stability and accuracy of unwrapping and time-series inversion, while also reducing the difficulty of interferometric processing and coherence calculation under large-scale data, and can support the needs of large-scale, long-term, and near-real-time monitoring.

The application provides a drought-flood sudden change early warning method and system for coupling satellite and ground base station signals, and comprises the following steps: acquiring multi-source data of a research area; loading a hydrological climate reconstruction model to reconstruct long-series gridded rainfall data and soil moisture data of the research area in a historical period; optimizing a plurality of rain attenuation rain intensity models for rainfall inversion by a microwave link signal; constructing a correction module of the rain attenuation rain intensity model to correct real-time regional rainfall series inverted by the microwave link; constructing a drought-flood sudden change event intensity correction module to generate a calibrated historical drought-flood sudden change event library; constructing a drought-flood sudden change dynamic early warning module fusing a circulation signal to output early warning results of drought-flood sudden change in a future period; and generating and releasing drought-flood sudden change risk early warning information based on the early warning results output by the drought-flood sudden change dynamic early warning module. The application provides a real-time, dynamic and high-precision drought-flood sudden change early warning mode by fusing satellite remote sensing and mobile communication base station signals.

The invention relates to an ecologically vulnerable area identification and ecological restoration method and system based on a remote sensing image. The method comprises the following steps: collecting optical and synthetic aperture radar multi-source remote sensing data, calculating a space correction parameter to complete image registration, and filling a cloud layer shielding area by adopting time sequence interpolation to generate a complete remote sensing image; inputting the complete image into a soil humidity inversion model to generate humidity time sequence data, extracting vegetation parameters to determine a change trend, and delimiting an ecological degradation area through correlation analysis and trend matching of the two; extracting time-space distribution characteristics of the degradation area to judge an abnormal area, processing data of the abnormal area by adopting a spatial interpolation algorithm, and quantitatively evaluating a degradation risk level in combination with a multi-level risk standard; and verifying the ecological restoration effect based on the risk level, and comparing the initial monitoring data to generate a standardized restoration effect index. By adopting the method, the pertinence and effectiveness of ecologically vulnerable region identification and restoration can be improved, and the manual investigation cost and period can be reduced.

This invention discloses a graphite grounding device, buried in a foundation pit. A metal core column is arranged within the pit, with permeable holes on its sidewalls. The metal core column has a water channel connected to an external water supply source, and the permeable holes are connected to the water channel. The metal core column is electrically connected to a grounding wire. A graphite cylinder is fitted onto the metal core column, and the two are electrically connected. The graphite cylinder has a through hole connected to the permeable holes. One end of a flexible graphite grounding wire is fixed to the metal core column and electrically connected. Multiple flexible graphite grounding wires are arranged sequentially along the length of the metal core column. This invention, by setting a metal core column inside the graphite cylinder, ensures a reliable electrical connection between the grounding device and the grounding wire. An external water supply source can supply water to the water channel, with water flowing out through the through hole. This design increases the soil moisture around the grounding device, reduces grounding resistance, and improves the grounding effect. The flexible graphite grounding wires can fully contact the soil, thereby improving the grounding effect and reducing grounding resistance.

The invention relates to the technical field of ecological data monitoring and analysis, and particularly discloses an ecological monitoring data integrated analysis method and system. Soil moisture content and pH value data of each sub-region are collected in real time through a capacitive soil humidity sensor and an electrode pH value sensor, a soil moisture content abnormal index and a pH value abnormal index are calculated by using fast Fourier transform and a K-Means clustering algorithm, and a soil degradation coefficient is obtained by combining weighted normalization processing; and evaluating the soil health condition of each sub-region, constructing a machine learning model based on the data features to predict the future soil degradation level, further analyzing the relationship between precipitation and soil degradation for the region predicted to be seriously degraded, and starting a dynamic precipitation treatment scheme if it is found that precipitation increase can prevent soil degradation.

The application provides a high-altitude area sub-seasonal precipitation prediction method, system, device and medium, and aims to construct a high-altitude area sub-seasonal precipitation prediction optimization system based on soil moisture memory. First, the physical mechanism of soil moisture affecting precipitation is revealed in depth and a statistical prediction model is constructed by fusing multi-source observation data. Then, the reproduction ability of the main dynamic model to the mechanism is evaluated and the deviation source is diagnosed. Finally, by fusing the physical statistics and the dynamic model, an optimization framework with high prediction skill and strong interpretability is constructed to significantly improve the sub-seasonal precipitation prediction level of the high-altitude area in the rainy season.

The invention relates to the technical field of monitoring systems, in particular to an intelligent monitoring system for crop growth. The system comprises a main control chip, an environment illumination intensity detection module, an environment temperature and humidity detection module, a light supplement lamp module, a soil humidity detection module, a water supplement control module, a sound alarm module, an OLED display screen module, a network communication module, a power supply module and a delay control module. The system can automatically control water replenishing according to a preset threshold value, allows a user to manually replenish water through a local button or remote control mode, can automatically adjust the brightness of the light replenishing lamp according to the change of the ambient brightness so as to ensure that plants obtain proper illumination conditions, triggers an alarm when detecting that the temperature or the humidity exceeds a preset range, and improves the water replenishing efficiency. A user can check remote monitoring data anytime and anywhere, various functions of the device can be directly controlled, and agricultural management on fingertips is truly achieved.

The utility model belongs to the technical field of agricultural planting equipment, and particularly relates to a peony and Chinese herbaceous peony tissue culture seedling electric heating seedling raising device which comprises a device shell and a support, the support is installed in the device shell, a seedling raising device is installed in the device shell, and the seedling raising device comprises a monitoring unit, a spraying unit and an illumination unit. According to the electric heating seedling raising device for the peony and paeonia lactiflora tissue culture seedlings, the monitoring unit is installed, the temperature is accurately controlled to be 0-20 DEG C, and the temperature needed by the peony and paeonia lactiflora tissue culture seedlings in the seedling hardening stage, the rooting stage, the vernalization stage and the abnormal weather is met. The spraying unit is installed and comprises a spraying head, a soil humidity sensor, a ventilation assembly and the like, and the requirements of peony and peony tissue culture seedlings for soil humidity in the germination stage, the leaf expansion stage, the flowering stage and the dormancy stage are met. The illumination unit is installed, the LED lamp tube assembly is utilized, and proper light supplement is provided according to weather conditions, so that the temperature, humidity and illumination required by the growth environment of the peony and paeonia lactiflora tissue culture seedlings are provided, and the peony and paeonia lactiflora tissue culture seedlings grow better.

The present application relates to the technical field of agricultural intelligent irrigation and precise pesticide application, and discloses a quantitative pesticide spraying system and method for standardized planting of traditional Chinese medicinal materials. A coordinate system and an equidistant sampling grid are established on the surface of a field, a capacitive soil humidity sensor is laid out and calibrated, real-time voltage data is accurately converted into the soil water content of the grid nodes, and four-point bilinear interpolation is used to realize the acquisition of the soil water distribution of the continuous field in the field. Based on the node difference calculation, the water content spatial gradient and the average gradient of the whole field are calculated, the area is divided according to the number of nozzles, the regional boundary is dynamically adjusted to ensure the data validity, and the average gradient of each area is extracted. Combined with the unit area pesticide spraying demand and the coverage area, the basic pesticide spraying volume is obtained, the adjustment factor is generated by linear mapping of the regional gradient and the global extreme value, the pesticide spraying volume is differentiated and controlled, and the boundary clamping is implemented, and finally the opening time is calculated according to the spraying speed, and the controller executes the operation in sequence.

The invention discloses a high temporal-spatial resolution water body inversion method based on multi-source data fusion. The method comprises the following steps: acquiring CYGNSS surface reflectance data, SMAP soil humidity data and FABDEM digital elevation data in a preset time window; performing space-time alignment and resampling preprocessing on the CYGNSS surface reflectance data, the SMAP soil humidity data and the FABDEM digital elevation data to generate a standard input sample with unified spatial resolution and coordinate system; inputting the standard input sample into a pre-trained STRUE model, and extracting multi-level features through a double-branch decoder structure of the STRUE model; based on multi-level features, a student-teacher framework is adopted to generate pseudo tags and calculate loss so as to drive the model to carry out weak supervision semantic segmentation; and outputting a classification result graph of the water body and the non-water body to realize high-temporal-spatial-resolution water body inversion. According to the invention, high-temporal-spatial-resolution inland water body inversion is realized.

The application discloses a kind of photovoltaic shade interplanting methods of Amorphophallus konjac, comprising: establishing interplanting area between photovoltaic array row;According to photovoltaic panel projection range, interplanting area is divided into fixed shade area and variable light transmission area, fixed shade area is located in the area directly below photovoltaic panel, and variable light transmission area is located in the light transmission zone between adjacent photovoltaic panel;Planting ditch is opened according to row distance 40-50 centimeters in fixed shade area;Selecting Amorphophallus konjac tuber, planting in planting bed;Variable light transmission area is provided with sunshade net slide rail system driven by stepping motor, light intensity sensor is installed on slide rail, sensor is connected with controller, and controller calculates model according to solar elevation angle and real-time illumination data, and automatically adjusts sunshade net horizontal displacement daily;Establish intelligent drip irrigation system.The application can provide stable shade environment and suitable soil humidity for Amorphophallus konjac, reduce manual operation, improve the automation level of interplanting process, and meet the specific requirements of crops on growth environment.

The utility model provides a degradable bio-based seedling raising tray special for pseudo-ginseng seedling raising. The special degradable bio-based seedling raising tray for pseudo-ginseng seedling raising comprises a lower tray body; the upper tray body is arranged on the lower tray body; the water permeable holes are formed in the bottom of the upper tray body; the supporting columns are fixedly mounted at the bottom of the lower tray body; the same water tank is fixedly mounted at the bottom ends of the plurality of supporting columns; the heat-preserving cover is positioned at the top of the upper tray body; the opening and closing mechanism is mounted on the water tank and used for controlling opening and closing of the heat preservation cover; and the irrigation mechanism is mounted on the inner wall of the heat preservation cover and is used for irrigating the pseudo-ginseng seedlings in the upper disc body. The degradable bio-based seedling raising plate special for pseudo-ginseng seedling raising has the advantages that soil humidity in the seedling raising plate can be controlled in different areas, the auxiliary irrigation function is achieved, and operation is convenient.

The invention discloses a tailing pond underlying surface runoff and confluence simulation and real-time monitoring analysis system, which is characterized in that a special underlying surface environment of a tailing pond is accurately reproduced by constructing a multi-gradient contrast experiment unit, an artificial rainfall simulation unit and a runoff quality-based collection unit; a soil humidity, liquid level, rainfall and surface flow state multi-source sensing network is integrated, and the whole process of production and confluence is sensed synchronously; on the basis of an intelligent data processing platform, monitoring data are fused in real time, and a runoff generation rule is dynamically analyzed. The technical problem that a traditional method cannot give consideration to multi-factor control, whole-process monitoring and real-time analysis is solved, and a complete experimental research platform is provided for revealing the non-linear production and confluence mechanism of the tailings pond and flood risk early warning.

A double-row reverse soil feeding, fertilizing, film mulching and sowing all-in-one machine comprises a machine frame, a three-point suspension frame, two furrow ploughs, two fertilizing boxes, two seed boxes, a mulching film frame and two sets of automatic soil covering systems are arranged on the machine frame, the three-point suspension frame and the two furrow ploughs are all installed on the front side of the machine frame, and two land wheels are further installed on the front side of the machine frame; in conclusion, the machine integrates operations of ditching, fertilizing, seeding, film mulching, soil covering and the like, so that the agricultural production process is greatly simplified, and the working efficiency is improved; the mulching film is beneficial to keeping soil humidity, inhibiting weed growth, increasing ground temperature and promoting early growth of crops; due to the design of a chain transmission pair of the automatic soil covering system, the soil covering process is more uniform and consistent, the mulching film is effectively covered on the soil, and the automation level of agricultural production is enhanced; production cost can be reduced, crop yield can be increased, and economic benefits of farmers can be improved.

The invention discloses a rapid assessment method for groundwater resource stock in a hilly area based on a gravity satellite and river base flow, and relates to the technical field of groundwater resource stock assessment, and the method comprises the steps: collecting GRACE data, WGHM hydrological model data, soil humidity data and runoff data, and filling and processing a data blank; calculating the base flow by adopting a digital filtering algorithm; according to the principle of water balance, non-groundwater signals are removed from the land water signals inverted by GRACE to obtain a groundwater stock change value; calculating underground water resource stock offset and absolute stock by constructing a linear correlation between an underground water stock change value and base flow; and the actually-measured groundwater level data is used for calculating the actually-measured groundwater storage amount, and the absolute groundwater resource storage amount obtained through evaluation is verified. Technical support can be provided for rapid assessment of groundwater resource stock in the hilly region, and the method has positive significance in protection and utilization of groundwater.

The invention discloses a flood disaster early warning system based on the Internet of Things. The flood disaster early warning system comprises a distributed Internet of Things sensor network, an edge computing node and a cloud intelligent analysis platform. The sensor network collects water level, rainfall, soil humidity and meteorological data and communicates through a low-power wide area network; performing real-time anomaly detection by the edge computing node, and computing a comprehensive risk index by adopting a sliding time window mechanism; and the cloud platform fuses the multi-source data by using an improved deep learning model to generate a high-precision prediction result. According to the invention, real-time acquisition and intelligent analysis of multi-dimensional data can be realized, the early warning timeliness and accuracy are significantly improved, and an efficient and reliable solution is provided for flood disaster prevention and control under complex terrain and severe weather conditions.

The invention relates to the technical field of smart agriculture, and particularly discloses a water, pesticide and fertilizer integrated precise spraying method and system for smart agriculture. The method comprises the steps that a multi-mode sensor array is arranged in a farmland operation area, soil humidity, nutrient concentration and pH value signals are collected and subjected to normalization processing, and centimeter-level space-time alignment soil parameters with confidence coefficients are generated; calculating a deviation value between the soil parameter and a dynamic threshold value to generate a partition control parameter set; binding the device codes and the timestamps and then outputting the device codes and the timestamps to the communication module and the cloud platform; an execution verification code is transmitted and generated through a time-sensitive network and is fed back to the control module; and generating a structured weight coefficient table, and performing closed-loop feedback to optimize filtering processing parameters of the sensor. The agricultural production cost can be effectively reduced, non-point source pollution is relieved, the optimal water and fertilizer environment is provided for crop growth through precise control, and the yield and quality of crops can be improved.

The invention discloses a flat depression intelligent sowing precision control method and device based on plant shrinkage and densification, and belongs to the technical field of intelligent sowing precision control. According to the method, noise interference influences of two key factors of flat depression soil humidity and field micro-topography fluctuation on sensor acquisition signals are analyzed; deciding whether to trigger the self-adaptive calibration process of the humidity sensor, if so, rechecking the correlation analysis of the environmental noise of the flat depression after the calibration is completed, otherwise, continuously judging whether the self-adaptive calibration of the terrain elevation sensor needs to be started, and rechecking whether the angle deviation parameter of the terrain elevation sensor meets the standard after starting; if the standard is not met, a terrain adaptation self-adaption calibration failure prompt is sent, sowing regulation and control dynamic matching degree judgment is carried out according to the standard, and targeted plant shrinkage densification and sparse plant densification adjustment is carried out according to a judgment result, so that the precision of intelligent sowing precision control of the flat depression is effectively improved; the technical problem of low precision control accuracy of intelligent sowing of flat depression in the prior art is solved.