218 results about "Environmental analysis" patented technology

The invention discloses a time sequence marine ecological environment early warning monitoring data abnormal point detection method, and relates to the technical field of marine ecological environment analysis, and the method comprises the steps: collecting a plurality of types of marine monitoring indexes, constructing a multi-source and multi-dimensional time sequence data set, and carrying out the preprocessing and unification of the data into a standard input format. And based on the causal relationship and co-evolution characteristics between the factors, constructing a graph structure model, and depicting a coupling propagation path between the factors. Generating a local time sequence model by adopting a sliding window, constructing an anti-fact path, comparing the propagation difference of an original path in a map structure, and identifying a key disturbance moment; and in combination with historical event similarity and space consistency information, the early warning credibility of abnormal points is evaluated, and efficient and interpretable graded early warning response is realized. According to the method, accurate identification and credible early warning of abnormal points are realized, causal modeling, anti-factual reasoning and hierarchical response capabilities are realized, and the intelligence and interpretability of marine ecological monitoring are improved.

The invention provides an unmanned aerial vehicle group path planning method and system based on environment analysis, and relates to the technical field of unmanned aerial vehicle path planning. Unmanned aerial vehicle operation data are collected, unmanned aerial vehicle operation abnormity is analyzed based on the unmanned aerial vehicle operation data, an unmanned aerial vehicle group flight path is collected, and the flight distance in the unmanned aerial vehicle flight process is obtained; the method comprises the steps of screening out a flight risk interval based on a flight interval in a flight process of an unmanned aerial vehicle, collecting weather data, analyzing flight abnormity generated by the flight risk interval under the weather influence based on the weather data, and obtaining unmanned aerial vehicle group density in a set range when the unmanned aerial vehicle generates the flight abnormity based on an unmanned aerial vehicle group flight path. The flight influence of flight abnormity on the unmanned aerial vehicle group is analyzed based on the unmanned aerial vehicle group density, the optimal flight path of the unmanned aerial vehicle group is screened out based on the flight influence of the flight abnormity on the unmanned aerial vehicle group, potential flight risks such as out-of-control, course deviation and even crash of the unmanned aerial vehicles can be predicted, and therefore the flight safety is improved.

The invention relates to the technical field of intelligent agricultural equipment, in particular to a tomato disease diagnosis method based on multi-modal data analysis, which comprises the following steps of: 1, synchronously acquiring and preprocessing multi-modal data, synchronously triggering a hyperspectral imaging device and a microscopic camera, respectively acquiring a plant canopy hyperspectral image and a stem microscopic image, and acquiring a plant canopy hyperspectral image and a stem microscopic image; meanwhile, temperature, conductivity and dissolved oxygen environment parameters are continuously collected in the root zone; 2, self-adaptive feature extraction and fusion in the growth stage are carried out, reflectivity correction and leaf segmentation are carried out on the hyperspectral image, and leaf surface spectrum curve features are extracted; step 3, hybrid model construction and space-time analysis: constructing a hybrid model comprising spectrum, microscopy and environment analysis networks, and dynamically adjusting each network weight through a gating network; and 4, generating a disease decision. The method can realize accurate, efficient and real-time tomato disease diagnosis, has high practical value, and can effectively improve the disease prevention and control capability in agricultural production.

The invention relates to the technical field of ecological environment monitoring, and discloses a regional ecological environment monitoring method and system based on remote sensing image processing, and the method comprises the following steps: collecting remote sensing image data and climate factor data of a target region; performing spatial gridding and standardization processing on the data; establishing a nonlinear regression model to analyze a relation between climate factors and vegetation indexes; extracting spatio-temporal topological characteristics of the climate factor data and identifying a change mode; long-term prediction of regional vegetation productivity is carried out through time sequence model training; the regional ecological environment is analyzed and evaluated based on the prediction result, and a scientific basis is provided for ecological environment monitoring; the system comprises a data acquisition module, a data processing module, a nonlinear regression modeling module, a spatio-temporal topology analysis module, a time sequence prediction module and an ecological evaluation module. According to the method, the problems of small data coverage, low prediction precision and insufficient capture of nonlinear influence of climate change in the existing method are solved.

The invention discloses an urban ventilation corridor construction method based on local climate region classification and remote sensing inversion, and belongs to the technical field of urban climate regulation and space optimization. According to the method, a multi-scale urban thermal environment analysis framework is constructed, a coupling mechanism of an urban form and a thermal effect is systematically identified from macroscopic, mesoscopic and microscopic levels, and fine modeling and regulation and control path identification of the thermal environment are realized. Meanwhile, in combination with machine learning and interpretability analysis methods, scientificity and transparency of thermal environment driving factor identification are enhanced. Through combination of remote sensing inversion, morphological factor construction and three-dimensional analogue simulation, a complete technical path of cold source identification, resistance modeling, path optimization and microclimate response evaluation is provided, and the aeration-cooling potential identification capability of blue-green infrastructures is effectively improved. The method is suitable for wind gallery planning and climate adaptation type update design of various urban spaces, and has wide popularization and application prospects.

The invention discloses a heparin production process optimization method and system based on environmental analysis, and aims to improve the purity and quality of heparin production. The method comprises the following steps: acquiring historical environmental monitoring data and multispectral data of an enzymolysis reaction kettle, and determining substance generation paths under different environmental conditions; establishing a nonlinear mapping model of environmental parameters and production purity based on a random forest algorithm, and calculating the influence weight of each parameter; generating an environment-adaptive enzymolysis reaction optimization scheme according to the weight; the method comprises the following steps: detecting molecular weight distribution data of a heparin crude product, and dynamically adjusting enzymolysis reaction parameters in combination with vibration spectrum and molecular conformation change characteristics; and finally, carrying out multi-target matching on the environment optimization scheme and the reaction parameters to generate a production optimization scheme containing an environment-process parameter mapping relation. The method can effectively improve the heparin production efficiency and quality, and is suitable for industrial production optimization.

The invention relates to the technical field of oil and gas geological exploration, in particular to an over-mature hydrocarbon source rock parent material type distinguishing method and system.The method comprises the following steps that regional deposition characteristics are studied, an over-mature hydrocarbon source rock deposition environment is recognized, principal elements and microelements are extracted in combination with a geological background, and component relevance is judged; and sorting representative sedimentary environment elements, and establishing a sedimentary environment associated element set. According to the method, accurate recognition of the sedimentary environment is achieved by extracting major elements and trace elements, representative elements are screened, proportional analysis is combined with the macerals, distribution characteristics of saprolite groups, exinite groups and the like are determined, the ratio relation between the macerals and inorganic elements is recognized, a ratio operation set is constructed, and the relation between the macerals and the elements is analyzed in a multi-dimensional mode. The relationship between parent material types and maceral characteristics is disclosed, a maceral type index model is constructed, hydrocarbon source rock parent material type division precision and sedimentary environment analysis systematicness are improved, and a scientific basis is provided for oil and gas resource exploration.

The invention discloses a self-adaptive searchlight based on visual perception and an intelligent control system, belongs to the technical field of searchlight control, and solves the problems that an intelligent control unit of an existing system only depends on basic parameters such as ambient light intensity and temperature, lacks dynamic personnel behavior analysis, cannot perceive scene semantics, and cannot realize intelligent control of the searchlight. The system comprises a visual perception module, an environment analysis module, a self-adaptive control module and a searchlight end. The visual perception module and the environment analysis module are arranged, the visual perception module can provide a more comprehensive information basis for the environment analysis module, misjudgment caused by a single data type is avoided, the environment analysis module can accurately recognize and analyze information such as personnel positions and the number in a complex scene, environment changes are accurately perceived, and the environment analysis efficiency is improved. Therefore, the light intensity of each lamp bead is dynamically distributed through a Newton optimization algorithm in combination with temperature field distribution, and the comprehensive energy efficiency, precision and response speed of the searchlight end are adaptively improved.

The invention provides a Yangtze river export deep and far sea environment data association analysis method based on multi-modal fusion, belongs to the technical field of far sea environment analysis, and achieves accurate data registration by establishing a multi-source data space-time standardization model and adopting an adaptive space-time Kriging interpolation algorithm. A sparse coding ocean signal separation algorithm is utilized to construct an over-complete dictionary separation mixed signal to extract pure features, a feature extraction network is constructed based on an attention mechanism to automatically learn deep feature representation of physicochemical biological parameters, and a matrix rank loss detection algorithm is adopted to automatically supplement feature compensation vectors to ensure feature integrity. A cross-scale attention mechanism is constructed based on wavelet transform to fuse multi-scale features, a Shapley value interpretability evaluation system is established to quantify correlation feature importance, and the technical problem that correlation feature extraction is inaccurate in the multi-source heterogeneous marine environment data fusion process is solved.

The invention provides a deep vertical shaft soft rock large deformation comprehensive index evaluation method comprising the following steps: carrying out geological environment analysis on a target area to obtain large deformation influence factors; calculating a large deformation evaluation index according to the large deformation influence factor; constructing a large deformation case database and a machine learning model, and performing risk prediction on the large deformation case database through the machine learning model to obtain a prediction result; dividing the soft rock large deformation grade according to the prediction result and the large deformation evaluation index; and executing different supporting schemes according to the soft rock large deformation grade. According to the method, the rock mass quality grading system is established through the multi-dimensional data and the large deformation evaluation indexes, meanwhile, the soft rock large deformation grade is divided according to the prediction result of the machine learning model on the large deformation case database, the soft rock large deformation prediction precision and the support design scientificity are improved, and the safety and efficiency of the deep vertical shaft project are guaranteed.

The invention discloses a landslide particle flow and live-action three-dimensional geographical environment analysis method and device, a medium and a product, and relates to the field of geological landslide simulation, and the method comprises the steps: determining a sliding body and a sliding bed region based on digital elevation model data before and after a landslide; establishing a three-dimensional landslide model by adopting a three-dimensional particle flow discrete element PFC3D based on the digital elevation model data before and after the landslide and the sliding mass and sliding bed areas; performing landslide particle motion simulation based on the three-dimensional landslide model; acquiring remote sensing images before and after the landslide; constructing a three-dimensional terrain scene based on a live-action three-dimensional technology according to the remote sensing data and the digital elevation model data of the corresponding period; obtaining and updating particle data according to the landslide particle motion simulation result; performing fusion rendering on the particle data and the three-dimensional terrain scene to obtain a simulation result of superposition of landslide simulation and the three-dimensional scene; the complete process of landslide occurrence can be visually displayed, and damage analysis can be accurately carried out on the landslide.

The invention provides a terrestrial ecosystem service function monitoring and evaluation method, and the method comprises the steps: generating a biological feature vector and an environment feature vector according to biological data and environment data collected in an ecological protection region; performing species identification on the biological feature vector based on a biological large model, performing environment analysis on the environment feature vector based on an environment large model, and obtaining animal and plant information and environment quality evaluation conditions in the ecological protection area; and based on an ecological system evaluation model, carrying out comprehensive reasoning analysis on the organisms, the environment, the comprehensive feature vectors, animal and plant information in the ecological protection area and environment quality evaluation conditions, and evaluating an ecological system service function of the ecological protection area. Wherein the comprehensive feature vector is determined based on the fusion of the biological feature vector, the environment feature vector and the dynamically adjusted weight. According to the method, the overall ecological condition of the ecological protection area can be more comprehensively understood by adopting a large model technology, and more comprehensive, accurate, dynamic and scientific ecological system service function evaluation is provided.

The invention discloses a monitoring, regulating and controlling system and method for a cattle house environment. The system is provided with six units including a multi-dimensional heterogeneous environment parameter real-time acquisition unit and a binocular vision environment image acquisition unit. The acquisition unit acquires data such as temperature, humidity and gas concentration of a cattle house through multiple types of sensors, and the image acquisition unit acquires an environment image by using a binocular camera; after feature extraction and three-dimensional environment reconstruction, the environment state analysis unit comprehensively analyzes data in combination with a preset threshold value, and then the regulation and control execution unit controls ventilation equipment, temperature control equipment and the like to carry out environment regulation. The method comprises the steps of data acquisition, image acquisition, feature processing, environment analysis, equipment regulation and control and the like. According to the invention, comprehensive monitoring and accurate regulation and control of multiple parameters of the environment of the cattle pen are realized, the defects of single monitoring and static regulation and control strategy in the prior art are overcome, a suitable growth environment is created for cattle herds, and the breeding benefit is improved.

The invention relates to the technical field of environment analysis, in particular to a system for evaluating the influence of land-based aquaculture on a marine environment, which comprises a data center and a water quality monitoring end. The water quality monitoring end is used for being arranged in a water body around the land-based aquaculture farm so as to obtain water quality data around the land-based aquaculture farm. The data center is used for determining the types and volumes of pollutants released to the water body by the land-based aquaculture farm according to the water quality data, and determining a water flow path from the land-based aquaculture farm to the ocean according to a hydrodynamic model; according to the water flow path, the pollutant types, the pollutant volume and the self-cleaning capacity of the water flow path, the types and the volume of the residual pollutants entering the ocean are determined, and finally according to the types and the volume of the residual pollutants, the influence degree on the ocean environment is evaluated. The method can effectively evaluate the potential influence of land-based aquaculture on the surrounding water environment and marine environment, and can provide reference for water environment treatment and land-based aquaculture.

The invention discloses a regional thermal environment analysis implementation method and device and a storage medium, and relates to the technical field of thermal environment analysis. According to the regional thermal environment analysis implementation method, the change trends corresponding to all adjacent positions of different land cover types in remote sensing data can be mined by lengthening the time dimension, and the weight parameter corresponding to each land cover is determined by combining all the change trends; the weight parameter can measure the influence degree of the earth surface coverage on the thermal environment of the target area. And finally, analyzing the thermal environment corresponding to the target area according to all the land surface coverage and the weight parameter corresponding to each land surface coverage. Therefore, the effective content of the remote sensing data can be fully mined, so that the accuracy and reliability of regional thermal environment analysis are improved.

A system and method for contextual three-dimensional messaging in augmented reality (AR) environments is disclosed. The system receives chat messages with specified real-world destinations and stores them associated with those locations. When a user wearing an AR device enters a destination location, the system detects their presence using techniques like GPS, Wi-Fi positioning, or computer vision. It then generates a 3D visual representation of the message and determines an appropriate spatial position within the physical environment based on environmental analysis and object detection. The 3D message is displayed at the determined position in the AR view. The system can analyze message content to identify topics and match them to detected real-world objects for contextual placement. Users can interact with displayed messages through gestures or voice commands to reply, forward, delete, or reposition messages. This enables immersive, location-aware messaging experiences that seamlessly blend digital content with the physical world.

The invention relates to the technical field of ecological restoration, in particular to a plateau lake ecological restoration monitoring method and system. The method comprises the following steps: acquiring a target plateau lake image and spectral image data, and performing water storage and environment analysis on the acquired image data and spectral image data; constructing a target plateau lake ecological model according to the water storage capacity and a water area analysis result after environment analysis, segmenting the ecological model according to water areas, and performing ecological assessment on different water areas; combining evaluation results, displaying the combined evaluation results in a grade form, dividing the combined evaluation results into four grades from high to low, setting a restoration threshold value, highlighting and marking the water area with the evaluation grade lower than the restoration threshold value, and displaying the ecological problem and the restoration method of the water area; the system comprises an image acquisition module, an ecological evaluation module and a restoration determination module. According to the method, the ecological difference of different areas in the lake can be revealed, a clear direction is provided for making a restoration plan, the actual restoration work can be guided, and the restoration efficiency and effect are improved.

The invention discloses a rapid diagnosis method for blueberry continuous cropping soil obstacle factors, and belongs to the technical field of soil environment analysis. Based on combined analysis of soil physical and chemical factors, metagenome and metabolome, pathogenic bacteria types and key metabolites significantly related to the blueberry continuous cropping obstacle are extracted, and a characteristic diagnostic index system is formed. The index system comprises main pathogenic bacteria types, typical harmful metabolites, key soil physical and chemical factors and appropriate or risk threshold ranges thereof, and provides a scientific basis for rapid identification of soil continuous cropping obstacles. Comparative analysis is carried out by establishing a standardized index library, rapid comparison of related indexes and standard indexes in a newly sampled soil sample is realized, and whether the soil has continuous cropping obstacle risks or not is judged in an auxiliary manner by integrating the deviation degree of physical and chemical factors and biological factors.

The invention discloses an ultratrace mercury isotope analysis method, and relates to the technical field of environmental analysis. The method comprises the following steps: purging a liquid sample to be detected by nitrogen in a stannous chloride atmosphere, and trapping and concentrating mercury into a gold trapping tube; pyrolyzing the pyrolytic gold trapping tube to release mercury vapor; pyrolytic mercury vapor and thallium isotope internal standard aerosol are mixed to serve as a sample injection sample, and the sample injection sample is introduced into a multi-receiver inductively coupled plasma mass spectrometry; acquiring a mercury instantaneous signal and a thallium isotope signal; and calculating the mercury isotope ratio by adopting least square linear regression fitting in combination with a thallium internal standard ratio correction algorithm. According to the method, the instantaneous mercury isotope signal is generated by online combination of gold trapping and multi-receiver inductively coupled plasma mass spectrometry, the instantaneous signal is strategically collected and processed, the determination concentration of isotope analysis can be greatly reduced, the sensitivity of the method is remarkably improved, and direct determination of mercury isotope composition in a water sample with the concentration of 10 ng L <-1 > is met.

The invention discloses a forest tree planting environment analysis and optimization method based on big data, and relates to the field of forest tree planting, and the method comprises the steps: obtaining high-resolution vegetation index data of a target region for continuous N years; eliminating fluctuation interference of clouds and seasons of the high-resolution vegetation index data to construct a pixel-by-pixel vegetation growth track; obtaining artificial forest tending data, meteorological observation data and topographic data of the target area for continuous N years; according to the pixel-by-pixel vegetation growth track, the artificial forest tending data, the meteorological observation data and the topographic data, carrying out region attribute division to obtain a region division result; and optimizing forest planting strategies corresponding to the fluctuation area and the degradation area in the area division result in combination with artificial forest tending data. According to the method, the problems of unstable remote sensing data, insufficient adaptive modeling, extensive optimization strategy and the like in the prior art are solved, and the method has remarkable ecological value and application prospect.

The invention relates to the field of environmental analysis, and provides a gas hydrate three-phase coexistence region modeling method and system. The method comprises the following steps: acquiring three-dimensional seismic data and original logging data, and preprocessing the original logging data to obtain corrected logging data; respectively performing logging interpretation and structural interpretation according to the corrected logging data and the three-dimensional seismic data to obtain interpretation results; converting a structure interpretation result in the interpretation results into a three-dimensional geological structure model, and performing grid division on the research area by adopting a corner grid system to obtain a structure grid model; and performing attribute modeling on the constructed grid model based on variation function analysis, and predicting porosity and saturation in a three-dimensional space through a Kriging interpolation algorithm to obtain a three-phase coexistence region model. According to the method, the influence of complex geological conditions on the accuracy of the model is reduced, and the precision of the three-phase coexistence region model is remarkably improved.

The invention discloses an unmanned aerial vehicle outdoor charging platform and charging method, relates to the technical field of unmanned aerial vehicle charging management and control, and improves the outdoor charging efficiency of an unmanned aerial vehicle. The method comprises the following steps: filling a path environment analysis space according to real-time dynamic and static environment data, setting a base station charging point position in the path environment analysis space, setting a photovoltaic space point in the path environment analysis space, and marking each photovoltaic space point as a photovoltaic charging space point by analyzing real-time dynamic environment data of each photovoltaic space point; and setting a dynamic mark of a space-time dimension for each photovoltaic charging space point, setting a corresponding unmanned aerial vehicle node in the path environment analysis space, and carrying out charging simulation on each unmanned aerial vehicle node by taking the next inspection target of the unmanned aerial vehicle as an end point. And selecting a photovoltaic charging space point and a base station charging point in the path environment analysis space according to a simulation result to generate a short-term flight path.

The invention discloses homogenization equipment for rubber asphalt processing, and relates to the technical field of rubber asphalt processing equipment, the homogenization equipment comprises an intelligent control system, the intelligent control system comprises a data analysis module, a homogenization analysis module, a compensation analysis module and an execution judgment module; the data analysis module is used for receiving and processing the sensing data sent by the sensor group to obtain a statistical index of any parameter in the sensing data; performing environment analysis on the data preprocessed by the sensor group in combination with a statistical index to obtain a homogeneous analysis result; and the homogenization analysis module is used for evaluating the mixing quality in the stirring process based on the homogenization analysis result. By arranging the multi-dimensional sensor group in the mixing box and constructing the three-dimensional space model, real-time three-dimensional monitoring and intelligent analysis of temperature, viscosity and concentration parameters in the rubber asphalt mixing process are realized, parameter abnormal points and trend changes can be identified, and the problems that traditional equipment is lagged in monitoring and cannot capture spatial distribution characteristics are solved.

Provided are a smoke visualization detection system and method for a wind generating nacelle. When the video monitoring module judges that smoke exists in the wind generating nacelle, it issues a smoke change instruction; the smoke detection module collects smoke visualization detection data for a plurality of collection time intervals; the data analysis module analyses the smoke visualization detection data, calculates a sub-smoke visualization detection data change coefficient and a smoke visualization detection data transmission coefficient; the environment analysis module determines a historical transmission behavior and current data transmission environment data, and calculates a data transmission influence coefficient; the data transmission module obtains a target smoke visualization detection data transmission coefficient based on the data transmission influence coefficient, and adjusts a data transmission strategy, to ensure the transmission speed of the smoke visualization detection data, improves transmission stability and real-time performance, and enhances the fire safety level of the nacelle.

The invention discloses an agricultural inspection robot based on an artificial intelligence technology, relates to the technical field of agricultural inspection, and solves the problem that the growth condition of crops and the pesticide spraying amount in current agricultural farmland are judged according to artificial planting experience. Comprising an image recognition module, an environment analysis module, an acquisition range planning module and an abnormity management module, and the image recognition module is used for detecting and analyzing first image data of a farmland area; the abnormity management module is used for carrying out abnormity management on crops; the acquisition range planning module is used for planning a pesticide spraying area of the unmanned aerial vehicle, and the abnormity management module is used for performing fixed-point spraying by using the unmanned aerial vehicle according to the pesticide spraying area of the unmanned aerial vehicle; the environment analysis module is used for detecting and analyzing the farmland environment data of the farmland area after pesticide spraying, the abnormity management module is further used for managing crops, and intelligent analysis of the corresponding growth state of the crops and the pesticide spraying amount in the agricultural farmland is achieved.

The invention discloses a forest fire intelligent monitoring and early warning method and system based on a multi-modal large model, and the method comprises the steps: carrying out the fire recognition and environment analysis based on a multi-modal data fusion mechanism of the multi-modal large model in combination with multi-source data collected by an unmanned plane; an auxiliary early warning solution is automatically generated for the fire by combining a multi-modal model with a forest ranger inspection report, an unmanned aerial vehicle inspection video and a fire analysis result, and emergency processing suggestions are provided; massive multi-source heterogeneous data in the forest fire intelligent monitoring and early warning system is efficiently stored, managed and retrieved, the distributed training and reasoning process of a multi-modal large model is optimized, and it is ensured that the system can achieve rapid and accurate fire monitoring and early warning in a complex natural environment. According to the invention, full-process automatic management and comprehensive analysis from data acquisition, fire monitoring to analysis and decision making are realized, and problems of insufficient intelligent identification capability, high false alarm rate and low data integration analysis efficiency in the existing forest fire monitoring and early warning process are solved.

The invention discloses a GNSS integrated navigation positioning module positioning precision evaluation system, and relates to the technical field of satellite navigation. The specific implementation process comprises the steps that firstly, an environment analysis module is provided, the module combines environment meteorological data and environment point cloud data extracted by visual data to obtain positioning errors from the angles of weather change and obstacle shielding, and the influence of a complex environment on positioning precision is comprehensively considered; secondly, a dynamic precision evaluation module is designed, dynamic errors are calculated according to dynamic behaviors of visual data capture equipment, and the positioning performance of the module under complex motion is effectively evaluated; finally, the invention provides a comprehensive precision evaluation module, the positioning error of the module is comprehensively calculated and graded in combination with target position data, system errors, an environment analysis result and a dynamic evaluation result, and the accuracy of positioning precision evaluation is further improved.

The invention relates to the technical field of environment analysis, in particular to a building construction environment monitoring system based on big data analysis, which comprises a wind direction correlation analysis module, a flying dust data prediction and evaluation module and a flying dust detector anomaly monitoring module. The wind speed threshold value is determined, clues can be provided for determining the area corresponding to the flying dust data abnormity in combination with the wind direction information to a certain extent, although the positioning difficulty is increased due to flying dust drifting along with wind, the analysis of the module is beneficial to narrowing the abnormal area range, and a direction is provided for follow-up precise flying dust treatment; the flying dust data prediction and evaluation module can accurately predict the flying dust data influenced by the wind speed and determine the flying dust data generation area when establishing the multiple linear regression model, the flying dust data generation area can be determined through accurate prediction, a flying dust source can be quickly found, and management personnel can conveniently take dust prevention and falling measures in a targeted mode.

The invention discloses an intelligent agricultural management method and system based on computer analysis, and particularly relates to the technical field of agricultural information, and the method comprises the following steps: obtaining farmland resource information, obtaining and processing a farmland resource information set, obtaining an environment data set and a growth data set according to a processing result, and then carrying out the environment analysis and growth analysis, a growth deviation combination and an environment deviation combination are obtained, a crop classification combination set of the target farmland is further obtained, category code numbers are generated, corresponding abnormal type early warning signals and comprehensive abnormal levels are generated according to the category code numbers and a preset early warning strategy and summarized, and an early warning combination set is obtained; by monitoring and analyzing the environment condition and the crop growth state of the farmland in real time, problems in agricultural production can be found and solved in time, various potential problems and risk factors in the farmland can be identified, and basis data of a precise management strategy can be provided for agricultural production.

A system and method for managing autonomous aerial vehicle ingress and payload exchange is disclosed. A beacon unit receives a digitally encoded ingress request from an autonomous aerial vehicle, the request comprising an identity token. A smart contract engine evaluates the identity token against mission-specific conditions to authorize ingress. An environmental analysis processor generates a map of the region surrounding the beacon unit using data from multiple sensor modules, including LiDAR, radar, infrared, audio, and weather sensors. A trajectory guidance engine computes an ingress path based on the environmental map. A virtual protected area generation module defines a three-dimensional protected zone for descent, and a classification engine assigns a safety classification to the zone based on predefined criteria. A beacon control interface transmits the ingress path to the vehicle and monitors descent for compliance. A user authentication subsystem verifies the identity of a human user at the landing zone prior to payload release.