33 results about "Management zones" patented technology

The invention relates to the field of agricultural data analysis, in particular to a straw returning effect analysis method combining soil nutrients and crop yield, and the method comprises the steps: collecting a multi-source feature data matrix for risk assessment; performing conjoint analysis on the crop yield data and the soil attribute data to obtain a static nitrogen deficiency risk amplification factor; performing difference analysis on the vegetation index data, the yield data and the cluster centroid to obtain a dynamic growth response asymmetric regulatory factor; carrying out fusion evaluation on the static nitrogen deficiency risk amplification factor and the dynamic growth response asymmetric regulation factor to obtain risk perception asymmetric distance measurement based on yield data; the clustering process of risk perception asymmetric distance measurement based on yield data is subjected to zoning optimization, and an optimal management zoning result for formulating a variable fertilization strategy is obtained, so that the nitrogen deficiency risk of crops in the seedling stage is reduced, and the nutrient utilization efficiency and the yield stability are improved.

The invention discloses a distributed improvement method and device for farmland crop irrigation water productivity. The method comprises the steps that soil physical indexes and nutrient indexes are obtained; performing management area division on the farmland by using a fuzzy clustering method based on the soil physical indexes and the nutrient indexes; sorting the contribution rate of each soil index to the crop irrigation water productivity in each management partition by using a partial least square discriminant analysis method to obtain a driving factor of the crop irrigation water productivity; using a boundary line analysis method to determine a regulation threshold value of a crop irrigation water productivity driving factor in each management area; calculating actual stage water consumption of crops in each management area, establishing an irrigation system optimization model, and performing multi-objective optimization solution on the irrigation system optimization model by applying a genetic algorithm to obtain an optimized irrigation system; and combining the regulation and control threshold value of the crop irrigation water productivity driving factor with the optimized irrigation system to obtain a farmland distributed crop management scheme, so that the crop irrigation water productivity is improved.

The invention provides an underground drainage pipeline detection method and device, and belongs to the technical field of underground pipeline detection, and the method comprises the steps: recognizing and randomly extracting a first number of first pipeline nodes and a second number of second pipeline nodes, and updating the particle position and speed based on a particle swarm algorithm, and obtaining a target pipeline node corresponding to each particle until the absolute value of the difference between the updated total fitness value and the total fitness value obtained in the previous process is smaller than a target threshold value, and deploying a sensor on the target pipeline node to detect the drainage pipeline. According to the detection method of the underground drainage pipeline, the sensor deployment scheme is optimized through the particle swarm algorithm, the specific conditions of different management areas and different pipeline conditions can be fully considered under the condition that the number of the sensors is limited, the monitoring effect of an underground pipeline network is maximized, and the reliability of underground drainage pipeline detection is improved.

The invention discloses an oil sunflower field precise fertilization control system based on an unmanned aerial vehicle hyperspectral technology, and relates to the technical field of fertilization control. The system carries out precise region division on an oil sunflower field by utilizing a GIS technology through fusion of multi-source data such as hyperspectral data, soil humidity and temperature; and accurate fertilization can be carried out in different management areas according to soil characteristics and crop requirements. The differentiated fertilization strategy can reduce excessive fertilization and fertilizer waste and optimize the utilization efficiency of the fertilizer. The crop growth model is established through the deep learning technology, and the system can accurately calculate the required fertilization amount according to the specific growth conditions and historical data of each region, so that the growth conditions of the oil sunflowers are optimized, and the overall yield of crops is improved. The problem that a traditional fertilization system is difficult to effectively deal with soil and environment differences in different areas is solved. Through a hyperspectral technology and multi-source data acquired by a sensor, the system can realize accurate fertilization according to environmental differences in a field.

Methods and systems provided for generating a soil data map. One example method includes instructing, by a computing device, a user to draw a field boundary in a map of a geographic area and receiving an input, from the user, at the map of the geographic area, where the input includes multiple vertices of the field boundary. The method also includes appending, by the computing device, a shape of the field boundary to the map, based on the multiple vertices, and overlaying at least one management zone within the field boundary on the map. The at least one management zone is associated with specific soil data for the geographic area corresponding to the at least one management zone within the field boundary.

The invention relates to the technical field of water and fertilizer intelligent management, and particularly discloses an intelligent water and fertilizer management method and an operating system, and the method comprises the steps: obtaining region parameters of a water and fertilizer management region, and determining sampling points and movement tracks according to the region parameters; acquiring environmental data in real time according to sensors installed at sampling points, and determining the inhibition ratio distribution condition of the water and fertilizer management area at each moment according to the environmental data; acquiring actual growth parameters of the crops regularly, and correcting the inhibition ratio distribution condition at each moment according to the actual growth parameters; superposing the corrected inhibition rate distribution conditions, and determining a water and fertilizer management work order; according to the invention, the environmental data is obtained according to the sampling points, the environmental data is uniformly converted, the parameter of the inhibition ratio is obtained, the inhibition ratio of each position in a period of time is counted and is used as the reference of the water and fertilizer management process, and the obtained water and fertilizer management scheme is extremely high in refinement degree and intelligence degree.

A method and system for a hydrological process that describes and characterises either statically or temporally, soil moisture variability within agricultural fields, specific to zone-based field recommendations. Surface and subsurface hydrological processes are combined with soil physical properties, electrical conductivity (EC), topography, soil moisture sensors and climate parameters from weather stations, to produce a zone-based soil moisture balance. This process facilitates in-season optimization of crop inputs such as water from irrigation, seed, nutrients, herbicides, or pesticides based on the soil moisture conditions throughout a field.

The invention provides a forestry pest control management system and method, and belongs to the technical field of forestry pest control management, and the method comprises the steps: building a pest distribution diagram of a target forestry region through management block division and pest information of the target forestry region, and determining a distribution network of insect repelling points in each management block; determining a plurality of variable insect repelling points according to the recovery rate and the natural recovery rate of each management block in the insect repelling process, and determining a dynamic layout strategy of the insect repelling points in each management block according to all the variable insect repelling points; and through all the distribution networks and all the dynamic layout strategies, predicting an insect repelling controllable range of each management block of the target forestry region, and performing risk assessment on the pest and disease damage of the current target forestry region according to all the insect repelling controllable ranges. According to the scheme, the influence of non-uniform pest and disease distribution in the forestry area on pest and disease control of a forestry area monitoring department can be weakened, so that the control effect of the forestry area monitoring department is improved.

This invention discloses an ecological management zoning method and system based on static and dynamic supply and demand matching, belonging to the field of ecological management technology. The invention constructs a node feature matrix by calculating a comprehensive static supply and demand matching index and a comprehensive dynamic change trend index, then generates a dynamic spatiotemporal adjacency matrix to construct a spatiotemporal physical connectivity graph. This graph is then input into a spatiotemporal graph neural network for processing, outputting predicted static supply and demand matching indices and predicted dynamic change trend indices. Based on the zero-value boundaries of these indices, the study area is divided into initial four-level basic management zones. A Markov decision process is then constructed, and a Pareto optimal solution set is obtained through reinforcement learning algorithms to fine-tune the spatial boundaries of the initial four-level basic management zones. The resulting refined ecological management zoning map and management priority sequence are output, making the zoning results more targeted for management. This solves the problem that existing ecological management zoning results lag behind actual changes and are difficult to effectively support adaptive management.

The present invention is a system and method for agricultural management-zone delineation to be done over broad geographic extents without overly-localized field-specific data. The instant innovation guides precision agricultural sampling and management by delineating enhanced management zones based upon remote sensing and artificial intelligence and combining the two with data derived from an existing countrywide soil survey database. In an embodiment, the instant innovation uses artificial intelligence from multiple sources to provide granular zone detail. Output of the present innovation can be aggregated to produce management zone sizes that have a level of uncertainty compatible with the needs of the customer-farmer and implementable given the capabilities of available equipment.

A method and system for automatically capturing and extracting data from images of agricultural field crops, weeds, and soil within management zones representing soil, water, and topography (SWAT) features of a field wherein the camera system is mounted onto and powered by any vehicle that may pass over agricultural fields. Images and data extracted from the images are automatically uploaded to a processing server for viewing and analysis by farmers and agricultural service providers. The images are analyzed by machine learning processes to document critical weed and crop data by SWAT management zone and entire fields.

The invention discloses an agricultural data management system and method based on digital visualization, which belongs to the field of artificial intelligence technology. The invention comprises the following steps: establishing a map model; marking the plots of each farmer in the map model according to the farmer serial number; analyzing the crop yields of different crops planted in each plot in the to-be-managed area and the average crop yields of the same crops in the to-be-managed area, and screening the plots; analyzing the best management schemes for plots of different land types when different crops are planted in different seasons; analyzing the recommended management schemes for the plots to be managed in the to-be-managed area at the current time according to the plot data of the plots to be managed in the to-be-managed area at the current time; and outputting visualized data. The invention integrates the agricultural data of different farmers and their plots, thereby breaking the information island phenomenon between data collection and data analysis, and improving the utilization rate of land and the efficiency of agricultural production.

A geofence-based environment management system and method are disclosed. A geofence-based environment management system according to one embodiment may comprise: a control server for setting, as a geofence, a range of a region including a management zone, and analyzing the environment state of the management zone on the basis of environment information of the geofence; and one or more management devices which are disposed in the management zone and manage the environment of the management zone on the basis of the analysis of the control server.

The invention discloses a whole-chain intelligent tracing and grading system for agricultural products. Belongs to the technical field of intelligent agriculture, and the structure can integrate data of each link and automatically complete dynamic quality grading based on real-time and historical data in circulation, and comprises a data acquisition module, an identifier management module, a block chain evidence storage module, a grading processing module and a query service module. The data acquisition module acquires process data of each link; the identification management module generates a unique identification code and associates data; the block chain evidence storage module stores the identification code, the data and the hash value to form a traceable data chain; the grading processing module calculates the quality grade of the agricultural product through a preset analysis model according to the link data and the historical data on the chain in the processing, storage, transportation or sales link, and sends the result to the block chain evidence storage module for storage; and the query service module obtains and outputs a complete traceability data chain and all quality grade records from the chain according to the identification code.

The application discloses a kind of based on air-ground-water three-dimensional perception southern large irrigation district intelligent system and method, system includes air-ground-water three-dimensional data acquisition layer, internet of things platform layer, management area decision layer and production area execution layer, management area decision layer includes multi-source heterogeneous data space-time fusion module, to adaptive Kalman filtering and space-time Kriging interpolation realizes the two-stage space-time fusion of air-based, ground, water body three types of sensor data Generation full irrigation area gridded physical quantity distribution field, and model online calibration and decision confidence evaluation module, to variational bayes inference and extended Kalman filtering realizes model parameter posterior inference and state real-time prediction, when parameter relative uncertainty is over threshold, it is automatically switched to safe scheduling mode, still include based on Saint-Venant equation group's four prediction function hierarchical progressive execution and based on FAO Penman-Monteith formula's water resource supply and demand balance optimization;The method is suitable for the intelligent construction of southern large irrigation district.

The present invention is a system and method for agricultural management-zone delineation to be done over broad geographic extents without overly-localized field-specific data. The instant innovation guides precision agricultural sampling and management by delineating enhanced management zones based upon remote sensing and artificial intelligence and combining the two with data derived from an existing countrywide soil survey database. In an embodiment, the instant innovation uses artificial intelligence from multiple sources to provide granular zone detail. Output of the present innovation can be aggregated to produce management zone sizes that have a level of uncertainty compatible with the needs of the customer-fanner and implementable given the capabilities of available equipment.

The application relates to the technical field of intelligent water and fertilizer management, and particularly discloses an intelligent water and fertilizer management method and an operation system, which comprises the following steps: acquiring regional parameters of a water and fertilizer management area, determining sampling points and their motion trajectories according to the regional parameters; acquiring environmental data in real time according to sensors installed at the sampling points, determining the inhibition rate distribution of the water and fertilizer management area at each moment according to the environmental data; acquiring actual growth parameters of crops at regular time intervals, correcting the inhibition rate distribution at each moment according to the actual growth parameters; superimposing the corrected inhibition rate distribution to determine a water and fertilizer management work order; and the application obtains environmental data according to the sampling points, uniformly converts the environmental data, obtains the inhibition rate as a parameter, and statistically obtains the inhibition rate at each position within a period of time as a reference for the water and fertilizer management process, so that the obtained water and fertilizer management scheme has extremely high refinement and intelligence.

The present invention relates to the technical field of environmental data monitoring, and discloses an agricultural environment comprehensive monitoring support system based on multi-source data fusion, constructs an environmental monitoring blockchain, divides the environmental monitoring blockchain into multiple planting management areas through vegetation area deployment, collects plant planting information with timestamps in the planting management areas, processes the plant planting information and divides it into multiple plant species fields, and respectively sets storage nodes based on the plant species fields; hierarchically sets the data in the plant species fields based on the storage nodes, collects the monitoring information of the current plant species in real time, and extracts planting feature data from the monitoring information according to the timestamp; predicts the crop biomass and the corresponding yield estimate of the next stage based on the monitoring information in the plant species fields; evaluates the growth status of the current crop based on the yield estimate, writes an intelligent contract based on the growth status of the crop, and establishes a crop management strategy based on the intelligent contract.

The invention discloses a landscaping management method and system based on data monitoring, and relates to the field of greening management, and the method comprises the following steps: setting each management region, and collecting predicted meteorological data and image data in the management region; dividing the image data into image sub-regions according to greening function differences of the corresponding image data; setting a meteorological data distribution interval, judging the climate to which the management area belongs according to the meteorological data distribution interval to which the predicted meteorological data belongs, and setting a comparison threshold value of the meteorological data and the greening area in the corresponding greening function image sub-area according to the climate to which the management area belongs; the collected data information is compared with a set comparison threshold value, and corresponding task information is generated; setting priorities of the task information, and setting task completion time thresholds from small to large according to a sequence of the priorities from high to low; task completion conditions of workers are obtained, and tasks of all the management areas are scheduled; according to the method, the scientificity of greening management is improved to a certain extent.

The application relates to the technical field of intelligent agricultural control, and particularly discloses an intelligent agricultural control system based on big data, which collects soil conductivity time series data, yield data, elevation data, meteorological data and variety cultivation attributes in multiple growth seasons; generates a whole field intrinsic conductivity distribution map after removing high-frequency disturbance of conductivity; separates variety effects and cultivation effects based on causal inference to obtain a corrected yield distribution map; superimposes the intrinsic conductivity, the corrected yield and the elevation, and generates a fine management area boundary through compression embedding and spatial constraint clustering; takes a benchmark reference area as a reference, determines unique fertilizer amount and irrigation threshold values of each management area according to a comprehensive coefficient, and generates a variable operation prescription map; the application eliminates the interference of short-term environmental fluctuations and human management on management area division, reduces the uneven growth phenomenon, and realizes water and fertilizer distribution according to needs.

The invention discloses an efficient digital WMS warehouse management system and method, and relates to the technical field of warehouse goods identification, and the system comprises a central scheduling engine which is used for program execution and data calculation, a multi-level storage module which is used for managing regional warehouses and maintenance point warehouses, and a dynamic cost optimization module. The industrial equipment consumable scheduling cost between a warehouse and a maintenance point is calculated in real time, the hidden weighing terminal integrates an RFID scanning module and a hidden weighing sensor and completes warehousing of the multi-level warehousing module, and the weight deviation analysis module is used for measuring and analyzing the weight of industrial equipment consumables. An optimal scheduling scheme is calculated in real time through a dynamic cost optimization module, the long-term industrial equipment consumables are accurately distributed to a high-usage-amount maintenance point for centralized promotion, a dynamic discount strategy is matched, logistics and storage cost is compressed, a maintenance point warehouse is used as an emergency node to replace a traditional rental warehouse, manual operation cheating is completely eradicated, and the maintenance point warehouse is used as an emergency node to replace the traditional rental warehouse. The hidden weighing terminal adopts a triple anti-cheating design.

The present application relates to the field of agricultural data analysis, and more particularly to a method for analyzing the effect of straw returning to field in combination with soil nutrients and crop yield, which comprises: collecting a multi-source feature data matrix for risk assessment; obtaining a static nitrogen deficiency risk amplification factor by jointly analyzing crop yield data and soil attribute data; obtaining a dynamic growth response asymmetric adjustment factor by performing difference analysis on vegetation index data, yield data and cluster centroid; obtaining a risk perception asymmetric distance measure based on yield data by fusing and evaluating the static nitrogen deficiency risk amplification factor and the dynamic growth response asymmetric adjustment factor; and obtaining optimal management zoning results for variable fertilization strategy formulation by partition optimization of the clustering process of the risk perception asymmetric distance measure based on yield data, so as to reduce the nitrogen deficiency risk of crops in the seedling stage, improve the nutrient utilization efficiency and yield stability.

The invention is suitable for the technical field of natural resource management, and provides a natural resource fine management method and platform. The method comprises the following steps: dividing a plurality of management areas, and determining a plurality of corresponding natural resource types; planning a plurality of monitoring routes and monitoring parameters; monitoring and controlling the unmanned aerial vehicle; electric wire and telegraph pole identification is carried out, influence analysis is carried out, and a plurality of influence extension segments are determined; and performing optimization analysis on the plurality of influence extension fragments to generate a plurality of optimized extension fragments. Management areas corresponding to a plurality of natural resource types can be divided, monitoring planning and monitoring control can be carried out, monitoring data of a plurality of areas can be acquired, identification, influence analysis and optimization analysis of electric wires and telegraph poles can be carried out, and a plurality of influence extension segments with adverse influences of the electric wires and the telegraph poles can be determined according to different natural resource types. And a plurality of corresponding optimized extension segments are planned, so that the damage of the electric wire and the telegraph pole to the diversity of land, vegetation and biology is reduced.

The object of the present invention is to provide a decision-making method, system and device for cluster irrigation operation of unmanned farm sprinkler units, which relate to the fields of agricultural information measurement and agricultural irrigation technology. The method includes: dividing the current variable irrigation management unit into multiple management blocks based on the shape and size of the minimum management block; determining the expected irrigation water volume of all management blocks in the current variable irrigation management unit based on the management block division map, the canopy temperature spatial distribution map and the vegetation index spatial distribution map; controlling the current sprinkler unit to complete irrigation according to the expected irrigation water volume of each management block in the current variable irrigation management unit, so as to complete the irrigation control of the to-be-irrigated unmanned farm. The present invention determines the expected irrigation water volume of each different management block based on the management block division map, the canopy temperature spatial distribution map and the vegetation index spatial distribution map, and can perform automatic irrigation operation on the unmanned farm, improving the automation level of the cluster irrigation operation of the sprinkler unit.

In one implementation, yield data representing the yields of crops harvested in an agricultural field is received, along with field characteristic data, to determine various management zone delineation options. Each option comprises zone design data. These options are determined by: establishing several count values ​​for a management class; generating, for each value, a management delineation option by grouping the yield data and field characteristics, assigning zones to the groups, and including those zones in the option. One or more options are selected to determine one or more planting plans. A graphical representation of the options and planting plans is displayed to the user.

A soil modeling and mapping framework for use in precision agriculture analyzes remotely-sensed data pertaining to characteristics of one or more agricultural fields, and determines optimal sampling locations from information in remotely-sensed information, terrain derivatives and satellite imagery, to develop a customized sampling design for modeling soil properties in such agricultural fields that optimized for the particular landscape in such fields. The soil modeling and mapping framework then analyzes soil samples collected based on the customized sampling design in machine learning-based models that predict soil properties in sampled, semi-sampled, and unsampled target fields. The predicted soil properties are used to develop highly-accurate maps of soil properties such as fertility maps, which may further be used for defining and creating one or more management zones with recommendations for applying the right amount of nutrients at variable rates in the correct areas.

The application discloses a kind of deep well double working face meeting compound disaster energy segmentation control method, first in mining area 1 and mining area 2 between determining management area, and in management area within division first to fourth area form continuous management zone, each area has specific function, first area and third area are energy absorption zone, for absorbing subsequent mining and tunneling process produced in situ stress energy and gas impact energy;Second area is energy segmentation zone, for the energy produced by mining area 1 and the energy produced by mining area 2 is segmented;Fourth area is energy resistance zone, for resisting the in-situ stress energy from mining area 1 after weakening through first area to third area;Through the synergistic effect of four areas, in-situ stress absorption, segmentation and resistance can be realized simultaneously, the in-situ stress energy and gas energy in the whole coal seam are segmented and absorbed respectively, to reduce the risk of compound disaster, so as to realize the safe mining of mining area 1 and mining area 2.

The invention relates to the related technical field of cultivated land measurement planning, discloses a land measuring method and system for space planning, and is suitable for cultivated land planning management in an agricultural scene. The terrain structure, terrain features and the like of the ground are obtained and modeled through ground remote sensing data obtained through high-altitude shooting based on a satellite or unmanned equipment, so that feature gradient evaluation is performed on a planning region under a twin model, and cultivated land region division can be performed based on the feature gradient; the cultivated land in the same management area has better feature consistency, and subsequent cultivated land management and maintenance are facilitated.

The present invention is a system and method for delineating agricultural management zones over a broad geographic area without overly local, field-specific data. The current innovation guides precision agriculture sampling and management by delineating enhanced management zones based on remote sensing and artificial intelligence and combining the two with data derived from existing national soil survey databases. In an embodiment, the current innovation uses artificial intelligence from multiple sources to provide granular area details. The output of this innovation can be aggregated to produce management zone sizes with an uncertainty level that is adaptable to the needs of the customer farmer and implementable given the capabilities of the available equipment.