19 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 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.

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 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 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 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.

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.

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.

This invention relates to the field of agricultural fertilization, and more particularly to an optimized method for straw return fertilization that integrates soil carbon-nitrogen ratio. The method includes: standardizing farmland static feature data to obtain standardized feature vectors and feature standardization thresholds; performing coupling analysis on the straw return amount and soil carbon-nitrogen ratio in the standardized feature vector pool to obtain risk factors; integrating the risk potential energy field function using path gradients to obtain symmetric path cost gain factors; correcting path cost gain using Euclidean distance to obtain an adaptive distance metric; and performing fuzzy C-means clustering on the standardized farmland feature vectors using the adaptive distance metric to obtain differentiated fertilization management zones. This solves the problem that existing Euclidean distance-based management zones cannot identify key feature nonlinear coupling risks, leading to inaccurate fertilization decisions.

The invention relates to the technical field of soil fertility detection, in particular to a soil fertility intelligent evaluation method and system combined with weed growth characteristics, and the method comprises the steps: collecting and preprocessing image data of a target planting area, and obtaining standard image data; inputting pixel blocks in the standard image data into a pre-constructed classification result prediction model, and outputting a classification result of the pixel blocks; dividing the target planting area into regular grids according to a fixed scale; the weed density in each grid area is sequentially obtained, a weed density difference threshold value is preset, when the weed density difference value of the adjacent grids is smaller than or equal to the preset weed density difference threshold value, the adjacent grids are combined into an independent fertilization management area, and a plurality of independent fertilization management areas are obtained. According to the method, the target planting area is divided into the regular grids, and the adjacent grids are combined in combination with the weed density difference threshold value, so that a plurality of independent fertilization management areas are formed, and the extensive management problem caused by traditional whole land fertilization is effectively avoided.