220 results about "Farming environment" patented technology

The invention discloses an agricultural environment intelligent control system based on artificial intelligence and a control method thereof, and belongs to the technical field of agricultural intelligent control and artificial intelligence application. According to the method, agricultural sensor data and image data are jointly packaged into a standardized AI input structure by adopting prompt engineering and semantic modeling means; a general large language model or an image recognition model is accessed, and comprehensive evaluation of complex crop states is realized through customizing a Prompt semantic structure; constructing a natural language analysis engine, and converting the control suggestion returned by the AI into a structured command; the Agent module is used for completing control opportunity judgment, control path planning and effect feedback adjustment, and strategic intervention on the whole agricultural control process is achieved.

The invention relates to the technical field of soil moisture content monitoring, and discloses a method and a system for accurately monitoring soil moisture content through remote sensing inversion of an unmanned aerial vehicle. Acquiring original spectral data of different soil types and environmental conditions through a spectral sensor to obtain an initial multispectral image data set; dividing soil types by using a support vector machine classification method according to pixel reflection characteristics to form a soil type grouping set; calculating a multispectral band reflectivity variance for each group, and screening candidate bands to construct a set; processing the candidate wave band set through a random forest regression model, adjusting the weight in combination with an environment variable, and performing iterative screening to form an optimized wave band combination sequence; extracting spectral features of the optimized wave band, and carrying out weighted fusion on the soil variation region to output a processed image; and calculating the soil moisture content by using a linear inversion model based on the pixel reflectivity of the processed image, and outputting a distribution diagram when the deviation reaches the standard. The method is suitable for different soil and environments, the wave band is accurately selected, the precision is improved, and high-quality data is provided for agricultural and environmental governance.

The invention provides an intelligent cattle farm feeding management system, which belongs to the technical field of intelligent agriculture and animal husbandry, and comprises a data acquisition module, a data processing module, a control module, a user interface module, a communication module and a storage module. The system obtains cattle farm environment and cattle physiological behavior data in real time through a multi-source sensor and image acquisition equipment, intelligent analysis and decision generation are carried out through algorithms such as machine learning, reinforcement learning and fuzzy logic, and automatic management of functions such as feed feeding, environment regulation and control and health early warning is achieved. The system has the characteristics of comprehensive perception, intelligent decision making and accurate execution, the cattle farm feeding efficiency can be effectively improved, cattle health is guaranteed, and the operation cost is reduced.

The invention relates to the field of animal husbandry industry environment regulation and control system optimization, in particular to a lightweight digital twinborn breeding environment monitoring method and system, and the method comprises the following steps: S1, carrying out the construction of a computational fluid dynamics (CFD) model for a breeding farm environment; s2, environment data are collected; s3, comparing model prediction with real-time data, and monitoring a breeding environment according to a comparison result; and S4, data presentation. According to the invention, through cooperative work of the flow field modeling unit, the environment data acquisition unit, the model prediction and data calibration unit and the visualization unit, light-weight, full-range and high-precision breeding environment monitoring and regulation are realized.

Methods for optimizing path planning for agricultural vehicles are provided. In one embodiment, a field is defined, passes completely covering the field are created, the ends of each pass are transformed into nodes, distance and time matrices for the nodes are computed, and an optimization problem incorporating the time and distance matrices, agricultural constraints, and time window requirements is formulated. Prior to solving the optimization problem, verification that a feasible solution to the optimization problem exists is performed, and constraints are adjusted if a feasible solution does not exist. The optimization problem may be solved using a quantum annealing process to achieve an optimized route that performs well in an agricultural setting.

A system is provided for localizing an autonomous work vehicle within mapped agricultural environments when GPS may be unavailable. Range sensors capture LiDAR images that are segmented by a trained model into features such as trunks and canopy. Trunk points are clustered to compute centroids, which are used to estimate left and right tree lines and a lane centerline relative to the vehicle. This sensor-derived centerline is compared with georeferenced lane and row geometry stored in a digital map. A particle filter maintains multiple pose hypotheses, propagates them using vehicle odometry, and weights them according to alignment between the lane centerline relative to the vehicle and the mapped lane geometry for the particle. Resampling and averaging of high-weight hypotheses produces an adjusted pose that corrects for lateral and heading errors. The adjusted pose serves as input to a navigation controller that issues steering and speed commands, enabling accurate autonomous operation.

The invention discloses a greenhouse climate multi-target intelligent control method fusing rule constraint and reinforcement learning, and relates to the technical field of agricultural environment control, and the method comprises the following steps: building a temperature and humidity dynamic model based on an energy conservation law, and coupling an external environment disturbance term to obtain a temperature and humidity dynamic model; establishing a mapping relation among the temperature, the relative humidity and actuator input data, generating multiple groups of interval training data based on the mapping relation, constructing an intelligent decision model, and screening out an optimal actuator state vector by taking the deviation degree of an environment target value and an interval range as an evaluation criterion; and setting a difference mediation threshold value of mutual exclusion operation for safety correction, adopting environment adjustment difference and energy consumption minimization as optimization objectives, designing a multi-objective reward function, and determining an optimal control instruction, thereby updating an intelligent decision-making model, realizing accurate and efficient greenhouse climate control, enabling the comprehensive control of temperature and humidity to be more accurate and reasonable, and improving the reliability of the greenhouse climate control. And the energy consumption is reduced.

The invention discloses a dexterous hand fruit and vegetable grabbing control method based on fuzzy variable impedance control. The method comprises the following steps: firstly, establishing a multi-finger collaborative kinematics model based on a spinor theory, and determining fingertip poses, grabbing force of each finger and multi-finger resultant force distribution; on the basis of force sealing, an optimization model with the minimum contact force as a target is constructed, an NSGA-II algorithm is adopted for solving, and the minimum grabbing force needed by stable and lossless grabbing is obtained; establishing an impedance control model in a Cartesian space, enabling a grabbing system to be equivalent to a mass-spring-damping system, analyzing the influence of an impedance parameter on grabbing performance, and determining an inertial parameter and a damping coefficient as key adjustment objects; fuzzy control is further introduced, the grabbing force error and the change rate of the grabbing force error serve as input and output inertia and damping adjustment amount, a fuzzy self-adaptive variable impedance controller is constructed, and dynamic optimization of impedance parameters and accurate tracking of the grabbing force are achieved. The fruit and vegetable grabbing device can be effectively applied to rapid, stable and lossless grabbing of various fruits and vegetables in an unstructured agricultural environment.

The invention relates to the technical field of agricultural environment information, and discloses a rice field nitrogen and phosphorus loss amount remote regulation and control method oriented to environment data. The method comprises the following steps: acquiring historical nitrogen and phosphorus loss data, real-time meteorological data and water and fertilizer operation information of the rice field; constructing a mechanism constraint sub-model fusing nitrogen migration and transformation kinetics and phosphorus adsorption and desorption balance; performing multi-source feature extraction on the meteorological data to generate a standardized environment vector; inputting the lightweight residual convolutional neural network to output an initial prediction value; on-line fine adjustment is carried out through a Lagrangian multiplier method in combination with the mechanism model, and a corrected predicted value conforming to substance conservation is generated; and when the predicted value exceeds a threshold value, generating a drainage gate opening degree and fertilization plan adjustment instruction, and issuing the instruction to an edge terminal for execution through the narrowband Internet of Things.

The invention relates to the technical field of agricultural environmental engineering and control, and discloses an agricultural non-point source pollution multistage control planning system and method based on a discussion hall architecture, and the system comprises an organization-level module, an adaptation-level module, a coordination-level module, an operation control-level module, a controlled-level module, a comprehensive integration discussion hall module, and an open external interface module. The organization level uses deep learning and causal inference to generate a full-watershed strategy; the discussion hall module fuses expert experience conversion constraints and carries out case migration; the adaptation level utilizes a recursive algorithm to dynamically correct model parameters; the coordination level adopts a hybrid optimization algorithm to solve a multi-objective optimization problem; the operation control level is combined with a feedforward feedback mechanism to generate an instruction; the controlled level executes actions and collects feedback; and the interface module is responsible for security encryption and verification of data interaction. According to the method, the expert intelligence of the discussion hall and the five-level hierarchical architecture are fused, qualitative and quantitative combination and full-basin dynamic collaborative optimization are realized, and the management and control precision and the response speed are improved.

The invention relates to the technical field of farm environment monitoring and control, in particular to a farm environment monitoring system based on digital twinning. Comprising a data acquisition module for acquiring multi-dimensional state data of a culture water body in real time; the twinborn modeling module is used for describing a digital twinborn model of a delay relation between control input and state response; the sequence generation module is used for generating a plurality of candidate multi-step control sequences; the simulation module is used for obtaining a plurality of corresponding prediction state trajectories; the evaluation module is used for extracting multi-target performance indexes of the plurality of prediction state trajectories; the control decision module is used for determining a sequence with the minimum comprehensive cost value as an optimal multi-step control sequence; the state monitoring module is used for monitoring an actual state track; the confidence coefficient calculation module is used for calculating the twin deduction confidence coefficient; and the correction triggering module is used for triggering the twinborn modeling module to update the digital twinborn model by utilizing the monitored actual state track. According to the system, accurate, efficient and low-cost regulation and control of the breeding environment are realized, and the scientificity of decision making is improved.

The invention belongs to the technical field of microorganisms, and particularly relates to Chryseobacterium sp. 2R14A and application of the Chryseobacterium sp. 2R14A. The strain is excellent in oxidation resistance, still can grow after being treated by 80mM hydrogen peroxide for 30 minutes, and is not completely inactivated after being treated by 160mM hydrogen peroxide, and a genome contains antioxidant related genes; growth conditions are mild, sodium chloride is not needed, large-scale culture is easy, cost is low, and physiological and biochemical characteristics are stable. The strain can be used for treating oxidizing agent-containing polluted environment and improving stress resistance of crops or microorganisms, can also be used as a gene engineering recipient bacterium or a mutation breeding material, and expands application in the fields of agriculture, environment and medicine.

The present application relates to the field of agricultural environmental protection method, particularly to a method for reducing the pollution of vegetable field soil non-point source and N2O.The method provided by the present application fully considers the carbon and nitrogen content, C / N and cellulose content of different exogenous carbon materials, reduces the application of chemical fertilizer nitrogen under the premise of ensuring the nitrogen supply of vegetables according to the nitrate nitrogen content of vegetable field soil, increases the amount of effective state carbon and the content of holocellulose by optimizing the combination and proportion of different exogenous carbon materials, improves the nitrate nitrogen assimilation of vegetable field soil, reduces the nitrogen leaching and soil N2O emission, and realizes the coordinated reduction and regulation of the pollution of vegetable field soil non-point source and N2O.The method is clear, simple, convenient, easy to implement.

The invention relates to the technical field of early warning devices, in particular to a cow farm multi-gas monitoring and moisture and heat index early warning device which comprises a shell body, a sampling gas inlet, a guide gas circuit pipeline, a sensor mounting array, a miniature power gas pump, a miniature gas pump connecting seat, a main control circuit board mounting point, a relay group mounting point and a shell rear cover. The humidity and heat index early warning and regulation functions are achieved, the humidity and heat index in the farm can be calculated in real time, and early warning is conducted according to a preset threshold value; the equipment operation parameters can be automatically adjusted according to the humidity and heat index change, and all-weather, intelligent and automatic regulation and control of the cow farm environment are achieved; the system has the real-time monitoring capability, can continuously and dynamically monitor the gas concentration and environmental parameters in the farm environment, and updates the monitoring data in real time through the high-speed data acquisition and processing system, so that farm managers can master the latest change of the environmental condition at any time.

The invention belongs to the field of polluted soil remediation materials in agricultural environment technology, and particularly discloses a preparation method and application of a composite material for adsorbing and degrading polycyclic aromatic hydrocarbon in soil. The preparation method of the composite material comprises the following steps: co-pyrolyzing the oily sludge and the straws to generate pyrolytic carbon, and loading humic acid to obtain the composite material. The pyrolytic carbon humic acid composite material prepared by the invention is used for adsorbing and degrading polycyclic aromatic hydrocarbon in soil, compared with only pyrolytic carbon or humic acid, the composite material has a better degradation effect, the material preparation process is simple and efficient, the cost is low, and meanwhile, the purposes of improving soil and treating waste with waste are achieved.

The invention discloses an agricultural non-point source pollution treatment system, and relates to the technical field of agricultural environmental protection and water treatment, and the agricultural non-point source pollution treatment system comprises an ecological ditch unit, an ecological pond unit, a connecting pipeline and a control unit; the ecological ditch unit is used for carrying out primary pretreatment on sewage through a plant enhanced corridor and an ecological filter dam to remove suspended solids and part of pollutants; the ecological reservoir pond unit realizes deep purification through a multi-stage process of flocculent precipitation, enhanced denitrification, ecological treatment and a stable area; the control unit intelligently regulates and controls water flow based on water quality monitoring data, water reaching the standard is directly reused in farmland or lakes, and water not reaching the standard enters a pond to be further treated. According to the invention, stepped deep removal of pollutants, cyclic utilization of water resources and self-adaptive operation of the system are realized, and the treatment efficiency and stability are improved.

The present invention relates to a virtual sensor performance monitoring device. The device includes a sensor, and a processor configured to monitor performance of a virtual sensor that predicts an amount of dissolved oxygen in an aquaculture farm on the basis of aquaculture farm environment data collected through the sensor.

The invention relates to the technical field of robot autonomous navigation and environmental perception, in particular to a multi-sensor fusion SLAM and autonomous exploration method in a complex agricultural environment. The method comprises the following steps: correcting motion distortion through IMU forward propagation and laser radar back propagation; fusing the laser point-surface residual error and the visual luminosity residual error by adopting error state iteration Kalman filtering with sequence updating; carrying out object-level segmentation on the local point cloud map, and removing dynamic objects based on a weighted residual mechanism; carrying out loopback detection based on feature matching of deep learning; fusing three factors of a laser-visual odometer, IMU pre-integration and loopback through a factor graph model to obtain a global consistent track and map; autonomous exploration is carried out based on an optimization result, and automatic map construction is realized through terrain analysis and hierarchical path planning. The method effectively improves the positioning precision, robustness and automation level in an agricultural environment with dynamic interference and sparse features, and supports long-time reliable operation.

The invention discloses a path tracking control method suitable for crawler-type agricultural equipment. The method comprises the following steps: S1, building a navigation hardware control system on crawler-type equipment; s2, designing a Kalman filtering algorithm to filter the course angle of the crawler-type equipment; s3, correcting an equipment positioning error caused by the attitude angle; s4, a fusion algorithm of the Stanley algorithm and the Pure Pursuit algorithm is designed; s5, designing an enhanced SPP algorithm; s6, performing secondary optimization on the control law output by the SPP algorithm by using a fuzzy PID control algorithm; and S7, fitting a total control law equation in combination with the control algorithm, and converting the control law into the linear speed of the left and right tracks of the crawler-type equipment so as to realize steering and straight movement of the crawler-type equipment. According to the invention, a complex agricultural environment is regarded as a black box system, and item-by-item optimization is carried out by superposing an algorithm with high interpretability, so that the adaptability of a control system to the black box system is improved, and finally, the equipment path tracking precision is improved step by step.

The invention discloses a method for preventing and controlling cadmium accumulation of rice grains and strengthening zinc concentration at the same time, and relates to the technical field of agricultural environment and crop nutrition regulation, the single regulation defect is precisely overcome through the synergistic effect of a compound foliage regulator, salicylic acid and a zinc amino acid chelate are compounded to form the regulator, and the regulation effect is improved. Salicylic acid is utilized to induce synthesis of plant chelating peptide in rice, cadmium vacuole partitioning is enhanced, cadmium transporter protein expression is reduced, and migration of cadmium to grains is prevented and controlled from a transport path; meanwhile, zinc is rapidly supplemented by means of the efficient absorption characteristic of the zinc amino acid chelate, and the zinc amino acid chelate can cooperate with a salicylic acid signal to further inhibit cadmium distribution, so that the problems that a single zinc fertilizer cannot resist cadmium and single salicylic acid cannot be rich in zinc are solved, cadmium resistance and zinc enrichment are synchronously promoted, and meanwhile, dry-wet alternate irrigation in the booting stage and the mature stage is matched, so that the yield is increased. By regulating the soil moisture state, the physiological metabolism environment of the rice is optimized, the absorption and utilization of a regulating agent are promoted, and the vacuole partitioning effect of cadmium and the phloem transfer efficiency of zinc are enhanced.

The invention discloses a residual agricultural film three-dimensional distribution inversion method based on satellite radar collaborative calibration, and belongs to the technical field of agricultural environment remote sensing monitoring, and the method comprises the steps: extracting surface environment characteristics and underground dielectric characteristics from a multispectral satellite image and a ground penetrating radar signal; inversion of surface agricultural film content hot area distribution is carried out by using a random forest and a Kriging interpolation model, and soil internal dielectric constant distribution is acquired from radar data based on a hybrid inversion method; the method comprises the following steps: constructing an encoder-decoder model based on Transform, and establishing a cross-modal mapping relation between satellite features and radar parameters through a multi-head attention mechanism; and fusing earth surface and underground inversion results to generate a three-dimensional space distribution diagram of the residual agricultural film. The method effectively overcomes the technical limitations that traditional optical remote sensing can only identify earth surface coverage and the on-site sampling space is discontinuous, and provides a reliable technical means for farmland residual film pollution assessment and treatment.

A computer-implemented method and system for planning an operation in an agricultural environment comprises; receiving working region data indicative of the environment’s characteristics; receiving da

The invention discloses an agricultural plunger pump, and relates to the technical field of agricultural plunger pumps, the agricultural plunger pump realizes self-cleaning of a filter screen II through ball valve switching, has no complex electrical control, is suitable for agricultural environment use, can prevent the filter screen II from being blocked through regular back flushing, and improves long-term working efficiency, and multiple layers of filter screen plates are arranged in a filter screen cylinder and are arranged in a stepped manner, so that the filter screen cylinder is convenient to clean. Meshes are reduced layer by layer, large-particle impurities are blocked by the first-layer filter screen, fine particles are intercepted by the subsequent filter screens, and the problems that the load of a single filter screen is too large, water flow pressure disappears after flushing is completed, a compressed spring pushes a movable column to rebound, a baffle rapidly closes an inlet groove, physical sealing is formed, and a filter screen cylinder can be detached and cleaned at regular intervals are solved. And the auxiliary cylinder can be synchronously cleaned through thread disassembly, the overall service life is prolonged, smooth water inlet is ensured through the clean filter screen II, continuous flow and pressure output can be realized, and the irrigation efficiency is ensured.

The invention discloses application of agrobacterium tumefaciens C53 in converting cow dung water into efficient liquid microbial fertilizer, and relates to the field of agricultural environment microbial technology and organic waste resource utilization, agrobacterium tumefaciens C53 bacterial liquid is inoculated into cow dung water, fermentation is carried out under the aerobic condition, and the liquid microbial fertilizer is obtained. The inoculation volume of the C53 bacterial liquid accounts for 20% of the total volume of the cow dung water. According to the strain C53, high-load cow dung water is transformed into a liquid fertilizer with better nutrient form and remarkable growth promoting effect, after the efficient liquid microbial fertilizer is applied to corn, the leaf weight and the root weight of the corn can be increased by about 48.9% and 58.8% respectively compared with blank control, and a feasible microbial technical scheme is provided for green and high-value resource utilization of breeding dung.

The invention belongs to the technical field of agricultural environment control and unmanned aerial vehicle application, and relates to an under-forest cultivation area microclimate precise regulation and control system based on an unmanned aerial vehicle. Comprising an environment modeling and initialization module, a prediction and decision module, an instruction execution and observation module, a data verification and extraction module, an error calculation and correction source item generation module, a correction source item propagation and field updating module and a closed loop iteration scheduling module. A three-dimensional voxel grid is constructed, an initial microclimate prediction field is generated, a target voxel is identified based on a prediction trend, a predictive control frame is generated, an unmanned aerial vehicle executes an intervention action and collects observation data, a correction source item is generated after verification and error calculation, and the microclimate prediction field is propagated and updated according to predicted airflow, so that closed-loop iteration regulation and control are realized. According to the method, the problems of regulation lag and insufficient intervention pertinence caused by lack of three-dimensional microclimate field dynamic prediction and digital twinborn linkage capabilities in the existing fixed sensor network and the traditional unmanned aerial vehicle operation mode are solved.

The invention discloses a vertical farm integrated control system and method and a computer readable storage medium, and the system comprises a sensor group which is used for collecting environment and crop growth data; the quality prediction module is used for predicting future quality indexes of crops; the joint optimization module is used for constructing a multi-objective function containing quality indexes and energy cost and calculating first control input; the security shielding module defines a security set based on the control barrier function, and projects the first control input into the security set to generate a second control input when the first control input violates a security constraint. And the actuator group is used for adjusting the farm environment according to the second control input. According to the invention, through establishing the quality prediction model and performing joint optimization with the real-time energy cost, the system can actively use the electricity price valley period to adjust the environment on the premise of ensuring the target quality, the energy cost is significantly reduced, and the economic benefit is maximized.

The invention relates to a distributed intelligent rice transplanter cluster navigation method based on deep reinforcement learning and speed obstacles, which comprises the following steps: acquiring a reciprocal speed obstacle and a speed obstacle vector, inputting the reciprocal speed obstacle and the speed obstacle vector into a BiLTSM network model, and acquiring an environment perception vector; the BiLTSM network model is obtained through training of a training set; and combining the environment perception vector with an ontology perception measurement value to generate an observation space, and setting a reward function for iteratively updating a multi-intelligent-vehicle obstacle avoidance strategy so as to optimize driving control of an individual level in an intelligent vehicle cluster and generate an optimal navigation scheme. The method still faces many challenges in application in the agricultural environment, the defects in the aspects of environment state representation, action mapping and reward design are overcome, and the problem of multi-machine collision avoidance in the complex dynamic environment is effectively solved.

There is described a system and method for measuring properties of water, such as surface water at site. That site may be in an agricultural setting. The properties of water, such as surface water may include nitrates and / or dissolved organic carbons. An example system may comprise a light source configured to emit a broadband source signal comprising a particular bandwidth for use in measuring a range of particular properties of water as well as an optical device configure to split the source signal into a measurement signal, and a corresponding reference signal. The system may also comprise a sensor unit configured to communicate a measurement signal through water at the sensor unit (e.g., when located in a stream), and a spectrometer configured to receive both a measurement signal having been communicated through water at the sensor unit and a reference signal from the optical device. Such a spectrometer may be configured to separate received measurement signals and reference signals into common component wavelengths, those common component wavelengths being associated with expected properties of water; and the system may be further configured to use respective component wavelengths of a measurement signal together with those of a reference signal to determine one or more particular properties of measured water.

This invention relates to the field of agricultural environment and soil fertilizer technology, and in particular to a method for increasing paddy field yield and reducing N2O emissions by regulating the application rate of zero-valent iron. The method includes the following steps: at the early tillering stage of rice, zero-valent iron is mixed with tillering fertilizer and applied to the paddy field soil; the application rate of zero-valent iron is 20-50 mg / kg (dry soil basis). ‑1 The method involves applying booting fertilizer to the paddy soil during the early booting stage of rice, and irrigating throughout the entire rice growth cycle. This invention, by applying an appropriate amount of zero-valent iron in a single application on top of conventional fertilizer application, can synergistically achieve greenhouse gas emission reduction and increased grain yield, providing a feasible path for green production in paddy fields.