163 results about "Agricultural management" patented technology

An apparatus comprises a base vehicle, a takeoff and landing system, a rack system, a refueling system associated with the base vehicle, and a controller. The rack system comprises a group of racks with slots in which the slots receive unmanned aerial vehicles, provide refueling connections that facilitate refueling of the unmanned aerial vehicles located in the slots, and provide data connections that facilitate data transmission with the unmanned aerial vehicles located in the slots. The refueling system refuels an unmanned aerial vehicle located in a slot using a refueling connection in the refueling connections. The controller communicates with the unmanned aerial vehicle using a data connection and control the refueling of the unmanned aerial vehicles by the refueling system while the unmanned aerial vehicle is in the slot, enabling exchanging data with the unmanned aerial vehicle and the refueling of the unmanned aerial vehicle simultaneously.

A system and method for estimating agricultural parameters for growing crops is well suited for promoting efficient utilization of agricultural inputs (e.g., water consumption). Sensors collect data via one or more vehicles equipped with location-determining receivers. A transmitter transmits the collected environmental data to a data processing system. The data processing system applies the collected environmental data to an agronomic model for determining an agricultural management parameter. A prescription is made available for application of an agricultural input (e.g., water) to a crop in a particular location consistent with the collected environmental data and the agronomic model.

The invention discloses a big data agricultural management system. The system includes an Internet of things sensor platform, a big Data Analysis Platform, a meteorological warning and forecasting platform, a Platform for Disease and Pest Control and Disaster Early Warning, a real-time mobile monitoring platform, a Platform for Agricultural Management and Production Forecasting. The large-data agricultural management system realizes the collection of agricultural data in the agricultural greenhouse, data on human nutritional status, Genomic analysis of biological populations, analyzing of therelationship between the parameters of crop growing environment, forecast of weather conditions, the monitoring of agricultural products and food production environment, industrial chain management, pre-production, post-production, warehousing and processing, logistics data, the analysis of agricultural products sales price, sales volume, sales demand, consumer purchase behavior data, the releaseand management of meteorological data and other information, the development of disease and insect pests, the prediction of the scope of influence and the regulation of various equipment.

The invention discloses an IoT-based intelligent agricultural management system which comprises an environmental parameter acquisition unit, a management platform, a safety monitoring unit, an alarm unit, an environment regulation unit, an equipment control unit and a cloud server, wherein the environmental parameter acquisition unit, the safety monitoring unit, the alarm unit, the environment regulation unit, the equipment control unit and the cloud server wirelessly communicate with the management platform. The different units in the system communicate with each other in a wireless manner, lots of wiring is not needed, and the problems that the data loss probability is high and the control efficiency is low are solved.

The invention discloses an agricultural management and control system based on an IOT (Internet of Things) cloud platform, and relates to the IOT and agriculture crossing field. The system comprises amobile client, an IOT platform, and a local control terminal. The mobile client is connected with the IOT platform through the Internet or a mobile network, so as to complete the remote control and management of a local network. The IOT platform is connected with the local control terminal through the Internet, so as to complete the local data collection, calculation and optimization. The systemcan monitor the growth environment information of plants in real time, completes the safety data storage, calculation and analysis of mass data, quickly generates optimal data of the growth of plantsthrough the calculation capability of the cloud platform and an optimization algorithm, and sequentially drives execution systems to carry out the agricultural management. Meanwhile, the system carries out the analysis of the collected images of plants from plantation to harvesting through the image recognition technology, judges the production conditions, timely monitors the disease conditions, achieves the timely adjustment of the environment, reduces the loss, improves the yield, and promotes the industrialized and intelligent agricultural production.

A system and method for estimating agricultural parameters for growing crops is well suited for promoting efficient utilization of agricultural inputs (e.g., water consumption). Sensors collect data via one or more vehicles equipped with location-determining receivers. A transmitter transmits the collected environmental data to a data processing system. The data processing system applies the collected environmental data to an agronomic model for determining an agricultural management parameter. A prescription is made available for application of an agricultural input (e.g., water) to a crop in a particular location consistent with the collected environmental data and the agronomic model.

The invention relates to a crop pest detection system positioned on an unmanned aerial vehicle. The crop pest detection system comprises a random access memory, a high-definition camera, an image processor and a main controller, wherein the high-definition camera is used for capturing a crop image; the image processor is connected with the high-definition camera and is used for processing the crop image to obtain a crop pest type in the crop image; the main controller is connected with the random access memory and the image processor respectively and is used for storing the crop pest type in the random access memory. By virtue of the crop pest detection system positioned on the unmanned aerial vehicle, the pest type of a field crop can be automatically obtained, and relevant agricultural management departments can conveniently call the system when the unmanned aerial vehicle returns, so that targeted pest prevention and control measures are taken.

The invention discloses a virtual reality-based farmland agricultural condition information real-time monitoring system. The system includes a front-end information sensing system, a communication network, a front-end server and a remote server; the front-end information sensing system comprises a plurality of agricultural condition information sensing sub-nodes and a plurality of unmanned aerial vehicles; the communication network includes a wireless communication system, an Ethernet and an Internet; the unmanned aerial vehicles transmit data to the agricultural condition information sensing sub-nodes through the wireless communication system; the agricultural condition information sensing sub-nodes transmit the data to the front-end server through the Ethernet; and the front-end server transmits the data to the remote server through the Internet. According to the system of the invention, a VR technology, unmanned aerial vehicle remote sensing, a network technology, a database technology and the like are applied to agricultural condition monitoring of crops, and therefore, the system is of positive significance for the automation and informatization of agricultural management.

The invention discloses an agricultural and sideline product tracing information management system based on the IOT (Internet of Things), and the system mainly comprises an information data recording module, a monitoring management module and an early-warning information processing module. The information data recording module records the information of agricultural and sideline products in the monitoring management module through a remote Internet. The monitoring management module carries out the querying, supervision and complaint processing of all the upstream and downstream information of agricultural and sideline products: production main body information, storage information and sales data. The early-warning information processing module carries out the information early-warning of all related responsibility subjects through the mobile Internet, and carries out the processing according to a preset emergency scheme. According to the invention, the system enables all producers at agricultural production links to be managed in the system in different organization modes, achieves the registration and recording of the basic information of producers, the information of sales enterprises, use information of agricultural inputs and the information of the production links, builds a new agricultural product quality safety supervision mechanism, and creates a new modern agricultural management mode.

A mesh-based wireless network 10 of sensor / actuator devices I, D, T for an agricultural production area involves battery-powered sensors and actuators deployed under or within the foliage for broadcast communication with at least one repeater R according to broadcast time slots. The repeaters R are mounted above the vegetation canopy so as to be powered by solar panels. The repeaters R form a mesh network for routing data and commands to and from the sensors and actuators and at least one gateway GW. The gateway communicates over a cellular network with a remote agricultural management server 14 and database 16.

The invention discloses an intelligent agricultural management control system based on Internet of things. The system comprises a crop monitoring system, a livestock monitoring system, a meteorological monitoring system, a soil monitoring system, a video monitoring system, a satellite remote sensing system, a wireless communication module, a data processing center, a data storage center, an intelligent irrigation system, a fertilization system, a ventilation and light supplement system, an intelligent agricultural machine, an intelligent robot and an unmanned aerial vehicle. The data processing center receives real-time farmland data collected by the crop monitoring system, the livestock monitoring system, the meteorological monitoring system, the soil monitoring system, the video monitoring system and the satellite remote sensing system through the wireless communication module. A fine management algorithm model of various agricultural products is formulated for machine learning. Andthe data processing center is connected with the intelligent irrigation system, the fertilization system, the ventilation and light supplement system, the intelligent agricultural machine, the intelligent robot and the unmanned aerial vehicle. In the invention, agricultural production can be remotely and intelligently controlled according to an optimal scheme.

The invention discloses an ecological agricultural management system which has the functions of constant pressure monitoring and control, water level monitoring and control, fertilizer monitoring and control, irrigation monitoring and control, wireless valve control monitoring and control, voice promoting, prepayment monitoring, internet of things communication, water quality monitoring, shading illumination monitoring and control, humidity ventilation monitoring and control, temperature monitoring and control, video capture, soil entropy monitoring, plant disease and insect pest monitoring, product trace management, meteorological monitoring, cloud data management, application program visual management.The system can record the agricultural product variety, growth environment and growth process all the way, improve agricultural production automation degree, and reduce inconsistency caused by human factors in the agricultural production process, the quality of agricultural products is improved, various natural hazards are effectively avoided, a user can know the production process and related data of agricultural products immediately, and the increment space of agricultural products is enlarged.

An apparatus comprises a base vehicle, a takeoff and landing system, a rack system, a refueling system associated with the base vehicle, and a controller. The rack system comprises a group of racks with slots in which the slots receive unmanned aerial vehicles, provide refueling connections that facilitate refueling of the unmanned aerial vehicles located in the slots, and provide data connections that facilitate data transmission with the unmanned aerial vehicles located in the slots. The refueling system refuels an unmanned aerial vehicle located in a slot using a refueling connection in the refueling connections. The controller communicates with the unmanned aerial vehicle using a data connection and control the refueling of the unmanned aerial vehicles by the refueling system while the unmanned aerial vehicle is in the slot, enabling exchanging data with the unmanned aerial vehicle and the refueling of the unmanned aerial vehicle simultaneously.

The present invention relates to an indoor farming management system comprising at least one sensor; a central processing unit arranged in signal communication with the at least one sensor; a device adapted to operate between an operative state and a non-operative state; the central processing unit is operable to control at least one indoor environmental parameter of a farming system based on data received from the sensor; the central processing unit further operable to send a control signal to the device to operate the device between the operative state and the non-operative state.

The invention discloses a smart agricultural management system. In a plantation preparation phase, sensors arranged in a greenhouse acquire soil information of the current state in real time, and a control center provides scientific plantation information and data experience thereof; in a plantation cultivation phase, the sensors acquire real-time temperature and humidity and environmental data, and the control center automatically controls agricultural equipment according to the temperature and humidity and environmental data; in a plantation growth phase, the sensors monitor growth environmental information and nutrient information of crops and the disease and insect pest condition of the crops, and the control center regulates crop growth environment through cooperation with a control system by combination of the received detection data and expert experience maintained in the control center; and in a harvesting phase, the sensors are installed on agricultural product transport vehicles, the sensors detect the position, temperature and humidity of the vehicles, and the control center manages the agricultural product transport vehicles according to position, load, temperature and humidity information of the vehicles. The advantages of enhancing agricultural production efficiency and fine management can be realized.

The invention discloses an intelligent remote agricultural management system. The intelligent remote agricultural management system comprises a shooting device and an artificial rainfall device and is characterized by further comprising a soil water sensor and a three-dimensional mobile platform arranged in farmland, wherein the shooting device, the artificial rainfall device, the soil water sensor and the three-dimensional mobile platform are connected with a cloud server through the network, the cloud server is connected with an administrator terminal and / or a user terminal, and the cloud server is further separately connected with a weather forecast obtaining module and a soil water management module. According to the intelligent remote agricultural management system, accuracy and timeliness of farmland management are guaranteed, influence on plant growth caused by artificial omission can be avoided, the time, manpower and material resources are effectively saved, and user experience fun in remote leisure agriculture is improved.

The invention relates to an intelligent agricultural management method and system. The method comprises the steps that the nutrient data and the moisture data of soil are monitored; historical weather data and forecast weather data are acquired; historical price data are acquired; the nutrient data and the nutrient content standard value are compared, and the moisture data and the moisture content standard value are compared; the historical price data and the historical weather data of the crops are processed and analyzed, and the crop price trend prediction result is obtained through combination of the forecast weather data; and the crop harvest time is controlled according to the crop price trend prediction result. The system comprises a management and control center, a soil monitoring module, a weather information acquisition module and a price information acquisition module. The crop situation is monitored and more attention is put on the price trend of the crops, the principal factors influencing the crop price are analyzed and the correlation between the crop price and all the factors is found so that the price trend of the crops can be predicted and the farmers can be assisted to control the harvest time accordingly.

The embodiment of the invention discloses a greenhouse environment monitoring system based on a mobile internet, and particularly relates to the technical field of environment monitoring intelligent agricultural management. The greenhouse environment monitoring system comprises a service management terminal, the connection end of the service management terminal is provided with a scene collection system, a scene adjusting system and a remote observation system, the connection end of the service management terminal is further provided with a database. According to the invention, a cycle adjusting unit is used for planning the optimal planting environment data according to a crop type, the crop growth cycle is adjusted, a day and night replacing unit is used for planning the internal environment change of a greenhouse, the nutritional ingredients of the plants are improved while the plant growth is accelerated, the regional environment information of the planting blocks is collected, the environmental adjustment range value of each planting block is analyzed according to the crop habit, the scene adjusting system is used for achieving difference optimization adjustment, the GPS module and the timing module are used for marking the time and the specific coordinate of data collection, and the timeliness of monitoring and adjustment and the regional positioning accuracy are improved.

The invention relates to the technical field of agricultural management, in particular to an agricultural irrigation system on the basis of big data. The agricultural irrigation system comprises a farmland. A rainwater collecting basin is arranged on the farmland, a rainwater purifier is arranged on the rainwater collecting basin, a filter element is arranged in the rainwater purifier, a first water pump is arranged in the rainwater collecting basin and is connected with an irrigation water tower by pipelines, a water level sensor and an electromagnetic valve are arranged inside and outside the irrigation water tower, a water well is arranged on a side of the rainwater collecting basin, a second water pump is arranged in the water well, a control desk is arranged on a side of the irrigation water tower, a control panel and a power device are arranged outside and inside the control desk, irrigation desks are connected with the irrigation water tower by pipelines, sprayers are arranged on the irrigation desks, a fertilizer basin and a pesticide basin are arranged on a side of the corresponding irrigation desk, a fertilizer pump is arranged in the fertilizer basin, a pesticide pump isarranged in the pesticide basin, and a soil humidity sensor, a soil fertilizer concentration sensor and a plant growth sensor are arranged in the farmland. The agricultural irrigation system has theadvantages that irrigation, fertilizer application and pesticide spray can be automatically carried out by the agricultural irrigation system, and accordingly the time and labor can be saved.

The invention discloses an agricultural economy electronic map data service interface method, which mainly comprises generation of an agricultural professional business data dictionary; introduction of attribute data involved by the business; automatic association and verification of business attribute data and space elements; and finally space information query and analysis of data service. The agricultural economy electronic map data service interface method is suitable for an agricultural economy electronic map service platform, caters to electronic map data service interfaces of different agricultural professions, can be regarded as further function expansion of an agricultural economy information electronic map. By means of the agricultural economy electronic map data service interface method, quick personalized electronic map data service can be provided for agricultural management users of different levels and different professional departments.

The invention discloses a practical method for repairing cadmium pollution in farmland soil by planting Suliu 795, and belongs to the field of soil restoration. A practical method for repairing cadmium-contaminated farmland soil by planting Suliu 795, the steps are: (1) after selecting the cadmium-contaminated farmland, plowing, breaking up the soil, dividing ridges, and designing drainage ditches; (2) planting Suliu 795 795 young branches; (3) ensure the survival of more than 90% of willow trees through agronomic management and protection, and reduce the Cd content of the original polluted farmland soil by 30% within 2 years. This method can make the Cd content in the polluted soil be reduced by more than 20% on average in the first year by planting the young branches of Suliu 795 in the farmland soil with serious Cd pollution; The farmland with soil Cd content greater than 3.0mg / kg was restored until the Cd content of farmland soil was all less than 1.0mg / kg.

The invention discloses an agricultural management system comprising a crop information acquisition module used for acquiring crop information and sending to a data analysis module; a natural information acquisition module for acquiring environment information of a geographical location where crops are located and sending the information to the data analysis module; the data analysis module used for receiving the environment information and location information or coordinate information of the crops, extracting the environment information of the geographical location corresponding to the crops, and sending the extracted information to a data monitoring module; the data monitoring module used for judging whether an environment information parameter is within the most proper growth environment parameters of the crops, and sending control information to a control module if a judgment result is no; and the control module used for executing the control information to adjust the growth environment parameter of the crops. According to the system and method provided by the invention, a lot of manpower and resources are saved, the geographical location is used as a collection sensing pointfor forming a data system, and accurate cultivation is implemented on the crops at each site, and the crop yield is effectively improved.

The invention discloses an intelligent agricultural management system based on Internet of Things. The system comprises an environmental parameter acquisition unit, a management platform, a safety monitoring unit, an alarm unit, an environment adjusting unit, a device control unit and a cloud server, and the environmental parameter acquisition unit, the safety monitoring unit, the alarm unit, the environment adjusting unit, the device control unit and the cloud server communicate with the management platform in a wireless manner. According to the intelligent agricultural management system based on the Internet of Things, the units communicate with each other in a wireless manner, a lot of wiring is avoided, and problems of high data loss probability and low control efficiency are solved.

The invention discloses a wheat yield estimation method based on unmanned aerial vehicle multispectral images. According to the wheat yield estimation method based on the unmanned aerial vehicle multispectral images, wheat canopy multispectral image data and yield data are combined, and a wheat yield prediction model is constructed by adopting different modeling methods from single-factor and multi-factor modeling perspectives. According to the method, the formation process mechanism of the yield and the influence of different growth periods on wheat yield estimation are fully considered, andthe wheat yield under different treatments can be accurately and nondestructively estimated through screening of sensitive vegetation indexes, combination of the multiple growth periods and the application of a machine learning method. With the method adopted, a new thought is provided for a wheat yield accurate estimation method, and an important theoretical basis and technical support are provided for regional-scale accurate agricultural management and decision making.

The invention relates to the technical field of the agricultural management, especially a big data agricultural management system. The system comprises a master control module, the master control module is electrically connected with a crop monitoring unit, a meteorological monitoring unit, a big data analysis unit, a disaster early-warning unit and a management unit; the crop monitoring unit comprises a data acquisition module, the data acquisition module is electrically connected with a soil humidity detection module, a soil nutrient detection module, a growth state detection module and a carbon dioxide detection module; an output end of the data acquisition module is electrically connected with a data analysis module, the data analysis module is electrically connected with an assessment module. A growth data model of the crop is established through the growth state of the crops and the local meteorological condition, thereby predicting the future yield of the crops; the future crop market sales volume can be estimated, and the crops selling is convenient.

The invention relates to a precision agricultural management platform and method based on big data technology, which is characterized in that a data acquisition end, a storage platform, a central server, an execution device, a human-computer interaction device and a transmission network are provided. The storage platform adopts the combination of memory and cloud data platform, the memory platformreceives data streams output from the data acquisition terminal, the central server, the execution device and the human-computer interaction device, the central server is provided with an arithmeticunit and a controller for generating control instructions, the controller realizes the control of the execution device, the human-computer interaction device, the data acquisition terminal, the arithmetic unit, the storage platform and the transmission network itself through the transmission network. The instructions and data in the storage platform are stored in the memory of the storage platformin the same storage mode and transmitted to the controller through the instruction stream. The invention can realize data collection of crop growth state, growth environment, soil moisture and the like, and provide sufficient data accumulation for the follow-up.

The invention discloses a remote-sensing quick monitoring method of winter wheat powdery mildew in a field, and belongs to the technical field of crop growth monitoring. The remote-sensing quick monitoring method of the winter wheat powdery mildew in the field aims at solving the problems that the traditional monitoring method of the winter wheat powdery mildew in the field is high in manpower and time consumption, limited in monitoring range and sample capacity and hysteretic in observing and predicting information. The method uses a remote-sensing vegetation index, a chlorophyll content of winter wheat plant leaves, a moisture content of the leaves and average daily temperature of the wheat field to monitor the occurrence of the winter wheat powdery mildew in the field. The method has the advantages that as the method integrates satellite remote-sensing data, winter wheat growth information and climatic factors to monitor the winter wheat powdery mildew in the field, the occurrence of the large-area winter wheat powdery mildew can be monitored immediately and accurately in a wide range and at lower cost; and a produced remote-sensing monitoring information map for the winter wheat powdery mildew is high in information content, visual, and easy to comprehend and use, and has a high reference for formulating preliminary agricultural management measures.

The invention relates to a wisdom agricultural management system which is characterized by comprising camera monitoring equipment, video-conference equipment, an unmanned aerial vehicle, encoding equipment and mobile equipment, wherein all the equipment is connected with information management equipment by networks; the information management equipment is used for processing various agricultural information data; the information management equipment is connected with a control center by a high-definition hybrid matrix; and the high-definition hybrid matrix is simultaneously connected with the video-conference equipment and the mobile equipment. Therefore, working efficiency and working accuracy of the Agriculture Committee can be improved, the disaster response ability and the emergency commanding ability are promoted, and a decision is supported by management data. The growth and disaster conditions of the agricultural field can be known anytime anywhere, and guidance is provided for the agricultural production operation by reliable data. Human input and material input can be saved, productivity is improved, and yield and revenue are increased.

The invention provides a rice nitrogen fertilizer recommendation method based on a multispectral image of a fixed-wing unmanned aerial vehicle based on spectral data of the image of the fixed-wing unmanned aerial vehicle, which is used for recommending the nitrogen fertilizer application amount in a key growth period of rice topdressing. Through a rice field test, a rice plant nitrogen accumulation amount monitoring model is constructed, and a time sequence spectrum dynamic curve of the unmanned aerial vehicle is fitted. And a sufficient index nitrogen fertilizer recommendation algorithm is constructed by using the model and the curve, and the algorithm is verified through an independent test. According to the method, the spectral data characteristics of an unmanned aerial vehicle platform are fully considered, the nitrogen nutrition status of the rice in the key growth period can be accurately and nondestructively monitored through sensitive vegetation index screening and optimal curve fitting methods, and finally the accurate nitrogen fertilizer recommendation amount is given through the sufficient index algorithm in combination with the monitoring result and the unmanned aerial vehicle spectral characteristics. According to the method, an optimization approach is provided for precise nitrogen management of the rice, and important theoretical basis and technical support are provided for precise agricultural management and decision-making of a regional scale.

The invention relates to the field of agricultural technology and in particular to an agricultural recycling farming calculation method and an agricultural recycling farming calculation system. The method comprises the steps of firstly acquiring a soil type and soil nutrient substance contents of a to-be-calculated region; then calculating the nutrient substance contents in fertilizers obtained from livestock wastes through fermentation according to the nutrient substance contents in the livestock wastes; and finally establishing a fertilizer allocation model according to the nutrient substance contents of different fertilizers and a utilization rate of the fertilizers in current season, and calculating a planting scale of each crop according to the soil nutrient substance contents of the to-be-calculated region obtained in the above-mentioned step, the nutrient substance contents needed by each crop obtained in the above-mentioned step and the fertilizer allocation model. According to the agricultural recycling farming calculation method, systems of the planting industry and the breeding industry are organically combined, a novel agricultural management entity can be guided to apply a reasonable recycling agricultural development pattern, and the production cost is reduced.