CN110579987A - intelligent orchard information control system and method based on LORA communication - Google Patents
intelligent orchard information control system and method based on LORA communication Download PDFInfo
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- G—PHYSICS
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/04—Programme control other than numerical control, i.e. in sequence controllers or logic controllers
- G05B19/042—Programme control other than numerical control, i.e. in sequence controllers or logic controllers using digital processors
- G05B19/0423—Input/output
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/38—Services specially adapted for particular environments, situations or purposes for collecting sensor information
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/70—Services for machine-to-machine communication [M2M] or machine type communication [MTC]
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- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
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Abstract
The invention belongs to the technical field of data monitoring, and discloses an intelligent orchard information control system and method based on LORA communication. The data platform is connected with the application platform, and camera, electromechanical device are connected with LORA data acquisition terminal, and external relay, fan and sluice, video equipment are connected with the LORA gateway. The intelligent orchard system is communicated with the data platform, and the intelligent orchard system solution with low cost, low power consumption and high reliability is realized. Decision support such as irrigation, fertilization and the like is provided for the kiwi fruit orchard, and machine intellectualization is realized; the production process is controlled remotely, fixed-point operation is carried out, and a set of scientific and systematic accurate agricultural intelligent production control system is provided for planting personnel.
Description
Technical Field
the invention belongs to the technical field of data monitoring, and particularly relates to an intelligent orchard information control system and method based on LORA communication.
background
the production process of the traditional planting industry needs the whole-process nursing of planting personnel and takes measures of watering, fertilizing, weeding, expelling insects and the like for different growth conditions of crops depending on the planting experience of management personnel, but the phenomenon of low utilization rate of water, fertilizer and pesticide due to the fact that the technology does not reach the standard exists, resource waste is caused, and even more, the safety of crop food cannot reach the standard and the personal health of citizens is damaged. In recent years, haze is abused, rivers are polluted, 80% of the land in China is polluted in different degrees, resources and ecological environment are exposed to red lines, and the traditional planting experience of managers cannot be met in the face of severe planting environment. The phenomenon of information asymmetry in the market transaction of agricultural products is very obvious, the planting area, the yield and the price of the agricultural products are directly caused to fluctuate violently, the high yield of the agricultural products is not high, and at present,
The GPRS is adopted as the communication network in the existing intelligent orchard system, and the existing problems are as follows: GPRS depends on cellular network communication base stations established by operators, and long-term communication cost and operation cost can be generated by adopting GPRS as a communication network, so that the system maintenance cost is high, and the GPRS is not suitable for long-term use; the GPRS is adopted as a communication network, the success rate of data acquisition is not high, and data blockage is serious. Compared with other technologies, the LoRa communication technology has the advantages of high resolution, strong network reliability and extremely low power consumption; the LoRa network architecture is a star topology network, namely, each terminal node and each gateway can directly carry out information intercommunication, so that not only is the complexity of network operation reduced, but also the power consumption is effectively reduced; the use and maintenance cost of the system is greatly reduced by adopting the LoRa communication technology, and meanwhile, the long-distance and high-stability multi-platform control is realized.
disclosure of Invention
aiming at the problems in the prior art, the invention provides an intelligent orchard information control system and method based on LORA communication.
the invention is realized in this way, a smart orchard information control system based on LORA communication includes:
the LORA data acquisition terminal is connected with the sensor and used for realizing LORA communication and data interaction with the gateway; the LORA node mode is realized, and the data acquisition function is realized by communicating with an LORA gateway 3 or an LORA relay; realizing an LORA relay mode; the low power consumption control function is realized, and power supply and data acquisition to the sensor are started according to the preset state;
The LORA gateway is connected with the LORA data acquisition terminal through LORA wireless and used for realizing LORA communication, and adopts a gateway mode to communicate with an LORA node or an LORA relay; providing LAN or 4G communication technology to communicate with a remote data platform; providing a relay output terminal or controlling an external relay through a serial port and Ethernet output to control the operation of the field control equipment; and providing an Ethernet interface and a wifi AP function, and accessing the video monitoring equipment.
The data platform is connected with the LORA gateway through wires or wirelessly and is used for providing the communication capacity of the LORA equipment and carrying out data collection and command output; a LORA device or gateway that manages the front end; providing a video viewing function; and providing data information display and alarm data browsing of each greenhouse.
Further, wisdom orchard information control system based on LORA communication still includes: the system comprises an application platform, a camera, electromechanical equipment, an external relay, a fan, a water gate and video equipment;
The data platform is connected with the application platform, and camera, electromechanical device are connected with LORA data acquisition terminal, and external relay, fan and sluice, video equipment are connected with the LORA gateway.
Further, the LORA data collecting terminal includes: LORA module, CPU, disposable battery;
the disposable battery is connected with the LORA module, the CPU and the sensor; the sensor is connected with CPU, and CPU is connected with the LORA module.
Further, the LORA gateway includes: the system comprises a gateway main control module, an RJ45 module, a built-in relay, RS485 and RS232 modules, an AI/DI module, a 4G module, a WIFI module and a gateway LORA module;
The gateway master control is connected with RJ45, built-in relay, RS485 and RS232, AI/DI, 4G module, WIFI module, gateway LORA module respectively.
further, the RJ45 is connected with a video device;
the RJ45 is in wired connection with the data platform, and the 4G module and the WIFI module are in wireless connection with the data platform respectively;
The built-in relay is connected with the fan/water gate.
Further, serial ports are RS485 and RS232, and the RS485 and RS232 are connected with the fan/water gate through an external relay;
the AI/DI is an AI/DI input module for connecting to a sensor.
Further, wisdom orchard information control system based on LORA communication still includes: the system comprises a garden planning module, a fruit tree archive module and an accurate planting module;
The system comprises a garden planning module, a smart orchard system and a control module, wherein the garden planning module is used for uploading basic information of the kiwi fruits to the smart orchard system after a user selects a planting area of the kiwi fruit garden; the garden environment information acquisition module comprises a temperature and humidity sensor, a temperature sensor, an air quality sensor, a soil temperature and humidity sensor, a carbon dioxide sensor and the like, and transmits acquired real-time information to the garden planning module; the agricultural market information collection module transmits the collected information such as the market supply and demand of the information related to the fruit trees in the past year to the garden planning module; the garden planning module combines the acquired garden information with the market information of the kiwi fruit trees to scientifically plan the garden and provide a reasonable fruit tree matching scheme;
The fruit tree archive module is used for constructing a growth model for each kiwi fruit tree, creating a health archive, and recording planting position, variety, tree age, tree height, growth condition, yield per year and economic benefit data per year of the kiwi fruit tree; the growth condition of each fruit tree is detected in real time, and scientific and systematic differentiated planting guidance is provided; providing technical operation guidance according to the variety of the kiwi fruit tree and the environmental data of an orchard from the beginning of planting in the life cycle of the kiwi fruit tree; monitoring the health condition and the branch bud growth condition of a kiwi fruit tree according to an image acquisition technology, and carrying out shaping and pruning guidance by combining the tree age and the annual cycle period of the kiwi fruit tree to judge branch buds needing to be pruned and reserved; carrying out economic benefit evaluation on kiwi fruit trees in the mature period every year, when the economic benefit does not reach the pre-judging standard or the input and output are inconsistent, prompting the replacement of fruit trees by a system to guide ecological rotation, and guiding the pruning of mature trees for the fruit trees with good economic benefit; the fruit tree archive module guides the planting personnel to carry out corresponding farming operation according to meteorological information, the health condition of the fruit tree and growth environment data every year, provides scientific and intelligent decision guidance and realizes accurate planting and intelligent planting; the real-time yield estimation is carried out on each fruit tree, and the influence of the operation on the yield of the fruit tree can be estimated after the relevant farming operation is carried out each time; in 3, last ten days of spring to 4, the fruit tree archive module provides irrigation, harrowing and weeding guide opinions for a user according to recent meteorological data and the current growth situation of the fruit tree, and the user agrees and executes the operation, and then the precise planting module remotely controls the designated equipment; in the 5 th month, the current branch sprouting situation of the current fruit tree is known according to an image acquisition technology, a user is guided to carry out branch sprout selection and retention and add a required supporting arch in combination with the tree age, and a branch promoting fertilizer with a corresponding proportion is applied according to the actual growth condition of each fruit tree; in the germination period of 6 months, the kiwi fruit tree is subjected to pruning work guidance according to the growth condition of branch buds of the fruit tree, and an intelligent weeding robot weeding and water and fertilizer integrated intelligent irrigation system is remotely controlled by using a precise planting management system to use a flower promoting fertilizer; the flowering period of the kiwi fruit trees is a high-incidence season of powdery mildew and insect pests, pest control work is carried out according to the current growth situation of the fruit trees, different fertilizers are applied to each tree in a targeted manner, and top dressing operation is carried out on the kiwi fruit trees with the tree ages of 2-3 years; when the fruit trees enter a fruiting period, automatically prompting to apply foliar fertilizer to the fruit trees, topdressing the fruit trees for 2-3 years, and selecting different fertilizing operations and water-fertilizer ratios according to the existing growth condition and the annual period of each fruit tree; after the fruit trees enter the dormancy stage, according to the fruit tree age prompting irrigation operation time and frequency, performing small irrigation on 1-3-year trees, performing 6-7 times irrigation on fruit trees with the age of more than 4 years, and performing 5-6 times irrigation on mature trees; judging the garden sealing time according to the meteorological data, and guiding scientific means to seal the garden, such as using a lime sulphur mixture to clean the garden to reduce the ova and germs of the overwintering pests; waiting for a new orchard establishment in the second year, and then performing kiwi fruit planting guidance in the new year;
the accurate planting module is used for remotely managing intelligent equipment in the orchard to perform specified farming operation on target fruit trees; the water and fertilizer integrated intelligent irrigation equipment selects and executes a corresponding scheme on an intelligent orchard system by a user according to water and fertilizer decision guidance provided by fruit tree health files, the water and fertilizer integrated intelligent irrigation system can select different fertilizer types and carry out corresponding water and fertilizer proportioning, and specified equipment is remotely controlled to operate a target fruit tree to realize accurate and scientific planting management; after a user sets fertilizer types and water and fertilizer ratios, the unmanned aerial vehicle fertilization appoints unmanned aerial vehicle equipment to intelligently plan a spraying route, and carries out scientific and efficient fertilization work; the infrasonic wave insect expelling can set sound waves of different wave bands to correspondingly expel insects and birds, the specified working duration and the equipment starting work are realized, and the refinement and the intellectualization are realized; the intelligent weeding robot carries out weeding work in a designated area after being remotely started, and designates the management time of a park; after each time of operation execution by the automation equipment, the automation equipment is recorded in an operation log, the influence condition of the operation on a target fruit tree and the estimation of the yield of kiwi fruits can be judged in advance, the aging condition of the equipment is recorded in real time, and the equipment is recommended to be updated and replaced;
the fruit tree growth model module in the fruit tree archive module is divided into a fruit tree growth model construction module and a fruit tree growth condition diagnosis module;
The fruit tree growth model training module constructs a convolution neural network model based on the fruit tree growth sample set, and obtains a neural network diagnosis model of the fruit tree growth by analyzing images in the fruit tree growth sample set; the fruit tree growth condition diagnosis module judges by using a neural network diagnosis model based on the input image to obtain the diagnosis results of water, fertilizer and plant diseases and insect pests required by the growth of the fruit tree;
the fruit tree growth model module also comprises a correction module used for correcting the fruit tree growth condition diagnosis result by the planting personnel and feeding back the correction data to the neural network model training module, and the neural network model training module optimizes the neural network diagnosis model based on the data; the fruit tree growth model building module comprises a sample data acquisition module, an image processing module and a training module; the sample data acquisition module is used for acquiring a training image in a kiwi fruit tree growth chart sample set; the image processing module is used for carrying out standardization processing on the training image to obtain a standardized image; the training module is used for analyzing the obtained normalized image and carrying out continuous analysis training by combining the agricultural data in the fruit tree growth chart sample set year to obtain a neural network diagnosis model;
The fruit tree growth condition diagnosis module is used for analyzing the normalized image and obtaining the fruit tree growth condition and the diagnosis result of plant diseases and insect pests according to the analysis of the neural network model; the fruit tree growth condition diagnosis module is divided into a diagnosis image acquisition module, an image processing module and a diagnosis module; the diagnostic image acquisition module acquires an image of an object to be diagnosed based on the Internet of things technology, and the intelligent orchard system acquires a growth image of a fruit tree based on the Internet of things technology; the image processing module is used for carrying out standardized processing on the image to be diagnosed to obtain a standardized image; the diagnosis module is used for analyzing the normalized images and obtaining the growth condition of the fruit trees and the diagnosis result of the diseases and the pests according to the analysis of the neural network model; the correction module feeds back the diagnosis result, the fruit tree growth diagnosis result after analysis and correction of the planting personnel and the diagnosis image as correction data to the neural network model training stage; the standardized processing comprises marking the growing branch buds and the disease and insect pest points of the fruit trees, carrying out batch processing on the obtained training images, including uniform format, equalization and denoising, and then extracting candidate frames and pre-training; the training module is used for pre-training on a fruit tree growth sample set based on a neural network, then performing parameter fine tuning on the training sample set to obtain high-level characteristics of a sample set image, and inputting the high-level characteristics into a next layer network training module; the diagnosis module extracts a candidate region from the normalized image, predicts the position and the category information of the branch bud and the pest by using the characteristics of the amplitude image, and directly learns the global information of the image; the target detection method of the candidate frame is realized by screening the comprehensive score of the candidate frame, the confidence coefficient of each candidate frame is multiplied by the predicted category information of the candidate frame to obtain the comprehensive score, then the non-maximum value inhibition processing is carried out, the parameters of the candidate frame are continuously predicted and are closest to the real frame along with the continuous iteration progress, and finally the position information and the classification information of the real frame are output; and the image processing module is used for carrying out format discrimination on the training image or the diagnostic image, carrying out format conversion according to the requirement of the normalized image, simultaneously calculating the resolution of the training image or the diagnostic image, and reacquiring the normalized image with the resolution lower than a set threshold value.
Another object of the present invention is to provide a smart orchard information control method based on LORA communication, which executes the smart orchard information control system based on LORA communication, and the smart orchard information control method based on LORA communication includes the following steps:
Firstly, an LORA gateway or an LORA relay communication realizes a data acquisition function through a sensor; realizing an LORA relay mode; the method comprises the following steps of realizing long-period replacement of a primary battery according to power supply and data acquisition of a preset start-up sensor;
The second step, the LORA gateway realizes the LORA communication technology, adopts the gateway mode, and communicates with the LORA node or the LORA relay; providing LAN or 4G communication technology to communicate with a remote data platform; providing a relay output terminal or controlling an external relay through a serial port and Ethernet output to control the operation of the field control equipment; providing an Ethernet interface and a wifi AP function, and accessing the video monitoring equipment;
Thirdly, providing communication capability of LORA equipment by a data platform, and collecting data and outputting commands; managing LORA equipment or a gateway at the front end, including parameter configuration and system firmware upgrade; providing a video viewing function; and providing data information display and alarm data browsing of each greenhouse.
Another object of the present invention is to provide a computer program for implementing the smart orchard information control system based on LORA communication.
the invention further aims to provide an information data processing terminal for realizing the intelligent orchard information control system based on LORA communication.
another object of the present invention is to provide a computer-readable storage medium, which includes instructions that, when executed on a computer, cause the computer to execute the smart orchard information control system based on LORA communication.
in summary, the advantages and positive effects of the invention are: the invention utilizes LORA technology to solve several important problems of intelligent orchard application:
First, the low cost, LORA itself operates in an unlicensed frequency band, data communication is free, only the final gateway and the remote data platform may need communication cost, and the cost is greatly reduced. Meanwhile, the cost of the equipment is low, and the equipment is beneficial to being used in large quantities.
Secondly, the deployment is convenient, and LORA is a low-power consumption wide area network communication technology, and the consumption is extremely low, uses the battery of small volume just can satisfy long-period use, is not being restricted to and draws the mode of power or building solar energy power supply.
thirdly, high reliability, LORA is a technology that the interference killing feature is very strong, and stability and penetrability are strong, and communication distance is far away, can place in various topography, also can eliminate the blind area through the relay function.
The LORA is a wireless communication technology working in an unauthorized frequency band, can cover a range of about 10 kilometers, and has low operation power consumption and strong anti-interference capability. According to the intelligent orchard system, a data acquisition communication network at the forefront end of the intelligent orchard is established by using an LORA technology, and then the intelligent orchard system is communicated with a data platform through the LAN/4G remote communication capacity of an LORA gateway, so that the intelligent orchard system solution with low cost, low power consumption and high reliability is realized, and a data acquisition link is focused.
Drawings
fig. 1 is a schematic structural diagram of an intelligent orchard information control system based on LORA communication according to an embodiment of the present invention;
fig. 2 is a schematic diagram of a LORA data acquisition terminal according to an embodiment of the present invention;
fig. 3 is a schematic diagram of a LORA gateway provided by an embodiment of the present invention;
in the figure: 1. a sensor; 2. an LORA data acquisition terminal; 2-1, LORA module; 2-2, CPU; 2-3, a disposable battery; 3. a LORA gateway; 3-1, gateway master control; 3-2, RJ 45; 3-3, a built-in relay; 3-4, RS485 and RS 232; 3-5, AI/DI; 3-6, 4G modules; 3-7, a WIFI module; 3-8, a gateway LORA module; 4. a data platform; 5. an application platform; 6. a camera; 7. an electromechanical device; 8. an external relay; 9. a fan and a sluice; 10. a video device.
fig. 4 is a flowchart of a smart orchard information control method based on LORA communication according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
aiming at the problems in the prior art, the invention provides an intelligent orchard information control system and method based on LORA communication, and the invention is described in detail below with reference to the accompanying drawings.
As shown in fig. 1, the smart orchard information control system based on LORA communication according to the embodiment of the present invention includes: the system comprises a sensor 1, an LORA data acquisition terminal 2, an LORA gateway 3, a data platform 4, an application platform 5, a camera 6, electromechanical equipment 7, an external relay 8, a fan and water gate 9 and video equipment 10.
Sensor 1 is connected with LORA data acquisition terminal 2, and LORA data acquisition terminal 2 is connected with LORA gateway 3 through LORA is wireless, and LORA gateway 3 is connected with data platform 4 through wired or wireless. Data platform 4 is connected with application platform 5, and camera 6, electromechanical device 7 are connected with LORA data acquisition terminal 2, and external relay 8, fan and sluice 9, video equipment 10 are connected with LORA gateway 3.
the LORA data acquisition terminal 2 is used for realizing an LORA communication technology and realizing data interaction with a gateway; the LORA node mode is realized, communication with the LORA gateway 3 or an LORA relay can be realized, and a terminal of the type needs to be accessed into a sensor to realize a data acquisition function; the LORA relay mode is realized, and a terminal of one type in communication with the LORA gateway 3 or the LORA node is only used for communication relay without accessing a sensor; the low-power consumption control function is realized, and the primary battery can be replaced for a long period according to the preset power supply and data acquisition of the sensor 1. When the battery is used for supplying power to rice, the rice can be very conveniently deployed on site.
the LORA gateway 3 is used for realizing the LORA communication technology, adopts a gateway mode and communicates with the LORA node or the LORA relay; providing communication technologies such as LAN or 4G and the like to communicate with a remote data platform 4; providing a relay output terminal or controlling an external relay 8 through a serial port and Ethernet output to control the operation of the field control equipment; and an Ethernet interface and a wifi AP function are provided, and the video monitoring equipment can be accessed.
The data platform 4 is used for providing communication capacity of LORA equipment, and performing data collection and command output; managing LORA equipment or a gateway at the front end, wherein the LORA equipment or the gateway comprises the functions of parameter configuration, system firmware upgrade and the like; providing a video viewing function; and providing data information display and alarm data browsing of each greenhouse.
as shown in fig. 2, the LORA data collecting terminal 2 includes: LORA module 2-1, CPU 2-2, disposable battery 2-3.
The disposable battery 2-3 is connected with the LORA module 2-1, the CPU 2-2 and the sensor 1; the sensor 1 is connected with the CPU 2-2, and the CPU 2-2 is connected with the LORA module 2-1.
as shown in fig. 3, the LORA gateway 3 includes: the system comprises 3-1 parts of gateway master control, 3-2 parts of RJ453-2 parts, 3-3 parts of built-in relays, RS485 and RS2323-4 parts of AI/DI 3-5 parts, 3-6 parts of 4G modules, 3-7 parts of WIFI modules and 3-8 parts of gateway LORA modules.
The gateway master control 3-1 is respectively connected with the RJ453-2, the built-in relay 3-3, the RS485, the RS2323-4, the AI/DI 3-5, the 4G module 3-6, the WIFI module 3-7 and the gateway LORA module 3-8.
In a preferred embodiment of the present invention, the gateway master 3-1 is powered externally.
In a preferred embodiment of the present invention, RJ453-2 is connected to video unit 10.
In the preferred embodiment of the invention, the RJ453-2 is connected with the data platform 4 in a wired mode, and the 4G module 3-6 and the WIFI module 3-7 are respectively connected with the data platform 4 in a wireless mode.
in the preferred embodiment of the invention, the built-in relay 3-3 is connected to a fan/water gate 9.
In the preferred embodiment of the invention, the serial ports are RS485 and RS2323-4, and the RS485 and RS2323-4 are connected with a fan/water gate 9 through an external relay 8.
In a preferred embodiment of the present invention, AI/DI 3-5 is an AI/DI input module for connection to sensor 1.
The intelligent orchard information control system based on LORA communication provided by the embodiment of the invention further comprises: garden planning module, fruit tree archives module and accurate module of planting.
After a user selects a planting area of a kiwi fruit garden, basic information (such as geographical position, area size and the like) of kiwi fruits is uploaded to an intelligent orchard system. The garden environment information acquisition module comprises a temperature and humidity sensor, a temperature sensor, an air quality sensor, a soil temperature and humidity sensor, a carbon dioxide sensor and the like, and transmits acquired real-time information to the garden planning module. The agricultural market information collection module transmits the collected information such as the market supply and demand of the fruit trees related to the past year to the garden planning module. The garden planning module combines the garden information and the kiwi fruit tree market information that acquire, carries out garden scientific planning, provides reasonable fruit tree apolegamy scheme.
The fruit tree archive module constructs a growth model and creates a health archive for each kiwi fruit tree, and records data such as planting position, variety, tree age, tree height, growth condition, yield over the years, economic benefit over the years and the like of the kiwi fruit tree. The module can detect the growth condition of each fruit tree in real time and provide scientific and systematic differentiated planting guidance. Providing technical operation guidance such as planting row spacing, planting distance, depth, diameter, organic fertilizer, irrigation and the like during planting according to the variety of the kiwi fruit tree and the environmental data of an orchard from the beginning of planting in the life cycle of the kiwi fruit tree, and providing 2-water and 3-water irrigation opportunity prompt and irrigation guidance according to soil humidity and recent meteorological data; monitoring the health condition and branch bud growth condition of kiwi fruit trees according to an image acquisition technology, carrying out shaping pruning guidance by combining the age and the period of the annual period, judging branch buds needing to be pruned and retained, for example, implementing a trunk fixing and strengthening strategy on an annual tree, culturing a permanent basal layer crown main branch (removing useless shoots in time in summer to shorten and cut off intermediate branches, carrying out bud picking and secondary bud picking, and pruning and retaining branches in a resting period), consolidating a basal layer branch group expanding crown of a biennial tree (selecting and retaining 'grade 1 and grade 2 side branches' during summer pruning, selecting and retaining oblique or flat side branches during a resting period), culturing a permanent 2-layer crown skeleton of a body of a quartic tree (forming a stable crown main branch skeleton foundation during summer pruning, selecting and retaining side branches during a resting period), carrying out economic benefit evaluation on kiwi fruit trees in an age stage, and when economic benefit can not reach a predetermined standard or is not met every year, the system prompts replacement of fruit trees to guide ecological rotation, and conducts pruning work of mature trees for the guidance of fruit trees with good economic benefit (semi-circle tree shape is consolidated, sprout is cut off in summer, the tree shape is stable, and fruit branches are selected and remained in the dormant period).
the fruit tree archive module guides the planting personnel to carry out corresponding farming operation according to meteorological information, the health condition and the growth environment data of the fruit tree every year, scientific and intelligent decision guidance is provided, and accurate planting and intelligent planting are achieved. The module carries out real-time yield estimation on each fruit tree, and the influence of the operation on the yield of the fruit tree can be estimated after relevant farming operations are carried out each time. In the last 3 th to last 4 th of spring each year, the fruit tree archive module provides guidance suggestions such as irrigation, harrowing, weeding and the like for a user according to recent meteorological data and the current growth situation of the fruit tree, and after the user agrees to and executes the operation, the accurate planting module remotely controls specified equipment such as water and fertilizer integrated intelligent irrigation equipment, an intelligent weeding robot and the like to perform scientific and intelligent farming operation. In the 5 months, the module learns the current branch sprouting situation of the current fruit tree according to an image acquisition technology, guides a user to select and retain branches and sprouts and add a required supporting arch by combining the tree age, and applies branch promoting fertilizers with corresponding proportions according to the actual growth condition of each fruit tree, and the step can be remotely operated by a water and fertilizer integrated intelligent irrigation system. In the germination period of the kiwi fruit tree in 6 months, the module conducts pruning work guidance according to the growth condition of branches and buds of the fruit tree, and the intelligent weeding robot is remotely controlled by the accurate planting management system to weed and a water and fertilizer integrated intelligent irrigation system to use the flower promoting fertilizer. The flowering period of the kiwi fruit trees is a high-emergence season of powdery mildew and insect pests, the module carries out pest control according to the current growth situation of the fruit trees, different fertilizers are applied to each tree in a targeted mode, and top dressing operation is carried out on the kiwi fruit trees with the tree ages of 2-3 years. When the fruit trees enter the fruiting period, the module automatically prompts to apply foliar fertilizer to the fruit trees, and topdressing is performed on the fruit trees for 2-3 years. Different fertilizing operations and water-fertilizer ratios are selected according to the existing growth condition and the annual period of each fruit tree. The fruit trees in 6-11 months enter a picking period, the module judges the mature state of the kiwi fruits according to an image acquisition technology, prompts a user to pick in time, carries out pest control work, avoids economic loss caused by pests, selects corresponding fertilizer and water-fertilizer ratio according to the individual condition of the fruit trees, and is irrigated by remote control of a precise planting module on designated equipment. After the fruit trees enter the dormancy stage, the module performs small-amount irrigation on 1-3-year trees, performs irrigation 6-7 times on fruit trees with the age of more than 4 years, and performs irrigation 5-6 times on mature trees according to the irrigation operation time and frequency prompted by the age of the fruit trees. The module judges the garden sealing time according to meteorological data and guides scientific means to seal the garden, such as using a lime sulphur mixture to clean the garden to reduce the ova and germs of the overwintering pests. And finally, the module waits for a new orchard establishment in the second year and then conducts kiwi fruit planting guidance in the new year.
The fruit tree growth model module in the fruit tree archive module is divided into a fruit tree growth model construction module and a fruit tree growth condition diagnosis module. The fruit tree growth model training module constructs a convolution neural network model based on the fruit tree growth sample set, and obtains a neural network diagnosis model of the fruit tree growth by analyzing images in the fruit tree growth sample set. The fruit tree growth condition diagnosis module judges by using the neural network diagnosis model based on the input image to obtain the diagnosis results of water, fertilizer and pesticide and plant diseases and insect pests required by the growth of the fruit tree. The fruit tree growth model module also comprises a correction module which is used for the grower to correct the fruit tree growth condition diagnosis result and feed back the correction data to the neural network model training module, and the neural network model training module optimizes the neural network diagnosis model based on the data. The fruit tree growth model building module comprises a sample data acquisition module, an image processing module and a training module. The sample data acquisition module is used for acquiring training images in the kiwi fruit tree growth chart sample set. The image processing module is used for carrying out standardization processing on the training image to obtain a standardized image. The training module is used for analyzing the obtained normalized images and carrying out continuous analysis training by combining the agricultural data in the fruit tree growth chart sample set year to obtain a neural network diagnosis model. The fruit tree growth condition diagnosis module is used for analyzing the normalized images and obtaining the diagnosis results of the growth condition of the fruit trees and the plant diseases and insect pests according to the neural network model analysis. The fruit tree growth condition diagnosis module is divided into a diagnosis image acquisition module, an image processing module and a diagnosis module. The diagnostic image acquisition module acquires images of the object to be diagnosed based on the Internet of things technology, and the intelligent orchard system acquires growth images of the fruit trees based on the Internet of things technology. The image processing module is used for carrying out standardization processing on the image to be diagnosed to obtain a standardized image. The diagnosis module is used for analyzing the normalized images and obtaining the growth condition of the fruit trees and the diagnosis result of the diseases and the pests according to the analysis of the neural network model. And the correction module feeds back the diagnosis result, the fruit tree growth diagnosis result after analysis and correction by the planting personnel and the diagnosis image as correction data to the neural network model training stage. The standardized processing comprises marking the growing branch buds and the disease and insect pest points of the fruit trees, carrying out batch processing on the obtained training images, including uniform format, equalization and denoising, and then extracting candidate frames and pre-training; the marking of the branch buds and the disease and insect pest points is to perform focus characteristic marking on a normalized image obtained from a training image to form a focus information label, wherein the focus information label comprises the condition of the new branch buds, the period of the disease and insect pest and the lesion part, the marking also comprises label information and coordinates of an upper left corner point and a lower right corner point of a target in the normalized image, and the label information refers to whether the target belongs to a focus and the category information of the focus development stage. The training module is used for pre-training on a fruit tree growth sample set based on a neural network, then parameter fine-tuning is carried out on the training sample set, high-level characteristics of the sample set images are obtained, and the high-level characteristics are input into a next layer network training module. The diagnosis module extracts a candidate region from the normalized image, predicts the position and the category information of the branch bud and the pest by using the characteristics of the amplitude image, and directly learns the global information of the image; the target detection method of the candidate frame is realized by screening the comprehensive score of the candidate frame, the confidence coefficient of each candidate frame is multiplied by the predicted category information of the candidate frame to obtain the comprehensive score, then the non-maximum value inhibition processing is carried out, the parameters are continuously predicted frames and are closest to the real frame along with the continuous iteration progress, and finally the position information and the classification information of the real frame are output. And the image processing module is used for carrying out format discrimination on the training image or the diagnostic image, carrying out format conversion according to the requirement of the normalized image, simultaneously calculating the resolution of the training image or the diagnostic image, and reacquiring the normalized image with the resolution lower than a set threshold value.
The intelligent equipment in the accurate planting module orchard can be remotely managed to carry out appointed farming operation on target fruit trees, is an implementation part for decision generation of the fruit tree archive module, records operation logs and carries out effect prediction, and can improve the utilization rate of resources and avoid manpower consumption. The water and fertilizer integrated intelligent irrigation equipment selects and executes a corresponding scheme on the intelligent orchard system by a user according to water and fertilizer decision guidance provided by the fruit tree health file, the water and fertilizer integrated intelligent irrigation system can select different fertilizer types and carry out corresponding water and fertilizer proportioning, and the equipment designated by remote control is used for operating a target fruit tree to realize accurate scientific planting management, such as irrigation, agriculture application and the like. Unmanned aerial vehicle fertilizies and sets up fertilizer kind and liquid manure ratio back at the user, appointed unmanned aerial vehicle equipment intelligent planning sprays the route, carries out scientific efficient fertilization work. Infrasonic wave expelling parasite can set up the sound wave of different wave bands and carry out the expelling parasite that corresponds and drive the bird, and appointed operating duration and equipment open work do the intellectuality that becomes more meticulous. The intelligent weeding robot can carry out weeding work in a specified area after being remotely started, and specifies the management time of a park. After the automation equipment executes the operation each time, the operation log can be recorded, the influence condition of the operation on a target fruit tree and the yield estimation of the kiwi fruit can be judged in advance, the aging condition of the equipment is recorded in real time, and the equipment is recommended to be updated and replaced.
As shown in fig. 4, the smart orchard information control method based on LORA communication according to the embodiment of the present invention includes the following steps:
s401: the LORA gateway or the LORA relay communication realizes the data acquisition function through a sensor; realizing an LORA relay mode; the method comprises the following steps of realizing long-period replacement of a primary battery according to power supply and data acquisition of a preset start-up sensor;
S402: the LORA gateway is used for realizing the LORA communication technology and communicating with the LORA node or the LORA relay by adopting a gateway mode; providing communication technologies such as LAN or 4G and the like to communicate with a remote data platform; providing a relay output terminal or controlling an external relay through a serial port and Ethernet output to control the operation of the field control equipment; providing an Ethernet interface and a wifi AP function, and accessing the video monitoring equipment;
s403: the data platform provides communication capability of LORA equipment, and performs data collection and command output; managing LORA equipment or a gateway at the front end, wherein the LORA equipment or the gateway comprises the functions of parameter configuration, system firmware upgrade and the like; providing a video viewing function;
It should be noted that the embodiments of the present invention can be realized by hardware, software, or a combination of software and hardware. The hardware portion may be implemented using dedicated logic; the software portions may be stored in a memory and executed by a suitable instruction execution system, such as a microprocessor or specially designed hardware. Those skilled in the art will appreciate that the apparatus and methods described above may be implemented using computer executable instructions and/or embodied in processor control code, such code being provided on a carrier medium such as a disk, CD-or DVD-ROM, programmable memory such as read only memory (firmware), or a data carrier such as an optical or electronic signal carrier, for example. The apparatus and its modules of the present invention may be implemented by hardware circuits such as very large scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., or by software executed by various types of processors, or by a combination of hardware circuits and software, e.g., firmware.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (10)
1. the utility model provides a wisdom orchard information control system based on LORA communication which characterized in that, wisdom orchard information control system based on LORA communication includes:
The LORA data acquisition terminal is connected with the sensor and used for realizing LORA communication and data interaction with the gateway; the LORA node mode is realized, and the data acquisition function is realized by communicating with an LORA gateway 3 or an LORA relay; realizing an LORA relay mode; the low power consumption control function is realized, and power supply and data acquisition to the sensor are started according to the preset state;
The LORA gateway is connected with the LORA data acquisition terminal through LORA wireless and used for realizing LORA communication, and adopts a gateway mode to communicate with an LORA node or an LORA relay; providing LAN or 4G communication technology to communicate with a remote data platform; providing a relay output terminal or controlling an external relay through a serial port and Ethernet output to control the operation of the field control equipment; providing an Ethernet interface and a wifi AP function, and accessing the video monitoring equipment;
the data platform is connected with the LORA gateway through wires or wirelessly and is used for providing the communication capacity of the LORA equipment and carrying out data collection and command output; a LORA device or gateway that manages the front end; providing a video viewing function; and providing data information display and alarm data browsing of each greenhouse.
2. the intelligent orchard information control system based on LORA communication of claim 1, wherein the intelligent orchard information control system based on LORA communication further comprises: the system comprises an application platform, a camera, electromechanical equipment, an external relay, a fan, a water gate and video equipment;
the data platform is connected with the application platform, and camera, electromechanical device are connected with LORA data acquisition terminal, and external relay, fan and sluice, video equipment are connected with the LORA gateway.
3. the intelligent orchard information control system based on LORA communication of claim 1, wherein the LORA data acquisition terminal comprises: LORA module, CPU, disposable battery;
The disposable battery is connected with the LORA module, the CPU and the sensor; the sensor is connected with CPU, and CPU is connected with the LORA module.
4. The intelligent orchard information control system based on LORA communication of claim 1, wherein the LORA gateway includes: the system comprises a gateway main control module, an RJ45 module, a built-in relay, RS485 and RS232 modules, an AI/DI module, a 4G module, a WIFI module and a gateway LORA module;
The gateway master control is connected with RJ45, built-in relay, RS485 and RS232, AI/DI, 4G module, WIFI module, gateway LORA module respectively.
5. The intelligent orchard information control system based on LORA communication of claim 4, wherein the RJ45 is connected with a video device;
the RJ45 is in wired connection with the data platform, and the 4G module and the WIFI module are in wireless connection with the data platform respectively;
the built-in relay is connected with the fan/water gate.
6. the intelligent orchard information control system based on LORA communication of claim 4, wherein the serial ports are RS485 and RS232, and the RS485 and RS232 are connected with the fan/water gate through an external relay;
The AI/DI is an AI/DI input module for connecting to a sensor.
7. the intelligent orchard information control system based on LORA communication of claim 1, wherein the intelligent orchard information control system based on LORA communication further comprises: the system comprises a garden planning module, a fruit tree archive module and an accurate planting module;
The system comprises a garden planning module, a smart orchard system and a control module, wherein the garden planning module is used for uploading basic information of the kiwi fruits to the smart orchard system after a user selects a planting area of the kiwi fruit garden; the garden environment information acquisition module comprises a temperature and humidity sensor, a temperature sensor, an air quality sensor, a soil temperature and humidity sensor, a carbon dioxide sensor and the like, and transmits acquired real-time information to the garden planning module; the agricultural market information collection module transmits the collected information such as the market supply and demand of the information related to the fruit trees in the past year to the garden planning module; the garden planning module combines the acquired garden information with the market information of the kiwi fruit trees to scientifically plan the garden and provide a reasonable fruit tree matching scheme;
the fruit tree archive module is used for constructing a growth model for each kiwi fruit tree, creating a health archive, and recording planting position, variety, tree age, tree height, growth condition, yield per year and economic benefit data per year of the kiwi fruit tree; the growth condition of each fruit tree is detected in real time, and scientific and systematic differentiated planting guidance is provided; providing technical operation guidance according to the variety of the kiwi fruit tree and the environmental data of an orchard from the beginning of planting in the life cycle of the kiwi fruit tree; monitoring the health condition and the branch bud growth condition of a kiwi fruit tree according to an image acquisition technology, and carrying out shaping and pruning guidance by combining the tree age and the annual cycle period of the kiwi fruit tree to judge branch buds needing to be pruned and reserved; carrying out economic benefit evaluation on kiwi fruit trees in the mature period every year, when the economic benefit does not reach the pre-judging standard or the input and output are inconsistent, prompting the replacement of fruit trees by a system to guide ecological rotation, and guiding the pruning of mature trees for the fruit trees with good economic benefit; the fruit tree archive module guides the planting personnel to carry out corresponding farming operation according to meteorological information, the health condition of the fruit tree and growth environment data every year, provides scientific and intelligent decision guidance and realizes accurate planting and intelligent planting; the real-time yield estimation is carried out on each fruit tree, and the influence of the operation on the yield of the fruit tree can be estimated after the relevant farming operation is carried out each time; in 3, last ten days of spring to 4, the fruit tree archive module provides irrigation, harrowing and weeding guide opinions for a user according to recent meteorological data and the current growth situation of the fruit tree, and the user agrees and executes the operation, and then the precise planting module remotely controls the designated equipment; in the 5 th month, the current branch sprouting situation of the current fruit tree is known according to an image acquisition technology, a user is guided to carry out branch sprout selection and retention and add a required supporting arch in combination with the tree age, and a branch promoting fertilizer with a corresponding proportion is applied according to the actual growth condition of each fruit tree; in the germination period of 6 months, the kiwi fruit tree is subjected to pruning work guidance according to the growth condition of branch buds of the fruit tree, and an intelligent weeding robot weeding and water and fertilizer integrated intelligent irrigation system is remotely controlled by using a precise planting management system to use a flower promoting fertilizer; the flowering period of the kiwi fruit trees is a high-incidence season of powdery mildew and insect pests, pest control work is carried out according to the current growth situation of the fruit trees, different fertilizers are applied to each tree in a targeted manner, and top dressing operation is carried out on the kiwi fruit trees with the tree ages of 2-3 years; when the fruit trees enter a fruiting period, automatically prompting to apply foliar fertilizer to the fruit trees, topdressing the fruit trees for 2-3 years, and selecting different fertilizing operations and water-fertilizer ratios according to the existing growth condition and the annual period of each fruit tree; after the fruit trees enter the dormancy stage, according to the fruit tree age prompting irrigation operation time and frequency, performing small irrigation on 1-3-year trees, performing 6-7 times irrigation on fruit trees with the age of more than 4 years, and performing 5-6 times irrigation on mature trees; judging the garden sealing time according to the meteorological data, and guiding scientific means to seal the garden, such as using a lime sulphur mixture to clean the garden to reduce the ova and germs of the overwintering pests; waiting for a new orchard establishment in the second year, and then performing kiwi fruit planting guidance in the new year;
The accurate planting module is used for remotely managing intelligent equipment in the orchard to perform specified farming operation on target fruit trees; the water and fertilizer integrated intelligent irrigation equipment selects and executes a corresponding scheme on an intelligent orchard system by a user according to water and fertilizer decision guidance provided by fruit tree health files, the water and fertilizer integrated intelligent irrigation system can select different fertilizer types and carry out corresponding water and fertilizer proportioning, and specified equipment is remotely controlled to operate a target fruit tree to realize accurate and scientific planting management; after a user sets fertilizer types and water and fertilizer ratios, the unmanned aerial vehicle fertilization appoints unmanned aerial vehicle equipment to intelligently plan a spraying route, and carries out scientific and efficient fertilization work; the infrasonic wave insect expelling can set sound waves of different wave bands to correspondingly expel insects and birds, the specified working duration and the equipment starting work are realized, and the refinement and the intellectualization are realized; the intelligent weeding robot carries out weeding work in a designated area after being remotely started, and designates the management time of a park; after each time of operation execution by the automation equipment, the automation equipment is recorded in an operation log, the influence condition of the operation on a target fruit tree and the estimation of the yield of kiwi fruits can be judged in advance, the aging condition of the equipment is recorded in real time, and the equipment is recommended to be updated and replaced;
The fruit tree growth model module in the fruit tree archive module is divided into a fruit tree growth model construction module and a fruit tree growth condition diagnosis module;
The fruit tree growth model training module constructs a convolution neural network model based on the fruit tree growth sample set, and obtains a neural network diagnosis model of the fruit tree growth by analyzing images in the fruit tree growth sample set; the fruit tree growth condition diagnosis module judges by using a neural network diagnosis model based on the input image to obtain the diagnosis results of water, fertilizer and plant diseases and insect pests required by the growth of the fruit tree;
The fruit tree growth model module also comprises a correction module used for correcting the fruit tree growth condition diagnosis result by the planting personnel and feeding back the correction data to the neural network model training module, and the neural network model training module optimizes the neural network diagnosis model based on the data; the fruit tree growth model building module comprises a sample data acquisition module, an image processing module and a training module; the sample data acquisition module is used for acquiring a training image in a kiwi fruit tree growth chart sample set; the image processing module is used for carrying out standardization processing on the training image to obtain a standardized image; the training module is used for analyzing the obtained normalized image and carrying out continuous analysis training by combining the agricultural data in the fruit tree growth chart sample set year to obtain a neural network diagnosis model;
The fruit tree growth condition diagnosis module is used for analyzing the normalized image and obtaining the fruit tree growth condition and the diagnosis result of plant diseases and insect pests according to the analysis of the neural network model; the fruit tree growth condition diagnosis module is divided into a diagnosis image acquisition module, an image processing module and a diagnosis module; the diagnostic image acquisition module acquires an image of an object to be diagnosed based on the Internet of things technology, and the intelligent orchard system acquires a growth image of a fruit tree based on the Internet of things technology; the image processing module is used for carrying out standardized processing on the image to be diagnosed to obtain a standardized image; the diagnosis module is used for analyzing the normalized images and obtaining the growth condition of the fruit trees and the diagnosis result of the diseases and the pests according to the analysis of the neural network model; the correction module feeds back the diagnosis result, the fruit tree growth diagnosis result after analysis and correction of the planting personnel and the diagnosis image as correction data to the neural network model training stage; the standardized processing comprises marking the growing branch buds and the disease and insect pest points of the fruit trees, carrying out batch processing on the obtained training images, including uniform format, equalization and denoising, and then extracting candidate frames and pre-training; the training module is used for pre-training on a fruit tree growth sample set based on a neural network, then performing parameter fine tuning on the training sample set to obtain high-level characteristics of a sample set image, and inputting the high-level characteristics into a next layer network training module; the diagnosis module extracts a candidate region from the normalized image, predicts the position and the category information of the branch bud and the pest by using the characteristics of the amplitude image, and directly learns the global information of the image; the target detection method of the candidate frame is realized by screening the comprehensive score of the candidate frame, the confidence coefficient of each candidate frame is multiplied by the predicted category information of the candidate frame to obtain the comprehensive score, then the non-maximum value inhibition processing is carried out, the parameters of the candidate frame are continuously predicted and are closest to the real frame along with the continuous iteration progress, and finally the position information and the classification information of the real frame are output; and the image processing module is used for carrying out format discrimination on the training image or the diagnostic image, carrying out format conversion according to the requirement of the normalized image, simultaneously calculating the resolution of the training image or the diagnostic image, and reacquiring the normalized image with the resolution lower than a set threshold value.
8. a LORA communication-based intelligent orchard information control method for executing the LORA communication-based intelligent orchard information control system of any one of claims 1-7, wherein the LORA communication-based intelligent orchard information control method comprises the following steps:
Firstly, an LORA gateway or an LORA relay communication realizes a data acquisition function through a sensor; realizing an LORA relay mode; the method comprises the following steps of realizing long-period replacement of a primary battery according to power supply and data acquisition of a preset start-up sensor;
Secondly, the LORA gateway realizes an LORA communication technology and adopts a gateway mode to communicate with an LORA node or an LORA relay; providing LAN or 4G communication technology to communicate with a remote data platform; providing a relay output terminal or controlling an external relay through a serial port and Ethernet output to control the operation of the field control equipment; providing an Ethernet interface and a wifi AP function, and accessing the video monitoring equipment;
Thirdly, providing communication capability of LORA equipment by a data platform, and collecting data and outputting commands; managing LORA equipment or a gateway at the front end, including parameter configuration and system firmware upgrade; providing a video viewing function; and providing data information display and alarm data browsing of each greenhouse.
9. An information data processing terminal for implementing the intelligent orchard information control system based on LORA communication according to any claim 1-7.
10. A computer-readable storage medium comprising instructions that, when executed on a computer, cause the computer to execute the LORA communication-based smart orchard information control system according to any of claims 1-7.
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Application publication date: 20191217 |