CN104881017A - Beidou-based crop growth monitoring system - Google Patents
Beidou-based crop growth monitoring system Download PDFInfo
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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
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Abstract
The invention discloses a Beidou-based crop growth monitoring system including an image acquisition device, an image processing device, a detection device, a computer control center, a positioning device, and a crop monitoring control center, the computer control center is connected with the image acquisition device, the image processing device, the detection device, the positioning device, and the crop monitoring control center to control the positioning of the positioning device. The Beidou-based crop growth monitoring system can comprehensively monitor the parameter data values of the growth condition and growth environment of crops in real time and performs intelligent management on the crops based on the parameter data values, and because of the intelligent management system, crop growers can save a lot of workload and work time.
Description
Technical field
The present invention relates to crops monitoring technical field, particularly relate to a kind of crop growth supervisory systems based on the Big Dipper.
Background technology
Current China most area for the monitoring management of crop growth aspect mainly by manually managing, the aspects such as such as soil irrigation, pesticide spraying, soil application.Especially for the crops of establishing in large scale, the management process of labor management compares to waste time and energy.In addition, for different time crops growing state and growing environment all need artificial Real-Time Monitoring manage, this understands bring huge work workload to plant personnel.Therefore this area in the urgent need to a kind of can the time saving and energy saving again crops supervisory systems of the growth information of Real-Time Monitoring crops, intelligent management crops.
Summary of the invention
Embodiments of the invention are intended to overcome above technical matters, propose a kind of can comprehensively Real-Time Monitoring crop growth information, intelligent management crops and can be time saving and energy saving the crop growth supervisory systems based on the Big Dipper.
For solving the problems of the technologies described above, according to a first aspect of the invention, a kind of crop growth supervisory systems based on the Big Dipper is provided, wherein, comprises:
Image collecting device, for gathering the image information of crops, is convenient to the upgrowth situation observing crops;
Image processing apparatus, for carrying out analyzing and processing to the image information of the described crops collected, draws first parameter data values of crops self;
Pick-up unit, for detecting the second parameter data values of crop growth environment;
Computer controlling center, for arranging the desired parameters value range of different crops self and growing environment, and for receiving described first parameter data values and described second parameter data values, and described parameter area value and described first parameter data values and described second parameter data values are carried out com-parison and analysis and to reach a conclusion data;
Locating device, sprays region for unmanned plane being navigated to target and positions monitoring to target irrigated area; Described locating device comprises Beidou satellite navigation equipment and radio receiver-transmitter, and described Beidou satellite navigation equipment is for receiving the real-time Beidou navigation position of the described unmanned plane of Beidou navigation satellite transmission; Radio receiver-transmitter, be connected to receive described target with described computer controlling center and spray region or described target irrigated area, and to described computer controlling center return state information, described target sprays region or described target irrigated area comprises target Beidou navigation position and object height, and described status information comprises real-time Beidou navigation position, unmanned plane height, residue agricultural chemicals dosage or the soil nutrient content in real time of described unmanned plane;
Crops supervision control center, for receiving the described findings data of described computer controlling center and sending corresponding crops supervision steering order according to described findings data;
Described computer controlling center is supervised control center with described image collecting device, described image processing apparatus, described pick-up unit, described locating device, described crops and is connected respectively, for controlling the location of described locating device.
According to a second aspect of the invention, a kind of crop growth supervisory systems based on the Big Dipper is provided, wherein, described first parameter data values is crops self foliage disease worm kind, blade face integrity degree, blade face color, rhizome color or rhizome thickness, and described second parameter data values is air ambient temperature value, air ambient humidity value or soil nutrient compositional data value in crop growth environment.
According to a third aspect of the invention we, a kind of crop growth supervisory systems based on the Big Dipper is provided, wherein, described pick-up unit comprises soil nutrient detector, temperature sensor or humidity sensor, described soil nutrient detector for detect crop growth environment soil in nutrient data value, described nutrient data value comprises the content data value of nitrogen, phosphorus, potassium, organic matter or moisture, described temperature sensor is for detecting the temperature data value of crop growth environment, and described humidity sensor is for detecting the humidity data value of crop growth environment.
According to a forth aspect of the invention, a kind of crop growth supervisory systems based on the Big Dipper is provided, wherein, described image processing apparatus comprises image storage unit, median filter unit, image division unit, image binaryzation unit and analysis and processing unit, described image storage unit is for storing the image information of described crops and the crops image information relevant with described first parameter data values, described median filter unit is connected with described image collecting device, for to the image information of described crops based on median filtering algorithm with output filtering image, described image division unit is connected with described median filter unit, for receiving described filtering image and the proportional numerical value shared in brightness value of the green component values calculating each pixel in described filtering image, when described proportional numerical value is greater than preset proportion threshold value, the pixel that described proportional numerical value is corresponding is green pixel, when described proportional numerical value is less than described preset proportion threshold value, the pixel that described proportional numerical value is corresponding is non-green pixel, described image binaryzation unit is for receiving the described green pixel of described image division unit output and described non-green pixel, based on image binaryzation to export binaryzation crops subimage, described analysis and processing unit is connected with described image binaryzation unit and described image storage unit, for drawing described first parameter data values after analyzing and processing.
According to a fifth aspect of the invention, a kind of crop growth supervisory systems based on the Big Dipper is provided, wherein, described image collecting device, described image processing apparatus, described pick-up unit, described locating device, described computer controlling center and described crops are supervised control center and are provided with wireless communication module.
According to a sixth aspect of the invention, provide a kind of crop growth supervisory systems based on the Big Dipper, wherein, described crops supervision steering order comprises pesticide spraying instruction or crop irrigation instruction.
According to a seventh aspect of the invention, provide a kind of crop growth supervisory systems based on the Big Dipper, wherein, described pesticide spraying instruction comprises pesticide spraying position, agricultural chemicals ratio or spray rate.
According to an eighth aspect of the invention, provide a kind of crop growth supervisory systems based on the Big Dipper, wherein, described crop irrigation instruction comprises the position of irrigation, the water yield of irrigation or water velocity.
According to a ninth aspect of the invention, there is provided a kind of crop growth supervisory systems based on the Big Dipper, wherein, described pesticide spraying instruction is completed by described unmanned plane, described crop irrigation instruction is completed by automatic irrigation system, and described Crops in Applying Fertilizer instruction is completed by control terminal.
Crop growth supervisory systems based on the Big Dipper provided by the invention, can the parameter data values of the growing state of comprehensive monitoring crops and the growing environment of crops in real time, and carry out intelligent management crops by this parameter data values, due to its intelligentized management system, make proportion of crop planting personnel can save a large amount of work workloads and working time.
Accompanying drawing explanation
Fig. 1 is the framed structure schematic diagram of the crop growth supervisory systems based on the Big Dipper of the present invention;
Fig. 2 is the framed structure schematic diagram of the image processing apparatus of the crop growth supervisory systems based on the Big Dipper of the present invention.
Description of reference numerals:
1, image collecting device 2, image processing apparatus
3, pick-up unit 4, computer controlling center
5, locating device 6, crops supervision control center
21, image storage unit 22, median filter unit
23, image division unit 24, image binaryzation unit
25, analysis and processing unit
Embodiment
For making object of the present invention, technical scheme and advantage clearly understand, below in conjunction with embodiment also with reference to accompanying drawing, the present invention is described in more detail.Should be appreciated that, these describe just exemplary, and do not really want to limit the scope of the invention.In addition, in the following description, the description to known features and technology is eliminated, to avoid unnecessarily obscuring concept of the present invention.
Embodiments provide a kind of crop growth supervisory systems based on the Big Dipper, Fig. 1 is the framed structure schematic diagram of the crop growth supervisory systems based on the Big Dipper of the present invention, as shown in Figure 1, should comprise based on the crop growth supervisory systems of the Big Dipper: image collecting device 1, image processing apparatus 2, pick-up unit 3, computer controlling center 4, locating device 5 and crops supervision control center 6, computer controlling center 4 and image collecting device 1, image processing apparatus 2, pick-up unit 3, locating device 5, crops supervision control center 6 connects respectively, for controlling the location of locating device 5.
Image collecting device 1, for gathering the image information of crops, is convenient to the upgrowth situation observing crops.Image processing apparatus 2, for carrying out analyzing and processing to the image information of the crops collected, draws the first parameter data values that crops own growth is relevant.Pick-up unit 3, for detecting the second relevant parameter data values of crop growth environment.Computer controlling center 4, for arranging the desired parameters value range of different crops self and growing environment, and for receiving the first parameter data values and the second parameter data values, and the desired parameters value range of different crops self and growing environment and the first parameter data values and the second parameter data values are carried out com-parison and analysis to reach a conclusion data, here it should be noted that, different crops can be wheat, corn, tomato, paddy rice etc., can be provided with the relative growth Parameter data information of often kind of crops in computer-internal.Locating device 5, sprays region for unmanned plane being navigated to target and positions monitoring to target irrigated area; This locating device 5 comprises Beidou satellite navigation equipment and radio receiver-transmitter, and wherein, Beidou satellite navigation equipment is for receiving the real-time Beidou navigation position of the unmanned plane of Beidou navigation satellite transmission; Radio receiver-transmitter, be connected with computer controlling center 4 and spray region or target irrigated area with receiving target, and to computer controlling center 4 return state information, target sprays region or target irrigated area comprises target Beidou navigation position and object height, and status information comprises real-time Beidou navigation position, unmanned plane height, residue agricultural chemicals dosage or the soil nutrient content in real time of unmanned plane.Crops supervision control center 6, for the findings data of receiving computer control center 4 and send corresponding crops supervision steering order according to findings data.
Fig. 2 is the framed structure schematic diagram of the image processing apparatus of the crop growth supervisory systems based on the Big Dipper of the present invention.As shown in Figure 2, image processing apparatus 2 comprises image storage unit 21, median filter unit 22, image division unit 23, image binaryzation unit 24 and analysis and processing unit 25, image storage unit 21 is for storing the image information of crops and the crops image information relevant with the first parameter data values, median filter unit 22 is connected with image collecting device 1, for to the image information of crops based on median filtering algorithm with output filtering image, image division unit 23 is connected with median filter unit 22, for accepting filter image and the proportional numerical value that in calculation of filtered image, the green component values of each pixel is shared in brightness value, when proportional numerical value is greater than preset proportion threshold value, the pixel that proportional numerical value is corresponding is green pixel, when proportional numerical value is less than preset proportion threshold value, the pixel that proportional numerical value is corresponding is non-green pixel, image binaryzation unit 24 is for receiving green pixel and the non-green pixel of image division unit 23 output, based on image binaryzation to export binaryzation crops subimage, analysis and processing unit 25 is connected with image binaryzation unit 24 and image storage unit 21, for drawing the first parameter data values after analyzing and processing.
As further technical scheme, the image information that can gather image collecting device 1 based on the image processing apparatus 2 in the crop growth supervisory systems of the Big Dipper of the present invention is carried out analyzing and processing and is drawn the first parameter data values that crops own growth is relevant.It should be noted that, this first parameter data values can be crops self foliage disease worm kind, blade face integrity degree, blade face color, rhizome color or rhizome thickness.By the measurement of these parameter data values, the upgrowth situation of crops can be directly acquainted with, and measuring process is fast easy, detection method is intelligent, a large amount of work workloads can be reduced like this for the plant personnel of plantation Large Area of Crops, also crops can be made to be detected in real time, avoid because artificial origin may be inconsiderate to crop management, to such an extent as to the situation of crop growth information can not be understood in time.
As further technical scheme, relevant second parameter data values that can be gone out crop growth environment based on the pick-up unit 3 in the crop growth supervisory systems of the Big Dipper by checkout equipment direct-detection of the present invention.This second parameter data values can be air ambient temperature value, air ambient humidity value or soil nutrient compositional data value in crop growth environment.Wherein pick-up unit 3 i.e. monitoring equipment can comprise following equipment, such as: the checkout equipments such as soil nutrient detector, temperature sensor or humidity sensor.Wherein, soil nutrient detector for detect crop growth environment soil in nutrient data value, this nutrient data value comprises the content data value of nitrogen, phosphorus, potassium, organic matter or moisture, temperature sensor is for detecting the temperature data value of crop growth environment, and humidity sensor is for detecting the humidity data value of crop growth environment.By the measurement of these parameter data values, the conditions associated of the growing environment of crops can be directly acquainted with, make proportion of crop planting personnel can understand the growing state of crops in real time.Because the second parameter data values completes by pick-up unit 3 Intelligent Measurement, the error that artificial origin causes so both can be reduced, again can quickly and easily for proportion of crop planting personnel provide growth parameter(s) data value.
In addition, in order to transmit data better, the present invention is based on the image collecting device 1 in the crop growth supervisory systems of the Big Dipper, image processing apparatus 2, pick-up unit 3, computer controlling center 4, locating device 5 and supervising in control center 6 with crops and be provided with wireless communication module.Arrange like this and data can be made to be transferred to receiving trap quickly in a wireless form, convenient and swift, practical simple.Preferably, this wireless communication module can be Zigbee wireless communication module, due to Zigbee network power saving, reliable, cost is low, capacity is safer greatly again, and ZigBee technology target is applied in the aspects such as Industry Control, home automation, remote measuring and controlling, automotive automation, agricultural automation and medical treatment and nursing at present, such as light Automated condtrol, the data acquisition of sensor and monitoring, oil field, electric power, the application such as mine and logistics management, it can also moving target in localized region in addition, and such as, vehicle in city positions.
The present invention is based on crops supervision control center 6 in the crop growth supervisory systems of the Big Dipper can the concluding data of receiving computer control center 4, and according to this concluding data analysis process, finally sends crops supervision steering order.Wherein, these crops supervision steering order mainly comprises pesticide spraying instruction, crop irrigation instruction or Crops in Applying Fertilizer instruction.It should be noted that, pesticide spraying instruction mainly comprises target that unmanned plane sprays insecticide and sprays the information such as the spray rate that position, the ratio of agricultural chemicals of sprinkling or unmanned plane spray insecticide, wherein, for the agricultural chemicals ratio that the ratio of the agricultural chemicals sprayed can preferably select experienced proportion of crop planting personnel to advise according to the growing state of crops.After agricultural chemicals proportioning completes, its pesticide spraying instruction is completed by unmanned plane, and the flight path of unmanned plane can carry out navigator fix by big-dipper satellite, thus makes unmanned plane intellectuality can complete pesticide spraying process, so both can alleviate the work workload of proportion of crop planting personnel, can also save time.In addition, crop irrigation instruction mainly comprises the information such as the target location of irrigation, the water yield of irrigation or water velocity, and wherein, the target location of irrigation positions primarily of big-dipper satellite, and the water yield of irrigation or water velocity are by automatic irrigation system Based Intelligent Control.After crop irrigation instruction sends, this instruction can be transferred to automatic irrigation system, thus completes automatic irrigation crops.
In addition, can also according to the findings data of the testing result of pick-up unit 3 and computer controlling center 4, by crops supervise control center 6 send soil environment nutrient data value and relevant measures of fertilizer instruction to control terminal, can for topdressing, seed manure or punching fertilising.For the ease of management crops, enable the convenient management of crops intellectuality, punching fertilising can be selected.For the ease of operation and management, the process can applied fertilizer by control terminal intelligent operation, such as, can select crops to need the correspondence punching fertilising of nutrient while crop irrigation.Owing to rushing the features such as fertilising has easy to use, and fertilizer efficiency is rapid, while irrigating, also give the soil nutrient of crops like this, the normal growth of crops can be ensured.In addition, select fertilization mode in grasp crops growth characteristic and nutritive peculiarity, and on the basis of local soil, weather and cultivation technique etc., must to vary in different localities, reasonably combined, make crops obtain best management.
Should be understood that, above-mentioned embodiment of the present invention only for exemplary illustration or explain principle of the present invention, and is not construed as limiting the invention.Therefore, any amendment made when not departing from spirit of the present invention and scope, equivalent replacement, improvement etc., all should be included within protection scope of the present invention.In addition, claims of the present invention be intended to contain fall into claims scope and border or this scope and border equivalents in whole change and modification.
Claims (9)
1., based on a crop growth supervisory systems for the Big Dipper, it is characterized in that, comprising:
Image collecting device, for gathering the image information of crops, is convenient to the upgrowth situation observing crops;
Image processing apparatus, for carrying out analyzing and processing to the image information of the described crops collected, draws first parameter data values of crops self;
Pick-up unit, for detecting the second parameter data values of crop growth environment;
Computer controlling center, for arranging the desired parameters value range of different crops self and growing environment, and for receiving described first parameter data values and described second parameter data values, and described parameter area value and described first parameter data values and described second parameter data values are carried out com-parison and analysis and to reach a conclusion data;
Locating device, sprays region for unmanned plane being navigated to target and positions monitoring to target irrigated area; Described locating device comprises Beidou satellite navigation equipment and radio receiver-transmitter, and described Beidou satellite navigation equipment is for receiving the real-time Beidou navigation position of the described unmanned plane of Beidou navigation satellite transmission; Radio receiver-transmitter, be connected to receive described target with described computer controlling center and spray region or described target irrigated area, and to described computer controlling center return state information, described target sprays region or described target irrigated area comprises target Beidou navigation position and object height, and described status information comprises real-time Beidou navigation position, unmanned plane height, residue agricultural chemicals dosage or the soil nutrient content in real time of described unmanned plane;
Crops supervision control center, for receiving the described findings data of described computer controlling center and sending corresponding crops supervision steering order according to described findings data;
Described computer controlling center is supervised control center with described image collecting device, described image processing apparatus, described pick-up unit, described locating device, described crops and is connected respectively, for controlling the location of described locating device.
2. the crop growth supervisory systems based on the Big Dipper according to claim 1, it is characterized in that, described first parameter data values is crops self foliage disease worm kind, blade face integrity degree, blade face color, rhizome color or rhizome thickness, and described second parameter data values is air ambient temperature value, air ambient humidity value or soil nutrient compositional data value in crop growth environment.
3. the crop growth supervisory systems based on the Big Dipper according to claim 1, it is characterized in that, described pick-up unit comprises soil nutrient detector, temperature sensor or humidity sensor, described soil nutrient detector for detect crop growth environment soil in nutrient data value, described nutrient data value comprises the content data value of nitrogen, phosphorus, potassium, organic matter or moisture, described temperature sensor is for detecting the temperature data value of crop growth environment, and described humidity sensor is for detecting the humidity data value of crop growth environment.
4. the crop growth supervisory systems based on the Big Dipper according to claim 1, it is characterized in that, described image processing apparatus comprises image storage unit, median filter unit, image division unit, image binaryzation unit and analysis and processing unit, described image storage unit is for storing the image information of described crops and the crops image information relevant with described first parameter data values, described median filter unit is connected with described image collecting device, for to the image information of described crops based on median filtering algorithm with output filtering image, described image division unit is connected with described median filter unit, for receiving described filtering image and the proportional numerical value shared in brightness value of the green component values calculating each pixel in described filtering image, when described proportional numerical value is greater than preset proportion threshold value, the pixel that described proportional numerical value is corresponding is green pixel, when described proportional numerical value is less than described preset proportion threshold value, the pixel that described proportional numerical value is corresponding is non-green pixel, described image binaryzation unit is for receiving the described green pixel of described image division unit output and described non-green pixel, based on image binaryzation to export binaryzation crops subimage, described analysis and processing unit is connected with described image binaryzation unit and described image storage unit, for drawing described first parameter data values after analyzing and processing.
5. the crop growth supervisory systems based on the Big Dipper according to claim 1, it is characterized in that, described image collecting device, described image processing apparatus, described pick-up unit, described locating device, described computer controlling center and described crops are supervised control center and are provided with wireless communication module.
6. a kind of crop growth supervisory systems based on the Big Dipper according to claim 1, is characterized in that, described crops supervision steering order comprises pesticide spraying instruction, crop irrigation instruction or Crops in Applying Fertilizer instruction.
7. the crop growth supervisory systems based on the Big Dipper according to claim 6, is characterized in that, described pesticide spraying instruction comprises pesticide spraying position, agricultural chemicals ratio or spray rate.
8. the crop growth supervisory systems based on the Big Dipper according to claim 6, is characterized in that, described crop irrigation instruction comprises the position of irrigation, the water yield of irrigation or water velocity.
9. the crop growth supervisory systems based on the Big Dipper according to claim 6, is characterized in that, described pesticide spraying instruction is completed by described unmanned plane; Described crop irrigation instruction is completed by automatic irrigation system, and described Crops in Applying Fertilizer instruction is completed by control terminal.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2012142050A1 (en) * | 2011-04-10 | 2012-10-18 | Earthtec Solutions Llc | Methods and systems for monitoring crop management and transport |
| CN103744369A (en) * | 2013-12-23 | 2014-04-23 | 苏州亚安智能科技有限公司 | Method for realizing intelligent management of crop monitoring platform |
| CN104049625A (en) * | 2014-07-09 | 2014-09-17 | 华南农业大学 | Internet-of-things irrigation facility regulating and controlling platform and method based on unmanned aerial vehicle |
| CN204116927U (en) * | 2014-09-20 | 2015-01-21 | 无锡北斗星通信息科技有限公司 | Based on the pesticide spraying platform of image acquisition |
| CN104351020A (en) * | 2014-11-04 | 2015-02-18 | 无锡北斗星通信息科技有限公司 | Image acquisition-based farmland automatic irrigation system |
-
2015
- 2015-06-11 CN CN201510320328.6A patent/CN104881017B/en not_active Expired - Fee Related
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2012142050A1 (en) * | 2011-04-10 | 2012-10-18 | Earthtec Solutions Llc | Methods and systems for monitoring crop management and transport |
| CN103744369A (en) * | 2013-12-23 | 2014-04-23 | 苏州亚安智能科技有限公司 | Method for realizing intelligent management of crop monitoring platform |
| CN104049625A (en) * | 2014-07-09 | 2014-09-17 | 华南农业大学 | Internet-of-things irrigation facility regulating and controlling platform and method based on unmanned aerial vehicle |
| CN204116927U (en) * | 2014-09-20 | 2015-01-21 | 无锡北斗星通信息科技有限公司 | Based on the pesticide spraying platform of image acquisition |
| CN104351020A (en) * | 2014-11-04 | 2015-02-18 | 无锡北斗星通信息科技有限公司 | Image acquisition-based farmland automatic irrigation system |
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