CN108334139A - A kind of method and system of the greenhouse automation control based on big data - Google Patents
A kind of method and system of the greenhouse automation control based on big data Download PDFInfo
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- CN108334139A CN108334139A CN201810172469.1A CN201810172469A CN108334139A CN 108334139 A CN108334139 A CN 108334139A CN 201810172469 A CN201810172469 A CN 201810172469A CN 108334139 A CN108334139 A CN 108334139A
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- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
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Abstract
The method of this application discloses a kind of greenhouse automation control based on big data, including：Pretreatment operation is carried out to the chamber crop big data received, obtains training set；Initial model is trained according to training set, obtains plantation Policy model；When receiving the Crop Information of input, most preferably plantation strategy is obtained according to Crop Information using plantation Policy model；According to best plantation policy control greenhouse.This method completes the integration to chamber crop big data, eliminate the process of the feature of artificial extraction chamber crop big data, and the plantation Policy model enable handles the Crop Information of input, obtain the best plantation strategy based on chamber crop big data, so that the precision improvement of every plantation strategy of various crops so that the yield and quality of crop get a promotion.The application additionally provides a kind of system, equipment and the computer readable storage medium of the greenhouse automation control based on big data simultaneously, has above-mentioned advantageous effect.
Description
Technical field
This application involves greenhouse intelligent control field, more particularly to the side of a kind of greenhouse automation control based on big data
Method, system, equipment and computer readable storage medium.
Background technology
Greenhouse (greenhouse), also known as greenhouse, energy light transmission, heat preservation, are the facilities for cultivated plant and cultivated animals.
In the season for being not suitable for plant and animal growth, yield can be increased and breeding time is provided, be chiefly used in low temperature season warm season vegetable, flower
The plant cultures such as grass, forest or nursery etc., it is generally warming by the way that confined space progress is arranged, and light transmission and irrigation can be carried out.
Also occur the system much automatically controlled about crop growth environment in the prior art, passes through intelligent control module
Greenhouse is adjusted in control irrigation equipment, heat-preserving equipment etc., to reach the environment of crop suitable growth, however, existing
The tactful basic source of various plantations used in Greenhouse System is in laboratory data, and there are certain errors so that the production of crop
Amount and quality are unable to reach optimal.
In the current of big data fast development, the essence of the various plantation strategies of various crops how is promoted using big data
Degree, and then the yield of promotion crop and quality are a technical problem that technical personnel in the field need to solve at present.
Invention content
The purpose of the application is to provide a kind of method, system, equipment and the meter of the greenhouse automation control based on big data
Calculation machine readable storage medium storing program for executing, the precision of the various plantation strategies for promoting various crops using big data, and then promote crop
Yield and quality.
In order to solve the above technical problems, the application provides a kind of method of the greenhouse automation control based on big data, it should
Method includes：
Pretreatment operation is carried out to the chamber crop big data received, obtains training set；Wherein, the chamber crop is big
Data include crop species, environmental parameter and crop quality parameter；
Initial model is trained according to the training set, obtains plantation Policy model；
When receiving the Crop Information of input, obtained most preferably according to the Crop Information using the plantation Policy model
Plantation strategy；
According to the best plantation policy control greenhouse.
Optionally, the described pair of chamber crop big data received carries out pretreatment operation, obtains training set, including：
Housekeeping operation is carried out to the crop received, obtains the pending data with same format；
The pending data is subjected to processing operation, obtains normal data；Wherein, the processing operation includes that data are clear
Wash, data interpolation, data conversion, data normalization, in data verification at least one of；
The training set is established according to the normal data.
Optionally, it is obtained most preferably planting strategy according to the Crop Information using the plantation Policy model, including：
Crop species and the growth date of crop are determined according to the Crop Information；
The crop species and the growth date are analyzed using the plantation Policy model, obtain the optimal of the crop
The corresponding environmental parameter of crop quality parameter；
Best plantation strategy is formulated according to the environmental parameter.
Optionally, according to the best plantation policy control greenhouse, including：
It parses the best plantation strategy and obtains suitable environment parameter；Wherein, the suitable environment parameter includes most thermophilic
Degree, optimum humidity, most suitable light intensity and optimum moisture；
Temperature control device is adjusted, so that the temperatures approach in the greenhouse is in the optimum temperature；
Humidity conditioner is adjusted, so that the humidity in the greenhouse levels off to the optimum humidity；
Light controlling device is adjusted, so that the light intensity in the greenhouse levels off to the most suitable light intensity；
Water volume control device is adjusted, so that the moisture in the greenhouse levels off to the optimum moisture.
The application also provides a kind of system of the greenhouse automation control based on big data, which includes：
Preprocessing module obtains training set for carrying out pretreatment operation to the chamber crop big data received；Its
In, the chamber crop big data includes crop species, environmental parameter and crop quality parameter；
Training module obtains plantation Policy model for training initial model according to the training set；
Tactful acquisition module, for when receiving the Crop Information of input, using the plantation Policy model according to institute
Crop Information is stated to obtain most preferably planting strategy；
Control module, for according to the best plantation policy control greenhouse.
Optionally, the preprocessing module includes：
Submodule is arranged, for carrying out housekeeping operation to the crop that receives, obtains having same format to wait locating
Manage data；
Submodule is handled, for the pending data to be carried out processing operation, obtains normal data；Wherein, the place
Reason operation includes at least one in data cleansing, data interpolation, data conversion, data normalization, data verification；
Setting up submodule, for establishing the training set according to the normal data.
Optionally, the tactful acquisition module includes：
Determination sub-module, the crop species for determining crop according to the Crop Information and growth date；
Submodule is analyzed, for analyzing the crop species and the growth date using the plantation Policy model, is obtained
To the corresponding environmental parameter of optimal crop quality parameter of the crop；
Submodule is formulated, for formulating best plantation strategy according to the environmental parameter.
Optionally, the control module includes：
Analyzing sub-module obtains suitable environment parameter for parsing the best plantation strategy；Wherein, the suitable environment
Parameter includes optimum temperature, optimum humidity, most suitable light intensity and optimum moisture；
First adjusts submodule, for adjusting temperature control device, so that the temperatures approach in the greenhouse is in the optimum temperature；
Second adjusts submodule, for adjusting humidity conditioner so that the humidity in the greenhouse level off to it is described most suitable
Humidity；
Third adjusts submodule, for adjusting light controlling device, so that the light intensity in the greenhouse levels off to the most suitable light intensity；
4th adjusts submodule, for adjusting water volume control device so that the moisture in the greenhouse level off to it is described most suitable
Moisture.
The application also provides a kind of greenhouse automation control appliance based on big data, and it is automatic to be somebody's turn to do the greenhouse based on big data
Changing control device includes：
Memory, for storing computer program；
Processor realizes that the greenhouse based on big data is certainly as described in any of the above-described when for executing the computer program
The step of method of dynamicization control.
The application also provides a kind of computer readable storage medium, and calculating is stored on the computer readable storage medium
Machine program realizes the greenhouse automation based on big data as described in any of the above-described when the computer program is executed by processor
The step of method of control.
The method of greenhouse automation control provided herein based on big data, by big to the chamber crop received
Data carry out pretreatment operation, obtain training set；Wherein, chamber crop big data includes crop species, environmental parameter and crop
Quality parameter；Initial model is trained according to training set, obtains plantation Policy model；When receiving the Crop Information of input, profit
Most preferably plantation strategy is obtained according to Crop Information with plantation Policy model；According to best plantation policy control greenhouse.
Technical solution provided herein is obtained by carrying out pretreatment operation to the chamber crop big data received
Training set completes the integration to chamber crop big data；It trains initial model to obtain plantation Policy model by training set, exempts from
Crop of the plantation Policy model for having gone the process of the feature of artificial extraction chamber crop big data, and having enable to input
Information is handled, and the best plantation strategy based on chamber crop big data is obtained so that every plantation strategy of various crops
Precision improvement；By most preferably planting policy control greenhouse so that the yield and quality of crop get a promotion.The application is same
When additionally provide a kind of system, equipment and the computer readable storage medium of the greenhouse automation control based on big data, have
Above-mentioned advantageous effect, details are not described herein.
Description of the drawings
In order to illustrate the technical solutions in the embodiments of the present application or in the prior art more clearly, to embodiment or will show below
There is attached drawing needed in technology description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
The embodiment of application for those of ordinary skill in the art without creative efforts, can also basis
The attached drawing of offer obtains other attached drawings.
A kind of flow of the method for greenhouse automation control based on big data that Fig. 1 is provided by the embodiment of the present application
Figure；
A kind of reality of the Fig. 2 by S103 in a kind of method of Fig. 1 greenhouse automation controls based on big data provided
The flow chart of manifestation mode；
A kind of structure of the system for greenhouse automation control based on big data that Fig. 3 is provided by the embodiment of the present application
Figure；
The structure of the system for another greenhouse automation control based on big data that Fig. 4 is provided by the embodiment of the present application
Figure；
A kind of structure chart for greenhouse automatic control device based on big data that Fig. 5 is provided by the embodiment of the present application.
Specific implementation mode
The core of the application is to provide a kind of method, system, equipment and the meter of the greenhouse automation control based on big data
Calculation machine readable storage medium storing program for executing, the precision of the various plantation strategies for promoting various crops using big data, and then promote crop
Yield and quality.
To keep the purpose, technical scheme and advantage of the embodiment of the present application clearer, below in conjunction with the embodiment of the present application
In attached drawing, technical solutions in the embodiments of the present application is clearly and completely described, it is clear that described embodiment is
Some embodiments of the present application, instead of all the embodiments.Based on the embodiment in the application, those of ordinary skill in the art
The every other embodiment obtained without making creative work, shall fall in the protection scope of this application.
Referring to FIG. 1, a kind of side for greenhouse automation control based on big data that Fig. 1 is provided by the embodiment of the present application
The flow chart of method.
It specifically comprises the following steps：
S101：Pretreatment operation is carried out to the chamber crop big data received, obtains training set；
Also occur the system much automatically controlled about crop growth environment in the prior art, passes through intelligent control module
Greenhouse is adjusted in control irrigation equipment, heat-preserving equipment etc., to reach the environment of crop suitable growth, however, existing
The tactful basic source of various plantations used in Greenhouse System is in laboratory data, and there are certain errors so that the production of crop
Amount and quality are unable to reach optimal, are based on this, the method for this application provides a kind of greenhouse automation control based on big data,
Big data can be utilized to promote the precision of the various plantation strategies of various crops；
Chamber crop big data mentioned herein includes crop species, environmental parameter and crop quality parameter, wherein environment
Parameter refers to temperature, humidity, light intensity and the moisture of crop growth environment, affects the crop quality parameter of crop, that is, makees
The yield and quality or nutrient content of object；
Optionally, since chamber crop big data purposes is different, there is the skimble-scamble situations of data format, therefore here
That mentions carries out pretreatment operation to the chamber crop big data received, obtains training set, can specifically include：
Housekeeping operation is carried out to the chamber crop big data received, obtains the pending data with same format；
Pending data is subjected to processing operation, obtains normal data；Wherein, processing operation includes data cleansing, data
At least one of in interpolation, data conversion, data normalization, data verification；
Training set is established according to normal data；
After carrying out data prediction through this embodiment, available higher-quality chamber crop big data can solve
Certainly since the data of real world are imperfect, inconsistent and original source data is because of temporal evolution factor, cause loss of learning or
The problem of containing noise.
S102：Initial model is trained according to training set, obtains plantation Policy model；
Optionally, mentioned herein that initial model is trained according to training set, it is specifically as follows and stops after iteration 300,000 times
It only trains, obtains the plantation Policy model based on chamber crop big data so that plantation Policy model can be to the crop of input
Information is handled, and the best plantation strategy based on chamber crop big data is obtained.
S103：When receiving the Crop Information of input, best kind is obtained according to Crop Information using plantation Policy model
Plant strategy；
For example, when the Crop Information for receiving input includes crop species and growth date, analysis Crop Information obtains
The Crop Group of the crop be potato, growth the date be 60 days, at this time using plantation Policy model analyze growth the date be
The best plantation strategy of 60 days potatos：By taking temperature as an example, since the thermophilic of tuber growth is 16 DEG C~18 DEG C, when ground temperature height
When 25 DEG C, stem tuber stops growing；The thermophilic of cauline leaf growth is 15 DEG C~25 DEG C, is stopped growing more than 39 DEG C, and grows the date
It has been grown completely for the cauline leaf of 60 days potatos, therefore the tactful potato growth environment in order to control of the best plantation of the potato
Temperature be 16 DEG C~18 DEG C, humidity, light intensity and the computational methods of moisture are similar with temperature computation method, and details are not described herein；
Optionally, the input mode of Crop Information mentioned herein can be the dynamic input of user hand, or system exists
The Crop Information of selected crop is transferred in plantation database, the application is not specifically limited the input mode of Crop Information.
S104：According to best plantation policy control greenhouse.
Based on the above-mentioned technical proposal, the method for a kind of greenhouse automation control based on big data provided herein,
Training set is obtained by carrying out pretreatment operation to the chamber crop big data received, is completed to chamber crop big data
It integrates；It trains initial model to obtain plantation Policy model by training set, eliminates the spy of artificial extraction chamber crop big data
The process of sign, and the plantation Policy model enable handles the Crop Information of input, obtains being based on chamber crop
The best plantation strategy of big data so that the precision improvement of every plantation strategy of various crops；By most preferably planting tactful control
Greenhouse processed so that the yield and quality of crop get a promotion.
Based on above-described embodiment, referring to FIG. 2, Fig. 2 automates control by a kind of greenhouse based on big data that Fig. 1 is provided
The flow chart of a kind of practical manifestation mode of S103 in the method for system.
It specifically includes following steps：
S201：Crop species and the growth date of crop are determined according to Crop Information；
S202：Using plantation Policy model analysis crop species and growth date, the optimal crop quality ginseng of crop is obtained
The corresponding environmental parameter of number；
S203：Best plantation strategy is formulated according to environmental parameter.
Further, step S104 is mentioned in a upper embodiment, according to best plantation policy control greenhouse, specifically
Can be：
The best plantation strategy of parsing obtains suitable environment parameter；Wherein, suitable environment parameter includes optimum temperature, most suitable humidity
Degree, most suitable light intensity and optimum moisture；
Temperature control device is adjusted, so that the temperatures approach in greenhouse is in optimum temperature；
Humidity conditioner is adjusted, so that the humidity in greenhouse levels off to optimum humidity；
Light controlling device is adjusted, so that the light intensity in greenhouse levels off to most suitable light intensity；
Water volume control device is adjusted, so that the moisture in greenhouse levels off to optimum moisture.
Based on the above-mentioned technical proposal, the embodiment of the present application can by determined according to Crop Information crop crop species and
The date is grown, and then using plantation Policy model analysis crop species and growth date, obtains the optimal crop quality of the crop
The corresponding environmental parameter of parameter finally formulates best plantation strategy according to environmental parameter so that every plantation plan of various crops
Precision improvement slightly, and then according to best plantation policy control greenhouse, so that the yield and quality of crop get a promotion.
Referring to FIG. 3, a kind of greenhouse automation control based on big data that Fig. 3 is provided by the embodiment of the present application is
The structure chart of system.
The system may include：
Preprocessing module 100 obtains training set for carrying out pretreatment operation to the chamber crop big data received；
Wherein, chamber crop big data includes crop species, environmental parameter and crop quality parameter；
Training module 200 obtains plantation Policy model for training initial model according to training set；
Tactful acquisition module 300, for when receiving the Crop Information of input, using plantation Policy model according to crop
Information obtains most preferably planting strategy；
Control module 400, for according to best plantation policy control greenhouse.
Referring to FIG. 4, another greenhouse automation control based on big data that Fig. 4 is provided by the embodiment of the present application
The structure chart of system.
The preprocessing module 100 may include：
Submodule is arranged, for carrying out housekeeping operation to the chamber crop big data received, is obtained with same format
Pending data；
Processing submodule obtains normal data for pending data to be carried out processing operation；Wherein, processing operation packet
Include at least one in data cleansing, data interpolation, data conversion, data normalization, data verification；
Setting up submodule, for establishing training set according to normal data.
The strategy acquisition module 300 may include：
Determination sub-module, the crop species for determining crop according to Crop Information and growth date；
Submodule is analyzed, for using plantation Policy model analysis crop species and growth date, obtaining the optimal of crop
The corresponding environmental parameter of crop quality parameter；
Submodule is formulated, for formulating best plantation strategy according to environmental parameter.
The control module 400 may include：
Analyzing sub-module obtains suitable environment parameter for parsing best plantation strategy；Wherein, suitable environment parameter includes
Optimum temperature, optimum humidity, most suitable light intensity and optimum moisture；
First adjusts submodule, for adjusting temperature control device, so that the temperatures approach in greenhouse is in optimum temperature；
Second adjusts submodule, for adjusting humidity conditioner, so that the humidity in greenhouse levels off to optimum humidity；
Third adjusts submodule, for adjusting light controlling device, so that the light intensity in greenhouse levels off to most suitable light intensity；
4th adjusts submodule, for adjusting water volume control device, so that the moisture in greenhouse levels off to optimum moisture.
Each component part in system above can be applied in following step：
It arranges submodule and housekeeping operation is carried out to the chamber crop big data that receives, obtain having same format to wait locating
Manage data；Pending data is carried out processing operation by processing submodule, obtains normal data；Setting up submodule is according to normal data
Establish training set；
Training module trains initial model according to training set, obtains plantation Policy model；Determination sub-module is believed according to crop
Breath determines crop species and the growth date of crop；Submodule is analyzed using plantation Policy model analysis crop species and growth day
Phase obtains the corresponding environmental parameter of optimal crop quality parameter of crop；It formulates submodule and formulates best kind according to environmental parameter
Plant strategy；
The best plantation strategy of analyzing sub-module parsing obtains suitable environment parameter；First, which adjusts submodule, adjusts temperature control dress
It sets, so that the temperatures approach in greenhouse is in optimum temperature；Second, which adjusts submodule, adjusts humidity conditioner, so that the humidity in greenhouse
Level off to optimum humidity；Third adjusts submodule and adjusts light controlling device, so that the light intensity in greenhouse levels off to most suitable light intensity；4th adjusts
Knot module adjusts water volume control device, so that the moisture in greenhouse levels off to optimum moisture.
Referring to FIG. 5, a kind of greenhouse automation control appliance based on big data that Fig. 5 is provided by the embodiment of the present application
Structure chart.
Greenhouse automation control appliance based on big data can generate bigger difference because configuration or performance are different, can
With include one or more processors (central processing units, CPU) 522 (for example, one or one with
Upper processor) and memory 532, one or more storage application programs 542 or data 544 storage medium 530 (such as
One or more mass memory units).Wherein, memory 532 and storage medium 530 can be of short duration storage or persistently deposit
Storage.The program for being stored in storage medium 530 may include one or more modules (diagram does not mark), and each module can be with
Include to the series of instructions operation in device.Further, central processing unit 522 could be provided as and storage medium 530
Communication executes the series of instructions operation in storage medium 530 on the greenhouse automation control appliance 500 based on big data.
Greenhouse automation control appliance 500 based on big data can also include one or more power supplys 526, one
Or more than one wired or wireless network interface 550, one or more input/output interfaces 558, and/or, one or one
A above operating system 541, such as Windows ServerTM, Mac OS XTM, UnixTM, LinuxTM, FreeBSDTM etc.
Deng.
Step in the method for greenhouse automation control based on big data described in above-mentioned Fig. 1 to Fig. 2 is big by being based on
The greenhouse automation control appliance of data is based on the structure shown in fig. 5 and realizes.
It is apparent to those skilled in the art that for convenience and simplicity of description, the system of foregoing description,
The specific work process of device and module, can refer to corresponding processes in the foregoing method embodiment, and details are not described herein.
In several embodiments provided herein, it should be understood that disclosed system, apparatus and method, it can be with
It realizes by another way.For example, system embodiment described above is only schematical, for example, the division of module,
Only a kind of division of logic function, formula that in actual implementation, there may be another division manner, such as multiple module or components can be with
In conjunction with or be desirably integrated into another system, or some features can be ignored or not executed.Another point, it is shown or discussed
Mutual coupling, direct-coupling or communication connection can be by some interfaces, the INDIRECT COUPLING of system or module or
Communication connection can be electrical, machinery or other forms.
The module illustrated as separating component may or may not be physically separated, and be shown as module
Component may or may not be physical module, you can be located at a place, or may be distributed over multiple networks
In module.Some or all of module therein can be selected according to the actual needs to achieve the purpose of the solution of this embodiment.
In addition, each function module in each embodiment of the application can be integrated in a processing module, it can also
That modules physically exist alone, can also two or more modules be integrated in a module.Above-mentioned integrated mould
The form that hardware had both may be used in block is realized, can also be realized in the form of software function module.
If integrated module is realized and when sold or used as an independent product in the form of software function module, can
To be stored in a computer read/write memory medium.Based on this understanding, the technical solution of the application substantially or
Say that all or part of the part that contributes to existing technology or the technical solution can embody in the form of software products
Out, which is stored in a storage medium, including some instructions are used so that a computer equipment
(can be personal computer, funcall device or the network equipment etc.) executes the whole of each embodiment method of the application
Or part steps.And storage medium above-mentioned includes：USB flash disk, mobile hard disk, read-only memory (Read-Only Memory,
ROM), random access memory (Random Access Memory, RAM), magnetic disc or CD etc. are various can store program
The medium of code.
Above to a kind of method of greenhouse automation control based on big data provided herein, system, equipment and
Computer readable storage medium is described in detail.Principle and embodiment of the specific case to the application used herein
It is expounded, the description of the example is only used to help understand the method for the present application and its core ideas.It should be pointed out that
For those skilled in the art, under the premise of not departing from the application principle, can also to the application into
Row some improvements and modifications, these improvement and modification are also fallen into the application scope of the claims.
It should also be noted that, in the present specification, relational terms such as first and second and the like be used merely to by
One entity or operation are distinguished with another entity or operation, without necessarily requiring or implying these entities or operation
Between there are any actual relationship or orders.Moreover, the terms "include", "comprise" or its any other variant meaning
Covering non-exclusive inclusion, so that the process, method, article or equipment including a series of elements includes not only that
A little elements, but also include other elements that are not explicitly listed, or further include for this process, method, article or
The intrinsic element of equipment.In the absence of more restrictions, the element limited by sentence "including a ...", is not arranged
Except there is also other identical elements in the process, method, article or equipment including element.
Claims (10)
1. a kind of method of the greenhouse automation control based on big data, which is characterized in that including：
Pretreatment operation is carried out to the chamber crop big data received, obtains training set；Wherein, the chamber crop big data
Including crop species, environmental parameter and crop quality parameter；
Initial model is trained according to the training set, obtains plantation Policy model；
When receiving the Crop Information of input, most preferably planted according to the Crop Information using the plantation Policy model
Strategy；
According to the best plantation policy control greenhouse.
2. according to the method described in claim 1, it is characterized in that, the described pair of chamber crop big data received is located in advance
Reason operation, obtains training set, including：
Housekeeping operation is carried out to the chamber crop big data received, obtains the pending data with same format；
The pending data is subjected to processing operation, obtains normal data；Wherein, the processing operation include data cleansing,
At least one of in data interpolation, data conversion, data normalization, data verification；
The training set is established according to the normal data.
3. according to the method described in claim 1, it is characterized in that, using the plantation Policy model according to the Crop Information
It obtains most preferably planting strategy, including：
Crop species and the growth date of crop are determined according to the Crop Information；
The crop species and the growth date are analyzed using the plantation Policy model, obtain the optimal crop of the crop
The corresponding environmental parameter of quality parameter；
Best plantation strategy is formulated according to the environmental parameter.
4. according to the method described in claim 3, it is characterized in that, according to the best plantation policy control greenhouse, wrap
It includes：
It parses the best plantation strategy and obtains suitable environment parameter；Wherein, the suitable environment parameter includes optimum temperature, most
Suitable humidity degree, most suitable light intensity and optimum moisture；
Temperature control device is adjusted, so that the temperatures approach in the greenhouse is in the optimum temperature；
Humidity conditioner is adjusted, so that the humidity in the greenhouse levels off to the optimum humidity；
Light controlling device is adjusted, so that the light intensity in the greenhouse levels off to the most suitable light intensity；
Water volume control device is adjusted, so that the moisture in the greenhouse levels off to the optimum moisture.
5. a kind of system of the greenhouse automation control based on big data, which is characterized in that including：
Preprocessing module obtains training set for carrying out pretreatment operation to the chamber crop big data received；Wherein, institute
It includes crop species, environmental parameter and crop quality parameter to state chamber crop big data；
Training module obtains plantation Policy model for training initial model according to the training set；
Tactful acquisition module, for when receiving the Crop Information of input, using the plantation Policy model according to the work
Object information obtains most preferably planting strategy；
Control module, for according to the best plantation policy control greenhouse.
6. system according to claim 5, which is characterized in that the preprocessing module includes：
Submodule is arranged, for carrying out housekeeping operation to the chamber crop big data received, is obtained with same format
Pending data；
Submodule is handled, for the pending data to be carried out processing operation, obtains normal data；Wherein, the processing behaviour
Make to include at least one in data cleansing, data interpolation, data conversion, data normalization, data verification；
Setting up submodule, for establishing the training set according to the normal data.
7. system according to claim 5, which is characterized in that it is described strategy acquisition module include：
Determination sub-module, the crop species for determining crop according to the Crop Information and growth date；
Submodule is analyzed, for analyzing the crop species and the growth date using the plantation Policy model, obtains institute
State the corresponding environmental parameter of optimal crop quality parameter of crop；
Submodule is formulated, for formulating best plantation strategy according to the environmental parameter.
8. system according to claim 7, which is characterized in that the control module includes：
Analyzing sub-module obtains suitable environment parameter for parsing the best plantation strategy；Wherein, the suitable environment parameter
Including optimum temperature, optimum humidity, most suitable light intensity and optimum moisture；
First adjusts submodule, for adjusting temperature control device, so that the temperatures approach in the greenhouse is in the optimum temperature；
Second adjusts submodule, for adjusting humidity conditioner, so that the humidity in the greenhouse levels off to the optimum humidity；
Third adjusts submodule, for adjusting light controlling device, so that the light intensity in the greenhouse levels off to the most suitable light intensity；
4th adjusts submodule, for adjusting water volume control device, so that the moisture in the greenhouse levels off to the optimum moisture.
9. a kind of greenhouse automation control appliance based on big data, which is characterized in that including：
Memory, for storing computer program；
Processor realizes the temperature based on big data as described in any one of Claims 1-4 when for executing the computer program
The step of method of room automation control.
10. a kind of computer readable storage medium, which is characterized in that be stored with computer on the computer readable storage medium
Program realizes the greenhouse based on big data as described in any one of Claims 1-4 when the computer program is executed by processor
The step of method of automation control.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
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