CN110377961B - Crop growth environment control method, device, computer equipment and storage medium - Google Patents
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Abstract
The invention discloses a crop growth environment control method, a device, computer equipment and a storage medium, wherein the method can comprise the following steps: acquiring the current growth stage and growth state information of crops in a greenhouse; inputting the growth stage and growth state information into a prediction model to obtain a predicted optimal value of the environmental variable; the environmental variable values in the greenhouse are adjusted according to the predicted optimal values. By applying the scheme of the invention, crops can be in the optimal growing environment as much as possible, and the accuracy of the adjustment result and the like are improved.
Description
[ field of technology ]
The present invention relates to computer application technology, and in particular, to a method and apparatus for controlling crop growth environment, a computer device, and a storage medium.
[ background Art ]
Along with the development of modern agricultural technology, the greenhouse is gradually realizing informatization, automation and accurate management. The intelligent sensor, the image collector and other Internet of things equipment can be used for digitizing the crop growing environment, and the environment variable values in the greenhouse, such as indoor temperature, humidity, carbon dioxide concentration and the like, can be regulated through various environment variable controllers, so that the crop is in a good growing environment.
The desired growth environment, i.e., the desired environmental variable values, etc., will vary for any crop at different times. At present, the setting of the crop growth environment is mainly achieved by the following ways: and presetting an expert database, inquiring the values of the environment variables suitable for the crops in different periods, and adjusting the values correspondingly. However, the environment variable values stored in the expert database are more general and rough, so that the fine adjustment aiming at specific situations can not be realized, and the accuracy is poor.
[ invention ]
In view of this, the present invention provides a crop growth environment control method, apparatus, computer device, and storage medium.
The specific technical scheme is as follows:
a method of crop growth environmental control comprising:
acquiring the current growth stage and growth state information of crops in a greenhouse;
inputting the growth stage and growth state information into a prediction model to obtain a predicted optimal value of the environmental variable;
and adjusting the environmental variable value in the greenhouse according to the optimal value.
According to a preferred embodiment of the invention, the method further comprises: and adjusting the optimal value according to the data stored in the expert database, and adjusting the environmental variable value in the greenhouse according to the adjusted optimal value.
According to a preferred embodiment of the invention, the number of environmental variables is greater than one;
the adjusting the optimal value according to the data stored in the expert database comprises:
comparing, for each environment variable, an optimal value of the environment variable with a corresponding environment variable value stored in the expert database, the corresponding environment variable value being: the values of the environmental variables in the environmental variable values stored in the expert database and corresponding to the current growth stage and growth state of the crop;
and if the difference between the optimal value and the corresponding environment value is greater than a preset threshold value, generating an adjusted optimal value according to the threshold value and the corresponding environment value.
According to a preferred embodiment of the invention, the method further comprises:
acquiring the time predicted by the prediction model to reach the next growth stage;
if the time required for the crop to actually reach the next growth stage is shorter than the predicted time required to reach the next growth stage, the predictive model is modified.
According to a preferred embodiment of the invention, the method further comprises: acquiring the current environmental variable value in the greenhouse;
said adjusting environmental variable values within said greenhouse according to said optimal values comprises:
and adjusting an execution value of an environment variable controller according to the current environment variable value in the greenhouse and the optimal value so as to adjust the environment variable value in the greenhouse to the optimal value.
According to a preferred embodiment of the invention, the method further comprises: and periodically acquiring the environmental variable value in the greenhouse, and correcting the execution value of the environmental variable controller if the acquired environmental variable value is not consistent with the optimal value.
A crop growth environmental control apparatus comprising: the device comprises a first acquisition unit, a prediction unit and a control unit;
the first acquisition unit is used for acquiring the current growth stage and growth state information of the crops in the greenhouse;
the prediction unit is used for inputting the growth stage and growth state information into a prediction model to obtain a predicted optimal value of the environment variable;
and the control unit is used for adjusting the environmental variable value in the greenhouse according to the optimal value.
According to a preferred embodiment of the present invention, the prediction unit is further configured to adjust the optimal value according to data stored in an expert database;
the control unit is further used for adjusting the environmental variable value in the greenhouse according to the adjusted optimal value.
According to a preferred embodiment of the invention, the number of environmental variables is greater than one;
the prediction unit compares, for each environment variable, an optimal value of the environment variable with a corresponding environment value stored in the expert database, the corresponding environment value being: and if the difference between the optimal value and the corresponding environment variable value is greater than a preset threshold value, generating an adjusted optimal value according to the threshold value and the corresponding environment variable value.
According to a preferred embodiment of the present invention, the prediction unit is further configured to obtain a time required for reaching a next growth stage predicted by the prediction model, and correct the prediction model if the time required for the crop to actually reach the next growth stage is shorter than the predicted time required for reaching the next growth stage.
According to a preferred embodiment of the present invention, the apparatus further comprises: a second acquisition unit for acquiring the current environmental variable value in the greenhouse;
the control unit adjusts an execution value of an environment variable controller according to the current environment variable value in the greenhouse and the optimal value so as to adjust the environment variable value in the greenhouse to the optimal value.
According to a preferred embodiment of the invention, the second acquisition unit is further adapted to periodically acquire environmental variable values within the greenhouse;
the control unit is further configured to correct the execution value of the environment variable controller if it is determined that the environment variable value acquired each time does not match the optimal value.
A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing a method as described above when executing the program.
A computer readable storage medium having stored thereon a computer program which when executed by a processor implements a method as described above.
Based on the description, the scheme of the invention can be adopted to predict the optimal value of the environmental variable by using the prediction model according to the current growth stage and growth state of the crops in the greenhouse, and then the environmental variable value in the greenhouse can be adjusted according to the optimal value, so that the crops are in the optimal growth environment as much as possible, and the accuracy of the adjustment result and the like are improved.
[ description of the drawings ]
Fig. 1 is a flowchart of a first embodiment of a crop growth environment control method according to the present invention.
Fig. 2 is a schematic diagram of the overall implementation process of the crop growth environment control method according to the present invention.
Fig. 3 is a schematic structural diagram of an embodiment of a crop growth environment control device according to the present invention.
Fig. 4 illustrates a block diagram of an exemplary computer system/server 12 suitable for use in implementing embodiments of the present invention.
[ detailed description ] of the invention
In order to make the technical solution of the present invention more clear and obvious, the solution of the present invention will be further described below by referring to the accompanying drawings and examples.
It will be apparent that the described embodiments are some, but not all, embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to fall within the scope of the invention.
In addition, it should be understood that the term "and/or" herein is merely one association relationship describing the associated object, and means that three relationships may exist, for example, a and/or B may mean: a exists alone, A and B exist together, and B exists alone. In addition, the character "/" herein generally indicates that the front and rear associated objects are an "or" relationship.
FIG. 1 is a flow chart of an embodiment of a method for controlling the environment of crop growth according to the present invention. As shown in fig. 1, the following detailed implementation is included.
At 101, growth phase and growth status information of the crop in the greenhouse is acquired.
In 102, the acquired growth phase and growth state information is input into a predictive model to obtain predicted optimal values of the environmental variables.
At 103, the environmental variable values in the greenhouse are adjusted according to the predicted optimal values.
The different types of crops can comprise different growth stages, such as cabbage, for example, the different growth stages of germination stage, seedling stage, rosette stage, heading stage, core stage and the like, and each type of crop comprises the growth stages according to actual needs.
Preferably, the growing state may include a healthy state, which may include excellent, good, withered, etc., and a weight state, which may refer to the weight of crops, etc.
There is no limitation on how to obtain information on the growth stage and growth state in which the crop in the greenhouse is currently located. For example, the growth stage and growth state of the crop can be observed and evaluated by experienced personnel. For another example, the image containing the crop can be shot by a camera, and the growth stage, growth state and the like of the crop can be determined by analyzing the image. Other possible implementations may be used, and are not limiting in this embodiment.
The obtained growth phase and growth state information may be input into a predictive model to obtain an optimal value of the predicted environmental variable. Different types of crops can respectively correspond to different prediction models.
Taking 0.5 mu of cabbages as an example, the input of the growth state information of the prediction model may refer to the overall growth state information (or referred to as average growth state information) of the 0.5 mu of cabbages.
Preferably, after the predicted optimal value of the environmental variable is obtained, the predicted optimal value may be adjusted according to the data stored in the expert database, and the environmental variable value in the greenhouse may be adjusted according to the adjusted optimal value.
For different types of crops, the expert database may store relevant data of the type of crops, for example, the expert database may include environment variable values (environment variable values to be adjusted) corresponding to different growth stages and different growth states. Taking cabbage as an example, the method can comprise environmental variable values respectively corresponding to different growth states of the cabbage in a first growth stage, environmental variable values respectively corresponding to different growth states in a second growth stage, and the like. The different growth states need to cover each growth state of each growth stage as much as possible.
The data in the expert database can be generated manually and empirically, or can be data extracted from trusted data sources such as papers.
The number of environmental variables is typically greater than one and may include, for example, temperature, humidity, illuminance, carbon dioxide concentration, soil moisture, soil humidity, and the like.
For each environment variable, the optimal value of the environment variable may be compared with corresponding environment variable values stored in the expert database, respectively, and the corresponding environment variable values may be: and the values of the environmental variables in the environmental variable values stored in the expert database and corresponding to the current growth stage and the current growth state of the crops, wherein if the expert database does not have the growth state which is completely the same as the current growth state of the crops, the closest growth state can be selected, and if the difference between the optimal value of the environmental variable and the corresponding environmental variable value is greater than a preset threshold value, the adjusted optimal value of the environmental variable can be generated according to the threshold value and the corresponding environmental variable value. The specific value of the threshold value can be determined according to actual needs.
Taking humidity as an example, the predicted optimal value of humidity may be compared with the corresponding humidity value stored in the expert database, where the corresponding humidity value may refer to the value of the humidity variable among the environmental variable values corresponding to the current growth stage and growth state of the crop stored in the expert database, and if the predicted optimal value of humidity is 40, the corresponding humidity value stored in the expert database is 20, and the difference between the predicted optimal value and the corresponding humidity value is 20 and greater than the threshold value 10, the adjusted optimal value of humidity may be generated according to the threshold value 10 and the corresponding humidity value 20, and if 10+20 may be used as the adjusted optimal value of humidity.
If the difference between the optimal value of the environment variable and the corresponding environment value is less than or equal to the threshold value, no adjustment may be made to the optimal value of the environment variable.
By the method, the optimal value of the environment variable can be constrained according to the data stored in the expert database, so that the optimal value is dynamically adjusted within a reasonable range.
After the obtained information of the current growth stage and growth state of the crop is input into the prediction model, the optimal value of the environment variable predicted by the prediction model can be obtained, and the time information predicted by the prediction model to reach the next growth stage can be obtained at the same time.
If the time required for the crop to actually reach the next growth stage is shorter than the predicted time required to reach the next growth stage, the predictive model may be modified. That is, if the crop grows in the adjusted growth environment, the time taken to reach the next growth stage is shorter than the predicted time taken to reach the next growth stage, the predictive model may be modified so that the predictive model learns to the current positive example.
The initial prediction model can be obtained by initializing data in an expert database, namely, the initial training is obtained, and in order to enable the prediction model to have the function of predicting the time required to reach the next growth stage, the expert database can further store: for different growth states of each growth stage, the time information required to reach the next growth stage, respectively.
In the actual application, the prediction model can be continuously corrected, namely optimized. For example, if the crop grows in the adjusted growth environment and the time taken to reach the next growth stage is shorter than the predicted time taken to reach the next growth stage, the prediction model may be modified according to the optimal value of the adjusted environmental variable and the time taken to reach the next growth stage, so that the prediction result of the prediction model is more accurate.
In this embodiment, in addition to the information about the current growth stage and growth state of the crop in the greenhouse, the environmental variable value in the current greenhouse may be obtained. Specifically, various environmental variable values in the greenhouse, such as temperature, humidity, illuminance, carbon dioxide concentration, soil moisture, soil humidity and the like, acquired by various high-precision intelligent sensors can be acquired. The layout position of each high-precision intelligent sensor can be determined according to actual needs.
After the optimal value of the environmental variable or the adjusted optimal value of the environmental variable is obtained, the execution value of the environmental variable controller can be adjusted according to the obtained environmental variable value in the current greenhouse and the optimal value, so that the environmental variable value in the greenhouse is adjusted to the optimal value.
Different environmental variables may correspond to different environmental variable controllers, respectively, such as humidity may correspond to a humidifier, etc. According to the acquired environment variable value and the optimal value in the current greenhouse, the environment variable value in the greenhouse is determined to be adjusted to the optimal value, and the execution value of the environment variable controller is required to be adjusted, so that the environment variable controller can be correspondingly adjusted.
And then, the environmental variable value in the greenhouse can be obtained periodically, and if the obtained environmental variable value is not consistent with the optimal value, the execution value of the environmental variable controller can be corrected, so that the environmental variable value in the greenhouse reaches and is maintained at the optimal value, and the optimal growth state of crops is maintained.
Based on the above description, fig. 2 is a schematic diagram of the overall implementation process of the crop growth environment control method according to the present invention. As shown in fig. 2, information of a current growth stage and a growth state of crops in a greenhouse can be obtained and input into a prediction model, an optimal value of a predicted environmental variable and time required for reaching a next growth stage are obtained, the optimal value of the predicted environmental variable can be restrained/adjusted by data stored in an expert database, in addition, an environmental variable value in the current greenhouse can be obtained, and an execution value of an environmental variable controller can be adjusted according to the environmental variable value in the current greenhouse and the adjusted optimal value of the environmental variable, so that growth environmental control is realized.
It should be noted that, for the sake of simplicity of description, the foregoing method embodiments are expressed as a series of combinations of actions, but it should be understood by those skilled in the art that the present invention is not limited by the order of actions described, as some steps may be performed in other order or simultaneously in accordance with the present invention. Further, those skilled in the art will also appreciate that the embodiments described in the specification are all preferred embodiments, and that the acts and modules referred to are not necessarily required for the present invention.
In a word, by adopting the scheme of the embodiment of the invention, the optimal value of the environmental variable can be predicted by using the prediction model according to the current growth stage and growth state of the crops in the greenhouse, and then the environmental variable value in the greenhouse can be adjusted according to the optimal value, so that the crops are in the optimal growth environment as much as possible, and the accuracy of the adjustment result and the like are improved.
The above description of the method embodiments further describes the solution of the present invention by means of device embodiments.
Fig. 3 is a schematic structural diagram of an embodiment of a crop growth environment control device according to the present invention. As shown in fig. 3, includes: a first acquisition unit 301, a prediction unit 302, and a control unit 303.
The first acquiring unit 301 is configured to acquire growth stage and growth state information of a crop currently located in the greenhouse.
The prediction unit 302 is configured to input the obtained growth stage and growth state information into a prediction model, and obtain a predicted optimal value of the environmental variable.
And a control unit 303 for adjusting the environmental variable values in the greenhouse according to the predicted optimal values.
The first acquisition unit 301 does not limit how to acquire the growth stage and growth state information in which the crop in the greenhouse is currently located. For example, growth stage and growth state information of crops observed and estimated by experienced personnel can be obtained. For another example, an image containing the crop captured by the camera may be obtained, and the growth stage, growth state, etc. of the crop may be determined by analyzing the image. Other possible implementations may be used, and are not limiting in this embodiment.
Preferably, the growing state may include a healthy state, which may include excellent, good, withered, etc., and a weight state, which may refer to the weight of crops, etc.
The prediction unit 302 may input the acquired growth phase and growth state information into a prediction model, thereby obtaining the predicted optimal value of the environmental variable.
Preferably, the prediction unit 302 may further adjust the predicted optimal value according to the data stored in the expert database after obtaining the predicted optimal value of the environmental variable.
For different types of crops, the expert database may store relevant data of the type of crops, for example, may include environmental variable values corresponding to different growth stages and different growth states. The data in the expert database can be generated manually and empirically, or can be data extracted from trusted data sources such as papers.
The number of environmental variables is typically greater than one and may include, for example, temperature, humidity, illuminance, carbon dioxide concentration, soil moisture, soil humidity, and the like.
For each environment variable, the prediction unit 302 may compare the optimal value of the environment variable with corresponding environment variable values stored in the expert database, respectively, where the corresponding environment variable values may be: and if the difference between the optimal value of the environment variable and the corresponding environment variable value is greater than a preset threshold value, generating an adjusted optimal value of the environment variable according to the threshold value and the corresponding environment variable value. For example, if the optimal value of the environmental variable is greater than the threshold value, the sum of the threshold value and the corresponding environmental variable value may be used as the adjusted optimal value of the environmental variable.
After inputting the obtained information of the current growth stage and growth state of the crop into the prediction model, the prediction unit 302 may obtain the optimal value of the environmental variable predicted by the prediction model, and also obtain the time predicted by the prediction model to reach the next growth stage. Further, if it is determined that the time required for the crop to actually reach the next growth stage is shorter than the predicted time required for reaching the next growth stage, the prediction unit 302 may correct the prediction model so that the prediction model learns the current positive example.
The apparatus shown in fig. 3 may further comprise a second acquisition unit 304 for acquiring the environmental variable value in the current greenhouse. The control unit 303 may adjust the execution value of the environment variable controller according to the current environmental variable value in the greenhouse and the predicted or adjusted optimal value of the environmental variable so as to adjust the environmental variable value in the greenhouse to the optimal value.
In addition, the second obtaining unit 304 may also obtain the environmental variable value in the greenhouse periodically, and if the control unit 303 determines that the environmental variable value obtained each time does not match the optimal value, the execution value of the environmental variable controller may be corrected, so that the environmental variable value in the greenhouse reaches and is maintained at the optimal value, and the optimal growth state of the crop is maintained.
The specific workflow of the embodiment of the apparatus shown in fig. 3 is referred to the related description in the foregoing method embodiment, and will not be repeated.
Fig. 4 illustrates a block diagram of an exemplary computer system/server 12 suitable for use in implementing embodiments of the present invention. The computer system/server 12 shown in FIG. 4 is intended as an example, and should not be taken as limiting the functionality and scope of use of embodiments of the present invention.
As shown in fig. 4, the computer system/server 12 is in the form of a general purpose computing device. Components of computer system/server 12 may include, but are not limited to: one or more processors (processing units) 16, a memory 28, a bus 18 that connects the various system components, including the memory 28 and the processor 16.
Computer system/server 12 typically includes a variety of computer system readable media. Such media can be any available media that is accessible by computer system/server 12 and includes both volatile and non-volatile media, removable and non-removable media.
A program/utility 40 having a set (at least one) of program modules 42 may be stored in, for example, memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each or some combination of which may include an implementation of a network environment. Program modules 42 generally perform the functions and/or methods of the embodiments described herein.
The computer system/server 12 may also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), one or more devices that enable a user to interact with the computer system/server 12, and/or any devices (e.g., network card, modem, etc.) that enable the computer system/server 12 to communicate with one or more other computing devices. Such communication may occur through an input/output (I/O) interface 22. Also, the computer system/server 12 can communicate with one or more networks such as a Local Area Network (LAN), a Wide Area Network (WAN) and/or a public network, such as the Internet, through a network adapter 20. As shown in fig. 4, the network adapter 20 communicates with other modules of the computer system/server 12 via the bus 18. It should be appreciated that although not shown, other hardware and/or software modules may be used in connection with computer system/server 12, including, but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, data backup storage systems, and the like.
The processor 16 executes various functional applications and data processing, such as the method of the embodiment shown in fig. 1, by running programs stored in the memory 28.
The invention also discloses a computer-readable storage medium on which a computer program is stored which, when being executed by a processor, will carry out the method according to the embodiment shown in fig. 1.
Any combination of one or more computer readable media may be employed. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
The computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, either in baseband or as part of a carrier wave. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).
In the several embodiments provided in the present invention, it should be understood that the disclosed apparatus and method, etc. may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is merely a logical function division, and there may be other manners of division when actually implemented.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in hardware plus software functional units.
The integrated units implemented in the form of software functional units described above may be stored in a computer readable storage medium. The software functional unit is stored in a storage medium, and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) or a processor (processor) to perform part of the steps of the methods according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather to enable any modification, equivalent replacement, improvement or the like to be made within the spirit and principles of the invention.
Claims (8)
1. A method for controlling the growth environment of crops, comprising:
acquiring information of the current growth stage and growth state of crops in a greenhouse, wherein the information comprises the following steps: shooting an image containing the crop, and determining the growth stage and the growth state of the crop by analyzing and processing the image;
inputting the growth stage and growth state information into a predictive model obtained by pre-training corresponding to the crop to obtain the predicted optimal value of the environmental variable, wherein different types of crops correspond to different predictive models respectively;
adjusting the environmental variable value in the greenhouse according to the optimal value; the number of environmental variables is greater than one;
the method further comprises the steps of: adjusting the optimal value according to data stored in an expert database, including: comparing, for each environment variable, an optimal value of the environment variable with a corresponding environment variable value stored in the expert database, the corresponding environment variable value being: the values of the environmental variables in the environmental variable values stored in the expert database and corresponding to the current growth stage and the current growth state of the crop, if the difference between the optimal value and the corresponding environmental variable value is greater than a preset threshold value, generating an adjusted optimal value according to the threshold value and the corresponding environmental variable value, wherein the sum of the threshold value and the corresponding environmental variable value is used as the adjusted optimal value; adjusting the environmental variable value in the greenhouse according to the adjusted optimal value;
the method further comprises the steps of: and acquiring the predicted time required for reaching the next growth stage of the predictive model, and correcting the predictive model according to the adjusted optimal value and the predicted time required for reaching the next growth stage if the actual time required for reaching the next growth stage of the crop is shorter than the predicted time required for reaching the next growth stage.
2. The method of claim 1, wherein the step of determining the position of the substrate comprises,
the method further comprises the steps of: acquiring the current environmental variable value in the greenhouse;
said adjusting environmental variable values within said greenhouse according to said optimal values comprises:
and adjusting an execution value of an environment variable controller according to the current environment variable value in the greenhouse and the optimal value so as to adjust the environment variable value in the greenhouse to the optimal value.
3. The method of claim 2, wherein the step of determining the position of the substrate comprises,
the method further comprises the steps of: and periodically acquiring the environmental variable value in the greenhouse, and correcting the execution value of the environmental variable controller if the acquired environmental variable value is not consistent with the optimal value.
4. A crop growth environment control apparatus, comprising: the device comprises a first acquisition unit, a prediction unit and a control unit;
the first obtaining unit is configured to obtain information of a current growth stage and a current growth state of a crop in the greenhouse, and includes: shooting an image containing the crop, and determining the growth stage and the growth state of the crop by analyzing and processing the image;
the prediction unit is used for inputting the growth stage and growth state information into a prediction model which is obtained by training corresponding to the crops in advance to obtain the predicted optimal value of the environment variable, and different types of crops correspond to different prediction models respectively;
the control unit is used for adjusting the environmental variable value in the greenhouse according to the optimal value; the number of environmental variables is greater than one;
wherein the prediction unit is further configured to adjust the optimal value according to data stored in an expert database, and includes: comparing, for each environment variable, an optimal value of the environment variable with a corresponding environment variable value stored in the expert database, the corresponding environment variable value being: the values of the environmental variables in the environmental variable values stored in the expert database and corresponding to the current growth stage and the current growth state of the crop, if the difference between the optimal value and the corresponding environmental variable value is greater than a preset threshold value, generating an adjusted optimal value according to the threshold value and the corresponding environmental variable value, wherein the sum of the threshold value and the corresponding environmental variable value is used as the adjusted optimal value;
the control unit is further used for adjusting the environmental variable value in the greenhouse according to the adjusted optimal value;
the prediction unit is further configured to obtain a time predicted by the prediction model to reach a next growth stage, and if the time actually used by the crop to reach the next growth stage is shorter than the predicted time to reach the next growth stage, correct the prediction model according to the adjusted optimal value and the time actually used to reach the next growth stage.
5. The apparatus of claim 4, wherein the device comprises a plurality of sensors,
the device further comprises: a second acquisition unit for acquiring the current environmental variable value in the greenhouse;
the control unit adjusts an execution value of an environment variable controller according to the current environment variable value in the greenhouse and the optimal value so as to adjust the environment variable value in the greenhouse to the optimal value.
6. The apparatus of claim 5, wherein the device comprises a plurality of sensors,
the second acquisition unit is further used for periodically acquiring the environmental variable value in the greenhouse;
the control unit is further configured to correct the execution value of the environment variable controller if it is determined that the environment variable value acquired each time does not match the optimal value.
7. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method of any one of claims 1 to 3 when the program is executed.
8. A computer readable storage medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, implements the method according to any one of claims 1-3.
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