CN109116827B - Solar greenhouse water and fertilizer integrated irrigation control method and device based on Internet of things - Google Patents
Solar greenhouse water and fertilizer integrated irrigation control method and device based on Internet of things Download PDFInfo
- Publication number
- CN109116827B CN109116827B CN201811095803.4A CN201811095803A CN109116827B CN 109116827 B CN109116827 B CN 109116827B CN 201811095803 A CN201811095803 A CN 201811095803A CN 109116827 B CN109116827 B CN 109116827B
- Authority
- CN
- China
- Prior art keywords
- greenhouse
- substrate
- transpiration rate
- limit value
- water
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000003973 irrigation Methods 0.000 title claims abstract description 132
- 230000002262 irrigation Effects 0.000 title claims abstract description 132
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 title claims abstract description 112
- 239000003337 fertilizer Substances 0.000 title claims abstract description 90
- 238000000034 method Methods 0.000 title claims abstract description 39
- 239000000758 substrate Substances 0.000 claims abstract description 184
- 230000005068 transpiration Effects 0.000 claims abstract description 108
- 238000005286 illumination Methods 0.000 claims abstract description 19
- 238000012549 training Methods 0.000 claims description 24
- 238000012843 least square support vector machine Methods 0.000 claims description 17
- 238000001514 detection method Methods 0.000 claims description 12
- 238000004590 computer program Methods 0.000 claims description 7
- 239000013598 vector Substances 0.000 claims description 6
- 230000006870 function Effects 0.000 claims description 5
- 238000010845 search algorithm Methods 0.000 claims description 5
- 238000004891 communication Methods 0.000 description 11
- 230000000694 effects Effects 0.000 description 9
- 238000010586 diagram Methods 0.000 description 7
- 238000011161 development Methods 0.000 description 6
- 238000012544 monitoring process Methods 0.000 description 5
- 230000008569 process Effects 0.000 description 5
- 238000012545 processing Methods 0.000 description 5
- 239000002689 soil Substances 0.000 description 5
- CURLTUGMZLYLDI-UHFFFAOYSA-N Carbon dioxide Chemical compound O=C=O CURLTUGMZLYLDI-UHFFFAOYSA-N 0.000 description 4
- 238000012706 support-vector machine Methods 0.000 description 4
- 238000004364 calculation method Methods 0.000 description 3
- 230000008859 change Effects 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 229910002092 carbon dioxide Inorganic materials 0.000 description 2
- 239000001569 carbon dioxide Substances 0.000 description 2
- 230000010354 integration Effects 0.000 description 2
- 239000003621 irrigation water Substances 0.000 description 2
- 239000011159 matrix material Substances 0.000 description 2
- 238000007781 pre-processing Methods 0.000 description 2
- 238000012360 testing method Methods 0.000 description 2
- 230000005540 biological transmission Effects 0.000 description 1
- 230000037237 body shape Effects 0.000 description 1
- 238000004422 calculation algorithm Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 230000004720 fertilization Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
- 230000005855 radiation Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
- G05B19/4183—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM] characterised by data acquisition, e.g. workpiece identification
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D27/00—Simultaneous control of variables covered by two or more of main groups G05D1/00 - G05D25/00
- G05D27/02—Simultaneous control of variables covered by two or more of main groups G05D1/00 - G05D25/00 characterised by the use of electric means
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- General Engineering & Computer Science (AREA)
- Manufacturing & Machinery (AREA)
- Quality & Reliability (AREA)
- Cultivation Of Plants (AREA)
- Greenhouses (AREA)
Abstract
The embodiment of the invention provides a sunlight greenhouse water and fertilizer integrated irrigation control method and device based on the Internet of things, wherein the method comprises the following steps: acquiring greenhouse meteorological parameters and target substrate moisture information of a sunlight greenhouse, wherein the greenhouse meteorological parameters comprise air temperature information, air humidity information and illumination intensity information; inputting the greenhouse meteorological parameters into a trained transpiration rate model to obtain the transpiration rate of the sunlight greenhouse, wherein the trained transpiration rate model is obtained based on the greenhouse meteorological parameters; acquiring a substrate humidity lower limit value of the sunlight greenhouse, wherein the substrate humidity lower limit value is obtained according to target substrate moisture information and a transpiration rate; and acquiring a real-time substrate humidity value of the sunlight greenhouse, and deciding a target irrigation scheme according to the substrate humidity lower limit value and the real-time substrate humidity value so as to perform water and fertilizer integrated irrigation control on crops in the sunlight greenhouse. According to the embodiment of the invention, the precision of the solar greenhouse water and fertilizer integrated irrigation control based on the Internet of things is improved, and the water consumption rate of water and fertilizer irrigation is increased.
Description
Technical Field
The embodiment of the invention relates to the technical field of agricultural irrigation, in particular to a solar greenhouse water and fertilizer integrated irrigation control method and device based on the Internet of things.
Background
With the development of agricultural modernization, the importance of the irrigation and fertilization system in the aspects of developing facility agriculture, water-saving agriculture, ecological agriculture and the like is increasingly prominent. Agricultural sustainable development is a target pursued by modern agriculture, and a water and fertilizer integration concept is provided in order to improve the utilization rate of water and fertilizer in irrigation, reduce the continuous sitting disasters of soil and protect the environment. Water is used as a carrier for water and fertilizer integration, and the fertilizer and the water are irrigated into soil or a matrix simultaneously, so that the utilization rate of the water and fertilizer is greatly improved.
With the development of the technology of the internet of things, in the current water and fertilizer integrated irrigation technology, the prediction of the irrigation strategy by comprehensively considering greenhouse environment information and the moisture content of the matrix is more and more important, and a representative Wageningen model, a CROPWAT model and the like are compared in a plurality of simulation models. Particularly, the CROPWAT model has comprehensive functions, can carry out standard calculation on irrigation water demand, and can evaluate different irrigation strategies and the influence of insufficient irrigation on crop yield.
However, because these systems are too complicated, the amount of information to be processed is too large, and the configuration requirements on the systems are also high, the whole water and fertilizer integrated control system is in a high-load operation state for a long time, the performance and the service life of the whole system are reduced, and the control precision of water and fertilizer integrated irrigation is low, the applicability is poor, and the water use efficiency is low.
Disclosure of Invention
Aiming at the problems in the prior art, the embodiment of the invention provides a solar greenhouse water and fertilizer integrated irrigation control method and device based on the Internet of things.
In a first aspect, an embodiment of the invention provides a sunlight greenhouse water and fertilizer integrated irrigation control method based on the internet of things, which includes the following steps:
acquiring greenhouse meteorological parameters and target substrate moisture information of a sunlight greenhouse, wherein the greenhouse meteorological parameters comprise air temperature information, air humidity information and illumination intensity information;
inputting the greenhouse meteorological parameters into a trained transpiration rate model to obtain the transpiration rate of the sunlight greenhouse, wherein the trained transpiration rate model is obtained based on the greenhouse meteorological parameters;
acquiring a substrate humidity lower limit value of the sunlight greenhouse, wherein the substrate humidity lower limit value is obtained according to the target substrate moisture information and the transpiration rate;
and obtaining a real-time substrate humidity value of the sunlight greenhouse, and deciding a target irrigation scheme according to the substrate humidity lower limit value and the real-time substrate humidity value so as to perform water and fertilizer integrated irrigation control on crops in the sunlight greenhouse.
In a second aspect, an embodiment of the present invention provides a sunlight greenhouse water and fertilizer integrated irrigation control device based on the internet of things, including:
the greenhouse parameter acquisition module is used for acquiring greenhouse meteorological parameters and target substrate moisture information of the sunlight greenhouse, wherein the greenhouse meteorological parameters comprise air temperature information, air humidity information and illumination intensity information;
the transpiration rate detection module is used for inputting the greenhouse meteorological parameters into a trained transpiration rate model to obtain the transpiration rate of the sunlight greenhouse, and the trained transpiration rate model is obtained based on the greenhouse meteorological parameters;
the intelligent control module is used for acquiring a substrate humidity lower limit value of the sunlight greenhouse, and the substrate humidity lower limit value is obtained according to the target substrate moisture information and the transpiration rate;
and the substrate moisture detection module is used for acquiring a real-time substrate humidity value of the sunlight greenhouse, and deciding a target irrigation scheme according to the substrate humidity lower limit value and the real-time substrate humidity value so as to perform water and fertilizer integrated irrigation control on crops in the sunlight greenhouse.
In a third aspect, an embodiment of the present invention provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the method provided in the first aspect when executing the program.
In a fourth aspect, an embodiment of the present invention provides a non-transitory computer readable storage medium, on which a computer program is stored, which when executed by a processor, implements the steps of the method as provided in the first aspect.
According to the solar greenhouse water and fertilizer integrated irrigation control method and device based on the Internet of things, the corresponding transpiration rate is obtained through the air temperature information, the air humidity information and the illumination intensity information in the solar greenhouse, the lower limit value of the substrate humidity of the crop is obtained by combining the transpiration rate and the target substrate moisture information of the crop in the solar greenhouse, the corresponding irrigation scheme is decided according to the lower limit value of the substrate humidity of the crop and the real-time substrate humidity value, the precision of water and fertilizer integrated irrigation control based on the Internet of things is improved, the water consumption rate of water and fertilizer irrigation is increased, and the water saving effect is achieved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
Fig. 1 is a schematic flow chart of a solar greenhouse water and fertilizer integrated irrigation control method based on the internet of things provided by the embodiment of the invention;
FIG. 2 is a schematic diagram of a training process of a transpiration rate model based on a deep belief network-least squares support vector machine according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a solar greenhouse water and fertilizer integrated irrigation control device based on the internet of things, provided by the embodiment of the invention;
fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In a solar greenhouse water and fertilizer integrated irrigation system, irrigation water management is a very complex task because the water demand of crops is influenced not only by the growth and development period of the crops, but also by various environmental conditions such as temperature, humidity, rainfall, transpiration and the like. A large amount of irrigation test data show that: the amount of irrigation of crops is related to soil conditions (including soil texture, soil water content, structure, underground water level and the like), meteorological conditions (including solar radiation, air temperature, humidity and the like), agricultural technologies, irrigation drainage measures and the like. The condition that crops can normally grow is that the water content of the cultivation environment is higher than a certain value, and the crops can obtain a larger growth amount at the moment.
Fig. 1 is a schematic flow chart of a solar greenhouse water and fertilizer integrated irrigation control method based on the internet of things, which is provided by the embodiment of the invention, and as shown in fig. 1, the embodiment of the invention provides a solar greenhouse water and fertilizer integrated irrigation control method based on the internet of things, which includes:
step 101, acquiring greenhouse meteorological parameters and target substrate moisture information of a sunlight greenhouse, wherein the greenhouse meteorological parameters comprise air temperature information, air humidity information and illumination intensity information;
102, inputting the greenhouse meteorological parameters into a trained transpiration rate model to obtain the transpiration rate of the sunlight greenhouse, wherein the trained transpiration rate model is obtained by training based on the greenhouse meteorological parameters;
103, acquiring a substrate humidity lower limit value of the sunlight greenhouse, wherein the substrate humidity lower limit value is obtained according to the target substrate moisture information and the transpiration rate;
and 104, acquiring a real-time substrate humidity value of the sunlight greenhouse, and deciding a target irrigation scheme according to the substrate humidity lower limit value and the real-time substrate humidity value so as to perform water and fertilizer integrated irrigation control on crops in the sunlight greenhouse.
In the embodiment of the invention, in step 101, greenhouse meteorological parameters of a sunlight greenhouse are monitored through a sensor installed in the sunlight greenhouse, specifically, the greenhouse air temperature sensor is used for monitoring real-time air temperature information of the sunlight greenhouse, the greenhouse humidity sensor is used for monitoring real-time humidity information of the sunlight greenhouse, the greenhouse illumination intensity sensor is used for monitoring real-time illumination intensity information of the sunlight greenhouse, information monitored by various types of sensors is uploaded to a sunlight greenhouse water and fertilizer integrated irrigation control device based on the internet of things in a network mode, and a trained transpiration rate model and target substrate moisture information corresponding to a cultivated crop substrate are arranged in the control device. Then, the control device inputs the received greenhouse meteorological parameters into a trained transpiration rate model, the transpiration rate of the sunlight greenhouse is obtained through calculation, at the moment, the control device selects corresponding target substrate moisture information according to the crop type in the sunlight greenhouse, corresponding processing is conducted in combination with the transpiration rate, for example, in the embodiment of the invention, a fuzzy controller is arranged in the sunlight greenhouse water and fertilizer integrated irrigation control device based on the Internet of things, the target substrate moisture information and the transpiration rate corresponding to the crop needing water and fertilizer irrigation at this time are input into the fuzzy controller, and the substrate humidity lower limit value corresponding to the crop in the sunlight greenhouse is obtained through fuzzification processing. And at the moment, uploading the monitored real-time substrate humidity value to a control system, comparing the real-time substrate humidity value with a substrate humidity lower limit value by the control system, judging whether crops are irrigated, if the real-time substrate humidity value is less than or equal to the substrate humidity lower limit value at the moment, indicating that the crops are in a water and fertilizer shortage state, and providing water and fertilizer irrigation for the crops by a control device through corresponding water and fertilizer supply battery valves in a remote control sunlight greenhouse to decide a corresponding irrigation scheme. In addition, the transpiration rate change value of the sunlight greenhouse obtained through the trained transpiration rate model can be analyzed to obtain corresponding irrigation time, so that a more optimized irrigation scheme is obtained.
In the embodiment of the invention, each sensor in the sunlight greenhouse keeps continuously monitoring the temperature, the humidity, the illumination intensity, the substrate humidity value and the like in the greenhouse, so that the control system can decide a corresponding irrigation scheme in real time according to the change of parameters in the sunlight greenhouse, and in addition, the sensor for monitoring the carbon dioxide concentration or the crop leaf information in the sunlight greenhouse can be arranged, and the accuracy of the irrigation scheme is improved. In the embodiment of the invention, the sunlight greenhouse water and fertilizer integrated irrigation control system based on the Internet of things sends related data to the USB485 module through the communication serial port, the upper PC communicates with the USB485 module through the TCP/IP communication protocol, so that the upper PC and the control device can mutually transmit data through the Internet of things, meanwhile, the upper PC and the control device establish a protocol, the upper PC processes the data according to information sent by the control device and transmits feedback information to the control device, and the control device performs corresponding control processing according to the feedback information.
According to the solar greenhouse water and fertilizer integrated irrigation control method based on the Internet of things, the corresponding transpiration rate is obtained through the air temperature information, the air humidity information and the illumination intensity information in the solar greenhouse, the lower limit value of the substrate humidity of the crop is obtained by combining the transpiration rate and the target substrate moisture information of the crop in the solar greenhouse, the corresponding irrigation scheme is decided according to the lower limit value of the substrate humidity of the crop and the real-time substrate humidity value, the precision of water and fertilizer integrated irrigation control based on the Internet of things is improved, the water consumption rate of water and fertilizer irrigation is increased, and the water saving effect is achieved.
On the basis of the foregoing embodiment, fig. 2 is a schematic diagram of a training process of a transpiration rate model based on a deep belief network-least squares support vector machine provided in an embodiment of the present invention, and as shown in fig. 2, the trained transpiration rate model provided in the embodiment of the present invention is obtained by training through the following steps:
step 201, extracting a feature vector of a sample greenhouse meteorological parameter through a deep belief network to obtain a training sample set;
step 202, optimizing a hyper-parameter network structure of a least square support vector machine according to a grid search algorithm to obtain the least square support vector machine to be trained;
step 203, inputting the training sample set into the least square support vector machine to be trained, and training the least square support vector machine to be trained to obtain the sample transpiration rate of the training sample set, so as to obtain the trained transpiration rate model;
and 204, inputting the greenhouse meteorological parameters into the trained transpiration rate model to obtain the transpiration rate.
In the embodiment of the invention, a transpiration rate model combining a deep belief network DBN and a least square support vector machine is established according to air temperature information, air humidity information, illumination intensity information and a transpiration rate in a sunlight greenhouse. Before step 201, preprocessing the sample greenhouse meteorological parameters, removing irrelevant information in the parameters through preprocessing, then inputting the preprocessed sample greenhouse meteorological parameters into a deep belief network, thereby extracting the feature vectors of the greenhouse meteorological parameters, and using the extracted feature vectors as a training sample set of a least square support vector machine. Before inputting the training sample set into the least squares support vector machine, the network structure and various parameters of the hyper-parameters in the least squares support vector machine are optimized by combining the grid search algorithm, via step 202. And finally, inputting the training sample set into a least square support vector machine with the set hyper-parameters for training in the least square support vector machine, so as to obtain the transpiration rate corresponding to the training sample set and further obtain a trained transpiration rate model. In addition, the trained transpiration rate model is tested, and whether the transpiration rate predicted by the trained transpiration rate model is accurate or not is judged according to the test result.
According to the embodiment of the invention, the feature vectors of the greenhouse meteorological parameters are extracted in a multi-scale mode through the deep belief network, and the correlation of variables is eliminated, so that the sample input of a least square support vector machine is reduced, the network structure of the hyperparameter is optimized by combining a grid search algorithm, the prediction capability and the generalization capability of the model are improved, the obtained transpiration rate is faster and more accurate, and the accuracy of the water and fertilizer integrated irrigation control is improved.
On the basis of the above embodiment, the acquiring the substrate humidity lower limit value of the sunlight greenhouse comprises:
fuzzifying the target substrate moisture information and the transpiration rate, establishing a fuzzy rule according to a triangular membership function, converting the fuzzified result through the fuzzy rule to obtain a substrate humidity lower limit value, and determining the target irrigation scheme according to the real-time substrate humidity value.
In the embodiment of the invention, a fuzzy controller is arranged in a sunlight greenhouse water and fertilizer integrated irrigation control system based on the Internet of things, firstly, the transpiration rate obtained by target substrate moisture information and a trained transpiration rate model is converted into a corresponding fuzzy subset, then, a fuzzy rule is formed through fuzzy conditions, a fuzzy relation corresponding to the fuzzy rule is obtained through calculation and inference, namely fuzzy output judgment, and the fuzzy quantity is converted into an accurate quantity, so that a substrate humidity lower limit value is obtained, and a target irrigation scheme is determined according to a real-time substrate humidity value. In the embodiment of the invention, the target substrate moisture information and the transpiration rate are used as accurate input quantities, the target substrate moisture information and the transpiration rate need to be converted into membership functions of a fuzzy set before a fuzzy control method is adopted, and the membership functions usually adopt bell shapes, body shapes and triangles.
According to the embodiment of the invention, the fuzzy control algorithm is introduced into the water and fertilizer integrated irrigation control system, so that the accuracy of irrigation control is improved, the crop irrigation is more reasonable, the effect of saving water resources is achieved, and the growth and development of crops are facilitated.
On the basis of the above embodiment, the deciding a target irrigation scheme according to the substrate humidity lower limit value and the real-time substrate humidity value for performing water and fertilizer integrated irrigation control on crops in a sunlight greenhouse includes:
and setting a substrate humidity upper limit value according to the substrate humidity lower limit value and the transpiration rate, determining whether crops in the sunlight greenhouse are irrigated or not according to the substrate humidity lower limit value and the real-time substrate humidity value, and determining continuous irrigation time according to the substrate humidity upper limit value, so that the target irrigation scheme is decided for performing water-fertilizer integrated irrigation control on the crops in the sunlight greenhouse.
Further, on the basis of the above embodiment, the setting of the upper limit value of the substrate humidity according to the lower limit value of the substrate humidity and the transpiration rate, determining whether to irrigate the crops in the sunlight greenhouse according to the lower limit value of the substrate humidity and the real-time substrate humidity value, and determining the continuous irrigation time according to the upper limit value of the substrate humidity, so as to decide the target irrigation method for performing water and fertilizer integrated irrigation control on the crops in the sunlight greenhouse, includes:
if the real-time substrate humidity value is smaller than or equal to the substrate humidity lower limit value, performing water and fertilizer irrigation on the crops in the sunlight greenhouse, and stopping performing water and fertilizer irrigation on the crops in the sunlight greenhouse after the real-time substrate humidity value is larger than or equal to the substrate humidity upper limit value;
and if the real-time substrate humidity value is larger than the substrate humidity lower limit value, not carrying out water and fertilizer irrigation on the crops of the sunlight greenhouse.
In the embodiment of the invention, the upper limit value of the substrate humidity corresponding to the crop is obtained by decision through the lower limit value of the substrate humidity and the transpiration rate in the sunlight greenhouse and combining the growth rules of different crops in the sunlight greenhouse. The upper limit value of the substrate humidity and the lower limit value of the substrate humidity can be adjusted through the transpiration rate change, so that the optimal irrigation effect of crops and the water and fertilizer irrigation reach a relatively balanced state, for example, after the lower limit value of the substrate humidity of the sunlight greenhouse is obtained, the lower limit value of the substrate humidity is compared with the real-time substrate humidity, the real-time substrate humidity at the moment is judged and obtained to be smaller than the lower limit value of the substrate humidity, the corresponding water and fertilizer electromagnetic valve is controlled to be opened, the crops in the sunlight greenhouse are started to be continuously irrigated, meanwhile, the real-time substrate humidity of the crops is continuously monitored and compared with the upper limit value of the substrate humidity, the transpiration rate, the time required by the crop irrigation and the like are comprehensively analyzed, a corresponding irrigation scheme is decided, namely, the irrigation is stopped after the real-time substrate humidity reaches the upper limit value of the substrate humidity, and the substrate humidity is gradually reduced through the transpiration until the, in the process, the irrigation quantity of crops is most consistent with the growth rule of the crops, and the effects of saving water and fertilizer are achieved.
According to the embodiment of the invention, the upper limit value of the substrate humidity corresponding to the lower limit value of the substrate humidity of the crop is set, so that the crop can decide a corresponding irrigation scheme during water and fertilizer irrigation, the accuracy of irrigation control is improved, the crop irrigation is more reasonable, the effect of saving water resources is achieved, and the growth and development of the crop are more facilitated.
Fig. 3 is a schematic structural diagram of a solar greenhouse water and fertilizer integrated irrigation control device based on the internet of things according to an embodiment of the present invention, and as shown in fig. 3, an embodiment of the present invention provides a schematic structural diagram of a solar greenhouse water and fertilizer integrated irrigation control device based on the internet of things, including a greenhouse parameter acquisition module 301, a transpiration rate detection module 302, an intelligent control module 303, and a substrate moisture detection module 304, where the greenhouse parameter acquisition module 301 is configured to acquire greenhouse weather parameters of a solar greenhouse and target substrate moisture information, and the greenhouse weather parameters include air temperature information, air humidity information, and illumination intensity information; the transpiration rate detection module 302 is configured to input the greenhouse weather parameters into a trained transpiration rate model to obtain a transpiration rate of the sunlight greenhouse, wherein the trained transpiration rate model is obtained by training based on the greenhouse weather parameters; the intelligent control module 303 is configured to obtain a substrate humidity lower limit value of the sunlight greenhouse, where the substrate humidity lower limit value is obtained according to the target substrate moisture information and the transpiration rate; the substrate moisture detection module 304 is configured to obtain a real-time substrate humidity value of the sunlight greenhouse, and decide a target irrigation scheme according to the substrate humidity lower limit value and the real-time substrate humidity value, so as to perform water and fertilizer integrated irrigation control on crops in the sunlight greenhouse.
In the embodiment of the present invention, the greenhouse parameter acquisition module 301 first monitors greenhouse meteorological parameters of the sunlight greenhouse, specifically, the greenhouse parameter acquisition module 301 includes a greenhouse air temperature sensor, a greenhouse humidity sensor, and a greenhouse illumination intensity sensor, and simultaneously uploads information monitored by each type of sensor to the transpiration rate detection module 302 in a network manner. The transpiration rate detection module 302 calculates the transpiration rate of the sunlight greenhouse, at this time, the intelligent control module 303 selects corresponding target substrate moisture information according to the type of the crop in the sunlight greenhouse, and performs corresponding processing in combination with the transpiration rate, for example, in the embodiment of the present invention, a fuzzy controller is built in the intelligent control module 303, the target substrate moisture information and the transpiration rate corresponding to the crop needing water and fertilizer irrigation at this time are input into the fuzzy controller, and the substrate humidity lower limit value corresponding to the crop in the sunlight greenhouse is obtained through fuzzification processing. At this time, the substrate water and fertilizer detection module 304 in the sunlight greenhouse acquires the real-time substrate humidity value through the substrate moisture sensor, compares the real-time substrate humidity value with the substrate humidity lower limit value, and judges whether crops are irrigated, if the real-time substrate humidity value is smaller than or equal to the substrate humidity lower limit value at this time, it is indicated that the crops are in a water and fertilizer shortage state, the substrate water and fertilizer detection module 304 can provide water and fertilizer irrigation for the crops through corresponding water and fertilizer supply battery valves in the remote control sunlight greenhouse, and a corresponding irrigation scheme is decided.
According to the solar greenhouse water and fertilizer integrated irrigation control device based on the Internet of things, the corresponding transpiration rate is obtained through the air temperature information, the air humidity information and the illumination intensity information in the solar greenhouse, the lower limit value of the substrate humidity of the crop is obtained by combining the transpiration rate and the target substrate moisture information of the crop in the solar greenhouse, a corresponding irrigation scheme is decided according to the lower limit value of the substrate humidity of the crop and the real-time substrate humidity value, the precision of water and fertilizer integrated irrigation control based on the Internet of things is improved, the water consumption rate of water and fertilizer irrigation is increased, and the water saving effect is achieved.
On the basis of the above embodiment, the apparatus further comprises a main control tank and a water amount control device, wherein:
the main control box is used for sending a corresponding control instruction to the water quantity control equipment according to the target irrigation scheme, and is connected with the water quantity control equipment;
and the water quantity control equipment is used for executing a corresponding control instruction sent by the main control box so as to control the water and fertilizer integrated irrigation of crops in the sunlight greenhouse.
In the embodiment of the invention, the main control box comprises a single chip microcomputer, a peripheral circuit and an output signal amplifying circuit connected with the single chip microcomputer, wherein a transpiration rate model and a fuzzy controller are arranged in the single chip microcomputer. The method comprises the steps that firstly, a sensor in the sunlight greenhouse uploads corresponding data to a main control box, a corresponding transpiration rate is obtained through a transpiration rate model, then target substrate moisture information of corresponding crops stored in an upper PC (personal computer) connected with the main control box through a USB485 module is called, and a fuzzy controller calculates according to the transpiration rate and the target substrate moisture information to obtain a substrate humidity lower limit value of the sunlight greenhouse. Meanwhile, a sensor in the sunlight greenhouse uploads the real-time substrate humidity value to a single chip microcomputer of a main control box, the single chip microcomputer decides a corresponding target irrigation scheme according to the substrate humidity lower limit value and the real-time substrate humidity value, the main control box sends the target irrigation scheme to water quantity control equipment of the sunlight greenhouse through a driving circuit, the water quantity control equipment controls the dripping equipment according to a corresponding operation instruction, and a water and fertilizer electromagnetic valve is opened or closed so as to control the water and fertilizer integrated irrigation of crops in the sunlight greenhouse. In the embodiment of the invention, a memory can be arranged on the main control box and used for storing irrigation data of water and fertilizer integrated irrigation so as to improve the accuracy of the next irrigation and facilitate operators to call related data for research. In addition, a display device is arranged in the main control box and used for displaying parameters of real-time weather, substrate humidity and carbon dioxide concentration of the sunlight greenhouse.
According to the solar greenhouse water and fertilizer integrated irrigation control device based on the Internet of things, the corresponding transpiration rate is obtained through the air temperature information, the air humidity information and the illumination intensity information in the solar greenhouse, the lower limit value of the substrate humidity of crops is obtained by combining the transpiration rate and the target substrate moisture information of the crops in the solar greenhouse, and the corresponding irrigation scheme is decided according to the lower limit value of the substrate humidity of the crops and the real-time substrate humidity value, so that the precision of water and fertilizer integrated irrigation control based on the Internet of things is improved, the water consumption rate of water and fertilizer irrigation is increased, and the water-saving effect is achieved.
On the basis of the above embodiment, the device is connected with the upper PC computer through wireless or wired connection.
In the embodiment of the invention, the main control box and the upper PC machine transmit data in a wireless communication or wired communication mode, and related equipment of the water and fertilizer integrated irrigation device is monitored and controlled, so that data acquisition, equipment control, parameter adjustment and other data transmission are realized. In addition, the embodiment of the invention can also be provided with a mobile terminal and an upper PC for remote communication, so as to realize movable water and fertilizer integrated irrigation control.
The embodiment of the invention enables the remote upper PC to transmit and control information of the sunlight greenhouse water and fertilizer integrated irrigation control device in a wireless or wired connection mode, improves the practicability and achieves the effects of water and fertilizer saving, intelligence and high efficiency.
The apparatus provided in the embodiment of the present invention is used for executing the above method embodiments, and for details of the process and the details, reference is made to the above method embodiments, which are not described herein again.
Fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present invention, and as shown in fig. 4, the electronic device may include: a processor (processor)401, a communication Interface (communication Interface)402, a memory (memory)403 and a communication bus 404, wherein the processor 401, the communication Interface 402 and the memory 403 complete communication with each other through the communication bus 404. Processor 401 may call logic instructions in memory 403 to perform the following method: acquiring greenhouse meteorological parameters and target substrate moisture information of a sunlight greenhouse, wherein the greenhouse meteorological parameters comprise air temperature information, air humidity information and illumination intensity information; inputting the greenhouse meteorological parameters into a trained transpiration rate model to obtain the transpiration rate of the sunlight greenhouse, wherein the trained transpiration rate model is obtained based on the greenhouse meteorological parameters; acquiring a substrate humidity lower limit value of the sunlight greenhouse, wherein the substrate humidity lower limit value is obtained according to the target substrate moisture information and the transpiration rate; and obtaining a real-time substrate humidity value of the sunlight greenhouse, and deciding a target irrigation scheme according to the substrate humidity lower limit value and the real-time substrate humidity value so as to perform water and fertilizer integrated irrigation control on crops in the sunlight greenhouse.
In addition, the logic instructions in the memory 403 may be implemented in the form of software functional units and stored in a computer readable storage medium when the software functional units are sold or used as independent products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method 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), a magnetic disk or an optical disk, and other various media capable of storing program codes.
An embodiment of the present invention discloses a computer program product, which includes a computer program stored on a non-transitory computer readable storage medium, the computer program including program instructions, when the program instructions are executed by a computer, the computer can execute the methods provided by the above method embodiments, for example, the method includes: acquiring greenhouse meteorological parameters and target substrate moisture information of a sunlight greenhouse, wherein the greenhouse meteorological parameters comprise air temperature information, air humidity information and illumination intensity information; inputting the greenhouse meteorological parameters into a trained transpiration rate model to obtain the transpiration rate of the sunlight greenhouse, wherein the trained transpiration rate model is obtained based on the greenhouse meteorological parameters; acquiring a substrate humidity lower limit value of the sunlight greenhouse, wherein the substrate humidity lower limit value is obtained according to the target substrate moisture information and the transpiration rate; and obtaining a real-time substrate humidity value of the sunlight greenhouse, and deciding a target irrigation scheme according to the substrate humidity lower limit value and the real-time substrate humidity value so as to perform water and fertilizer integrated irrigation control on crops in the sunlight greenhouse.
An embodiment of the present invention provides a non-transitory computer-readable storage medium, where the non-transitory computer-readable storage medium stores server instructions, and the computer instructions enable a computer to execute the method for controlling integrated irrigation of water and fertilizer in a sunlight greenhouse based on the internet of things, where the method includes: acquiring greenhouse meteorological parameters and target substrate moisture information of a sunlight greenhouse, wherein the greenhouse meteorological parameters comprise air temperature information, air humidity information and illumination intensity information; inputting the greenhouse meteorological parameters into a trained transpiration rate model to obtain the transpiration rate of the sunlight greenhouse, wherein the trained transpiration rate model is obtained based on the greenhouse meteorological parameters; acquiring a substrate humidity lower limit value of the sunlight greenhouse, wherein the substrate humidity lower limit value is obtained according to the target substrate moisture information and the transpiration rate; and obtaining a real-time substrate humidity value of the sunlight greenhouse, and deciding a target irrigation scheme according to the substrate humidity lower limit value and the real-time substrate humidity value so as to perform water and fertilizer integrated irrigation control on crops in the sunlight greenhouse.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (9)
1. A sunlight greenhouse water and fertilizer integrated irrigation control method based on the Internet of things is characterized by comprising the following steps:
acquiring greenhouse meteorological parameters and target substrate moisture information of a sunlight greenhouse, wherein the greenhouse meteorological parameters comprise air temperature information, air humidity information and illumination intensity information;
inputting the greenhouse meteorological parameters into a trained transpiration rate model to obtain the transpiration rate of the sunlight greenhouse, wherein the trained transpiration rate model is obtained based on the greenhouse meteorological parameters;
acquiring a substrate humidity lower limit value of the sunlight greenhouse, wherein the substrate humidity lower limit value is obtained according to the target substrate moisture information and the transpiration rate;
acquiring a real-time substrate humidity value of the sunlight greenhouse, and deciding a target irrigation scheme according to the substrate humidity lower limit value and the real-time substrate humidity value so as to perform water and fertilizer integrated irrigation control on crops in the sunlight greenhouse;
wherein the trained transpiration rate model is obtained by training through the following steps:
extracting a characteristic vector of a sample greenhouse meteorological parameter through a deep belief network to obtain a training sample set;
optimizing a hyper-parameter network structure of the least square support vector machine according to a grid search algorithm to obtain the least square support vector machine to be trained;
inputting the training sample set into the least square support vector machine to be trained, and training the least square support vector machine to be trained to obtain the sample transpiration rate of the training sample set, so as to obtain the trained transpiration rate model;
and inputting the greenhouse meteorological parameters into the trained transpiration rate model to obtain the transpiration rate.
2. The method of claim 1, wherein obtaining the substrate humidity lower limit value of the solar greenhouse comprises:
fuzzifying the target substrate moisture information and the transpiration rate, establishing a fuzzy rule according to a triangular membership function, converting the fuzzified result through the fuzzy rule to obtain a substrate humidity lower limit value, and determining the target irrigation scheme according to the real-time substrate humidity value.
3. The method according to claim 1, wherein the deciding a target irrigation scheme according to the lower substrate humidity limit value and the real-time substrate humidity value for water-fertilizer integrated irrigation control of crops in a sunlight greenhouse comprises:
and setting a substrate humidity upper limit value according to the substrate humidity lower limit value and the transpiration rate, determining whether crops in the sunlight greenhouse are irrigated or not according to the substrate humidity lower limit value and the real-time substrate humidity value, and determining continuous irrigation time according to the substrate humidity upper limit value, so that the target irrigation scheme is decided for performing water-fertilizer integrated irrigation control on the crops in the sunlight greenhouse.
4. The method according to claim 3, wherein the setting of the upper substrate humidity limit value through the lower substrate humidity limit value and the transpiration rate, the determining of whether to irrigate the crops in the sunlight greenhouse according to the lower substrate humidity limit value and the real-time substrate humidity value, and the determining of the continuous irrigation time according to the upper substrate humidity limit value are used for deciding the target irrigation method for water-fertilizer integrated irrigation control of the crops in the sunlight greenhouse, comprises:
if the real-time substrate humidity value is smaller than or equal to the substrate humidity lower limit value, performing water and fertilizer irrigation on the crops in the sunlight greenhouse, and stopping performing water and fertilizer irrigation on the crops in the sunlight greenhouse after the real-time substrate humidity value is larger than or equal to the substrate humidity upper limit value;
and if the real-time substrate humidity value is larger than the substrate humidity lower limit value, not carrying out water and fertilizer irrigation on the crops of the sunlight greenhouse.
5. The control device for the solar greenhouse water and fertilizer integrated irrigation control method based on the Internet of things according to any one of claims 1 to 4 is characterized by comprising the following steps:
the greenhouse parameter acquisition module is used for acquiring greenhouse meteorological parameters and target substrate moisture information of the sunlight greenhouse, wherein the greenhouse meteorological parameters comprise air temperature information, air humidity information and illumination intensity information;
the transpiration rate detection module is used for inputting the greenhouse meteorological parameters into a trained transpiration rate model to obtain the transpiration rate of the sunlight greenhouse, and the trained transpiration rate model is obtained based on the greenhouse meteorological parameters;
the intelligent control module is used for acquiring a substrate humidity lower limit value of the sunlight greenhouse, and the substrate humidity lower limit value is obtained according to the target substrate moisture information and the transpiration rate;
the substrate moisture detection module is used for acquiring a real-time substrate humidity value of the sunlight greenhouse, and deciding a target irrigation scheme according to the substrate humidity lower limit value and the real-time substrate humidity value so as to perform water and fertilizer integrated irrigation control on crops in the sunlight greenhouse;
wherein the trained transpiration rate model is obtained by training through the following steps:
extracting a characteristic vector of a sample greenhouse meteorological parameter through a deep belief network to obtain a training sample set;
optimizing a hyper-parameter network structure of the least square support vector machine according to a grid search algorithm to obtain the least square support vector machine to be trained;
inputting the training sample set into the least square support vector machine to be trained, and training the least square support vector machine to be trained to obtain the sample transpiration rate of the training sample set, so as to obtain the trained transpiration rate model;
and inputting the greenhouse meteorological parameters into the trained transpiration rate model to obtain the transpiration rate.
6. The apparatus of claim 5, further comprising a main control tank and a water volume control device, wherein:
the main control box is used for sending a corresponding control instruction to the water quantity control equipment according to the target irrigation scheme, and is connected with the water quantity control equipment;
and the water quantity control equipment is used for executing a corresponding control instruction sent by the main control box so as to control the water and fertilizer integrated irrigation of crops in the sunlight greenhouse.
7. The device of claim 5, wherein the device is connected to the host PC via a wireless or wired connection.
8. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the steps of the method according to any of claims 1 to 4 are implemented when the processor executes the program.
9. A non-transitory computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 4.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811095803.4A CN109116827B (en) | 2018-09-19 | 2018-09-19 | Solar greenhouse water and fertilizer integrated irrigation control method and device based on Internet of things |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811095803.4A CN109116827B (en) | 2018-09-19 | 2018-09-19 | Solar greenhouse water and fertilizer integrated irrigation control method and device based on Internet of things |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109116827A CN109116827A (en) | 2019-01-01 |
| CN109116827B true CN109116827B (en) | 2020-01-03 |
Family
ID=64858509
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811095803.4A Active CN109116827B (en) | 2018-09-19 | 2018-09-19 | Solar greenhouse water and fertilizer integrated irrigation control method and device based on Internet of things |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109116827B (en) |
Families Citing this family (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109978265B (en) * | 2019-03-28 | 2021-01-22 | 中国农业科学院农业信息研究所 | Farmland nutrient release rate estimation method and system for controlled release fertilizer |
| CN110896761B (en) * | 2019-09-18 | 2022-09-16 | 北京农业信息技术研究中心 | Irrigation decision-making method and system for greenhouse |
| CN114879786B (en) * | 2022-05-23 | 2023-09-01 | 连云港银丰食用菌科技有限公司 | Method, system, device and medium for obtaining edible fungus decision scheme |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN202232350U (en) * | 2011-09-08 | 2012-05-30 | 甘肃大禹节水集团股份有限公司 | Automatic drip irrigation control system for greenhouse |
| CN103814795B (en) * | 2014-01-23 | 2015-10-28 | 江苏冠甲水利科技有限公司 | Rice field automatic intelligent irrigation system and adopt this system to carry out the method for field irrigation |
| CN205017965U (en) * | 2015-08-02 | 2016-02-10 | 华中农业大学 | Irrigation control device suitable for greenhouse list trunk crop |
| CN108510102A (en) * | 2018-02-07 | 2018-09-07 | 青岛农业大学 | A kind of water-fertilizer integral control method of irrigation using big data calculative strategy |
| CN108446997B (en) * | 2018-03-28 | 2019-10-01 | 江苏大学 | A kind of Crop Water-saving Technology irrigation decision method and TT&C system based on Multi-source Information Fusion |
-
2018
- 2018-09-19 CN CN201811095803.4A patent/CN109116827B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN109116827A (en) | 2019-01-01 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109116827B (en) | Solar greenhouse water and fertilizer integrated irrigation control method and device based on Internet of things | |
| CN110741914A (en) | Rice field automatic water-saving irrigation system and method based on recurrent neural network | |
| US20220248616A1 (en) | Irrigation control with deep reinforcement learning and smart scheduling | |
| CN107219759B (en) | Greenhouse environment control method and device | |
| CN110119169A (en) | A kind of tomato greenhouse temperature intelligent early warning system based on minimum vector machine | |
| CN110463587A (en) | Scale greenhouse water-saving irrigation system based on LoRa and GA-BP | |
| Karuniawati et al. | Optimization of grow lights control in IoT-based aeroponic systems with sensor fusion and random forest classification | |
| CN110119767A (en) | A kind of cucumber green house temperature intelligent detection device based on LVQ neural network | |
| CN114297907A (en) | Greenhouse environment spatial distribution prediction method and device | |
| US20220394943A1 (en) | Systems and methods for monitoring and controlling crop irrigation schedules | |
| CN109213240A (en) | A kind of strawberry greenhouse wireless monitor and control system based on self adaptive control | |
| KR102387765B1 (en) | Method and apparatus for estimating crop growth quantity | |
| CN117873238A (en) | Plant growth control method and system, computer equipment and storage medium | |
| Musa et al. | An intelligent plant dissease detection system for smart hydroponic using convolutional neural network | |
| CN117114448A (en) | Agricultural production management system and method based on machine learning and Internet of things technology | |
| CN117236650B (en) | Water-fertilizer integrated intelligent pump house control method | |
| Praveena et al. | IoT Based Water Showering Mechanism in Agriculture | |
| CN118011970A (en) | Intelligent agricultural production management system based on Internet of things | |
| CN118313650A (en) | Intelligent agriculture cloud platform monitored control system based on big data | |
| CN117313920A (en) | Intelligent grape planting environment monitoring system | |
| Tripathy et al. | Smart farming based on deep learning approaches | |
| Pierre et al. | Smart crops irrigation system with low energy consumption | |
| Mamatha et al. | Remotely monitored web based smart hydroponics system for crop yield prediction using IoT | |
| Hairu et al. | Fuzzy-based Nutrient System for Chili Cultivation in Urban Area | |
| CN113115679B (en) | Intelligent regulation and control method and device based on apple disease prediction |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |