CN108153357B - Intelligent management method and system for greenhouse - Google Patents
Intelligent management method and system for greenhouse Download PDFInfo
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- CN108153357B CN108153357B CN201711423181.9A CN201711423181A CN108153357B CN 108153357 B CN108153357 B CN 108153357B CN 201711423181 A CN201711423181 A CN 201711423181A CN 108153357 B CN108153357 B CN 108153357B
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- 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
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Abstract
The invention relates to an intelligent management method and system for a greenhouse, and relates to the field of intelligent control. The method comprises the following steps: acquiring a control instruction for controlling the control equipment of the main shed to adjust the environmental parameters in the main shed, and sending the control instruction to the control equipment of at least one slave shed; acquiring feedback information obtained after control equipment of each slave shed controls environment parameters in each slave shed according to the control instruction; and adjusting the control instruction according to the feedback information. According to the intelligent management method and system for the greenhouse, provided by the invention, linkage of the main greenhouse and the auxiliary greenhouse is realized, implementation information can be fed back in time according to the implementation effect of the auxiliary greenhouse, the control scheme of the main greenhouse is changed in time, the individual environment changing requirements of different crops can be met, manual adjustment is not needed, the agent adjusting speed is high, the efficiency is high, and the environment in the greenhouse can be always stabilized in an ideal state.
Description
Technical Field
The invention relates to the field of intelligent control, in particular to an intelligent management method and system for a greenhouse.
Background
In recent years, the production of facility crops develops rapidly, but for large-area greenhouses, manual management is usually needed, the management and control efficiency is low, for different crops, the environment parameters in the greenhouses are intelligently adjusted manually by depending on experience, the regulation and control efficiency is low, and the environment in the greenhouses cannot be kept under ideal conditions all the time.
Disclosure of Invention
The invention aims to solve the technical problem of the prior art and provides an intelligent management method and system for a greenhouse.
The technical scheme for solving the technical problems is as follows:
an intelligent management method for a greenhouse comprises the following steps:
acquiring a control instruction for controlling control equipment of a main shed to adjust environmental parameters in the main shed, and sending the control instruction to the control equipment of at least one slave shed;
feedback information obtained after the control equipment of each slave shed controls the environmental parameters in each slave shed according to the control instruction is obtained;
and adjusting the control instruction according to the feedback information.
The invention has the beneficial effects that: according to the intelligent management method for the greenhouse, provided by the invention, the environment parameters in the main greenhouse are controlled, and the control instructions are equally sent to the control equipment of each slave greenhouse, so that the control equipment of each slave greenhouse can automatically control the environment in the slave greenhouse, and the control instructions in the main greenhouse are adjusted according to the adjustment feedback in the slave greenhouse, thereby realizing the linkage of the main greenhouse and the slave greenhouse, timely feeding back the implementation information according to the implementation effect of the slave greenhouse, timely changing the control scheme of the main greenhouse, meeting the individual environment change requirements of different crops, being free from depending on manual adjustment, having high regulation speed and efficiency, and being capable of enabling the environment in the greenhouse to be always stable in an ideal state.
On the basis of the technical scheme, the invention can be further improved as follows.
Further, the control instructions include: the control method comprises the following steps of controlling a water quantity control instruction of a water pump of the main shed, controlling a fertilizer quantity control instruction of a fertilizer pump, controlling a roller shutter, controlling an air outlet, controlling a light supplement lamp and controlling a carbon dioxide concentration control instruction of a carbon dioxide generator.
Further, before the obtaining of the control instruction for controlling the control device of the main shed to adjust the environmental parameter in the main shed, the method further includes:
collecting environmental information in a main shed;
and processing and analyzing the environmental information to obtain a control instruction for adjusting the environmental parameters in the main shed.
Further, the processing and analyzing the environmental information specifically includes:
training and learning the acquired environmental information through a neural network to obtain an environmental model;
and processing and analyzing the environmental information according to the environmental model.
The beneficial effect of adopting the further scheme is that: the acquired environment information is trained and learned through the neural network, so that the regulation and control of the environment are more intelligent.
Further, still include:
and training and learning the feedback information through a neural network, and correcting the environment model.
Another technical solution of the present invention for solving the above technical problems is as follows:
a warmhouse booth intelligent management system includes:
the communication device is used for acquiring a control instruction for controlling the control equipment of the main shed to adjust the environmental parameters in the main shed, sending the control instruction to the control equipment of at least one slave shed and acquiring feedback information obtained after the control equipment of each slave shed controls the environmental parameters in each slave shed according to the control instruction;
and the controller is used for adjusting the control instruction according to the feedback information.
The invention has the beneficial effects that: according to the intelligent management system for the greenhouse, the controller is used for controlling the environmental parameters in the main greenhouse, the communication device is used for sending the control instructions to the control equipment of each slave greenhouse in a peer-to-peer manner, so that the control equipment of each slave greenhouse can automatically control the environment in the slave greenhouse, the control instructions in the main greenhouse are adjusted according to the adjustment feedback in the slave greenhouse, the linkage of the main greenhouse and the slave greenhouse is realized, the implementation information can be fed back in time according to the implementation effect of the slave greenhouse, the control scheme of the main greenhouse is changed in time, the individual environment changing requirements of different crops can be met, manual adjustment is not needed, the agent adjusting speed is high, the efficiency is high, and the environment in the greenhouse can be always stabilized in an ideal state.
Further, the control instructions include: the control method comprises the following steps of controlling a water quantity control instruction of a water pump of the main shed, controlling a fertilizer quantity control instruction of a fertilizer pump, controlling a roller shutter, controlling an air outlet, controlling a light supplement lamp and controlling a carbon dioxide concentration control instruction of a carbon dioxide generator.
Further, still include:
the acquisition sensor is used for acquiring environmental information in the main shed;
and the processor is used for processing and analyzing the environmental information to obtain a control instruction for adjusting the environmental parameters in the main shed.
Further, the processor includes:
the neural network learning unit is used for training and learning the acquired environmental information through a neural network to obtain an environmental model;
and the analysis unit is used for processing and analyzing the environmental information according to the environmental model.
Further, the neural network learning unit is further configured to train and learn the feedback information through a neural network, and modify the environment model.
Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
Drawings
Fig. 1 is a schematic flow chart of an intelligent management method for a greenhouse according to an embodiment of the present invention;
fig. 2 is a schematic flow chart of an intelligent management method for a greenhouse according to another embodiment of the present invention;
fig. 3 is a structural framework diagram of an intelligent management system for greenhouses according to another embodiment of the present invention.
Detailed Description
The principles and features of this invention are described below in conjunction with the following drawings, which are set forth by way of illustration only and are not intended to limit the scope of the invention.
As shown in fig. 1, a schematic flow chart of an intelligent management method for a greenhouse provided in an embodiment of the present invention includes:
and S1, acquiring a control instruction for controlling the control equipment of the main shed to adjust the environmental parameters in the main shed, and sending the control instruction to the control equipment of at least one slave shed.
It should be noted that the control device is a device capable of adjusting environmental parameters in the greenhouse, and may be, for example, a water pump for controlling the amount of soil water in the greenhouse, a fertilizer pump for controlling the amount of soil fertilizer in the greenhouse, a roller shutter for controlling the temperature and the sunlight intensity in the greenhouse, a ventilation opening for controlling the ventilation condition in the greenhouse, a light supplement lamp for controlling the illumination condition in the greenhouse, and a carbon dioxide generator for controlling the carbon dioxide concentration in the greenhouse.
And S2, obtaining feedback information obtained after the control equipment of each slave shed controls the environmental parameters in each slave shed according to the control command.
The feedback information refers to information such as the growth condition of crops in the shed, the yield of target output products, the crop fatality rate and the like after the control equipment of the slave shed controls the environmental parameters in the shed of the slave shed according to the control command of the master shed.
Several preferred embodiments for obtaining feedback information are given below.
Preferably, after controlling the environmental parameters in the slave canopy, the camera device can be used for acquiring the images of the crops in the canopy in real time, and the images in the slave canopy are analyzed to judge the growth condition of the crops in the slave canopy.
It should be noted that the growth condition of the crops can be judged through a pre-stored crop matching recognition algorithm, and the growth condition and the pest and disease damage condition of the crops in each shed can be obtained by performing comparative analysis on the leaf posture, the color and the like of the crops in the image and the preset leaf posture, the color and the like of the healthy crops.
In the preferred embodiment, the feedback of the growth of the crop can be made in the form of a numerical value as the feedback information.
For example, the leaf color of the crop can be classified into a plurality of grades, for example, grade 1 can represent that the leaf color of the crop is completely consistent with that of the healthy crop and belongs to the very healthy crop; the 2-level can represent that the color of the leaves of the crops is not much different from that of the leaves of healthy crops, and the crops belong to general healthy crops; grade 3 can represent that the color of the leaves of the crops is greatly different from that of healthy crops, and the crops belong to unhealthy crops.
The blade attitude can be divided into a plurality of grades, for example, grade 1 can represent that the blade is straight and completely consistent with the blade attitude of a healthy crop and belongs to a very healthy crop; the 2-stage can represent that the blade is slightly bent, has little difference with the blade posture of healthy crops and belongs to generally healthy crops; grade 3 can represent leaf curl, which is very different from the leaf attitude of healthy crops and belongs to unhealthy crops.
It should be noted that the above is only a preferred embodiment, and in practical applications, multiple gradient levels may be set according to practical situations to improve the accuracy of the feedback information.
Preferably, after controlling the environmental parameters in the slave shed, the camera device can collect the images of the crops in the slave shed in real time, send the collected images of the slave sheds to the user monitoring terminal, and manually monitor and judge the growth conditions of the crops, and then feed back the growth conditions of the crops.
For example, the monitoring personnel can score the growth condition of crops in the shed, and the obtained score is used as feedback information.
For example, when the monitoring personnel find that the crops in the shed grow well, 100 points can be scored, and then the 100 points can be used as feedback information to be sent to the main shed; and 60 points can be made, and then the 60 points can be sent to the main shed as feedback information.
It should be noted that the above is only a preferred embodiment, and in practical applications, the accuracy of feedback can be improved by scoring the growth vigor of crops, the death condition of crops, the blade posture, the blade color, and the like.
Preferably, the system can also acquire and analyze the environmental information in the shed through a sensor after controlling the environmental parameters in the shed of the slave shed to obtain the feedback information.
For example, the environment in the greenhouse can be monitored by a temperature sensor, a humidity sensor, an illumination sensor, a carbon dioxide concentration sensor and the like, the monitoring result is compared with a preset condition and analyzed, and the analysis result is used as feedback information.
For example, after controlling the control equipment of the slave shed, other indexes are found to meet the requirements, and the obtained feedback information is that the water pump needs to be controlled only if the humidity of the soil is insufficient, so that the water inflow is increased.
For another example, after controlling the control device of the slave shed, if other indexes are found to be satisfactory, the intensity of the light is insufficient but the concentration of the carbon dioxide is excessive, the obtained feedback information needs to enhance the light and reduce the concentration of the carbon dioxide.
And S3, adjusting the control command according to the feedback information.
For example, when feedback information of 1-level leaf color and 1-level leaf posture is received, the feedback information is analyzed, so that the growth of crops in the shed is considered to be good, and the control instruction does not need to be adjusted; when feedback information of 1-level color and 3-level posture of the leaves is received, the situation that crops in the shed grow badly is shown, the leaves curl badly is shown, and the water quantity is possibly insufficient, so that the control instruction can be adjusted, the watering times of the water pump are increased, the watering quantity is increased, and the like.
For another example, when receiving feedback information that the illumination needs to be enhanced and the carbon dioxide concentration needs to be reduced, the control command can be modified accordingly to increase the illumination time of the fill light and reduce the working time of the other generator.
It should be noted that data CAN be transmitted between the master shelf and the slave shelf through a CAN bus, a 485 bus, or the like.
According to the intelligent management method for the greenhouse, the environment parameters in the main greenhouse are controlled, the control instructions are sent to the control equipment of each slave greenhouse in a peer-to-peer manner, the control equipment of each slave greenhouse can automatically control the environment in the slave greenhouse, the control instructions in the main greenhouse are adjusted according to the adjustment feedback in the slave greenhouse, the linkage of the main greenhouse and the slave greenhouse is realized, the implementation information can be fed back in time according to the implementation effect of the slave greenhouse, the control scheme of the main greenhouse can be changed in time, the individual environment changing requirements of different crops can be met, manual adjustment is not needed, the agent adjusting speed is high, the efficiency is high, and the environment in the greenhouse can be always stabilized in an ideal state.
As shown in fig. 2, a schematic flow chart of a greenhouse intelligent management method according to another embodiment of the present invention is provided, where the method includes:
and S1, acquiring a control instruction for controlling the control equipment of the main shed to adjust the environmental parameters in the main shed, and sending the control instruction to the control equipment of at least one slave shed.
Preferably, the control instructions include: the control system comprises a water quantity control instruction for controlling a water pump of the main shed, a fertilizer quantity control instruction for controlling a fertilizer pump, a rolling shutter control instruction for controlling a rolling shutter machine, a ventilation quantity control instruction for controlling an air port, a light control instruction for controlling a light supplement lamp and a carbon dioxide concentration control instruction for controlling a carbon dioxide generator.
Preferably, before step S1, the following steps may be further included:
and S01, collecting environmental information in the main shed.
It should be noted that the environmental information in the main shed may include: air temperature, air humidity, illumination intensity, soil temperature, soil humidity, carbon dioxide concentration and the like. This environmental information can be collected by sensors located in the shed and in the soil.
And S02, training and learning the acquired environmental information through a neural network to obtain an environmental model.
It should be noted that the environment model refers to an updated and improved optimal growth environment of various crops obtained through intelligent learning, and the obtained environment model can be stored in a model library, so that the environment model obtained through training and learning can be corrected and supplemented conveniently.
And S03, processing and analyzing the environmental information according to the environmental model.
It should be noted that, the collected environmental information can be automatically analyzed according to the environmental model to obtain the values of various currently required environmental parameters.
For example, when the illumination intensity required by the crop A is a, the water amount is B, the illumination intensity required by the crop B is c, and the water amount is d, after analysis is performed according to the environment model, the illumination intensity amount and the water amount required to be adjusted can be obtained according to the current environment information.
And S04, obtaining a control command for adjusting the environmental parameters in the main shed.
And generating a control instruction for controlling the corresponding control equipment according to the value of the environmental parameter needing to be adjusted, which is obtained in the last step.
For example, when a water pump of the main shed needs to be controlled, a water quantity control instruction is generated; when the fertilizer pump needs to be controlled; generating a fertilizer amount control instruction; when the rolling machine needs to be controlled, a rolling control instruction is generated; when the tuyere needs to be controlled; generating a ventilation control instruction; when the light supplement lamp needs to be controlled, a light control instruction is generated; when the carbon dioxide generator needs to be controlled, a carbon dioxide concentration control command is generated.
And S05, training and learning the feedback information through the neural network, and correcting the environment model.
The acquired environmental information is trained and learned through the neural network, so that the regulation and control of the environment are more intelligent.
And S2, obtaining feedback information obtained after the control equipment of each slave shed controls the environmental parameters in each slave shed according to the control command.
And S3, adjusting the control command according to the feedback information.
According to the intelligent management method for the greenhouse, the environment information in the main greenhouse is trained and learned in advance through the neural network, the environment parameters are controlled, the control instructions are sent to the control equipment of each slave greenhouse in a peer-to-peer mode, the control equipment of each slave greenhouse can automatically control the environment in the slave greenhouse, the control instructions in the main greenhouse are adjusted according to the adjustment feedback in the slave greenhouse, the linkage of the main greenhouse and the slave greenhouse is achieved, the implementation information can be fed back in time according to the implementation effect of the slave greenhouse, the control scheme of the main greenhouse is changed in time, the individual environment changing requirements of different crops can be met, manual adjustment is not needed, the agent adjusting speed is high, the efficiency is high, and the environment in the greenhouse can be kept stable in an ideal state all the time.
As shown in fig. 3, a structural framework diagram of an intelligent management system for greenhouses according to another embodiment of the present invention is provided, the system includes two parts, namely a main greenhouse 1 and a secondary greenhouse 2, the number of the main greenhouse may be 1, the number of the secondary greenhouse 2 may be multiple according to actual requirements, a corresponding control device 21 is disposed in each secondary greenhouse 2, and the main greenhouse 1 includes:
and the communication device 12 is used for acquiring a control instruction for controlling the control equipment 11 of the main shed 1 to adjust the environmental parameters in the main shed 4, sending the control instruction to the control equipment 21 of at least one slave shed 2, and acquiring feedback information obtained after the control equipment 21 of each slave shed 2 controls the environmental parameters in each slave shed 2 according to the control instruction.
And the controller 13 is used for adjusting the control instruction according to the feedback information.
Preferably, the control instructions include: the control system comprises a water quantity control instruction for controlling a water pump of the main shed, a fertilizer quantity control instruction for controlling a fertilizer pump, a rolling shutter control instruction for controlling a rolling shutter machine, a ventilation quantity control instruction for controlling an air port, a light control instruction for controlling a light supplement lamp and a carbon dioxide concentration control instruction for controlling a carbon dioxide generator.
Preferably, the main shed 1 also comprises inside it:
and the acquisition sensor 14 is used for acquiring environmental information in the main shed 1.
And the processor 15 is used for processing and analyzing the environmental information to obtain a control instruction for adjusting the environmental parameters in the main shed 1.
Preferably, the processor 15 comprises:
and the neural network learning unit 151 is configured to train and learn the acquired environment information through a neural network to obtain an environment model.
And an analysis unit 152, configured to perform processing analysis on the environment information according to the environment model.
Preferably, the neural network learning unit 151 is further configured to train and learn the feedback information through a neural network, so as to modify the environment model.
According to the intelligent management system for the greenhouse, the controller is used for controlling the environmental parameters in the main greenhouse, the communication device is used for sending the control instructions to the control equipment of each slave greenhouse in a peer-to-peer manner, the control equipment of each slave greenhouse can automatically control the environment in the slave greenhouse, the control instructions in the main greenhouse are adjusted according to the adjustment feedback in the slave greenhouse, the linkage of the main greenhouse and the slave greenhouse is realized, the implementation information can be fed back in time according to the implementation effect of the slave greenhouse, the control scheme of the main greenhouse is changed in time, the individual environment changing requirements of different crops can be met, manual adjustment is not needed, the agent adjusting speed is high, the efficiency is high, and the environment in the greenhouse can be always stabilized in an ideal state.
The reader should understand that in the description of this specification, reference to the description of the terms "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, a division of a unit is merely a logical division, and an actual implementation may have another division, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed.
Units described as separate parts may or may not be physically separate, and parts displayed 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 can be selected according to actual needs to achieve the purpose of the solution of the embodiment of the present invention.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention essentially or partially contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product stored in a storage medium and including 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: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-only memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
While the invention has been described with reference to specific embodiments, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (6)
1. An intelligent management method for a greenhouse is characterized by comprising the following steps:
collecting environmental information in a main shed;
training and learning the acquired environmental information through a neural network to obtain an environmental model;
processing and analyzing the environmental information according to the environmental model to obtain a control instruction for adjusting environmental parameters in the main shed;
acquiring a control instruction for controlling control equipment of a main shed to adjust environmental parameters in the main shed, and sending the control instruction to the control equipment of at least one slave shed;
feedback information obtained after the control equipment of each slave shed controls the environmental parameters in each slave shed according to the control instruction is obtained;
and adjusting the control instruction according to the feedback information.
2. The intelligent management method for the greenhouse of claim 1, wherein the control instruction comprises: the control method comprises the following steps of controlling a water quantity control instruction of a water pump of the main shed, controlling a fertilizer quantity control instruction of a fertilizer pump, controlling a roller shutter, controlling an air outlet, controlling a light supplement lamp and controlling a carbon dioxide concentration control instruction of a carbon dioxide generator.
3. The intelligent management method for the greenhouse as claimed in claim 1, further comprising:
and training and learning the feedback information through a neural network, and correcting the environment model.
4. The utility model provides a warmhouse booth intelligent management system which characterized in that includes:
the acquisition sensor is used for acquiring environmental information in the main shed;
the processor is used for processing and analyzing the environmental information to obtain a control instruction for adjusting the environmental parameters in the main shed;
the communication device is used for acquiring a control instruction for controlling the control equipment of the main shed to adjust the environmental parameters in the main shed, sending the control instruction to the control equipment of at least one slave shed and acquiring feedback information obtained after the control equipment of each slave shed controls the environmental parameters in each slave shed according to the control instruction;
the controller is used for adjusting the control instruction according to the feedback information;
wherein the processor comprises:
the neural network learning unit is used for training and learning the acquired environmental information through a neural network to obtain an environmental model;
and the analysis unit is used for processing and analyzing the environmental information according to the environmental model.
5. The intelligent management system for greenhouses according to claim 4, wherein the control instruction comprises: the control method comprises the following steps of controlling a water quantity control instruction of a water pump of the main shed, controlling a fertilizer quantity control instruction of a fertilizer pump, controlling a roller shutter, controlling an air outlet, controlling a light supplement lamp and controlling a carbon dioxide concentration control instruction of a carbon dioxide generator.
6. The intelligent management system for greenhouses according to claim 4, wherein the neural network learning unit is further configured to train and learn the feedback information through a neural network to modify the environment model.
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| CN201711423181.9A CN108153357B (en) | 2017-12-25 | 2017-12-25 | Intelligent management method and system for greenhouse |
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| Application Number | Priority Date | Filing Date | Title |
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| CN201711423181.9A CN108153357B (en) | 2017-12-25 | 2017-12-25 | Intelligent management method and system for greenhouse |
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| CN108153357B true CN108153357B (en) | 2020-09-29 |
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| CN111026199A (en) * | 2019-11-25 | 2020-04-17 | 南京大学（溧水）生态环境研究院 | Kitchen remains compost intelligent monitoring regulation and control system |
| CN114564056B (en) * | 2022-02-21 | 2023-05-26 | 蚌埠市鹏慈农业科技有限公司 | Intelligent control system for planting greenhouse |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103197655A (en) * | 2013-04-18 | 2013-07-10 | 河南邦友农业生态循环发展有限公司 | Intelligent multi-span greenhouse mushroom house remote control system |
| KR20130088954A (en) * | 2012-02-01 | 2013-08-09 | (주)유엠솔루션 | Mulitplex environment controller of greenhouse |
| CN103744457A (en) * | 2013-07-28 | 2014-04-23 | 江苏城市职业学院 | Temperature and humidity monitoring system for agricultural greenhouse |
| CN205375238U (en) * | 2015-12-24 | 2016-07-06 | 合肥恒诚智能技术有限公司 | Station district computer lab humiture centralization management system under PLC controls |
| CN206559395U (en) * | 2016-09-14 | 2017-10-13 | 中国农业大学 | A kind of intelligent monitor system suitable for greenhouse cluster |
-
2017
- 2017-12-25 CN CN201711423181.9A patent/CN108153357B/en not_active Expired - Fee Related
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20130088954A (en) * | 2012-02-01 | 2013-08-09 | (주)유엠솔루션 | Mulitplex environment controller of greenhouse |
| CN103197655A (en) * | 2013-04-18 | 2013-07-10 | 河南邦友农业生态循环发展有限公司 | Intelligent multi-span greenhouse mushroom house remote control system |
| CN103744457A (en) * | 2013-07-28 | 2014-04-23 | 江苏城市职业学院 | Temperature and humidity monitoring system for agricultural greenhouse |
| CN205375238U (en) * | 2015-12-24 | 2016-07-06 | 合肥恒诚智能技术有限公司 | Station district computer lab humiture centralization management system under PLC controls |
| CN206559395U (en) * | 2016-09-14 | 2017-10-13 | 中国农业大学 | A kind of intelligent monitor system suitable for greenhouse cluster |
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