CN115053735A - Constant temperature greenhouse temperature control system - Google Patents
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- A—HUMAN NECESSITIES
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Abstract
The invention discloses a constant-temperature greenhouse temperature control system, relates to the technical field of temperature control, and solves the technical problem of low efficiency caused by manually controlling the temperature of a greenhouse; the data acquisition module acquires environmental data and a preset temperature value; the data processing module acquires a temperature early warning signal according to the environmental data, and the intelligent early warning module receives the temperature early warning signal and reminds an administrator of the abnormal greenhouse; the temperature in the greenhouse is monitored, and when the temperature exceeds the adjustable range, early warning is timely carried out, so that loss is reduced; the data processing module acquires a state label according to the environmental data and the greenhouse detection model; identifying the state label, acquiring a temperature adjusting value according to the environmental data and a preset temperature value when the greenhouse is in an abnormal state, and sending the temperature adjusting value to the intelligent control module; the intelligent control module controls the temperature of the greenhouse according to the temperature regulating value; the automatic control of the temperature in the greenhouse is realized, the constant temperature state is kept, and the production efficiency is improved.
Description
Technical Field
The invention belongs to the field of constant-temperature greenhouses, relates to a temperature control technology, and particularly relates to a temperature control system of a constant-temperature greenhouse.
Background
Modern agriculture plants are more and more free from greenhouse, the greenhouse plays a greater and greater role in agricultural production, and the greenhouse is mainly established to form a high-temperature space at a relatively natural temperature, namely the greenhouse.
For greenhouses, one of the most important management factors is temperature control. The normal growth of plants and sudden weather changes can be influenced when the temperature is too low or too high, the growth speed of micro-crops and the yield are influenced when the temperature is too low, the temperature of the greenhouse needs to be controlled within a range suitable for the growth of crops all the time, and most temperature adjusting facilities of the greenhouse are manually completed. Each greenhouse temperature regulating device still requires multiple labors to complete and is asynchronous. The labor force can not be completely liberated, the working efficiency is greatly reduced, the labor resource is consumed only by manual control, and errors are easy to occur.
Therefore, a constant-temperature greenhouse temperature control system is provided.
Disclosure of Invention
The present invention is directed to solving at least one of the problems of the prior art. Therefore, the invention provides a constant-temperature greenhouse temperature control system which solves the problem of low efficiency caused by manual control of the temperature of a greenhouse.
In order to achieve the above object, an embodiment according to a first aspect of the present invention provides a constant temperature greenhouse temperature control system, including a data acquisition module, a data processing module, an intelligent control module, and an intelligent early warning module; information interaction is carried out among all modules based on a digital signal mode;
the data acquisition module is used for acquiring environmental data and a preset temperature value; wherein the environmental data comprises a temperature value and a humidity value;
sending the environmental data and the preset temperature value to the data processing module;
the data processing module is used for receiving the environment data and the preset temperature value;
acquiring a temperature early warning signal according to the environment data, and sending the temperature early warning signal to the intelligent early warning module;
acquiring a state label according to the environment data and the greenhouse detection model; the greenhouse detection model is established based on an artificial intelligence model; identifying the state label, acquiring a temperature adjusting value according to the environment data and the preset temperature value when the greenhouse is in an abnormal state, and sending the temperature adjusting value to the intelligent control module;
the intelligent early warning module is used for receiving the temperature early warning signal and reminding an administrator of the abnormal condition of the greenhouse;
the intelligent control module is used for receiving the temperature adjusting value and controlling the temperature of the greenhouse according to the temperature adjusting value.
Preferably, the data acquisition module comprises a temperature sensor and a humidity sensor.
Preferably, the data acquisition module acquires environmental data and a preset temperature value, and the specific process includes:
the administrator uploads a preset temperature value to the data acquisition module through the intelligent terminal;
the preset temperature value is marked as W Preparation of In units of;
setting an acquisition period T in seconds; wherein T is an integer greater than 0;
the temperature sensor collects temperature values once every Ts;
the temperature value is marked as W i In units of; wherein i is the number of the acquisition period, and the value of i is 1, 2, 3 … … n;
the humidity sensor collects humidity values once every Ts;
the humidity value is marked S i In units of RH;
and the data acquisition module sends the environmental data and the preset temperature value to a data processing module.
Preferably, the intelligent terminal comprises an intelligent mobile phone and a computer.
Preferably, the data processing module obtains the temperature early warning signal according to the environmental data, and the specific process includes:
the data processing module receives the environmental data and the preset temperature value;
the data acquisition module sets a temperature interval W [ W ] min ,W max ]；
W min Is the minimum temperature in units of;
W max is the maximum temperature in units of ℃;
when in use
And the data processing module generates a temperature early warning signal and sends the temperature early warning signal to the intelligent early warning module.
Preferably, the intelligent early warning module receives the temperature early warning signal and reminds an administrator of the abnormal condition of the greenhouse, and the specific process comprises the following steps:
the intelligent early warning module receives the temperature early warning signal;
generating an early warning short message according to the temperature early warning signal;
and sending the early warning short message to an intelligent terminal of an administrator.
Preferably, the state label is obtained according to the environmental data and the greenhouse detection model, and the specific process comprises the following steps:
the data processing module receives the environmental data;
acquiring a greenhouse detection model from a data processing module;
taking the time when the data processing module receives the environmental parameters as a reference time, extracting N groups of environmental parameters before the reference time from the environmental parameters, and integrating to generate original data; wherein N is an integer greater than or equal to 10;
and inputting the original data into the greenhouse detection model to obtain a corresponding state label.
Preferably, the greenhouse detection model is established based on an artificial intelligence model, and the specific process comprises the following steps:
acquiring standard training data from a data processing module;
training the artificial intelligence model through standard training data, and marking the trained artificial intelligence model as a greenhouse detection model;
the standard training data comprises a plurality of groups of input data and corresponding state labels, and the content attributes of the input data and the original data are consistent;
the artificial intelligence model comprises a deep convolution neural network model and an RBF neural network model.
Preferably, the temperature adjustment value is obtained according to the environmental data and the preset temperature value, and the specific process includes:
the data processing module receives the environmental data and the preset temperature value;
identifying the state label, and acquiring a temperature adjusting value when the greenhouse is in an abnormal state;
the temperature adjustment value is marked as Δ W, and the unit is;
the calculation formula of the temperature regulation value is as follows: Δ W ═ W i -W Preparation of ；
And sending the temperature adjusting value to the intelligent control module.
Preferably, the intelligent control module receives the temperature adjustment value, and controls the temperature in the greenhouse according to the temperature adjustment value, and the specific process comprises the following steps:
the intelligent control module receives the temperature adjusting value;
when the delta W is larger than 0, the intelligent control module sends a cooling signal to the ventilator, and the ventilator controls the air volume according to the temperature adjusting value;
when the delta W is less than 0, the intelligent control module sends a heating signal to the temperature booster, and the temperature booster controls the size of the heater according to the temperature adjusting value.
Compared with the prior art, the invention has the beneficial effects that:
the method comprises the steps of collecting environmental data and a preset temperature value through a data collection module; sending the environmental data and the preset temperature value to a data processing module; the data processing module acquires a temperature early warning signal according to the environmental data and sends the temperature early warning signal to the intelligent early warning module; the intelligent early warning module receives the temperature early warning signal and reminds an administrator of the abnormal condition of the greenhouse; the temperature in the greenhouse is monitored, and when the temperature exceeds the adjustable range, early warning is timely performed, so that the loss is reduced;
the data processing module acquires a state label according to the environmental data and the greenhouse detection model; identifying the state label, acquiring a temperature adjusting value according to the environmental data and a preset temperature value when the greenhouse is in an abnormal state, and sending the temperature adjusting value to the intelligent control module; the intelligent control module controls the temperature of the greenhouse according to the temperature regulating value; the automatic control of the temperature in the greenhouse is realized, the constant temperature state is kept, and the production efficiency is improved.
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Fig. 1 is a schematic diagram of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. 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.
As shown in fig. 1, a constant temperature greenhouse temperature control system comprises a data acquisition module, a data processing module, an intelligent control module and an intelligent early warning module; information interaction is carried out among all modules based on a digital signal mode;
the data acquisition module is used for acquiring environmental data and a preset temperature value; wherein the environmental data comprises a temperature value and a humidity value;
sending the environmental data and the preset temperature value to the data processing module;
the data processing module is used for receiving the environment data and the preset temperature value;
acquiring a temperature early warning signal according to the environmental data, and sending the temperature early warning signal to the intelligent early warning module;
acquiring a state label according to the environment data and the greenhouse detection model; the greenhouse detection model is established based on an artificial intelligence model; identifying the state label, acquiring a temperature adjusting value according to the environment data and the preset temperature value when the greenhouse is in an abnormal state, and sending the temperature adjusting value to the intelligent control module;
the intelligent early warning module is used for receiving the temperature early warning signal and reminding an administrator of the abnormal condition of the greenhouse;
the intelligent control module is used for receiving the temperature adjusting value and controlling the temperature of the greenhouse according to the temperature adjusting value.
In this embodiment, the data acquisition module includes a temperature sensor and a humidity sensor;
the temperature sensor is arranged in the greenhouse;
the humidity sensor is installed in the greenhouse.
The data acquisition module acquires environmental data and a preset temperature value, and the specific process comprises the following steps:
the administrator uploads a preset temperature value to the data acquisition module through the intelligent terminal;
the preset temperature value is marked as W Preparation of In units of;
setting an acquisition period T in seconds; wherein T is an integer greater than 0;
the temperature sensor collects temperature values once every Ts;
the temperature value is marked as W i In units of; wherein i is the number of the acquisition period, and the value of i is 1, 2, 3 … … n;
the humidity sensor collects humidity values once every Ts;
the humidity value is marked S i In units of RH;
and the data acquisition module sends the environmental data and the preset temperature value to a data processing module.
In this embodiment, the intelligent terminal includes intelligent devices such as a smart phone and a computer.
In this embodiment, the data processing module obtains the temperature early warning signal according to the environmental data, and the specific process includes:
the data processing module receives the environmental data and the preset temperature value;
the data acquisition module sets a temperature interval W [ W ] min ,W max ](ii) a It should be further explained that the preset temperature set by the administrator is within a temperature interval, the temperature interval is set by a professional, when the temperature value exceeds the temperature interval, which means that the temperature in the greenhouse exceeds the adjustable range, the administrator needs to timely drive to the greenhouse site to find out the specific reason of temperature increase or decrease, and make professional solutions;
W min is the minimum temperature in units of;
W max is the maximum temperature in units of ℃;
when the temperature is higher than the set temperature
And the data processing module generates a temperature early warning signal and sends the temperature early warning signal to the intelligent early warning module.
The intelligent early warning module receives the temperature early warning signal and reminds an administrator of the abnormal condition of the greenhouse, and the specific process comprises the following steps:
the intelligent early warning module receives the temperature early warning signal;
generating an early warning short message according to the temperature early warning signal;
sending the early warning short message to an intelligent terminal of an administrator;
and after receiving the early warning short message through the intelligent terminal, the administrator immediately drives to the greenhouse to check the field condition.
Acquiring a state label according to the environment data and the greenhouse detection model, wherein the specific process comprises the following steps:
the data processing module receives the environmental data;
acquiring a greenhouse detection model from a data processing module;
taking the time when the data processing module receives the environmental parameters as a reference time, extracting N groups of environmental parameters before the reference time from the environmental parameters, and integrating to generate original data;
and inputting the original data into the greenhouse detection model to obtain a corresponding state label.
In this embodiment, N is an integer greater than or equal to 10, and it is verified that an accurate status tag can only be obtained when there are at least 10 sets of environmental parameters; for example, the following steps are carried out:
assuming that the environmental parameters are acquired 1 time per second, the reference time is 0 minutes and 0 seconds at 10 am, 15 sets of environmental parameters before the reference time are extracted, namely data acquired from 9 hours, 59 minutes and 46 seconds are taken as a first set of environmental parameters until the reference time is 15 sets of environmental parameters in total, and the 15 sets of environmental parameters are sorted according to the acquisition time to form original data.
In this embodiment, the greenhouse detection model is established based on an artificial intelligence model, and the specific process includes:
acquiring standard training data from a data processing module;
training the artificial intelligence model through standard training data, and marking the trained artificial intelligence model as a greenhouse detection model.
In this embodiment, the standard training data includes a plurality of sets of input data and corresponding status labels, and the input data and the original data have consistent content attributes; it will be appreciated that both the input data and the raw data include a selected N set of environmental parameters, except for the magnitude of the environmental parameters.
In this embodiment, the artificial intelligence model includes a model with strong nonlinear fitting capability, such as a deep convolutional neural network model or an RBF neural network model.
Obtaining a temperature regulation value according to the environment data and the preset temperature value, wherein the specific process comprises the following steps:
the data processing module receives the environmental data and the preset temperature value;
identifying the state label, and acquiring a temperature adjusting value when the greenhouse is in an abnormal state;
the temperature adjustment value is marked as Δ W, and the unit is;
the calculation formula of the temperature regulation value is as follows: Δ W ═ W i -W Preparation of ；
And sending the temperature adjusting value to the intelligent control module.
The intelligent control module receives the temperature regulating value, controls the temperature in the greenhouse according to the temperature regulating value, and the specific process comprises the following steps:
the intelligent control module receives the temperature adjusting value;
when the delta W is larger than 0, namely the temperature value is higher than the preset temperature value, the intelligent control module sends a cooling signal to the ventilator, and the ventilator controls the air volume according to the temperature regulation value to achieve the effect of reducing the temperature of the greenhouse;
when the delta W is less than 0, namely the temperature value is lower than the preset temperature value, the intelligent control module sends a heating signal to the temperature booster, and the temperature booster controls the size of the hot air according to the temperature adjusting value, so that the effect of increasing the temperature of the greenhouse is achieved.
In this embodiment, the data acquisition module is in communication and/or electrical connection with the data processing module;
the data processing module is in communication and/or electrical connection with the intelligent control module;
the data processing module is in communication and/or electrical connection with the intelligent early warning module.
The above formulas are all calculated by removing dimensions and taking numerical values thereof, the formula is a formula which is obtained by acquiring a large amount of data and performing software simulation to obtain the closest real situation, and the preset parameters and the preset threshold value in the formula are set by the technical personnel in the field according to the actual situation or obtained by simulating a large amount of data.
The working principle of the invention is as follows:
the administrator uploads a preset temperature value to the data acquisition module through the intelligent terminal; the temperature sensor collects temperature values once every Ts; the humidity sensor collects humidity values once every Ts; the data acquisition module sends the environmental data and the preset temperature value to the data processing module;
the data acquisition module sets a temperature interval; when the temperature value is not in the temperature interval, the data processing module generates a temperature early warning signal and sends the temperature early warning signal to the intelligent early warning module;
the intelligent early warning module receives a temperature early warning signal; generating an early warning short message according to the temperature early warning signal; sending the early warning short message to an intelligent terminal of an administrator; after receiving the early warning short message through the intelligent terminal, the administrator immediately drives to the greenhouse and checks the field condition;
the data processing module receives environmental data; acquiring a greenhouse detection model from a data processing module; taking the time when the data processing module receives the environmental parameters as a reference time, extracting N groups of environmental parameters before the reference time from the environmental parameters, and integrating to generate original data; inputting the original data into a greenhouse detection model to obtain a corresponding state label;
the data processing module receives the environmental data and a preset temperature value; identifying the state label, and acquiring a temperature adjusting value when the greenhouse is in an abnormal state; sending the temperature adjusting value to an intelligent control module;
the intelligent control module receives the temperature adjusting value; when the temperature value is higher than the preset temperature value, the intelligent control module sends a cooling signal to the ventilator, and the ventilator controls the air volume according to the temperature adjusting value to achieve the effect of reducing the temperature of the greenhouse; when the temperature value is lower than the preset temperature value, the intelligent control module sends a heating signal to the temperature booster, and the temperature booster controls the size of the heater according to the temperature adjusting value, so that the effect of increasing the temperature of the greenhouse is achieved.
Although the present invention has been described in detail with reference to the preferred embodiments, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted for elements thereof without departing from the spirit and scope of the present invention.
Claims (10)
1. A constant-temperature greenhouse temperature control system is characterized by comprising a data acquisition module, a data processing module, an intelligent control module and an intelligent early warning module; information interaction is carried out among all modules based on a digital signal mode;
the data acquisition module is used for acquiring environmental data and a preset temperature value; wherein the environmental data comprises a temperature value and a humidity value;
sending the environmental data and the preset temperature value to the data processing module;
the data processing module is used for receiving the environment data and the preset temperature value;
acquiring a temperature early warning signal according to the environment data, and sending the temperature early warning signal to the intelligent early warning module;
acquiring a state label according to the environment data and the greenhouse detection model; the greenhouse detection model is established based on an artificial intelligence model; identifying the state label, acquiring a temperature adjusting value according to the environment data and the preset temperature value when the greenhouse is in an abnormal state, and sending the temperature adjusting value to the intelligent control module;
the intelligent early warning module is used for receiving the temperature early warning signal and reminding an administrator of the abnormal condition of the greenhouse;
the intelligent control module is used for receiving the temperature adjusting value and controlling the temperature of the greenhouse according to the temperature adjusting value.
2. The temperature control system of claim 1, wherein the data acquisition module comprises a temperature sensor and a humidity sensor.
3. The temperature control system of the constant-temperature greenhouse of claim 2, wherein the data acquisition module acquires environmental data and preset temperature values, and the specific process comprises:
the administrator uploads a preset temperature value to the data acquisition module through the intelligent terminal;
the preset temperature value is marked as W Preparation of In units of;
setting an acquisition period T in seconds; wherein T is an integer greater than 0;
the temperature sensor collects temperature values once every Ts;
the temperature value is marked as W i The unit is; wherein i is the number of the acquisition period, and the value of i is 1, 2, 3 … … n;
the humidity sensor collects humidity values once every Ts;
the humidity value is marked S i In units of RH;
and the data acquisition module sends the environmental data and the preset temperature value to a data processing module.
4. The temperature control system of claim 3, wherein the intelligent terminal comprises a smart phone and a computer.
5. The temperature control system of claim 4, wherein the data processing module obtains a temperature early warning signal according to the environmental data, and the specific process comprises:
the data processing module receives the environmental data and the preset temperature value;
the data acquisition module sets a temperature interval W [ W ] min ,W max ]；
W min Is the minimum temperature in units of;
W max is the maximum temperature in units of ℃;
when in use
And the data processing module generates a temperature early warning signal and sends the temperature early warning signal to the intelligent early warning module.
6. The temperature control system for the constant-temperature greenhouse of claim 5, wherein the intelligent early warning module receives the temperature early warning signal and reminds an administrator of the greenhouse of abnormality, and the specific process comprises the following steps:
the intelligent early warning module receives the temperature early warning signal;
generating an early warning short message according to the temperature early warning signal;
and sending the early warning short message to an intelligent terminal of an administrator.
7. The temperature control system of claim 6, wherein a status label is obtained according to the environmental data and the greenhouse detection model, and the specific process comprises:
the data processing module receives the environmental data;
acquiring a greenhouse detection model from a data processing module;
taking the time when the data processing module receives the environmental parameters as a reference time, extracting N groups of environmental parameters before the reference time from the environmental parameters, and integrating to generate original data; wherein N is an integer greater than or equal to 10;
and inputting the original data into the greenhouse detection model to obtain a corresponding state label.
8. The temperature control system of claim 7, wherein the greenhouse detection model is established based on an artificial intelligence model, and the specific process comprises:
acquiring standard training data from a data processing module;
training the artificial intelligence model through standard training data, and marking the trained artificial intelligence model as a greenhouse detection model;
the standard training data comprises a plurality of groups of input data and corresponding state labels, and the content attributes of the input data and the original data are consistent;
the artificial intelligence model comprises a deep convolution neural network model and an RBF neural network model.
9. The temperature control system of claim 8, wherein a temperature adjustment value is obtained according to the environmental data and the preset temperature value, and the specific process comprises:
the data processing module receives the environmental data and the preset temperature value;
identifying the state label, and acquiring a temperature adjusting value when the greenhouse is in an abnormal state;
the temperature adjustment value is marked as Δ W, and the unit is;
the calculation formula of the temperature regulation value is as follows: Δ W ═ W i -W Preparation of ；
And sending the temperature adjusting value to the intelligent control module.
10. The temperature control system of claim 9, wherein the intelligent control module receives the temperature adjustment value and controls the temperature in the greenhouse according to the temperature adjustment value, and the specific process comprises:
the intelligent control module receives the temperature adjusting value;
when the delta W is larger than 0, the intelligent control module sends a cooling signal to the ventilator, and the ventilator controls the air volume according to the temperature adjusting value;
when the delta W is less than 0, the intelligent control module sends a heating signal to the temperature booster, and the temperature booster controls the size of the hot air according to the temperature adjusting value.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116184873A (en) * | 2022-11-21 | 2023-05-30 | 广西师范大学 | Big data monitoring system of thing networking environment |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103760872A (en) * | 2014-01-27 | 2014-04-30 | 林兴志 | Alarming and intervening device for refined agricultural crop growth |
| KR20140056649A (en) * | 2012-10-30 | 2014-05-12 | (주) 코콤 | Fan heater temperature control system with the function maintain a uniform indoor temperature |
| CN106599568A (en) * | 2016-12-10 | 2017-04-26 | 潘敏 | Abnormal temperature diagnosis device for greenhouse |
| CN108919754A (en) * | 2018-06-21 | 2018-11-30 | 马鞍山中粮生物化学有限公司 | A kind of intelligence greenhouse real-time monitoring system and monitoring method |
| CN112230697A (en) * | 2020-10-19 | 2021-01-15 | 广州市企德友诚美信息技术开发有限公司 | Agricultural monitoring device based on internet |
| CN112419288A (en) * | 2020-11-28 | 2021-02-26 | 西安石油大学 | Unmanned vegetable greenhouse planting method based on computer vision |
| CN112667008A (en) * | 2020-12-16 | 2021-04-16 | 惠州城市职业学院(惠州商贸旅游高级职业技术学校) | Intelligent temperature control system for leaf vegetable greenhouse |
| KR20210103714A (en) * | 2020-02-14 | 2021-08-24 | 주식회사 조인트리 | K-Plant Integrated Control System |
-
2022
- 2022-07-13 CN CN202210826042.5A patent/CN115053735A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20140056649A (en) * | 2012-10-30 | 2014-05-12 | (주) 코콤 | Fan heater temperature control system with the function maintain a uniform indoor temperature |
| CN103760872A (en) * | 2014-01-27 | 2014-04-30 | 林兴志 | Alarming and intervening device for refined agricultural crop growth |
| CN106599568A (en) * | 2016-12-10 | 2017-04-26 | 潘敏 | Abnormal temperature diagnosis device for greenhouse |
| CN108919754A (en) * | 2018-06-21 | 2018-11-30 | 马鞍山中粮生物化学有限公司 | A kind of intelligence greenhouse real-time monitoring system and monitoring method |
| KR20210103714A (en) * | 2020-02-14 | 2021-08-24 | 주식회사 조인트리 | K-Plant Integrated Control System |
| CN112230697A (en) * | 2020-10-19 | 2021-01-15 | 广州市企德友诚美信息技术开发有限公司 | Agricultural monitoring device based on internet |
| CN112419288A (en) * | 2020-11-28 | 2021-02-26 | 西安石油大学 | Unmanned vegetable greenhouse planting method based on computer vision |
| CN112667008A (en) * | 2020-12-16 | 2021-04-16 | 惠州城市职业学院(惠州商贸旅游高级职业技术学校) | Intelligent temperature control system for leaf vegetable greenhouse |
Non-Patent Citations (9)
| Title |
|---|
| 吕太国;刘子政;: "温室恒温自动监控系统的设计", 湖北农业科学, vol. 1, no. 10, pages 2566 - 2568 * |
| 姚涛;许森;: "基于Modbus现场总线的分布式温度监控系统", 浙江树人大学学报(自然科学版), no. 04 * |
| 徐惠敏;占玲玲;: "基于触摸屏和PLC的温室大棚控制系统设计", 装备制造技术, no. 09, pages 21 - 24 * |
| 李勇;张以帅;唐广耀;赖惠鸽;: "基于MSP430的温室环境数据采集和控制系统设计", 微型机与应用, no. 07 * |
| 李美丽等: "农业大棚自动控制系统", 绥化学院学报, vol. 36, no. 05, pages 146 - 148 * |
| 李锐;: "基于AT89C51单片机的大棚温控系统设计", 电子制作, no. 02 * |
| 杨俊成;李淑霞;李亮;: "基于物联网与人工神经网络的温室监控方案", 控制工程, no. 09, pages 1649 - 1656 * |
| 谭励;李冬;郭雪;于重重;: "基于Zigbee网络的温室环境监测系统设计", 农机化研究, vol. 1, no. 03, pages 145 - 148 * |
| 郭立帅等: "智能化温室大棚控制系统的研究", 长沙大学学报, vol. 27, no. 02, pages 36 - 38 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116184873A (en) * | 2022-11-21 | 2023-05-30 | 广西师范大学 | Big data monitoring system of thing networking environment |
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