CN109688675A - Green housing Intelligent energy-saving system - Google Patents

Abstract

The invention provides an intelligent energy-saving system for a green house. The system includes: a meteorological data acquisition part for acquiring meteorological data in real time; a plurality of brightness detection parts for real-time detection of brightness to generate a plurality of brightness signals; a plurality of intelligent Street lamp components, used for lighting; and artificial intelligence automatic update information processing center, respectively connected with the meteorological data acquisition department, brightness detection department and intelligent street lamp components, the artificial intelligence automatic update information processing center according to meteorological data, brightness signals and initial control instructions The brightness control command is generated by the set control command algorithm, and the brightness control command is sent to the corresponding smart street light assembly to control the lighting brightness of the smart street light assembly. Intelligent continuous self-learning, self-adjustment, and self-renewal makes the lighting system more intelligent, the brightness control is more accurate, and it is energy-saving and environmentally friendly.

Description

Green residential intelligent energy-saving system

technical field

The invention relates to the field of construction technology, in particular to an intelligent energy-saving system for green houses.

Background technique

my country's building energy consumption accounts for a large proportion of energy consumption in China. In building energy consumption, outdoor lighting also occupies a large proportion, and the lighting facilities in residential quarters often cause energy waste and cannot be well distributed. This phenomenon causes a lot of waste of electric energy, which is not conducive to the sustainable development of the house and the good development of the economy.

It is urgent to solve the situation of energy shortage and environmental deterioration. The concept of green building is gradually being valued by the country, and the development of green building in my country has entered a stage of comprehensive development. At the same time, artificial intelligence technology is developing rapidly. Artificial intelligence based on big data has extremely high intelligence and flexibility. Applying it to the lighting system of residential quarters will greatly optimize the energy structure and utilization rate of the lighting system.

How to apply artificial intelligence technology to the lighting system of residential quarters has become an important research topic at present.

SUMMARY OF THE INVENTION

In order to solve the above problems, the purpose of the present invention is to provide an intelligent energy-saving system for green houses, which can intelligently control the outdoor brightness of a plurality of residential areas including a plurality of residential buildings in a residential area, and is energy-saving and environmentally friendly.

In order to solve the above problems, the present invention adopts the following technical solutions:

The invention provides an intelligent energy-saving system for green houses, which is used for intelligently controlling the outdoor brightness of a plurality of residential areas containing a plurality of residential buildings in a residential area. The meteorological data of the residential area detected by the Meteorological Bureau includes sunrise and sunset time, sky brightness and brightness; multiple brightness detection units are respectively set in multiple residential areas, and are used to detect the brightness in multiple residential areas in real time to generate Multiple brightness signals; multiple smart street light components, respectively set in multiple residential areas, respectively, for lighting multiple residential areas; and artificial intelligence automatic update information processing center, respectively, with the meteorological data acquisition department, brightness detection The unit and the intelligent street light assembly are connected in communication, wherein the meteorological data acquisition unit sends the weather data to the artificial intelligence automatic update information processing center, and the multiple brightness detection units respectively send the brightness signals corresponding to each residential area to the artificial intelligence automatic update information processing center. , the artificial intelligence automatic update information processing center receives the meteorological data and the brightness signal, and generates the brightness control command through the set control command algorithm according to the meteorological data, the brightness signal and the initial control command, and further sends the brightness control command to the corresponding residential area. The intelligent street lamp assembly is used to control the illumination brightness of the intelligent street lamp assembly, thereby realizing intelligent brightness control based on meteorological data for each residential area. The intelligent energy-saving system for green houses of the present invention also has the following characteristics: wherein the brightness detection part includes an infrared brightness monitoring camera arranged on the ceiling of the area and a brightness sensor arranged on the ground of the area.

The intelligent energy-saving system for green houses of the present invention also has the following characteristics: wherein, the intelligent street lamp assembly includes: a base, embedded on the ground of the residential area, a lamp pole, fixed on the base, an energy-saving LED lamp group, fixed Set on the light pole, for lighting, and the artificial intelligence chip, fixed in the base and communicated with the artificial intelligence automatic update information processing center, used to receive the brightness control instructions of the artificial intelligence automatic update information processing center and according to the brightness The control command controls the lighting brightness of the energy-saving LED lamp group.

The green house intelligent energy-saving system of the present invention also has the following characteristics, and further comprises: a power supply part, which is electrically connected with the human intelligent street lamp assembly through a cable, and is used for supplying power to the intelligent street lamp assembly, wherein the power supply part has: a plurality of first Photovoltaic solar panels, respectively arranged on the top of a plurality of residential buildings, are used to convert solar energy into electrical energy to supply power to the smart street light components, and a plurality of second photovoltaic solar panels are respectively arranged on a plurality of light poles to convert solar energy into electricity Power supply for the smart street light components, a plurality of wind generators, respectively arranged on the top of the plurality of light poles, used to convert wind energy into electric energy to supply power to the smart street light components, the power acquisition unit, respectively, through the cable with the municipal power grid And each smart street light component is electrically connected.

The intelligent energy-saving system for green houses of the present invention also has the following characteristics: wherein, the brightness detection part includes an infrared brightness monitoring camera arranged on the light pole and a brightness sensor arranged on the ground of the residential area.

The green house intelligent energy-saving system of the present invention also has the following characteristics: wherein, the set control instruction algorithm is an error back propagation algorithm, and the algorithm includes the following steps: Step 1, the artificial intelligence automatic update information processing center receives The _{meteorological data} and the _{brightness signal} of each residential area of the Get the intermediate control instruction y,

Step 3: Calculate the error e between the intermediate control command y and the initial control command P, as shown in the following formula (2)

e=y-p(2)

Step 3, adjust the weight w _i according to the error e, step 4, judge whether the error e is within a predetermined range, when it is judged to be no, go to step 2, when it is judged to be yes, use the intermediate control instruction y as the corresponding residential area. Brightness control command output, is the excitation function, and n is the total number of input values.

The intelligent energy-saving system for green houses of the present invention also has the characteristics of: a dedicated database, wherein once the artificial intelligence automatic update information processing center generates a brightness control instruction, the artificial intelligence automatic update information processing center uses the brightness control instruction as the brightness control instruction. The historical brightness control command, the brightness signal when the historical brightness control command is sent as the initial brightness signal, and the brightness signal after sending the historical brightness control command after a predetermined period of time are sent to the special database as the brightness signal after the command is implemented, and the special database receives the historical brightness control command. , the initial brightness signal and the brightness signal after the command is implemented, and store the historical brightness control command, the initial brightness signal, and the brightness signal after the command is implemented. Once the artificial intelligence automatically updates the information processing center and receives the brightness signal of each residential area, the artificial intelligence The automatic update information processing center takes the historical brightness control command corresponding to the brightness signal in the dedicated database as a new initial control command, thereby realizing the self-learning, self-adjustment and self-update of the artificial intelligence automatic update information processing center.

The intelligent energy-saving system for green houses of the present invention also has the following characteristics: wherein, the artificial intelligence automatic update information processing center is composed of a computer with artificial intelligence algorithm.

Invention action and effect

According to the intelligent energy-saving system for green houses according to the present invention, since it has the meteorological data acquisition unit, the meteorological data including sunrise and sunset time, sky brightness and brightness of the residential quarter detected by the meteorological bureau can be acquired in real time. Therefore, it can detect the brightness in multiple residential areas in real time to generate multiple brightness signals; because of the multiple smart street light components, it can illuminate multiple residential areas respectively; due to the artificial intelligence automatic update information processing center, respectively Communication and connection with the meteorological data acquisition part, the brightness detection part and the intelligent street light assembly, it can receive the meteorological data and the brightness signal, and generate the brightness control command through the set control command algorithm according to the meteorological data, the brightness signal and the initial control command, and further the brightness The control command is sent to the intelligent street light assembly in the corresponding residential area to control the lighting brightness of the intelligent street light assembly, thereby realizing the intelligent brightness control based on the meteorological data for each residential area, so that the lighting brightness of the residential area can be adjusted according to actual needs, It reduces power consumption and creates a comfortable and green brightness environment for residential quarters.

Because it has a power supply part, it is electrically connected with the human intelligent street light assembly through a cable, and can supply power to the intelligent street light assembly. The power supply part has: a plurality of first photovoltaic solar panels, a plurality of second photovoltaic solar panels and a plurality of wind power generators; A photovoltaic solar panel can convert solar energy into electrical energy to supply power to smart street light components, a second photovoltaic solar panel can convert solar energy into electrical energy to supply power to smart street light components, and a wind turbine can convert wind energy into electrical energy to supply power to smart street light components , so as to convert green and clean energy into electrical energy, which is green and environmentally friendly, and is conducive to sustainable development.

Due to the special database, once the artificial intelligence automatic update information processing center generates the brightness control command, the artificial intelligence automatic update information processing center will take the brightness control command as the historical brightness control command and the brightness signal when the historical brightness control command is sent as the initial brightness signal And the brightness signal after sending the historical brightness control command after a predetermined time is sent to the special database as the brightness signal after the command is implemented, the special database receives the historical brightness control command, the initial brightness signal and the brightness signal after the command is implemented, and the historical brightness control command, initial The brightness signal and the brightness signal after the instruction is implemented are stored correspondingly. Once the artificial intelligence automatic update information processing center receives the brightness signal of each residential area, the artificial intelligence automatic update information processing center will control the historical brightness corresponding to the brightness signal in the special database. The instruction is used as a new initial control instruction, so the artificial intelligence automatic update information processing center of the present invention can continuously perform self-update learning and self-adjustment, so that the intelligent control of brightness is more accurate and fast.

Description of drawings

1 is a schematic structural diagram of a residential area in an embodiment of the present invention;

2 is a schematic structural diagram of an intelligent energy-saving system for a green house in an embodiment of the present invention;

3 is a schematic diagram of a process of data fusion in an embodiment of the present invention;

4 is a schematic structural diagram of a smart street light assembly in an embodiment of the present invention;

5 is a schematic diagram of power transfer in an embodiment of the present invention;

6 is a schematic diagram of information transmission in an embodiment of the present invention;

Fig. 7 is a BP neural network model diagram;

Figure 8 is a flow chart of the steps of the BP algorithm; and

FIG. 9 is an action flow chart of a brightness control action of an intelligent energy-saving system for a green house in an embodiment of the present invention.

Detailed ways

In order to make the technical means, creative features, achieved goals and effects of the present invention easy to understand, the following describes the intelligent energy-saving system for green houses of the present invention in detail with reference to the accompanying drawings.

FIG. 1 is a schematic structural diagram of a residential area in an embodiment of the present invention.

As shown in FIG. 1 , the residential area 200 in this embodiment is a medium-sized residential area, and the residential area is divided into a plurality of residential areas 210 according to the requirements of lighting brightness and lighting time (the residential areas 210 may be, for example, a residential cultural center, residential building dense area, etc.), each residential area has a plurality of residential buildings 211 .

FIG. 2 is a schematic structural diagram of an intelligent energy-saving system for a green house in an embodiment of the present invention.

As shown in FIG. 2 , the intelligent energy-saving system 100 for a green house in this embodiment is used for intelligently controlling the outdoor brightness of a plurality of residential areas 210 in a residential area 200 , and includes a meteorological data acquisition unit (not shown in the figure), a plurality of A brightness detection unit (not shown in the figure), a plurality of smart street lamp assemblies 10 , a power supply unit 20 , an artificial intelligence automatic update information processing center 30 and a dedicated database 40 .

The meteorological data acquisition part is connected to the meteorological bureau 300 in communication, and is used to obtain the meteorological data including sunrise and sunset time, sky brightness, humidity and brightness of the residential quarters 200 detected by the meteorological bureau 300 in real time, and send the meteorological data to the artificial intelligence. The information processing center 30 is automatically updated.

A plurality of brightness detection units are respectively arranged in a plurality of residential areas 210, and are used to detect the brightness in the plurality of residential areas 210 in real time to generate a plurality of brightness signals, and send the corresponding brightness signals of each residential area 210 to the artificial intelligence automatic. The information processing center 30 is updated. The brightness detection unit includes an infrared brightness monitoring camera installed on the light pole 12 to be described later, and a brightness sensor installed on the ground of the residential area 210 .

FIG. 3 is a schematic diagram of a process of data fusion in an embodiment of the present invention.

As shown in Figure 3, taking humidity, brightness, and brightness as examples, most of these parameters are non-electrical signals with different characteristics, so firstly, they need to be converted into electrical signals, and after A/D conversion, they are converted into computer-friendly signals. Digital signal. Due to the influence of the environment or human factors, some interference signals and noise signals will be generated. Therefore, data preprocessing should be performed on the converted digital signals to filter out the interference information in the acquisition process; the processed useful signals are extracted by feature extraction. , Algorithm fusion to obtain the output result after the fusion of multiple sensor data. The main advantage of this fusion method is that it can provide subtle information that other fusion layers cannot provide. Because there is no information loss, it has high fusion performance. It is usually used in: multi-source image composite, image analysis and understanding, and multiple observations. Synthesis of source data.

FIG. 4 is a schematic structural diagram of a smart street light assembly in an embodiment of the present invention.

As shown in FIG. 4 , a plurality of smart street light assemblies 10 are respectively disposed in a plurality of residential areas, respectively, for lighting the plurality of residential areas 210, and have a base 11, a light pole 12, an energy-saving LED light group 13, and artificial Smart chip 14 .

The base 11 is embedded in the ground of the residential area for fixed support.

The light pole 12 is fixedly arranged on the base 11 .

The energy-saving LED lamp group 13 is fixedly arranged on the light pole 12 for lighting, and the energy-saving LED lamp group 13 has less power consumption.

The artificial intelligence chip 14 is fixedly arranged in the base 11 and is connected in communication with the artificial intelligence automatic update information processing center 30 for receiving the brightness control instruction of the artificial intelligence automatic update information processing center 30 and controlling the energy-saving LED lamp group according to the brightness control instruction The lighting brightness of the energy-saving LED lamp group 13 is further fed back to the artificial intelligence processing center 40 .

FIG. 5 is a schematic diagram of power transfer in an embodiment of the present invention.

As shown in FIG. 5 , the power supply unit 20 is electrically connected to the smart street light assembly and the household electricity of the residential building 211 through the cable 50 for supplying power to the smart street light assembly. The power supply unit 20 has a plurality of first photovoltaic solar panels 21 , a plurality of second photovoltaic solar panels 22 , a plurality of wind power generators 23 , and a power acquisition unit (not shown in the figure).

The plurality of first photovoltaic solar panels 21 are respectively disposed on the tops of the plurality of residential buildings 211 for converting solar energy into electrical energy so as to supply power to the smart street light assembly 10 .

The plurality of second photovoltaic solar panels 22 are respectively disposed on the plurality of light poles 12 for converting solar energy into electrical energy so as to supply power to the smart street light assembly 10 .

A plurality of wind power generators 23 are respectively disposed on the top ends of the plurality of light poles 12, and are used for converting wind energy into electrical energy to supply power to the smart street light assembly. The artificial intelligence chip 14 feeds back the lighting brightness of the energy-saving LED light group 13 to the artificial intelligence automatic update information processing center 30, and also feeds back the production capacity of the second photovoltaic solar panel 22 on the corresponding light pole 12 and the wind turbine 23. The information processing center 30 is automatically updated to the artificial intelligence.

The electric power acquisition unit is electrically connected to the municipal power grid 400 and each smart street light assembly through the cable 50, respectively, and is used to obtain power from the municipal power grid 400 when the first photovoltaic solar panel 21, the second photovoltaic solar panel 22 and the wind generator 23 cannot obtain energy. . Of course, when the energy obtained by the first photovoltaic solar panel 21 , the second photovoltaic solar panel 22 and the wind generator 23 is relatively abundant, the converted electricity can also be delivered to the household electricity of each residential building. This not only realizes the self-sufficiency of electric energy, but also can be used for household electricity when the electric energy is abundant.

FIG. 6 is a schematic diagram of information transfer in an embodiment of the present invention.

As shown in FIG. 6 , the artificial intelligence automatic update information processing center 30 is composed of a computer with artificial intelligence algorithm, and is the central information processing part of the green house intelligent energy-saving system 100 of this embodiment, which can be installed in the computer room of the residential area 200. computer or any other computer that can be controlled remotely. The artificial intelligence automatic update information processing center 30 is respectively connected to the weather data acquisition unit, the brightness detection unit, the smart street light assembly 10, the power supply unit 20 and the dedicated database 40 through the cable 50, so as to be able to process data from the weather data acquisition unit and the brightness detection unit. , the data information of the smart street light assembly 10 and the power supply unit 20 . When it is started for the first time, the artificial intelligence automatic update information processing center 30 receives the meteorological data from the meteorological data acquisition part and the brightness signal from the brightness detection part, and generates a set control command algorithm according to the meteorological data, the brightness signal and the initial control command. brightness control instruction, and further send the brightness control instruction to the intelligent street light assembly 10 in the corresponding residential area 210 to control the lighting brightness of the intelligent street light assembly 10, and then realize the intelligent brightness control based on the meteorological data for each residential area 210, Avoid too high or too low brightness, and achieve the purpose of intelligent regulation and energy saving. Sensors 1 . . . sensors n in the figure represent a weather data acquisition unit and a plurality of brightness detection units, respectively.

The set control command algorithm is an error back propagation algorithm.

Fig. 7 is a diagram of a BP neural network model, and Fig. 8 is a flow chart of the steps of the BP algorithm.

As shown in Figure 7 and Figure 8, the information flow direction of forward propagation in this algorithm is input layer→hidden layer→output layer, and its mathematical model is:

Among them, Wi and b are its weight and bias parameters, and f(W, b; x): R→R is called the excitation function. In practical applications, functions such as sigmoid, tanh, ReLU or their variants can be selected, hW, b(x) is the network output value.

The direction of back propagation is: output layer→hidden layer, and its mathematical model is:

Among them, e is the cost function, which can be obtained by the least square method; y is the expected value; λ>0 is a constant; λ/2W ² is the penalty term.

The specific learning algorithm of neural network adopts supervised learning, also known as supervised learning. In the process of learning and training, the network should be continuously provided with an input mode and a mode that expects the correct output of the network, that is, the expected output. When the actual output of the network does not match the expected output, the network weights are adjusted according to the direction and size of the two error signals, so that the actual output of the network is getting closer and closer to the expected output of the network.

The steps are summarized as follows:

① Provide the network with a training mode pair x ^k -p ^k and initial weights

② Calculate the actual output y ^k of the network

③ Calculate the error between the actual output and the expected output, e ^k =y ^k -p ^k

④ Change the connection weight according to the error, and repeat the above steps for each training mode until the total error is less than the target error requirement.

Among them, x ^k represents the k-th input value, p ^k represents the k-th preset value, and y ^k represents the k-th hidden layer output value.

In this embodiment, the error back propagation algorithm includes the following steps:

In step 1, the weather data and the brightness signal of each residential area 210 received by the artificial intelligence automatic update information processing center 30 are used as the input value _xi and the corresponding weight W _i of the input value _xi is set,

Step 2 _: Substitute the input value x _i and the corresponding weight Wi into the following formula (1) to calculate the intermediate control instruction y,

Step 3: Calculate the error e between the intermediate control command y and the initial control command P, as shown in the following formula (2)

e=y-p(2)

Step 3, adjust the weight Wi according to the error _e ,

Step 4, determine whether the error e is within a predetermined range, when it is determined to be no, go to step 2, when it is determined to be yes, output the intermediate control command y as the brightness control command of the corresponding residential area,

in, is the excitation function, and n is the total number of input values.

After the artificial intelligence automatic update information processing center 30 generates the brightness control command, the brightness control command is regarded as the historical brightness control command, the brightness signal when the historical brightness control command is sent is used as the initial brightness signal, and the historical brightness control command is sent after a predetermined time. The luminance signal is sent to the dedicated database 40 as the luminance signal after the command is executed.

The dedicated database 40 can be a database integrated with the artificial intelligence automatic update information processing center 30, or can be a cloud that can store data. The dedicated database 40 is used for receiving and correspondingly storing the historical brightness control instruction, the initial brightness signal and the brightness signal after the instruction is implemented, which are sent by the artificial intelligence automatic update information processing center 30 . Once the artificial intelligence automatic update information processing center receives the brightness signal of each residential area, the artificial intelligence automatic update information processing center will take the historical brightness control instruction corresponding to the brightness signal in the special database as a new initial control instruction, so as to adjust the historical brightness. The control instructions are constantly revised, and the artificial intelligence technology is used to continuously learn, so that the artificial intelligence automatically updates the information processing center 30 to become smarter and smarter, so as to control the lighting distribution of the entire residential area 200 more and more accurately.

FIG. 5 is an action flow chart of a brightness control action of the intelligent energy-saving system for a green house in an embodiment of the present invention.

As shown in FIG. 5 , in the first embodiment, the action flow S1 of the brightness control action of the green house intelligent energy-saving system 100 includes the following steps:

In step S1-1, the meteorological data acquisition unit acquires the meteorological data of the residential area 200 detected by the meteorological bureau 300, and sends the meteorological data to the artificial intelligence automatic update information processing center 30, and then proceeds to step S1-2.

In step S1-2, a plurality of brightness detection units detect the brightness in a plurality of residential areas 210 in real time to generate a plurality of brightness signals, and respectively send the corresponding brightness signals to the artificial intelligence automatic update information processing center 30, and then enter step S1- 3.

Step S1-3, the artificial intelligence automatic update information processing center 30 receives the meteorological data and the brightness signal of each area and obtains the historical control instruction corresponding to the similar brightness signal of the corresponding residential area 210 in the special database 40 based on the meteorological data and the brightness signal. And take the historical control instruction as the current initial control instruction, and then go to step S1-4.

Step S1-4, the artificial intelligence automatic update information processing center 30 generates a brightness control command through the set control command algorithm according to the weather data, the brightness signal and the initial control command, and further sends the brightness control command to the corresponding residential area 210. the smart street light assembly 10, and then enter step S1-5.

In step S1-5, the artificial intelligence automatic update information processing center 30 uses the control command as the historical control command, the brightness signal when sending the historical control command as the initial brightness signal, and the brightness signal after sending the historical control command after a predetermined time as the command implementation. The luminance signal is sent to the dedicated database 40, and the process proceeds to step S1-6.

In step S1-6, the dedicated database 40 accepts the historical control command, the initial brightness signal and the brightness signal after the command is implemented, and stores them accordingly, and then enters the end state.

Example function and effect

According to the intelligent energy-saving system for green houses involved in this embodiment, since it has a meteorological data acquisition unit, the meteorological data including sunrise and sunset time, sky brightness and brightness of the residential quarter detected by the meteorological bureau can be acquired in real time. The detection unit can detect the brightness in multiple residential areas in real time to generate multiple brightness signals; due to the multiple intelligent street lamp components, it can illuminate multiple residential areas respectively; due to the artificial intelligence automatic update information processing center, It is respectively connected with the meteorological data acquisition part, the brightness detection part and the intelligent street light assembly, and can receive the meteorological data and the brightness signal and generate the brightness control command through the set control command algorithm according to the meteorological data, the brightness signal and the initial control command. The brightness control command is sent to the smart street light components in the corresponding residential area to control the lighting brightness of the smart street light components, thereby realizing intelligent brightness control based on meteorological data for each residential area, so that the lighting brightness of the residential area can be adjusted according to actual needs. , reducing power consumption and creating a comfortable and green brightness environment for residential quarters.

Because it has a power supply part, it is electrically connected with the human intelligent street light assembly through a cable, and can supply power to the intelligent street light assembly. The power supply part has: a plurality of first photovoltaic solar panels, a plurality of second photovoltaic solar panels and a plurality of wind power generators; A photovoltaic solar panel can convert solar energy into electrical energy to supply power to smart street light components, a second photovoltaic solar panel can convert solar energy into electrical energy to supply power to smart street light components, and a wind turbine can convert wind energy into electrical energy to supply power to smart street light components , so as to convert green and clean energy into electrical energy, which is green and environmentally friendly, and is conducive to sustainable development.

Since the brightness detection part includes an infrared brightness monitoring camera arranged on the light pole and a brightness sensor arranged on the ground of the residential area, the installation positions of the infrared brightness monitoring camera and the brightness sensor are complementary, so that a comprehensive brightness detection can be performed on the residential area. Thus, the brightness regulation in this embodiment is more precise.

Due to the special database, once the artificial intelligence automatic update information processing center generates the brightness control command, the artificial intelligence automatic update information processing center will take the brightness control command as the historical brightness control command and the brightness signal when the historical brightness control command is sent as the initial brightness signal And the brightness signal after sending the historical brightness control command after a predetermined time is sent to the special database as the brightness signal after the command is implemented, the special database receives the historical brightness control command, the initial brightness signal and the brightness signal after the command is implemented, and the historical brightness control command, initial The brightness signal and the brightness signal after the instruction is implemented are stored correspondingly. Once the artificial intelligence automatic update information processing center receives the brightness signal of each residential area, the artificial intelligence automatic update information processing center will control the historical brightness corresponding to the brightness signal in the special database. The instruction is used as a new initial control instruction, so the artificial intelligence automatic update information processing center of this embodiment can continuously perform self-update learning and self-adjustment, so that the intelligent control of brightness is more accurate and fast.

The preferred embodiments of the present invention have been described in detail above. It should be understood that many modifications and changes can be made according to the concept of the present invention by those skilled in the art without creative efforts. Therefore, all technical solutions that can be obtained by those skilled in the art through logical analysis, reasoning or limited experiments on the basis of the prior art according to the concept of the present invention shall fall within the protection scope determined by the claims.

Claims (7)

1. an intelligent energy-saving system for green houses, for carrying out intelligent control of outdoor brightness to a plurality of residential areas containing a plurality of residential buildings in residential quarters, it is characterized in that, comprising: Meteorological data acquisition unit, used for real-time acquisition of meteorological data including sunrise and sunset time, sky brightness and temperature of the residential area detected by the Meteorological Bureau; a plurality of brightness detection units, respectively disposed in a plurality of the residential areas, and configured to detect the brightness in the plurality of the residential areas in real time to generate a plurality of brightness signals; a plurality of smart street light assemblies, respectively disposed in a plurality of the residential areas, respectively, for lighting the plurality of the residential areas; and The artificial intelligence automatic update information processing center is respectively connected with the meteorological data acquisition part, the brightness detection part and the intelligent street lamp assembly, Wherein, the meteorological data acquisition unit sends the meteorological data to the artificial intelligence automatic update information processing center, A plurality of the brightness detection units respectively send the brightness signal corresponding to each of the residential areas to the artificial intelligence automatic update information processing center, The artificial intelligence automatic update information processing center receives the meteorological data and the brightness signal and generates a brightness control command through the set control command algorithm according to the meteorological data, the brightness signal and the initial control command, and further the brightness The control instruction is sent to the smart street light assembly in the corresponding residential area to control the illumination brightness of the smart street light assembly, thereby realizing intelligent brightness control based on the weather data for each of the residential areas. 2. The intelligent energy-saving system for green houses according to claim 1, characterized in that: Wherein, the smart street light components include: a pedestal, embedded in the ground of said residential area, a light pole, fixed on the base, An energy-saving LED lamp group, fixedly arranged on the lamp pole, for lighting, and An artificial intelligence chip, fixedly arranged in the base and communicated with the artificial intelligence automatic update information processing center, for receiving the brightness control instruction of the artificial intelligence automatic update information processing center and according to the brightness control instruction The lighting brightness of the energy-saving LED lamp group is controlled. 3. The intelligent energy-saving system for green houses according to claim 2, characterized in that, further comprising: a power supply part, which is electrically connected to the human intelligent street lamp assembly through a cable, and is used for supplying power to the intelligent street lamp assembly, Wherein, the power supply part has: a plurality of first photovoltaic solar panels, respectively disposed on the tops of the plurality of residential buildings, for converting solar energy into electrical energy so as to supply power to the smart street light components, A plurality of second photovoltaic solar panels, respectively disposed on the plurality of the lamp poles, are used to convert solar energy into electrical energy so as to supply power to the smart street lamp assembly, a plurality of wind generators, respectively arranged on the tops of the plurality of the light poles, for converting wind energy into electrical energy to supply power to the smart street light assembly, The power acquisition unit is electrically connected to the municipal power grid and each of the smart street light assemblies through cables. 4. The intelligent energy-saving system for green houses according to claim 2, characterized in that: Wherein, the brightness detection part includes an infrared brightness monitoring camera arranged on the light pole and a brightness sensor arranged on the ground of the residential area. 5. The intelligent energy-saving system for green houses according to claim 1, characterized in that: Wherein, the set control instruction algorithm is an error back-propagation algorithm, and the algorithm includes the following steps: Step 1, take the weather data and the brightness signal of each residential area received by the artificial intelligence automatic update information processing center as the input value _xi and set the weight w _i corresponding to the input value _xi . , Step 2: Substitute the input value x _i and the corresponding weight w _i into the following formula (1) to calculate the intermediate control instruction y, Step 3: Calculate the error e between the intermediate control command y and the initial control command P, see the following formula (2) e=y-p(2) Step 3: Adjust the weight _wi according to the error e, Step 4, determine whether the error e is within a predetermined range, when it is determined to be no, go to the second step, and when it is determined to be yes, use the intermediate control instruction y as the brightness of the corresponding residential area. control command output, said is the excitation function, and the n is the total number of the input values. 6. The intelligent energy-saving system for green houses according to claim 1, further comprising: dedicated database, Wherein, once the artificial intelligence automatic update information processing center generates the brightness control instruction, the artificial intelligence automatic update information processing center takes the brightness control instruction as the historical brightness control instruction, and the The brightness signal is used as the initial brightness signal and the brightness signal after sending the historical brightness control command after a predetermined time is sent to the dedicated database as the brightness signal after the command is implemented, The dedicated database receives the historical brightness control command, the initial brightness signal, and the brightness signal after the command is implemented, and corresponds to the historical brightness control command, the initial brightness signal, and the brightness signal after the command is implemented. storage, Once the artificial intelligence automatic update information processing center receives the brightness signal of each of the residential areas, the artificial intelligence automatic update information processing center will control the historical brightness corresponding to the brightness signal in the special database The instruction is used as a new initial control instruction, so as to realize the self-learning, self-adjustment and self-renewal of the artificial intelligence automatic update information processing center. 7. The intelligent energy-saving system for green houses according to claim 1, characterized in that: Wherein, the artificial intelligence automatic update information processing center is composed of a computer with artificial intelligence algorithm.