CN111045468A - Self-induction low-carbon window system for smart home - Google Patents
Self-induction low-carbon window system for smart home Download PDFInfo
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- CN111045468A CN111045468A CN201911343634.6A CN201911343634A CN111045468A CN 111045468 A CN111045468 A CN 111045468A CN 201911343634 A CN201911343634 A CN 201911343634A CN 111045468 A CN111045468 A CN 111045468A
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Abstract
The invention relates to a smart home-oriented self-induction low-carbon window system, which is based on raspberry design development and comprises the following components: the sensor module is used for acquiring the temperature, humidity and pm2.5 air quality environment numerical values of the indoor environment; the crawler module is used for acquiring the temperature and humidity, PM2.5 concentration and wind power level which are issued by each monitoring station in the outdoor environment every hour; the database table module is used for storing indoor and outdoor environment information and the opening angle of a window; and the motor control module is used for controlling the opening and closing of the window. By adopting the technical scheme of the invention, the functions are perfect, the expansibility is strong, and the cost is low; meanwhile, the user can acquire indoor and outdoor environmental conditions.
Description
Technical Field
The invention belongs to the technical field of intelligent equipment, and particularly relates to a self-induction low-carbon window system for intelligent home.
Background
Most of the existing intelligent window designs are designed in a mode based on a single chip microcomputer, such as the design of an intelligent window remote control system based on the single chip microcomputer (Yang Yong 'town construction' 2019, 7 th year), the design of an intelligent shutter (Wuyufei Wang Yilin Lnli's technical View' 2019, 25 th year) and the like. At present, the cost is increased based on the design of a single chip microcomputer in the prior art, the function is single, and meanwhile, a user cannot acquire indoor and outdoor environmental conditions.
Disclosure of Invention
(1) The technical problem that the invention needs and can solve is solved.
The invention aims to provide a self-induction low-carbon window system for smart home, which can enable a user to monitor indoor and outdoor environments and complete control (user self-control or system self-induction operation) of a switch window.
(2) The specific technical scheme of the invention
In order to achieve the purpose, the invention adopts the following technical scheme:
the utility model provides a self-induction low carbon window system towards intelligent house, is based on raspberry group's design development, includes:
the sensor module is used for acquiring the temperature, humidity and pm2.5 air quality environment numerical values of the indoor environment;
the crawler module is used for acquiring the temperature and humidity, PM2.5 concentration and wind power level which are issued by each monitoring station in the outdoor environment every hour;
the database table module is used for storing indoor and outdoor environment information and the opening angle of a window;
and the motor control module is used for controlling the opening and closing of the window.
Preferably, the user can select to control the opening and closing window by himself or select a self-induction mode; the operations to be eventually reached for both modes are windowing 401 and closing 403; wherein the content of the first and second substances,
under the user self-control mode, a user directly sends out a corresponding instruction;
in the self-induction mode, when the environmental state is the state 402, that is, the PM2.5 reading is greater than 70 and the outdoor PM2.5 is less than 115, if the window is not opened at this time, the system forcibly completes the window opening operation 401; when the environmental state is the state 404, the corresponding operation priority in the state is higher than that in the state 402, namely the outdoor wind level reaches 5, and if the window is opened at the moment, the window is automatically closed; when the environmental state is 406, namely the outdoor PM2.5 is larger than 115, if the window is opened, the window is automatically closed; the time for monitoring the indoor environment information and the time for pre-windowing can be set through operation 405, if a state 408 occurs in the period, that is, if the current wind level is greater than 5 or the outdoor PM2.5 is greater than 115, the window is not opened, and if the two conditions are not met, the system forces the window closing operation 403.
Preferably, the sensors are temperature and humidity sensors, GP2Y1014AU dust sensors and DHT11 temperature and humidity sensors, and the sensors are connected with a GPIO interface of the raspberry pi.
Preferably, the motor control module adopts a stepping motor 28BYJ48 and a steering engine driving chip ULN2003, the output end of the ULN2003 is connected with an interface of the stepping motor, except that VCC and GND at the input end of the ULN2003 are directly connected with 5v and ground on the raspberry group GPIO, the connection of other interfaces is as follows: the IN1 is connected with the GPIO04, the IN2 is connected with the GPIO17, the IN3 is connected with the GPIO23, and the IN4 is connected with the GPIO24 to enable the stepping motor to rotate IN any direction at different speeds by controlling the high and low levels of the 4 interfaces through programs.
The invention adopts the development based on the raspberry pie, and the raspberry pie is provided with a complete system, so that the functions are perfect, the expansibility is strong, and the cost is low; meanwhile, data issued by each monitoring station in Beijing city is acquired in real time through a crawler technology, so that a user can acquire indoor and outdoor environmental conditions. The invention also discloses a method for constructing a web end system by using a lightweight development frame flash, which is a great innovation point of the method and is convenient for users to visually obtain environment monitoring data.
Drawings
FIG. 1 shows a wiring diagram of a DHT11 with a raspberry pie, according to an embodiment of the invention;
FIG. 2 shows a wiring diagram of a GP2Y1014AU dust sensor with a raspberry pi through a PCF8591AD/DA conversion module, according to an embodiment of the invention;
FIG. 3 shows a schematic block diagram of a low carbon window system in accordance with an embodiment of the invention;
FIG. 4 shows a schematic flow diagram of two control modes according to an embodiment of the invention;
fig. 5 shows a wiring diagram of the stepper motor 28BYJ48 and the steering engine driver chip ULN2003 to the raspberry pi according to an embodiment of the present invention.
Detailed Description
In order that the above objects, features and advantages of the present invention can be more clearly understood, a more particular description of the invention will be rendered by reference to the appended drawings.
The electronic part of the invention adopts a sensor to connect with the raspberry pi GPIO interface to obtain the environmental values of temperature, humidity and pm2.5 air quality. The temperature and humidity sensor selects DHT11, the sensor is packaged by a 4-pin single-row pin, when data is acquired, a pull-up resistor (4.7K-10K) is required to be connected in series between a power supply and a data pin (an uncertain signal is clamped at a high level through a resistor, the resistor plays a role of current limiting at the same time), DHT11pin1 is connected with a raspberry group 3.3v output, pin4 is connected with a raspberry group, pin2 is a transmission pin, and the pull-up resistor is connected to 3.3v and connected to a GPIO.BCM27 number (as an interface for reading data) in parallel. FIG. 1 is a diagram of DHT11 wiring with a raspberry pie. The reading data program part uses an Adafruit library provided by DHT11 officially (the library is specially used for reading the series of sensor values through a GPIO interface), improves the reading mode by rewriting the source code, meets the requirement of a low-carbon window, and finally stores the data into the database.
The PM2.5 sensor adopts a GP2Y1014AU dust sensor, a large hole is arranged in the middle of the sensor, air can freely flow through the sensor, an infrared light emitting diode and a phototransistor are arranged at the adjacent corners in the sensor, the infrared light emitting diode directionally sends infrared rays, when particles in the air block the infrared rays, the infrared rays send diffused reflection, and the phototransistor receives the infrared rays, so the voltage of a signal output pin sends changes. This design adopts this sensor to link to each other with raspberry group GPIO, but the raspberry group does not have the AD conversion function, leads to the output port of this sensor can't read. The present design therefore uses the PCF8591AD/DA conversion module to read the output voltage Vout. FIG. 2 is a wiring diagram of GP2Y1014AU dust sensor connected with raspberry pi through PCF8591AD/DA conversion module. The hardware connection requires 1 resistor of 150 ohms, and 1 capacitor of 220 muF. A150 ohm resistor is connected between the V-LED port of the sensor and 5V, and a capacitor of 220 muF is connected between the V-LED and the LED-GND. The Vcc port is raspberry 5Vgpio, the LED is connected with GPIO21, the output port of V0 is connected with the AIN0 port of PCF8591AD/DA conversion module for reading voltage data, and the S-GND is connected with raspberry group. The address, control, and data of PCF8591 are transmitted over the I2C bus. The 12 pins are clock selection pins, the circuit of the design adopts an internal clock, the 12 pins are directly connected with GND, meanwhile, the 11 pins are suspended, and the 13 pins are analog ground AGND. Through the chip, the I2C bus port of the raspberry pi is opened to read the AIN0 data. The specific connection is GP2Y1014AU dust sensor V0 output port is connected with PCF8591 AIN0 port, PCF8591 VCC GND SDA SCL is respectively connected with each corresponding pin on raspberry group GPIO port.
The programming language of the software part is python3, and the web end is built by selecting a flash framework. As shown in fig. 3, the low carbon window system designed by the present invention may have two control modes, a user self-control mode 301 and a system self-induction mode 303, each corresponding to four modules in the backend program. The first module is a sensor data module 302, which realizes monitoring of the indoor environment; the second module is a crawler module 304, which comprises the information of the temperature and humidity, the PM2.5 concentration, the wind power level and the like which are issued by each monitoring station in Beijing every hour, so that the user can acquire the outdoor environment information; the third module is a database module 306, the database is sqlite3, and the database table contains indoor and outdoor environment information and the opening angle of a window; the fourth module is a motor control module 308, which is called to finally implement the window opening and closing operation. The front end is written by HTML, CSS and JavaScript, and the visual environment monitoring of the user at the web end is realized. As shown in fig. 4, the user can select to control the switch window by himself or select a self-induction mode. The operations to be eventually reached for both modes are windowing 401 and closing 403. And under the user self-control mode, the user directly sends out a corresponding instruction. In the self-sensing mode, when the environmental status is status 402, i.e. the PM2.5 reading is greater than 70 and the outdoor PM2.5 reading is less than 115, if the window is not opened, the system will force the window opening operation 401 to be completed. When the environmental status is status 404 (the corresponding operation priority is higher than status 402), that is, the outdoor air level reaches level 5, and the window is automatically closed if the window is opened. When the environmental status is 406, i.e. the outdoor PM2.5 is greater than 115, the window is automatically closed if the window is opened. The user may set the time to monitor the indoor environmental information (how often the sensor is allowed to acquire data) and the time to pre-window (e.g., window ventilation during 10:00-12: 00) via operation 405. If the state 408 occurs during this period, i.e. if the current wind level is greater than 5 or the outdoor PM2.5 is greater than 115, then the window is not opened, and if the two conditions are not met during this period, the system will force the window closing operation 403.
The mechanical part adopts a stepping motor 28BYJ48 and a steering engine driving chip ULN2003, the stepping motor 28BYJ48 is a four-phase eight-beat permanent magnet stepping motor, and the voltage is DC5V-DC 12V; the output end of the ULN2003 is directly connected with the interface of the stepping motor. Fig. 5 is a wiring diagram of the stepping motor 28BYJ48 and the steering engine driving chip ULN2003 and the raspberry pie. Except that VCC and GND are directly connected with 5v and ground on a raspberry group GPIO at the input end, the other interfaces are connected with IN1 to GPIO04, IN2 to GPIO17, IN3 to GPIO23, and IN4 to GPIO24, and the high and low levels of the 4 interfaces are controlled by a program to enable the stepping motor to rotate IN any direction at different speeds.
Claims (4)
1. The utility model provides a self-induction low carbon window system towards intelligent house which characterized in that, based on raspberry group design development, includes:
the sensor module is used for acquiring the temperature, humidity and pm2.5 air quality environment numerical values of the indoor environment;
the crawler module is used for acquiring the temperature and humidity, PM2.5 concentration and wind power level which are issued by each monitoring station in the outdoor environment every hour;
the database table module is used for storing indoor and outdoor environment information and the opening angle of a window;
and the motor control module is used for controlling the opening and closing of the window.
2. The smart home-oriented self-induction low-carbon window system according to claim 1, wherein a user can select to control a switching window by himself or select a self-induction mode; the operations to be eventually reached for both modes are windowing 401 and closing 403; wherein the content of the first and second substances,
under the user self-control mode, a user directly sends out a corresponding instruction;
in the self-induction mode, when the environmental state is the state 402, that is, the PM2.5 reading is greater than 70 and the outdoor PM2.5 is less than 115, if the window is not opened at this time, the system forcibly completes the window opening operation 401; when the environmental state is the state 404, the corresponding operation priority in the state is higher than that in the state 402, namely the outdoor wind level reaches 5, and if the window is opened at the moment, the window is automatically closed; when the environmental state is 406, namely the outdoor PM2.5 is larger than 115, if the window is opened, the window is automatically closed; the time for monitoring the indoor environment information and the time for pre-windowing can be set through operation 405, if a state 408 occurs in the period, that is, if the current wind level is greater than 5 or the outdoor PM2.5 is greater than 115, the window is not opened, and if the two conditions are not met, the system forces the window closing operation 403.
3. The self-induction low-carbon window system for smart homes according to claim 2, wherein the sensors are temperature and humidity sensors, GP2Y1014AU dust sensors, DHT11 temperature and humidity sensors, and the sensors are connected with a raspberry GPIO interface.
4. The self-induction low-carbon window system for smart homes according to claim 3, wherein the motor control module adopts a stepping motor 28BYJ48 and a steering engine driving chip ULN2003, the output end of the ULN2003 is connected with an interface of the stepping motor, the input end of the ULN2003 is directly connected with 5v and ground on a raspberry group GPIO except VCC and GND, and other interfaces are connected as follows: the IN1 is connected with the GPIO04, the IN2 is connected with the GPIO17, the IN3 is connected with the GPIO23, and the IN4 is connected with the GPIO24 to enable the stepping motor to rotate IN any direction at different speeds by controlling the high and low levels of the 4 interfaces through programs.
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| CN201911343634.6A CN111045468A (en) | 2019-12-24 | 2019-12-24 | Self-induction low-carbon window system for smart home |
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| CN201911343634.6A CN111045468A (en) | 2019-12-24 | 2019-12-24 | Self-induction low-carbon window system for smart home |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN110320812A (en) * | 2019-07-29 | 2019-10-11 | 青岛海尔科技有限公司 | Smart home operating system and control method based on smart home operating system |
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| CN105299833A (en) * | 2015-11-02 | 2016-02-03 | 苏州美达瑞电子有限公司 | Household air quality monitoring system |
| CN106014078A (en) * | 2016-07-12 | 2016-10-12 | 东华理工大学 | Intelligent protective window |
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2019
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Patent Citations (5)
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| CN204667140U (en) * | 2015-04-10 | 2015-09-23 | 南昌航空大学 | A kind of intelligent home control device |
| CN105299833A (en) * | 2015-11-02 | 2016-02-03 | 苏州美达瑞电子有限公司 | Household air quality monitoring system |
| CN106014078A (en) * | 2016-07-12 | 2016-10-12 | 东华理工大学 | Intelligent protective window |
| CN206075027U (en) * | 2016-08-19 | 2017-04-05 | 陈必东 | Based on the intelligent domestic system that Fructus Rubi is sent |
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| CN110320812A (en) * | 2019-07-29 | 2019-10-11 | 青岛海尔科技有限公司 | Smart home operating system and control method based on smart home operating system |
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Application publication date: 20200421 |
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