CN106968979A - A kind of fan control system - Google Patents

Abstract

The invention belongs to the technical field of fan control, and in particular relates to a fan control system, which is characterized in that it includes a wristband for detecting human body data and a receiving terminal for receiving the data of the wristband and performing data processing, and the receiving terminal will The result of data processing is sent to the microprocessor for controlling the fan to control the working state of the fan; the wristband is provided with a temperature sensor for detecting the radiation temperature of the human body surface and a pulse detector for detecting the heart rate of the human body. The accelerometer and gyroscope used to collect the swing information data of the arm and wrist, and the control buttons; the receiving terminal is connected with the environmental parameter acquisition module, and is equipped with the human arm wrist for identifying and processing the data sent by the accelerometer and gyroscope. Gesture recognition module for swing information data. The system uses two control modes to achieve all-weather intelligent control, which not only has a large indoor control range, but also reduces the dependence on the environment and is more in line with the thermal comfort requirements of the human body.

Description

A fan control system

technical field

The invention belongs to the technical field of fan control, and in particular relates to a fan control system.

Background technique

Traditional fans have a single function, and it is difficult to realize remote control or automatic control, which is not convenient enough. Furthermore, it is also easy for people to forget to adjust the wind power or to turn off the fan after going out, resulting in the problem of wasting electricity.

The existing traditional smart fan has achieved remote control or automatic control to a certain extent, but its smart temperature control is based on the ambient temperature. There is a certain gap between the ambient temperature and the human body's physical sensation. Comfort, the adjustment achieved according to the ambient temperature does not necessarily meet the requirements of the thermal comfort of the human body at that time.

In the new generation of smart fans, there is no practical product that has been launched to apply the fan control method based on the thermal comfort of the indoor environment and the thermal comfort equation of the human body. Smart control based on sleep conditions alone cannot meet daily all-weather needs. On the other hand, the recognition of user gestures through the sensor of the fan body is based on computer vision. However, the amount of gesture signal data obtained by this method is large, the recognition algorithm is complicated, and it is highly dependent on the external environment such as background and light. , is not very suitable for dynamic real-time recognition, and has certain restrictions on the sensing distance and direction. Furthermore, a single control mode sometimes cannot fully meet the needs of users.

In terms of wearable wristbands, existing wristbands have limited functions, and the linkage between wristbands and smart homes mainly focuses on the use of human sleep conditions collected by wristbands to automatically control smart homes. The accelerometer and gyroscope embedded in the wristband are mostly used to count steps, identify exercise status and sleep status, and have not been used more effectively in the field of smart home.

Contents of the invention

Aiming at the deficiencies of the prior art, the invention provides a fan control system. The system adopts two control modes, which solves the problem that a single control mode cannot fully meet the needs of users, and realizes all-weather intelligent control. Compared with the gesture recognition based on computer vision of the fan body sensor, the indoor controllable range of this control system is also increased, and the dependence on the environment such as light is also reduced. Furthermore, compared with traditional smart fans that only control the wind force according to the ambient temperature, this control system is more in line with the thermal comfort requirements of the human body.

In order to achieve the above object, a fan control system of the present invention includes a wristband for detecting human body data and a receiving terminal for receiving the data of the wristband and performing data processing, and the receiving terminal sends the result of data processing to the user The microprocessor used to control the fan is used to control the working state of the fan; the wristband is provided with a temperature sensor for detecting the radiation temperature of the human body surface, a pulse detector for detecting the human heart rate, and for collecting arm and wrist swing information data accelerometer and gyroscope, and control buttons for switching the control mode of the bracelet; the receiving terminal is connected with an environmental parameter acquisition module for collecting surrounding environmental parameters, and the receiving terminal is equipped with a device for identifying and processing acceleration Gesture recognition module of the human arm and wrist swing information data sent by the meter and gyroscope.

Preferably, the surrounding environment parameters collected by the environment parameter collection module include air temperature parameters, air relative humidity parameters and air velocity parameters.

Preferably, the surrounding environmental parameters collected by the environmental parameter collection module include air temperature parameters, air relative humidity parameters and air velocity parameters; Combining with the surrounding environment parameters and obtaining the PMV value through the fuzzy neural network algorithm, the receiving terminal sends the result of data processing to the microprocessor to control the working state of the fan.

In terms of thermal comfort evaluation, the PMV index proposed by Professor Fanger is the most representative. This index comprehensively considers various factors that affect the thermal comfort of the human body, and represents most people's evaluation of thermal comfort. The PMV index can be expressed as a function of four environmental parameters and two human body parameters. Specifically, it includes air temperature parameters, air relative humidity parameters, air velocity parameters, human body surface radiation temperature, human body clothing thermal resistance, and human body metabolic rate, that is, heart rate.

The PMV calculation formula is as follows:

When the PMV value = 3, the thermal comfort feeling of the human body corresponds to heat; when the PMV value = 2, the thermal comfort feeling of the human body corresponds to warm; when the PMV value = 1, the thermal comfort feeling of the human body corresponds to slightly warm; when the PMV value = 0, the thermal comfort of the human body corresponds to moderate; when the PMV value = -1, the thermal comfort of the human body corresponds to slightly cool; when the PMV value = -2, the thermal comfort of the human body corresponds to cool; when the PMV value = -3 When , the thermal comfort of the human body corresponds to cold.

The existing evaluation system of indoor environment comfort generally obtains the comfort index value through cumbersome iterative calculations, but since the formula itself is a complex nonlinear function, the calculation is troublesome. Therefore, this system uses fuzzy neural network to establish a simulation evaluation model for four thermal environment variables and two human factors, which avoids tedious iterative calculation of formulas and realizes the intelligent detection of PMV thermal environment comfort index.

Preferably, the receiving terminal recognizes the human arm and wrist swing information data sent by the accelerometer and gyroscope through the gesture recognition module, and then sends a corresponding control signal to the microprocessor to control the operation of the fan.

Preferably, the data detected by the temperature sensor and the pulse detector are not sent to the receiving terminal at the same time as the data collected by the accelerometer and the gyroscope, and the two methods are switched through the control buttons on the wristband.

Preferably, the bracelet is also provided with an LED display module for displaying the current working status of the bracelet.

Preferably, the wristband is connected to the receiving terminal through Bluetooth communication, and the Bluetooth is Bluetooth Low Energy.

When the control mode is to control the fan through the physiological parameters of the human body and the surrounding environment parameters, the receiving terminal receives the human body surface radiation temperature and human heart rate data sent by the bracelet, then combines the surrounding environment parameters and obtains the PMV value through the fuzzy neural network algorithm, and then The receiving terminal sends the result of data processing to the microprocessor to control the wind force of the fan.

When the control button is switched to the mode of controlling the fan through the swing of the arm and wrist, the receiving terminal recognizes the gesture information through the gesture recognition module used to identify and process the swing information data of the human arm and wrist sent by the accelerometer and gyroscope, and sends The corresponding control signal is sent to the microcontroller to realize indoor wireless control of the fan.

The present invention adds and collects feedback links such as human body surface temperature and indoor temperature and humidity, and applies the PMV thermal comfort equation to the wristband to intelligently control the fan wind force to form a closed-loop temperature control, so that the human body is always automatically in the most comfortable indoor air conditioner The state of the environment without human manual regulation. And the system uses the smart bracelet acceleration sensor to recognize the user's gestures for remote control, which is relatively easy to operate and less affected by the environment.

The system adopts two control modes, which solves the problem that a single control mode cannot fully meet the needs of users, and realizes all-weather intelligent control. Compared with the gesture recognition based on computer vision of the fan body sensor, the indoor controllable range of this control system is also increased, and the dependence on the environment such as light is also reduced. Furthermore, compared with traditional smart fans that only control the wind force according to the ambient temperature, this control system is more in line with the thermal comfort requirements of the human body.

Description of drawings

Fig. 1 is the structural block diagram of this system;

Figure 2 is the main hardware schematic diagram of the wristband.

Among them, 1 is a bracelet, 11 is a temperature sensor, 12 is a pulse detector, 13 is a control button, 141 is an accelerometer, 142 is a gyroscope, 15 is an LED display module, 2 is a receiving terminal, and 21 is an environmental parameter acquisition module , 22 is a gesture recognition module, and 3 is a microprocessor.

detailed description

The present invention will be further described in detail below in conjunction with the embodiments and the accompanying drawings, but the embodiments of the present invention are not limited thereto.

Referring to Figures 1-2, a fan control system according to an embodiment of the present invention includes a wristband 1 for detecting human body data and a receiving terminal 2 for receiving data from the wristband 1 and performing data processing, and the receiving terminal 2 will The result of the data processing is sent to the microprocessor 3 for controlling the fan to control the working state of the fan; the wristband 1 is provided with a temperature sensor 11 for detecting the radiation temperature of the human body surface, for detecting the pulse of the human heart rate Device 12, an accelerometer 141 and a gyroscope 142 for collecting arm and wrist swing information data, a control button 13 for switching the control mode of the bracelet, and an LED display module 15 for displaying the current working state of the bracelet; The terminal 2 is connected to an environmental parameter collection module 21 for collecting surrounding environmental parameters, and the receiving terminal 2 is provided with gesture recognition for recognizing and processing the human arm and wrist swing information data sent by the accelerometer 141 and the gyroscope 142. Module 22.

With reference to Fig. 1～2, the ambient environment parameter that described environmental parameter collection module 21 collects comprises air temperature parameter, air relative humidity parameter and air velocity parameter; The temperature and human heart rate data are then combined with the surrounding environment parameters and the PMV value is obtained through the fuzzy neural network algorithm, and then the receiving terminal 2 sends the data processing result to the microprocessor 1 to control the working state of the fan.

In terms of thermal comfort evaluation, the PMV index proposed by Professor Fanger is the most representative. This index comprehensively considers various factors that affect the thermal comfort of the human body, and represents most people's evaluation of thermal comfort. The PMV index can be expressed as a function of four environmental parameters and two human body parameters. Specifically, it includes air temperature parameters, air relative humidity parameters, air velocity parameters, human body surface radiation temperature, human body clothing thermal resistance, and human body metabolic rate, that is, heart rate.

The PMV calculation formula is as follows:

When the PMV value = 3, the thermal comfort feeling of the human body corresponds to heat; when the PMV value = 2, the thermal comfort feeling of the human body corresponds to warm; when the PMV value = 1, the thermal comfort feeling of the human body corresponds to slightly warm; when the PMV value = 0, the thermal comfort of the human body corresponds to moderate; when the PMV value = -1, the thermal comfort of the human body corresponds to slightly cool; when the PMV value = -2, the thermal comfort of the human body corresponds to cool; when the PMV value = -3 When , the thermal comfort of the human body corresponds to cold.

The existing evaluation system of indoor environment comfort generally obtains the comfort index value through cumbersome iterative calculations, but since the formula itself is a complex nonlinear function, the calculation is troublesome. Therefore, this system uses fuzzy neural network to establish a simulation evaluation model for four thermal environment variables and two human factors, which avoids tedious iterative calculation of formulas and realizes the intelligent detection of PMV thermal environment comfort index.

1-2, the receiving terminal 2 recognizes the human arm and wrist swing information data sent by the accelerometer 141 and the gyroscope 142 through the gesture recognition module 22, and then sends a corresponding control signal to the microprocessor 3 to control The fan works.

1-2, the wristband 1 is connected to the receiving terminal 2 through low-power bluetooth communication, and the data detected by the temperature sensor 11 and the pulse detector 12 are different from the data collected by the accelerometer 141 and the gyroscope 142. At the same time, it is sent to the receiving terminal 2, and the two modes are switched through the control button 13 on the bracelet 1.

Referring to Figures 1-2, the main control chip DA14580 in the bracelet 1 is a 32-bit ARM Cortex MO series with Bluetooth function; the accelerometer uses ADXL362 to detect the swing of the human arm and wrist; the temperature sensor 11 can detect the temperature radiated by the human body ; The LED display module 15 is used to indicate the current working status of the wristband; the pulse detector 12 uses AFE4403 to detect the pulse; and the control button 13 is used to switch the control mode. The main control chip on the receiving terminal 2 is also DA14580, which combines the data sent by the bracelet 1 to obtain the PMV value through the fuzzy neural network algorithm, and thus controls the working state of the fan.

The ADXL362 accelerometer is selected as the acceleration data acquisition source of the algorithm. By extracting the key point information and using BP neural network technology to match the key point features, a relatively small calculation time and storage space complexity can be obtained to obtain a higher The purpose of gesture recognition accuracy.

In terms of gesture design, you can refer to the following:

1. To turn on/off the fan, shake the forearm twice in a row similar to knocking on the door;

2. Wind control, stretch the forearm forward and draw a circle clockwise to increase the wind force by one gear, and stretch the forearm forward and draw a circle counterclockwise to decrease the wind force by one gear;

3. Shake the head (wind direction), stretch the forearm forward and move it parallel to the left at a constant speed, the fan will shake its head to the left, stretch the forearm forward and move it parallel to the right at a constant speed, the fan will shake its head to the right.

Referring to Figures 1-2, when the control mode is to control the fan through the physiological parameters of the human body and the surrounding environment parameters, the receiving terminal 2 receives the human body surface radiation temperature and human heart rate data sent by the bracelet 1, and then combines the surrounding environment parameters and passes the fuzzy The neural network algorithm obtains the PMV value, and then the receiving terminal 2 sends the data processing result to the microprocessor 1 to control the working state of the fan.

Referring to Figures 1-2, when the control button 13 is switched to the mode of controlling the fan by swinging the arm and wrist, the receiving terminal 2 is used to identify and process the human arm and wrist swing information data sent by the accelerometer 141 and the gyroscope 142. The gesture recognition module 22 recognizes the gesture information, and sends a corresponding control signal to the microcontroller 3, so as to realize indoor wireless control of the fan.

Referring to Figures 1 and 2, the embodiment of the present invention adds feedback links such as collecting the body surface temperature of the human body and indoor temperature and humidity, and applies the PMV thermal comfort equation to the wristband to intelligently control the fan wind force to form a closed-loop temperature control, so that the human body It is always automatically in the most comfortable indoor air-conditioning environment without manual adjustment. And the system uses the smart bracelet acceleration sensor to recognize the user's gestures for remote control, which is relatively easy to operate and less affected by the environment.

The embodiment of the system adopts two control modes, which solves the problem that a single control mode cannot fully meet user needs, and realizes all-weather intelligent control. Compared with the gesture recognition based on computer vision of the fan body sensor, the indoor controllable range of this control system is also increased, and the dependence on the environment such as light is also reduced. Furthermore, compared with traditional smart fans that only control the wind force according to the ambient temperature, this control system is more in line with the thermal comfort requirements of the human body.

The above-mentioned embodiment is a preferred embodiment of the present invention, but the embodiment of the present invention is not limited by the above-mentioned embodiment, and any other changes, modifications, substitutions, combinations, Simplifications should be equivalent replacement methods, and all are included in the protection scope of the present invention.

Claims (7)

1. A fan control system, characterized in that: it includes a wristband for detecting human body data and a receiving terminal for receiving the data of the wristband and performing data processing, and the receiving terminal sends the result of data processing to the Control the microprocessor of the fan to control the working state of the fan; the wristband is provided with a temperature sensor for detecting the radiation temperature of the human body surface, a pulse detector for detecting the heart rate of the human body, and a sensor for collecting arm and wrist swing information data. Accelerometer and gyroscope, and control buttons for switching the control mode of the bracelet; the receiving terminal is connected with an environmental parameter acquisition module for collecting surrounding environmental parameters, and the receiving terminal is provided with an accelerometer for identification and processing And the gesture recognition module of the human arm and wrist swing information data sent by the gyroscope. 2 . The fan control system according to claim 1 , wherein the surrounding environment parameters collected by the environment parameter collection module include air temperature parameters, air relative humidity parameters and air velocity parameters. 3 . 3. A fan control system according to claim 1, characterized in that: the ambient parameters collected by the environmental parameter collection module include air temperature parameters, air relative humidity parameters and air velocity parameters; the receiving terminal After receiving the human body surface radiation temperature and human heart rate data sent by the wristband, combine the surrounding environment parameters and obtain the PMV value through the fuzzy neural network algorithm, and then the receiving terminal sends the data processing results to the microprocessor to control the working status of the fan . 4. A fan control system according to claim 1, characterized in that: the receiving terminal recognizes the human arm and wrist swing information data sent by the accelerometer and gyroscope through the gesture recognition module, and then sends the corresponding The control signal is given to the microprocessor to control the work of the fan. 5 . The fan control system according to claim 1 , wherein the data detected by the temperature sensor and the pulse detector are not sent to the receiving terminal at the same time as the data collected by the accelerometer and the gyroscope. 6 . The fan control system according to claim 1 , wherein an LED display module for displaying the current working status of the wristband is further provided on the wristband. 7 . 7 . The fan control system according to claim 1 , wherein the wristband is connected to the receiving terminal through Bluetooth communication.