Range hood control method and system based on Internet of Things

Abstract

The invention discloses a range hood control method and system based on the Internet of Things. The method comprises the following steps that S1, the working frequency of a range hood is started at the initial frequency; s2, fire parameters of the gas stove are obtained, and the final control frequency of the range hood is determined based on the fire parameters; s3, acquiring pressure change on the gas stove, judging whether the pressure change is larger than a pressure threshold value or not, if the pressure change is smaller than the pressure threshold value, modifying the working frequency of the range hood into the final control frequency, and if the pressure change is larger than the pressure threshold value, predicting the adjusting time based on the pressure change, modifying the working frequency of the range hood into the final control frequency at the adjusting time; and S4, repeatedly executing the steps S2 to S3 until the range hood is closed. The cooking fume generation time is predicted through the pressure change to serve as the adjustment time, the working frequency of the range hood is adjusted at the adjustment time to meet the cooking fume adsorption requirement, the range hood is adjusted more intelligently, and therefore the user experience is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of the Internet of Things, and particularly to a control method and system for a range hood based on the Internet of Things. Background Art

[0002] With the continuous acceleration of the intelligentization process of kitchen appliances, the linkage control technology between gas stoves and range hoods is gradually becoming an indispensable part of modern kitchens. This innovative design aims to achieve seamless cooperation between gas stoves and range hoods during the cooking process through intelligent means, thereby greatly improving the user's cooking experience and the comfort of the kitchen environment.

[0003] Specifically, traditionally, the linkage control between gas stoves and range hoods mostly relies on monitoring the temperature change of the stove head or the gas concentration, and automatically adjusts the air volume of the range hood based on this. However, in actual cooking scenarios, this control method often fails to accurately match the actual needs of users. The reason is that various factors such as the cooking amount, the material of the cookware, the characteristics of the ingredients, and the cooking skills will all have a significant impact on the amount and time of oil fume generated during the cooking process.

[0004] Taking the example of a user stir-frying the same dish with the same firepower, if the amount of ingredients is less, the moisture in the ingredients will evaporate faster, resulting in an earlier generation time of oil fume and a relatively large amount of oil fume. On the contrary, if the amount of ingredients is more, the evaporation process of moisture will be relatively slow, and the generation time and amount of oil fume will both decrease accordingly. Therefore, it is obviously difficult to meet the diverse needs of users in different cooking scenarios by simply regulating the air volume of the range hood based on the single index of the stove body firepower. Summary of the Invention

[0005] Aiming at the above defects, the purpose of the present invention is to propose a control method and system for a range hood based on the Internet of Things.

[0006] To achieve this purpose, the present invention adopts the following technical solutions: A control method for a range hood based on the Internet of Things, including the following steps:

[0007] Step S1: Start the working frequency of the range hood at the initial frequency;

[0008] Step S2: Obtain the firepower parameters of the gas stove, and determine the final control frequency of the range hood based on the firepower parameters;

[0009] Step S3: Obtain the pressure change on the gas stove, and determine whether the pressure change is greater than the pressure threshold. If the pressure change is less than the pressure threshold, modify the working frequency of the range hood to the final control frequency. If the pressure change is greater than the pressure threshold, predict the adjustment time based on the pressure change, and modify the working frequency of the range hood to the final control frequency at the adjustment time;

[0010] Step S4: Repeat steps S2 to S3 until the range hood is turned off.

[0011] Preferably, the steps of obtaining the firepower parameters of the gas stove in step S2 are as follows:

[0012] Step S21: constructing a detection area;

[0013] Step S22: calling a preset image as the first image;

[0014] Step S23: when the firepower adjustment knob is pressed, after waiting for a threshold time, an image of the firepower adjustment knob in the monitoring area is acquired using a camera as a second image;

[0015] Step S24: using the rotation and translation matrix to calculate the rotation angle of the first image to the second image, and determining the current firepower parameter based on the current rotation angle;

[0016] Step S25: Update the second image to the first image, and repeat steps S23 to S24 until the gas stove is turned off.

[0017] Preferably, when step S23 is re-executed, the following steps also need to be executed:

[0018] Step A1: dynamic background modeling is performed on the video stream of the firepower adjustment knob to obtain a firepower adjustment knob model;

[0019] Step A2: calling the firepower adjustment knob model to remove the firepower adjustment knob identified in the second image; and obtaining a modified identification photo;

[0020] Step A3: adjusting the gray value of the identification photo, and determining the smoke concentration according to the gray value in the identification photo;

[0021] Step A4: determining whether the oil fume concentration is greater than a concentration threshold; if so, modifying the operating frequency of the range hood to a final control frequency.

[0022] Preferably, the step of obtaining the final control frequency of the range hood in step S2 is as follows:

[0023] Step S26: Collecting the oil smoke concentration of different fire parameters in the historical data, taking the average oil smoke concentration as the input parameter, wherein the historical data is the data generated when the user uses the data and / or the data generated when other network users use the data;

[0024] Step S27: inputting the input parameters into the input layer of the neural network, and the neural network performs linear transformation through the weight matrix and the corresponding bias to obtain the required air volume of the range hood;

[0025] Step S28: Input the required air volume of the range hood into the PID controller to obtain the preliminary control frequency of the range hood;

[0026] Step S29: Use the gear frequency closest to the preliminary control frequency of the range hood as the final control frequency of the range hood.

[0027] Preferably, the steps for obtaining the adjustment time in step S3 are as follows:

[0028] Step S31: Obtain the contact area between the gas stove pot rack and the gas stove, and calculate the gravity change value based on the contact area and the pressure change;

[0029] The formula for obtaining the gravity change value in step S31 is as follows:

[0030] Where A is the contact area between the gas stove pot rack and the gas stove, ΔP is the pressure change value, and g is the acceleration due to gravity;

[0031] Step S32: Obtain the current temperature as the first temperature value, and obtain the difference between the first temperature value and 100 °C as the temperature difference;

[0032] Based on the gravity change value, the temperature difference, and the fire power parameter, obtain the adjustment time;

[0033] The specific formula for obtaining the adjustment time is as follows:

[0034]

[0035] Where m is the gravity change value, ΔT is the temperature difference, po is the fire power parameter, c′ = α1*c1 + α2*c2, α1 and α2 are proportionality parameters respectively, and c1 and c2 are the specific heat capacities of oil and water respectively.

[0036] An IoT-based range hood control system using the above IoT-based range hood control method, comprising:

[0037] A startup module for starting the operating frequency of the range hood at an initial frequency;

[0038] A frequency module for obtaining the fire power parameter of the gas stove and determining the final control frequency of the range hood based on the fire power parameter;

[0039] An adjustment module for obtaining the pressure change on the gas stove, determining whether the pressure change is greater than the pressure threshold. If the pressure change is less than the pressure threshold, modify the operating frequency of the range hood to the final control frequency. If the pressure change is greater than the pressure threshold, predict the adjustment time based on the pressure change and modify the operating frequency of the range hood to the final control frequency at the adjustment time;

[0040] The monitoring module is used to recall the frequency module and the adjustment module until the range hood is turned off.

[0041] Preferably, the frequency module includes a firepower determination sub-module;

[0042] The firepower determination sub-module includes a construction unit, a calling unit, an image acquisition unit, an angle acquisition unit, and a monitoring unit;

[0043] The construction unit is used to construct a detection area;

[0044] The calling unit is used to call a preset image as the first image;

[0045] The image acquisition unit is used to, when the firepower adjustment knob is pressed and after waiting for the threshold time, use a camera to acquire an image of the firepower adjustment knob in the monitoring area as the second image;

[0046] The angle acquisition unit is used to calculate the rotation angle of the first image changing to the second image using a rotation and translation matrix, and determine the current firepower parameter based on the current rotation angle;

[0047] The monitoring unit is used to update the second image to the first image, and recall the image acquisition unit and the angle acquisition unit until the gas stove is turned off.

[0048] Preferably, it further includes an instantaneous regulation module. When the angle acquisition unit executes, the instantaneous regulation module is called. The instantaneous regulation module includes a modeling sub-module, a removal sub-module, a judgment sub-module, and an adjustment sub-module;

[0049] The modeling sub-module is used to perform dynamic background modeling on the video stream of the firepower adjustment knob to obtain a firepower adjustment knob model;

[0050] The removal sub-module is used to call the firepower adjustment knob model to remove the recognized firepower adjustment knob from the second image; and obtain a modified recognized photo;

[0051] The judgment sub-module is used to adjust the gray value of the recognized photo and determine the oil fume concentration according to the gray value in the recognized photo;

[0052] The adjustment sub-module is used to judge whether the oil fume concentration is greater than the concentration threshold. If it is greater, the adjustment time is modified to the current time, and the working frequency of the range hood is modified to the final control frequency.

[0053] Preferably, the frequency module includes a frequency determination sub-module;

[0054] The frequency determination sub-module includes an input parameter acquisition unit, a neural network input unit, a PID control input unit, and a final frequency determination unit;

[0055] The input parameter acquisition unit is used to collect the oil fume concentration of different firepower parameters in historical data, and use the average oil fume concentration as the input parameter, where the historical data is the data generated when the user uses and / or the data generated when other users on the network use;

[0056] The neural network input unit is used to: input the input parameter into the input of the neural network, and the neural network performs a linear transformation through different weight matrices and corresponding biases to obtain the required air volume of the range hood;

[0057] The PID control input unit is used to input the required air volume of the range hood into the PID controller to obtain the preliminary control frequency of the range hood;

[0058] The final frequency determination unit is used to use the gear frequency closest to the preliminary control frequency of the range hood as the final control frequency of the range hood.

[0059] Preferably, the adjustment module includes a time sub-module, and the time sub-module is used to obtain the contact area between the gas stove pot rack and the gas stove, and calculate the gravity change value based on the contact area and the pressure change;

[0060] Take the current temperature as the first temperature value, and obtain the difference between the first temperature value and 100 °C as the temperature difference;

[0061] Based on the gravity change value, the temperature difference and the firepower parameters, obtain the adjustment time.

[0062] One of the technical solutions in the above technical solutions has the following advantages or beneficial effects: Predict the time when the oil fume is generated through the pressure change as the adjustment time. At the adjustment time, adjust the working frequency of the range hood to make it meet the adsorption of the oil fume, and adjust the range hood more intelligently, thereby improving the user experience. Description of the Drawings

[0063] Figure 1 is a flowchart of an embodiment of the present invention.

[0064] Figure 2 is a schematic structural diagram of an embodiment of the system of the present invention. Detailed Embodiments

[0065] The following describes the embodiments of the present invention in detail. The examples of the embodiments are shown in the drawings, where the same or similar reference numerals indicate the same or similar elements or elements with the same or similar functions throughout. The embodiments described below with reference to the drawings are exemplary and are only used to explain the present invention and should not be construed as a limitation of the present invention.

[0066] In the description of the embodiments of the present invention, the terms "first" and "second" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of the said features. In the description of the embodiments of the present invention, the meaning of "a plurality" is two or more, unless otherwise specifically defined.

[0067] In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the present invention, unless otherwise specified, the meaning of "a plurality" is two or more. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0068] As Figures 1-2 shown, an oil fume extractor control method based on the Internet of Things includes the following steps:

[0069] Step S1: Start the operating frequency of the oil fume extractor at the initial frequency;

[0070] Step S2: Obtain the fire power parameter of the gas stove, and determine the final control frequency of the oil fume extractor based on the fire power parameter;

[0071] Step S3: Obtain the pressure change on the gas stove, and judge whether the pressure change is greater than the pressure threshold. If the pressure change is less than the pressure threshold, modify the operating frequency of the oil fume extractor to the final control frequency. If the pressure change is greater than the pressure threshold, predict the adjustment time based on the pressure change, and modify the operating frequency of the oil fume extractor to the final control frequency at the adjustment time;

[0072] Step S4: Repeat steps S2 to S3 until the oil fume extractor is turned off.

[0073] In the control of existing oil fume extractors, the control frequency of the oil fume extractor is only determined by the fire power parameter. However, in actual cooking, the weight of the food being cooked is also one of the control keys. Taking the example that a user stir-fries the same dish with the same fire power, if the amount of ingredients is less, the moisture in the ingredients will volatilize faster, resulting in an earlier generation time of oil fume and a relatively large amount of oil fume. On the contrary, if the amount of ingredients is more, the volatilization process of moisture will be relatively slow, and the generation time and amount of oil fume will both decrease accordingly. Therefore, it is obviously difficult to meet the diverse needs of users in different cooking scenarios by regulating the air volume of the oil fume extractor based on the single index of the stove fire power alone.

[0074] Therefore, pressure monitoring is added in the present invention. A pressure sensor can be simply installed on the existing gas stove. The pressure change on the gas stove is detected by the pressure sensor, and the pressure change is in a direct proportional relationship with the weight of the cooked food. The weight change of the food can be determined by detecting the pressure change. When the amount of cooked food increases, the time for generating oil fume is relatively longer. Therefore, the time for generating oil fume is predicted through the pressure change as the adjustment time. At the adjustment time, the working frequency of the range hood is adjusted to make it meet the adsorption of oil fume, and the range hood is adjusted more intelligently, thereby improving the user experience. Of course, when the user performs cooking with a relatively small cooking amount, the pressure change is relatively small. If the user uses a high firepower for cooking at this time, the speed of generating oil fume will be very fast. Therefore, the judgment of the pressure threshold is added in the present invention. When the pressure change is less than the pressure threshold, the working frequency of the range hood will be immediately modified to the final control frequency, so as to meet the user's demand for oil fume. Of course, the absolute value is not taken for this pressure change. When the cooking amount decreases, the oil fume will form faster, and at this time, the working frequency of the range hood needs to be adjusted immediately.

[0075] Finally, steps S2 - S3 are continuously repeated until the range hood is turned off, forming a continuous monitoring and adjustment mechanism. During the whole cooking process, the working frequency of the range hood is continuously optimized according to the state of the gas stove in real time, ensuring that the range hood is always in the best working state, effectively coping with various changes during the cooking process, and improving the overall performance and user experience.

[0076] Preferably, the steps of obtaining the firepower parameters of the gas stove in step S2 are as follows:

[0077] Step S21: Construct a detection area;

[0078] Step S22: Call a preset image as the first image;

[0079] Step S23: When the firepower adjustment knob is pressed, after waiting for the threshold time, use the camera to obtain the image of the firepower adjustment knob in the monitoring area as the second image;

[0080] Step S24: Use the rotation - translation matrix to calculate the rotation angle of the first image changing to the second image, and determine the current firepower parameter based on the current rotation angle;

[0081] Step S25: Update the second image to the first image, and repeat steps S23 - S24 until the gas stove is turned off.

[0082] In the present invention, a camera can be installed at the range hood. When the fire power adjustment knob is pressed, a start signal will be sent to the camera, and the camera will acquire an image in the detection area. By setting the detection area, unnecessary feature intake can be reduced, and the fire power adjustment knob can be better recognized to obtain a second image. Then, a simple rotation and translation matrix calculation is performed using the second image and the first image to obtain the rotation angle by which the first image changes to the second image. Through the rotation angle, it can be known to which position the fire power adjustment knob has rotated. Based on the output specification of the gas stove and the rotation angle of the fire power adjustment knob, the fire power output (fire power parameter) of the gas stove can be obtained.

[0083] Wherein the predicted image is an image of the fire power adjustment knob when the gas stove is turned off.

[0084] Preferably, when step S23 is re-executed, the following steps also need to be performed:

[0085] Step A1: Perform dynamic background modeling on the video stream of the fire power adjustment knob to obtain a fire power adjustment knob model;

[0086] Step A2: Call the fire power adjustment knob model to eliminate the fire power adjustment knob recognized in the second image; obtain a modified recognized photo;

[0087] Step A3: Adjust the gray value of the recognized photo, and determine the oil fume concentration according to the gray value in the recognized photo;

[0088] Step A4: Determine whether the oil fume concentration is greater than the concentration threshold. If it is greater, modify the working frequency of the range hood to the final control frequency.

[0089] Since in actual cooking, people usually heat the pot first and then add ingredients. During the process of heating the pot, since no ingredients are added at this time, it is easier to generate oil fume. To better handle the oil fume at this time, the present invention monitors the oil fume at this time. Since the fire power adjustment knob serves as the background during oil fume recognition and will affect the recognition result during recognition, in the present invention, by constructing a fire power adjustment knob model, the fire power adjustment knob recognized in the second image is eliminated; a modified recognized photo is obtained, and then the gray value of the recognized photo is adjusted. The specific adjustment method can refer to the patent with the application number: CN108548199A. After adjusting the gray value, different oil fume concentrations can present different gray values. The oil fume concentration can be defined according to the gray value. Specifically, when the oil fume concentration is greater, its gray value in the recognized photo is greater. When the oil fume concentration is greater than the concentration threshold, the working frequency of the range hood is modified to the final control frequency to increase the oil fume suction volume until step S3 is executed and there is a pressure change on the gas stove, and then the working frequency of the range hood is adjusted back to the initial frequency.

[0090] Preferably, the steps for obtaining the final control frequency of the range hood in step S2 are as follows:

[0091] Step S26: Collect the oil fume concentration in historical data for different firepower parameters, and use the average oil fume concentration as the input parameter, where the historical data is the data generated when the user uses and / or the data generated when other users on the network use;

[0092] Step S27: Input the input parameter into the input layer of the neural network. The neural network performs a linear transformation through the weight matrix and the corresponding bias to obtain the required air volume of the range hood;

[0093] Step S28: Input the required air volume of the range hood into the PID controller to obtain the preliminary control frequency of the range hood;

[0094] Step S29: Use the gear frequency closest to the preliminary control frequency of the range hood as the final control frequency of the range hood.

[0095] First, since it is impossible to determine the cooking amount of the user in this firepower state, it is impossible to effectively infer how much oil fume there is. Therefore, in the present invention, historical data of the oil fume concentration under different firepower parameters will be collected. For example, at a certain firepower parameter, the second images at different times, and then the oil fume concentration of different second images will be determined by the methods of steps A1 to A3. Then, take the average value of the oil fume concentration as the input parameter, and then input the parameter into the input layer of the neural network. The neural network performs a linear transformation through different weight matrices and the corresponding biases to obtain the required air volume of the range hood;

[0096] The formula for the required air volume of the range hood is:

[0097] where W1 is the weight matrix, b1 is the bias, is the input parameter, and f1() is the activation function, such as ReLU or sigmoid.

[0098] The formula for obtaining the preliminary control frequency of the range hood by PID control is as follows:

[0099]

[0100] where H is the required air volume of the range hood, Kp, Ki, and Kd are the gains of the PID controller respectively, t is the adjustment time, usually set to 3 to 5 seconds, Sum(e error ) is the accumulation of the oil fume concentration that has not dropped to the concentration threshold after the adjustment time in history.

[0101] Generally, range hoods are set with working gears, and each gear corresponds to a frequency. If the range hood is directly driven by initially controlling the frequency, it is easy to cause conflicts in the main board program of the range hood. Therefore, the frequency of the gear closest to the initially controlled frequency of the range hood is selected as the final control frequency of the range hood.

[0102] Preferably, the steps for obtaining the adjustment time in step S3 are as follows:

[0103] Step S31: Obtain the contact area between the gas stove rack and the gas stove, and calculate the gravity change value based on the contact area and the pressure change;

[0104] The formula for obtaining the gravity change value in step S31 is as follows:

[0105] Where A is the contact area between the gas stove rack and the gas stove (i.e., the annular area at the bottom of the gas stove rack), ΔP is the pressure change value, and g is the acceleration due to gravity;

[0106] Step S32: Obtain the current temperature as the first temperature value, and obtain the difference between the first temperature value and 100 °C as the temperature difference;

[0107] Based on the gravity change value, the temperature difference, and the fire power parameter, obtain the adjustment time;

[0108] The specific formula for obtaining the adjustment time is as follows:

[0109]

[0110] Where m is the gravity change value, ΔT is the temperature difference, po is the fire power parameter, c′ = α1 * c1 + α2 * c2, α1 and α2 are proportional parameters respectively, and c1 and c2 are the specific heat capacities of oil and water respectively.

[0111] Since oil fumes are generated only when the substance reaches the vaporization point, and most of them are water vapor during cooking, 100 °C is taken as the final temperature of the cooked food, and the current temperature is taken as the initial temperature of the food. Then, the temperature difference is obtained by taking the difference between the two temperatures. Of course, at higher altitudes, 100 °C can be set lower. Based on the basic heat calculation formula, the total heat required for m weight of food to reach 100 °C is calculated, and then divided by the fire power parameter to obtain the corresponding time. The specific heat capacity coefficient c′ can adjust the proportion of α1 and α2 according to the eating habits of people in different regions. The sum of α1 and α2 is equal to 1.

[0112] Since the heat loss is not taken into account in the calculation of the adjustment time, the adjustment time t is earlier than the actual time when boiling generates oil fumes. At this time, the working frequency of the range hood can be adjusted in advance to reduce the oil fume concentration in the kitchen and improve the user experience.

[0113] An Internet of Things-based range hood control system using the above Internet of Things-based range hood control method, comprising:

[0114] A startup module, configured to start the working frequency of the range hood at an initial frequency;

[0115] A frequency module, configured to obtain the fire power parameter of the gas stove and determine the final control frequency of the range hood based on the fire power parameter;

[0116] An adjustment module, configured to obtain the pressure change on the gas stove, determine whether the pressure change is greater than a pressure threshold. If the pressure change is less than the pressure threshold, modify the working frequency of the range hood to the final control frequency. If the pressure change is greater than the pressure threshold, predict the adjustment time based on the pressure change, and modify the working frequency of the range hood to the final control frequency at the adjustment time;

[0117] A monitoring module, configured to re-invoke the frequency module and the adjustment module until the range hood is turned off.

[0118] Preferably, the frequency module includes a fire power determination sub-module;

[0119] The fire power determination sub-module includes a construction unit, a calling unit, an image acquisition unit, an angle acquisition unit, and a monitoring unit;

[0120] The construction unit is configured to construct a detection area;

[0121] The calling unit is configured to call a preset image as a first image;

[0122] The image acquisition unit is configured to, when the fire power adjustment knob is pressed and after waiting for a threshold time, use a camera to acquire an image of the fire power adjustment knob in the monitoring area as a second image;

[0123] The angle acquisition unit is configured to calculate the rotation angle of the first image changing to the second image using a rotation translation matrix, and determine the current fire power parameter based on the current rotation angle;

[0124] The monitoring unit is configured to update the second image to the first image, and re-invoke the image acquisition unit and the angle acquisition unit until the gas stove is turned off.

[0125] Preferably, it further includes an instantaneous regulation module. When the angle acquisition unit is executed, the instantaneous regulation module is called. The instantaneous regulation module includes a modeling sub-module, a removal sub-module, a judgment sub-module, and an adjustment sub-module;

[0126] The modeling sub-module is used to perform dynamic background modeling on the video stream of the fire adjustment knob to obtain the fire adjustment knob model;

[0127] The removal sub-module is used to call the fire adjustment knob model to remove the fire adjustment knob recognized in the second image; and obtain the modified recognized photo;

[0128] The judgment sub-module is used to adjust the gray value of the recognized photo and determine the oil fume concentration according to the gray value in the recognized photo;

[0129] The adjustment sub-module is used to judge whether the oil fume concentration is greater than the concentration threshold. If it is greater, the adjustment time is modified to the current time, and the working frequency of the range hood is modified to the final control frequency.

[0130] Preferably, the frequency module includes a frequency determination sub-module;

[0131] The frequency determination sub-module includes an input parameter acquisition unit, a neural network input unit, a PID control input unit, and a final frequency determination unit;

[0132] The input parameter acquisition unit is used to collect the oil fume concentration of different fire parameters in the historical data, and use the average oil fume concentration as the input parameter, where the historical data is the data generated when the user uses and / or the data generated when other users on the network use;

[0133] The neural network input unit is used to: input the input parameter into the input of the neural network, and the neural network performs linear transformation through different weight matrices and corresponding biases to obtain the air volume required by the range hood;

[0134] The PID control input unit is used to input the air volume required by the range hood into the PID controller to obtain the preliminary control frequency of the range hood;

[0135] The final frequency determination unit is used to use the gear frequency closest to the preliminary control frequency of the range hood as the final control frequency of the range hood.

[0136] Preferably, the adjustment module includes a time sub-module, and the time sub-module is used to obtain the contact area between the gas stove pot rack and the gas stove, and calculate the gravity change value based on the contact area and the pressure change;

[0137] Take the current temperature as the first temperature value, and obtain the difference between the first temperature value and 100 °C as the temperature difference;

[0138] Based on the gravity change value, the temperature difference, and the fire parameter, obtain the adjustment time.

[0139] In the description of this specification, the description with reference to terms such as "one embodiment", "some embodiments", "schematic embodiments", "examples", "specific examples", or "some examples", etc. means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0140] Although the embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the claims and their equivalents.

Claims

1. A range hood control method based on the Internet of Things, characterized in that: The following steps are involved: Step S1: starting the working frequency of the range hood with an initial frequency; Step S2: Obtain the firepower parameter of the gas stove, and determine the final control frequency of the range hood based on the firepower parameter; Step S3: Obtain the pressure change on the gas stove, determine whether the pressure change is greater than the pressure threshold, if the pressure change is less than the pressure threshold, modify the operating frequency of the range hood to the final control frequency, if the pressure change is greater than the pressure threshold, predict the adjustment time based on the pressure change, and modify the operating frequency of the range hood to the final control frequency during the adjustment time; Step S4: Repeat steps S2 to S3 until the range hood is turned off.

2. The range hood control method based on the Internet of Things according to claim 1, characterized in that: The steps of obtaining the firepower parameters of the gas stove in step S2 are as follows: Step S21: constructing a detection area; Step S22: calling a preset image as the first image; Step S23: when the firepower adjustment knob is pressed, after waiting for a threshold time, an image of the firepower adjustment knob in the monitoring area is acquired using a camera as a second image; Step S24: using the rotation and translation matrix to calculate the rotation angle of the first image to the second image, and determining the current firepower parameter based on the current rotation angle; Step S25: Update the second image to the first image, and repeat steps S23 to S24 until the gas stove is turned off.

3. The range hood control method based on the Internet of Things according to claim 2, characterized in that: When step S23 is re-executed, the following steps need to be performed: Step A1: dynamic background modeling is performed on the video stream of the firepower adjustment knob to obtain a firepower adjustment knob model; Step A2: calling the firepower adjustment knob model to remove the firepower adjustment knob identified in the second image; Obtain the modified identification photo; Step A3: adjusting the gray value of the identification photo, and determining the smoke concentration according to the gray value in the identification photo; Step A4: determining whether the oil fume concentration is greater than a concentration threshold; if so, modifying the operating frequency of the range hood to a final control frequency.

4. The range hood control method based on the Internet of Things according to claim 3 is characterized in that: The steps of obtaining the final control frequency of the range hood in step S2 are as follows: Step S26: Collecting the oil smoke concentration of different fire parameters in the historical data, taking the average oil smoke concentration as the input parameter, wherein the historical data is the data generated when the user uses the data and / or the data generated when other network users use the data; Step S27: inputting the input parameters into the input layer of the neural network, and the neural network performs linear transformation through the weight matrix and the corresponding bias to obtain the required air volume of the range hood; Step S28: inputting the required air volume of the range hood into the PID controller to obtain the preliminary control frequency of the range hood; Step S29: taking the gear frequency closest to the initial control frequency of the range hood as the final control frequency of the range hood.

5. The range hood control method based on the Internet of Things according to claim 1, characterized in that: The steps of obtaining the adjustment time in step S3 are as follows: Step S31: obtaining a contact area between the gas stove pot rack and the gas stove, and calculating a gravity change value based on the contact area and pressure change; The formula for obtaining the gravity change value in step S31 is as follows: Where A is the contact area between the gas stove pot rack and the gas stove, ΔP is the pressure change value, and g is the gravitational acceleration; Step S32: obtaining the current temperature as a first temperature value, and obtaining the difference between the first temperature value and 100° C. as a temperature difference; Based on the gravity change value, the temperature difference and the firepower parameter, obtaining the adjustment time; The formula for obtaining the adjustment time is as follows: Where m is the gravity change value, ΔT is the temperature difference, po is the firepower parameter, c′=α1*c1+α2*c2, α1 and α2 are proportional parameters, c1 and c2 are the specific heat capacity of oil and water respectively.

6. A range hood control system based on the Internet of Things, using the range hood control method based on the Internet of Things according to any one of claims 1 to 5, characterized in that: include: A starting module, used to start the working frequency of the range hood with an initial frequency; The frequency module is used to obtain the fire power parameters of the gas stove and determine the final control frequency of the range hood based on the fire power parameters; The adjustment module is used to obtain the pressure change on the gas stove and determine whether the pressure change is greater than the pressure threshold. If the pressure change is less than the pressure threshold, the operating frequency of the range hood is modified to the final control frequency. If the pressure change is greater than the pressure threshold, the adjustment time is predicted based on the pressure change, and the operating frequency of the range hood is modified to the final control frequency during the adjustment time. The monitoring module is used to recall the frequency module and the adjustment module until the range hood is turned off.

7. The range hood control system based on the Internet of Things according to claim 6, characterized in that: The frequency module includes a firepower determination submodule; The firepower determination submodule includes a construction unit, a calling unit, an image acquisition unit, an angle acquisition unit and a monitoring unit; The construction unit is used to construct a detection area; The calling unit is used to call a preset image as the first image; The image acquisition unit is used to use a camera to acquire an image of the firepower adjustment knob in the monitoring area as a second image after waiting for a threshold time when the firepower adjustment knob is pressed; The angle acquisition unit is used to calculate the rotation angle of the first image to the second image using the rotation and translation matrix, and determine the current firepower parameter based on the current rotation angle; The monitoring unit is used to update the second image to the first image, and re-call the image acquisition unit and the angle acquisition unit until the gas stove is turned off.

8. The range hood control system based on the Internet of Things according to claim 7, characterized in that: It also includes an instantaneous control module, which is called when the angle acquisition unit is executed, and includes a modeling submodule, a removal submodule, a judgment submodule and an adjustment submodule; The modeling submodule is used to perform dynamic background modeling on the video stream of the firepower adjustment knob to obtain the firepower adjustment knob model; The removal submodule is used to call the firepower adjustment knob model to remove the firepower adjustment knob identified in the second image; Obtain the modified identification photo; The judgment submodule is used to adjust the gray value of the identification photo and determine the smoke concentration according to the gray value in the identification photo; The adjustment submodule is used to determine whether the oil fume concentration is greater than the concentration threshold. If so, the adjustment time is modified to the current time, and the operating frequency of the range hood is modified to the final control frequency.

9. The range hood control system based on the Internet of Things according to claim 6, characterized in that: The frequency module includes a frequency determination submodule; The frequency determination submodule includes an input parameter acquisition unit, a neural network input unit, a PID control input unit and a final frequency determination unit; The input parameter acquisition unit is used to collect the oil smoke concentration of different fire parameters in the historical data to use the average oil smoke concentration as the input parameter, wherein the historical data is the data generated when the user uses it and / or the data generated when other network users use it; The neural network input unit is used to: input the input parameters to the input of the neural network, and the neural network performs linear transformation through different weight matrices and corresponding biases to obtain the required air volume of the range hood; The PID control input unit is used to input the required air volume of the range hood into the PID controller to obtain the preliminary control frequency of the range hood; The final frequency determination unit is used to use the gear frequency closest to the preliminary control frequency of the range hood as the final control frequency of the range hood.

10. The range hood control system based on the Internet of Things according to claim 6, characterized in that: The regulating module includes a time submodule, and the time submodule is used to obtain the contact area between the gas stove pot rack and the gas stove, and calculate the gravity change value based on the contact area and the pressure change; Taking the current temperature as the first temperature value, obtaining the difference between the first temperature value and 100° C. as the temperature difference; Based on the gravity change value, temperature difference and firepower parameters, the adjustment time is obtained.

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