Stove active noise reduction control method and device based on user identification and storage medium

Abstract

The application relates to a cooking utensil active noise reduction control method and device based on user identification and a storage medium, the method comprising: obtaining identification data in a kitchen area through a human body identification element according to a sampling period, the identification data comprising human body feature data and detection time; if individual data in the identification data obtained in continuous multiple sampling periods are all that a user does not exist, or the accumulated duration that the user does not exist exceeds a time threshold, then a controller is used to control the cooking utensil to perform noise reduction processing. The method judges whether the starting condition of the cooking utensil active noise reduction is met through the identification data obtained in the continuous multiple sampling periods, and if the condition is met, a control output instruction is output to instruct the cooking utensil to perform corresponding noise reduction processing, so that when no one is in the kitchen area, the noise reduction is reduced, the alarm sound of the cooking utensil continuous noise reduction caused by pot overflow or the sound of liquid splashing in the pot is avoided, the user cannot discover the pot overflow in time, the liquid may extinguish the flame and cause gas leakage, and there is a great safety hazard.

Description

Technical Field

[0001] This application belongs to the field of intelligent control technology for kitchen stoves, and particularly relates to a method, device and storage medium for active noise reduction control of stoves based on user identification. Background Technology

[0002] With the development of smart homes, some high-end range hoods are equipped with Active Noise Cancellation (ANC) devices, which use microphones to collect ambient noise and emit inverse sound waves to cancel out low-frequency noise during cooking, thus improving the user experience. Meanwhile, some cooktops are also equipped with overflow detection sensors to monitor for spills.

[0003] However, existing active noise cancellation systems for cooktops typically operate independently, aiming to continuously reduce cooking noise. However, in emergencies such as overflowing pots or liquid splashing from the cooktop, users need to hear the overflow alarm or notice any unusual sounds immediately within the kitchen area. If the user is not in the kitchen area, the active noise cancellation system may still be running at full power, potentially masking the overflow alarm or the sound of liquid splashing. This could prevent the user from noticing the overflow in time, and the liquid might extinguish the flame, causing a gas leak and posing a significant safety hazard. Summary of the Invention

[0004] One embodiment of this application provides a method, device, and storage medium for active noise reduction control of cooktops based on user identification, in order to solve the problem that existing active noise reduction methods applied to cooktops are based on the user being in the kitchen area, and are not applicable when the user is not in the kitchen area, thus affecting the safety of cooktop use.

[0005] In a first aspect, one embodiment of this application provides a cooktop active noise reduction control method based on user identification, applied in a kitchen area. The kitchen area includes a cooktop and a controller for controlling the cooktop to reduce noise. At least one human body recognition element for identifying the presence of a user is provided in the kitchen area, and the controller is connected to the human body recognition element. The cooktop active noise reduction control method includes the following steps: The identification data within the kitchen area is acquired through the human body recognition element according to the sampling period. The identification data includes human body feature data and detection time. If the individual data obtained in multiple consecutive sampling cycles are all of the user not existing, or the cumulative duration of the user not existing exceeds a time threshold, then the controller will control the stove to perform noise reduction processing. The cumulative duration of user absence is the cumulative duration between the detection time corresponding to the first detection of user absence and the detection time corresponding to the last detection of user absence.

[0006] Optionally, if in multiple consecutive sampling periods the identified data shows that the user does not exist, or the cumulative duration of the user not existing exceeds a time threshold, then the controller controls the stove to perform noise reduction processing, including: If all individual data in the identification data obtained in the sampling period of the first consecutive detection count are users that do not exist, or if the cumulative duration of users not existing exceeds the first time threshold but is less than the second time threshold, then the controller adjusts the noise reduction parameter of the stove according to the first noise reduction value to achieve noise reduction processing of the stove. If all individual data in the identification data obtained in the sampling period of the second consecutive detection cycle are users that do not exist, or if the cumulative duration of users not existing exceeds the second time threshold, then the controller adjusts the noise reduction parameter of the stove according to the second noise reduction value to achieve noise reduction processing of the stove. Wherein, the first number of detections is greater than a first value and not greater than a second value, the second number of detections is greater than a second value, and the noise reduction parameters include combustion noise.

[0007] Optionally, the first noise reduction value is 10 dB, and the second noise reduction value is 20 dB; and / or, the first value is 3 times, the second value is 5 times, the first time threshold is 7 minutes, and the second time threshold is 11 minutes.

[0008] Optionally, the human body recognition element may be an infrared sensor, a microwave sensor, an ultrasonic sensor, an image sensor, a radar sensor, or a photoelectric sensor.

[0009] Optionally, the controller includes a control module and an active noise cancellation module, a wireless communication module, and a human-computer interaction module connected to the control module, wherein the human body recognition element is connected to the control module; the active noise cancellation module includes a noise cancellation processing chip and an anti-phase sound wave transmitting element connected to the noise cancellation processing chip; The wireless communication module is used to communicate with the stove. The control module is used to control the active noise reduction module to output a noise reduction signal through the noise reduction processing chip and the transmitting anti-phase acoustic wave element according to the recognition data of the human body recognition element, and to transmit the noise reduction signal to the stove through the wireless communication module for noise reduction operation; The human-computer interaction module is used to display the identification data of the stove.

[0010] Secondly, one embodiment of this application provides a cooktop active noise reduction control device based on user identification, applied in a kitchen area, the kitchen area including a cooktop and a controller for controlling the cooktop to reduce noise, the kitchen area being provided with at least one human body identification element for identifying the presence of a user, the controller being connected to the human body identification element, the cooktop active noise reduction control device including: a data acquisition module and a noise reduction execution module; The data acquisition module is used to acquire recognition data in the kitchen area through the human body recognition element according to the sampling period. The recognition data includes human body feature data and detection time. The noise reduction execution module is used to control the stove to perform noise reduction processing through the controller if the individual data of the identification data obtained in multiple consecutive sampling cycles are all of the user's absence, or the cumulative time of the user's absence exceeds a time threshold. The cumulative duration of user absence is the cumulative duration between the detection time corresponding to the first detection of user absence and the detection time corresponding to the last detection of user absence.

[0011] Optionally, the noise reduction execution module is further configured to, based on the sampling period obtained from the first consecutive detection count, if all individual data in the identification data are of users not existing, or if the cumulative duration of user non-existence exceeds a first time threshold but is less than a second time threshold, then adjust the noise reduction parameter of the stove by the controller according to a first noise reduction value to achieve noise reduction processing of the stove; wherein, the first detection count is greater than a first value but not greater than a second value, and the noise reduction parameter includes combustion noise.

[0012] Optionally, the noise reduction execution module is further configured to, in the case where all individual data obtained in the sampling period during the second consecutive detection period are of users not existing, or the cumulative duration of users not existing exceeds the second time threshold, adjust the noise reduction parameter of the stove by the controller according to the second noise reduction value to achieve noise reduction processing of the stove; wherein, the second detection period is greater than the second value, and the noise reduction parameter includes combustion noise.

[0013] Optionally, the human body recognition element may be an infrared sensor, a microwave sensor, an ultrasonic sensor, an image sensor, a radar sensor, or a photoelectric sensor.

[0014] Thirdly, one embodiment of this application provides a computer-readable storage medium having a computer program / instructions stored thereon, which, when executed by a processor, implements the steps of the user-identified active noise reduction control method for cooktops.

[0015] One embodiment of this application provides a user-identification-based active noise reduction control method for cooktops. This method uses identification data obtained from multiple consecutive sampling cycles to determine whether the activation conditions for active noise reduction are met. If met, a control output command is sent to instruct the cooktop to perform corresponding noise reduction processing. This reduces noise when no one is in the kitchen area, preventing the cooktop from continuously reducing overflow alarm sounds or the sound of liquid splashing from the pot. This avoids situations where users cannot promptly detect overflow, and the liquid may extinguish the flame, causing gas leaks and posing a significant safety hazard. This method addresses the problem that existing active noise reduction methods for cooktops are based on the user being in the kitchen area, and are not applicable when the user is not in the kitchen area, thus affecting the safety of cooktop use.

[0016] This user-identification-based active noise reduction control device for cooktops uses a data acquisition module and a noise reduction execution module to obtain identification data from multiple consecutive sampling cycles to determine whether the activation conditions for active noise reduction of the cooktop are met. If the conditions are met, the control output command instructs the cooktop to execute the corresponding noise reduction process, thereby reducing noise when no one is in the kitchen area. This prevents the cooktop from continuously reducing the sound of overflow alarms or liquid splashing from the pot, which could prevent users from noticing the overflow in time. The liquid may extinguish the flame and cause gas leakage, posing a significant safety hazard. Attached Figure Description

[0017] To more clearly illustrate the technical solution in one embodiment of this application, the accompanying drawings used in the description of the embodiment will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any creative effort.

[0018] To gain a more complete understanding of this application and its beneficial effects, the following description will be provided in conjunction with the accompanying drawings. In the following description, the same reference numerals denote the same parts.

[0019] Figure 1 A flowchart illustrating the steps of a user-identified active noise reduction control method for cooktops provided in one embodiment of this application.

[0020] Figure 2 A schematic diagram of the framework of a user-identified active noise reduction control device for a cooktop provided in one embodiment of this application. Detailed Implementation

[0021] The technical solution of one embodiment of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0022] Patent terminology used in this application: Infrared sensors are among the most commonly used sensors for detecting the human body. They work by utilizing the infrared radiation emitted by the human body. The human body continuously radiates infrared light, and infrared sensors detect this radiation to sense the presence of the human. Infrared sensors have advantages such as fast response speed, high sensitivity, and strong anti-interference ability. Based on different detection principles, infrared sensors can be further divided into pyroelectric infrared sensors and quantum infrared sensors, among others.

[0023] Microwave sensors use electromagnetic waves in the microwave band to detect the human body. They emit microwave signals of a specific frequency; when a person enters the detection area, a portion of the microwave signal is reflected back. The sensor receives and analyzes these reflected signals to detect the presence of the person. Microwave sensors have advantages such as long detection distance, strong penetration, and immunity to ambient light.

[0024] Ultrasonic sensors use ultrasound to detect the human body. They emit ultrasonic signals, which are reflected when they encounter a human body. The sensor receives the reflected ultrasonic signals to calculate the distance between the human body and the sensor, thus detecting the presence of the human. Ultrasonic sensors have advantages such as high detection accuracy, good directionality, and insensitivity to light and color.

[0025] Image sensors, especially cameras, detect the human body by capturing images. They use image processing algorithms to analyze the captured images, identify human contours or feature points in the images, and thus determine the presence of a human. Image sensors have advantages such as a wide detection range, rich information, and the ability to recognize complex movements.

[0026] Radar sensors use radar principles to detect the human body. They emit electromagnetic waves and receive the reflected signals, analyzing parameters such as the signal's frequency and phase to sense the presence and movement of the human body. Radar sensors have advantages such as long detection range, strong penetration, and the ability to identify multiple targets.

[0027] Photoelectric sensors utilize the photoelectric effect to detect the human body. They emit a light beam and detect whether the beam is blocked or reflected back, thus sensing the presence of a person. Photoelectric sensors have advantages such as fast response speed and simple structure.

[0028] One embodiment of this application provides a method, device, and storage medium for active noise reduction control of cooktops based on user identification, in order to solve the problem that existing active noise reduction methods applied to cooktops are based on the user being in the kitchen area, and are not applicable when the user is not in the kitchen area, thus affecting the safety of cooktop use.

[0029] Example 1: One embodiment of this application provides a user-identified active noise reduction control method for cooktops; for example, please refer to [link to relevant documentation]. Figure 1 , Figure 1 A flowchart illustrating the steps of a user-identified active noise reduction control method for cooktops provided in one embodiment of this application.

[0030] like Figure 1 As shown, this application provides a user-identification-based active noise reduction control method for stoves, applied in a kitchen area. The kitchen area includes a stove and a controller for controlling the stove to reduce noise. At least one human body recognition element is provided in the kitchen area to identify the presence of a user, and the controller is connected to the human body recognition element.

[0031] To further clarify, the human body recognition element can be an infrared sensor, microwave sensor, ultrasonic sensor, image sensor, radar sensor, or photoelectric sensor, etc.

[0032] In this embodiment of the invention, the cooktop panel or burner end is equipped with an overflow sensor for detecting whether the cooktop is overflowing. The overflow sensor is used to collect real-time detection data such as the liquid level or contact status of the soup in the pot (capacitive, photoelectric, or conductive probe sensors can be used). The cooktop is equipped with a communication module that communicates with the controller. The communication module is used to package the data detected by the overflow sensor and send it to the controller.

[0033] Furthermore, the communication module can use communication methods such as Bluetooth and Wi-Fi.

[0034] In the embodiments of the present invention, the controller includes a control module and an active noise reduction module, a wireless communication module, and a human-computer interaction module connected to the control module; the human body recognition element is connected to the control module; the active noise reduction module includes a noise reduction processing chip and an anti-phase acoustic wave transmitting element connected to the noise reduction processing chip. Wireless communication module, used for communication connection with the stove; The control module is used to control the active noise reduction module to output a noise reduction signal through the noise reduction processing chip and the anti-phase sound wave transmitting element based on the recognition data of the human body recognition element, and to transmit the noise reduction signal to the stove through the wireless communication module for noise reduction operation. The human-computer interaction module is used to display the identification data of the stove.

[0035] Furthermore, the human-machine interaction module includes a display screen, buzzer, or speaker, allowing users to easily monitor the stove's status. The active noise cancellation module utilizes a noise reduction processing chip and sound-generating elements to generate anti-phase sound waves that cancel out stove noise. The wireless communication module establishes a signal transmission channel between the controller and the stove. The control module, combining the recognition data from the human body recognition element, outputs commands (such as noise reduction signals) according to a specified noise reduction algorithm (such as this user-recognition-based active noise reduction control method for stoves), and simultaneously synchronizes the noise reduction signal to the stove for noise reduction execution. The human-machine interaction module can visually display the stove's user-recognition-related data, allowing users to easily check its status.

[0036] like Figure 1 As shown, the active noise reduction control method for cooktops based on user identification includes the following steps: S10. According to the sampling period, the identification data in the kitchen area is obtained through the human body recognition element. The identification data includes human body feature data and detection time.

[0037] To further clarify, human feature data refers to the presence of a user in the kitchen area (e.g., whether someone is moving around in the kitchen area). The sampling period can be selected as 2 minutes. The detection time can be understood as the time corresponding to the detection data of the human body recognition element. Step S10 can be understood as the human body recognition element continuously scanning and collecting data in the designated area of ​​the kitchen according to a preset fixed sampling period, synchronously recording the timestamp corresponding to each collection action. The final acquired recognition data includes two parts: one is human-related feature data (such as human location, presence of a person, personnel identity attributes, etc.), and the other is the precise detection time corresponding to each collection. The recognition data will be transmitted to the controller's control module as the core basis for determining whether to trigger the stove's active noise reduction function, realizing intelligent control that automatically starts noise reduction when someone is present.

[0038] S20. If all individual data obtained in multiple consecutive sampling cycles are "user does not exist", or the cumulative duration of "user does not exist" exceeds a time threshold, then the controller will control the stove to perform noise reduction processing; wherein, the cumulative duration of "user does not exist" is the cumulative duration between the detection time corresponding to the first detection of "user does not exist" and the detection time corresponding to the last detection of "user does not exist".

[0039] To further clarify, step S20 can be understood as activating the cooktop's active noise reduction based on any one of the identified data conditions. Specifically, this means: no user is detected for multiple consecutive sampling cycles, or the cumulative duration of no user detection exceeds a preset time threshold, thus meeting the activation conditions for active noise reduction. The cumulative duration of no user detection can be understood as the total duration from the first detection to the end of the last detection. After the controller determines that the activation conditions are met, it will output a command (such as a noise reduction signal) to control the cooktop to perform the corresponding noise reduction processing, avoiding unnecessary noise interference when the cooktop is idle and preventing risks such as overflowing pots, liquid splashing, or dry burning. The time threshold can be set according to requirements.

[0040] In the embodiments of this invention, the active noise reduction control method for stoves based on user identification can reduce noise when no one is in the kitchen area, avoiding the continuous noise reduction alarm sound or the sound of liquid splashing in the pot, which would prevent the user from noticing the overflow in time. The liquid may extinguish the flame and cause gas leakage, which poses a significant safety hazard.

[0041] One embodiment of this application provides a user-identification-based active noise reduction control method for cooktops, applied in a kitchen area. The kitchen area includes a cooktop and a controller for controlling the cooktop to reduce noise. At least one human body recognition element is installed in the kitchen area to identify the presence of a user. The controller is connected to the human body recognition element. The active noise reduction control method includes acquiring identification data in the kitchen area through the human body recognition element at sampling cycles. The identification data includes human feature data and detection time. If the individual data obtained in multiple consecutive sampling cycles all indicate that the user is not present, or the cumulative duration of user absence exceeds a time threshold, the controller controls the cooktop to perform noise reduction processing. The cumulative duration of user absence is the cumulative duration between the detection time corresponding to the first detection of user absence and the detection time corresponding to the last detection of user absence. This user-identification-based active noise reduction control method for cooktops determines whether the activation conditions for active noise reduction are met by using identification data obtained from multiple consecutive sampling cycles. If the conditions are met, the control output command instructs the cooktop to execute the corresponding noise reduction process. This reduces noise when no one is in the kitchen area, preventing the cooktop from continuously reducing the sound of overflow alarms or liquid splashing from the pot, which could prevent users from noticing overflows in time. Liquid spills could extinguish the flame and cause gas leaks, posing a significant safety hazard. This method addresses the problem that existing active noise reduction methods for cooktops are only applicable when the user is in the kitchen area, and are not suitable when the user is not in the kitchen area, thus affecting the safety of cooktop use.

[0042] In one embodiment of the present invention, if the individual data obtained in multiple consecutive sampling cycles all indicate that the user does not exist, or the cumulative duration of the user not existing exceeds a time threshold, then the noise reduction processing is performed by controlling the stove through the controller, including: If all individual data obtained in the first consecutive sampling period of the first detection are of the user not existing, or if the cumulative duration of the user not existing exceeds the first time threshold but is less than the second time threshold, then the controller will adjust the noise reduction parameter of the stove according to the first noise reduction value to achieve noise reduction processing of the stove. If all individual data obtained in the second consecutive sampling period of detection are for users who do not exist, or if the cumulative duration of user non-existence exceeds the second time threshold, the controller will adjust the noise reduction parameter of the stove according to the second noise reduction value to achieve noise reduction processing of the stove. The first detection count is greater than the first value but not greater than the second value, the second detection count is greater than the second value, and the noise reduction parameters include combustion noise.

[0043] Furthermore, the first noise reduction value can be selected as 10 dB, and the second noise reduction value can be selected as 20 dB; and / or, the first value can be selected as 3 times, the second value can be selected as 5 times, the first time threshold can be selected as 7 minutes, and the second time threshold can be selected as 11 minutes. The activation condition of this user-identification-based active noise reduction control method for cooktops is as follows: when the number of consecutive samplings without a user in the kitchen area falls within the range greater than the first value and not greater than the second value, or the cumulative time without a user is between the first and second time thresholds, the controller adjusts the combustion noise and other noise reduction parameters according to the first noise reduction value to achieve initial noise reduction. When the number of consecutive samplings without a user in the kitchen area exceeds the second value, or the cumulative time without a user exceeds the second time threshold, the controller further adjusts the combustion noise and other parameters according to the second noise reduction value to perform deep noise reduction.

[0044] In other embodiments, the active noise reduction control method for cooktops based on user identification collects the remaining noise of the cooktop in real time through the microphone of the active noise reduction module, and fine-tunes the noise reduction parameters in reverse to ensure that the noise reduction effect is stable and meets the standards.

[0045] Example 2: Figure 2 A schematic diagram of the framework of a user-identified active noise reduction control device for a cooktop provided in one embodiment of this application.

[0046] like Figure 2As shown, this application provides a user-identification-based active noise reduction control device for stoves, which is applied in a kitchen area. The kitchen area includes a stove and a controller for controlling the stove to reduce noise. At least one human body recognition element is provided in the kitchen area to identify the presence of a user. The controller is connected to the human body recognition element. The active noise reduction control device for stoves includes a data acquisition module 100 and a noise reduction execution module 200. The data acquisition module 100 is used to acquire recognition data in the kitchen area through the human body recognition element according to the sampling period. The recognition data includes human body feature data and detection time. The noise reduction execution module 200 is used to control the stove to perform noise reduction processing if the individual data obtained in multiple consecutive sampling cycles are all of the user's absence, or the cumulative time of the user's absence exceeds a time threshold. Among them, the cumulative time for the user not being detected is the cumulative time between the detection time corresponding to the first identification data of the user not being detected and the detection time corresponding to the last identification data of the user not being detected.

[0047] It should be noted that the module content in this embodiment corresponds to the steps of the method in Embodiment 1. The content of the user-identification-based active noise reduction control method for stoves has been described in Embodiment 1, and the specific content of the user-identification-based active noise reduction control method for stoves will not be repeated in this embodiment. The user-identification-based active noise reduction control device for stoves uses the data acquisition module and the noise reduction execution module to obtain identification data obtained from multiple consecutive sampling cycles to determine whether the activation conditions for active noise reduction of the stove are met. If the conditions are met, the control output command instructs the stove to execute the corresponding noise reduction processing, so that when no one is in the kitchen area, the noise reduction is reduced, avoiding the continuous noise reduction of the stove's overflow alarm sound or the sound of liquid splashing in the pot, which would prevent the user from noticing the overflow in time. The liquid may extinguish the flame and cause gas leakage, posing a significant safety hazard.

[0048] In the embodiments of this invention, human feature data refers to whether a user exists in the kitchen area (e.g., whether someone is moving around in the kitchen area). The sampling period can be selected as 2 minutes. The detection time can be understood as the time corresponding to the detection data of the human body recognition element. The data acquisition module 100 can be understood as the human body recognition element continuously scanning and collecting data in a designated area of ​​the kitchen according to a preset fixed sampling period, and synchronously recording the timestamp corresponding to each collection action. The final acquired recognition data includes two parts: one is human-related feature data (such as human location, whether there is a person, personnel identity attributes, etc.), and the other is the precise detection time corresponding to each collection. The recognition data is transmitted to the control module of the controller as the core basis for determining whether to trigger the active noise reduction function of the stove, realizing intelligent control that automatically starts noise reduction when someone is present.

[0049] In an embodiment of the present invention, the noise reduction execution module 200 is further configured to, based on the fact that all individual data in the identification data obtained in the sampling period of the first consecutive detection count are of the absence of users, or the cumulative duration of the absence of users exceeds a first time threshold but is less than a second time threshold, adjust the noise reduction parameters of the stove by the controller according to the first noise reduction value to achieve noise reduction processing of the stove; wherein, the first detection count is greater than the first value and not greater than the second value, and the noise reduction parameters include combustion noise.

[0050] In an embodiment of the present invention, the noise reduction execution module 200 is further configured to reduce the noise reduction parameters of the stove by means of a second noise reduction value if the individual data of the identification data obtained in the second consecutive sampling period are all of the user's absence, or the cumulative duration of the absence of the user exceeds a second time threshold. The second detection period is greater than the second value, and the noise reduction parameters include combustion noise.

[0051] To further explain, the noise reduction execution module 200 of this user-identification-based active noise reduction control device for cooktops is based on the following: when the number of consecutive samplings without a user in the kitchen area falls within the range greater than a first value and not greater than a second value, or the cumulative time without a user is between a first time threshold and a second time threshold, the controller adjusts the noise reduction parameters such as combustion noise according to the first noise reduction value to achieve initial noise reduction. When the number of consecutive samplings without a user in the kitchen area exceeds the second value, or the cumulative time without a user exceeds the second time threshold, the controller further adjusts the combustion noise and other parameters according to the second noise reduction value to perform deep noise reduction.

[0052] In the embodiments of the present invention, the human body recognition element is an infrared sensor, a microwave sensor, an ultrasonic sensor, an image sensor, a radar sensor, or a photoelectric sensor.

[0053] Example 3: Based on the same inventive concept as other embodiments, this embodiment is a computer-readable storage medium storing a computer program / instruction thereon, which, when executed by a processor, implements the steps of the active noise reduction control method for stoves based on user identification described in Embodiment 1.

[0054] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0055] In the description of this application, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, features defined with "first" and "second" may explicitly or implicitly include one or more features.

[0056] The above provides a detailed description of an active noise reduction control method for stoves based on user identification, according to one embodiment of this application. Specific examples have been used to illustrate the principles and implementation methods of this application. The description of the above embodiments is only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A user-identification-based active noise reduction control method for cooktops, applied in a kitchen area, wherein the kitchen area includes a cooktop and a controller for controlling the cooktop to reduce noise, characterized in that, At least one human body recognition element is installed in the kitchen area to identify the presence of a user. The controller is connected to the human body recognition element. The active noise reduction control method for the stove includes the following steps: The identification data within the kitchen area is acquired through the human body recognition element according to the sampling period. The identification data includes human body feature data and detection time. If the individual data obtained in multiple consecutive sampling cycles are all of the user not existing, or the cumulative duration of the user not existing exceeds a time threshold, then the controller will control the stove to perform noise reduction processing. The cumulative duration of user absence is the cumulative duration between the detection time corresponding to the first detection of user absence and the detection time corresponding to the last detection of user absence.

2. The active noise reduction control method for cooktops based on user identification according to claim 1, characterized in that, If, in multiple consecutive sampling periods, all individual data points indicate that the user does not exist, or if the cumulative duration of user absence exceeds a time threshold, then the controller will control the stove to perform noise reduction processing, including: If all individual data in the identification data obtained in the sampling period of the first consecutive detection count are users that do not exist, or if the cumulative duration of users not existing exceeds the first time threshold but is less than the second time threshold, then the controller adjusts the noise reduction parameter of the stove according to the first noise reduction value to achieve noise reduction processing of the stove. If all individual data in the identification data obtained in the sampling period of the second consecutive detection cycle are users that do not exist, or if the cumulative duration of users not existing exceeds the second time threshold, then the controller adjusts the noise reduction parameter of the stove according to the second noise reduction value to achieve noise reduction processing of the stove. Wherein, the first number of detections is greater than a first value and not greater than a second value, the second number of detections is greater than a second value, and the noise reduction parameters include combustion noise.

3. The active noise reduction control method for cooktops based on user identification according to claim 2, characterized in that, The first noise reduction value is 10 dB, and the second noise reduction value is 20 dB; and / or, the first value is 3 times, the second value is 5 times, the first time threshold is 7 minutes, and the second time threshold is 11 minutes.

4. The active noise reduction control method for cooktops based on user identification according to any one of claims 1-3, characterized in that, The human body recognition element is an infrared sensor, microwave sensor, ultrasonic sensor, image sensor, radar sensor, or photoelectric sensor.

5. The active noise reduction control method for cooktops based on user identification according to any one of claims 1-3, characterized in that, The controller includes a control module and an active noise reduction module, a wireless communication module, and a human-computer interaction module connected to the control module. The human body recognition element is connected to the control module. The active noise reduction module includes a noise reduction processing chip and a wave-emitting anti-phase element connected to the noise reduction processing chip. The wireless communication module is used to communicate with the stove. The control module is used to control the active noise reduction module to output a noise reduction signal through the noise reduction processing chip and the transmitting anti-phase acoustic wave element according to the recognition data of the human body recognition element, and to transmit the noise reduction signal to the stove through the wireless communication module for noise reduction operation; The human-computer interaction module is used to display the identification data of the stove.

6. A user-identification-based active noise reduction control device for a cooktop, applied in a kitchen area, the kitchen area including a cooktop and a controller for controlling the cooktop to reduce noise, characterized in that, At least one human body recognition element is installed in the kitchen area to identify the presence of a user. The controller is connected to the human body recognition element. The active noise reduction control device for the stove includes a data acquisition module and a noise reduction execution module. The data acquisition module is used to acquire recognition data in the kitchen area through the human body recognition element according to the sampling period. The recognition data includes human body feature data and detection time. The noise reduction execution module is used to control the stove to perform noise reduction processing through the controller if the individual data of the identification data obtained in multiple consecutive sampling cycles are all of the user's absence, or the cumulative time of the user's absence exceeds a time threshold. The cumulative duration of user absence is the cumulative duration between the detection time corresponding to the first detection of user absence and the detection time corresponding to the last detection of user absence.

7. The active noise reduction control device for cooktops based on user identification according to claim 6, characterized in that, The noise reduction execution module is further configured to, based on the sampling period obtained from the first consecutive detection count, determine if all individual data in the identification data are of users not existing, or if the cumulative duration of user non-existence exceeds a first time threshold but is less than a second time threshold. In this case, the controller adjusts the noise reduction parameters of the stove by a first noise reduction value to achieve noise reduction processing of the stove. The first detection count is greater than a first value but not greater than a second value, and the noise reduction parameters include combustion noise.

8. The active noise reduction control device for cooktops based on user identification according to claim 6, characterized in that, The noise reduction execution module is also used to reduce the noise reduction parameters of the stove by the controller according to the second noise reduction value if the individual data of the identification data obtained in the sampling period of the second consecutive detection period are all of the user's absence, or the cumulative time of the user's absence exceeds the second time threshold, so as to realize the noise reduction processing of the stove; wherein, the second detection period is greater than the second value, and the noise reduction parameters include combustion noise.

9. The active noise reduction control device for cooktops based on user identification according to claim 6, characterized in that, The human body recognition element is an infrared sensor, microwave sensor, ultrasonic sensor, image sensor, radar sensor, or photoelectric sensor.

10. A computer-readable storage medium having a computer program / instructions stored thereon, characterized in that, When executed by a processor, the computer program / instructions implement the steps of the active noise reduction control method for cooktops based on user identification as described in any one of claims 1-5.

Images