Range hood and range hood control method and device

Abstract

The invention discloses a range hood and a range hood control method and device, and belongs to the technical field of kitchen appliances. The range hood comprises a plurality of gesture detection modules and a controller, wherein each gesture detection module comprises at least one laser transmitter and at least one receiver; the controller is used for controlling the laser transmitter of each gesture detection module to transmit a laser signal to the target direction of the range hood, and receiving a reflected light signal formed by reflecting the laser signal through the hand of the user through the receiver; and identifying a user gesture according to the time difference between the reflected light signal and the laser signal corresponding to each gesture detection module, and generating a control instruction corresponding to the user gesture to control the running state of the range hood. The non-contact control of the range hood can be realized, and the operation convenience of the range hood is improved.

Description

Technical Field

[0001] This application belongs to the field of kitchen appliance technology, and in particular relates to a range hood, a range hood control method and device. Background Technology

[0002] The core function of a range hood is to generate negative pressure through an internal fan system, capture oil fumes, gas exhaust gases, and suspended particulate matter produced during cooking, and then exhaust them outdoors through exhaust pipes, thereby improving kitchen air quality.

[0003] In related technologies, range hoods generally adopt a contact-based human-machine interaction solution, that is, buttons are set on the front or top surface of the casing, and users can control the range hood by directly pressing or touching the buttons with their fingers. However, during the cooking process, users' hands are usually contaminated with oil, water stains, flour and other stains, and users usually need to clean their hands before controlling the range hood by touch, which brings inconvenience to the user. Summary of the Invention

[0004] This application aims to at least solve one of the technical problems existing in the prior art. To this end, this application proposes a smoke hood, a smoke hood control method, and a device to achieve non-contact control of the smoke hood and improve the convenience of smoke hood operation.

[0005] In a first aspect, this application provides a range hood, which includes multiple gesture detection modules and a controller, each gesture detection module including at least one laser emitter and at least one receiver; The controller controls the laser emitters of each gesture detection module to emit laser signals toward the target direction of the smoke machine, and receives the reflected light signal formed by the laser signal after being reflected by the user's hand through the receiver; it identifies the user's gesture based on the time difference between the reflected light signal and the laser signal corresponding to each gesture detection module, and generates control commands corresponding to the user's gesture to control the operating status of the smoke machine.

[0006] According to the range hood of this application, by configuring a collaborative control architecture consisting of multiple gesture detection modules and a controller, each gesture detection module integrates at least one laser emitter and at least one receiver. The controller can uniformly schedule and process signals for each gesture detection module, drive the laser emitter to emit laser signals in the target direction of the range hood, and collect the reflected light signals formed by the user's hand reflection through the receiver. Then, based on the time difference between the laser signals and reflected light signals of each gesture detection module, the spatial position information of the hand under the viewpoint of different gesture detection modules is calculated, thereby realizing the recognition of the user's gestures and generating corresponding control commands to adjust the operating state of the range hood. This achieves non-contact control of the range hood, reduces the problem of oil stains from the user's hands contaminating the range hood components during cooking, and improves the convenience of operating the range hood and the accuracy of gesture recognition.

[0007] According to one embodiment of this application, multiple gesture detection modules are arranged at intervals along the length of the smoke machine.

[0008] In this embodiment, by arranging multiple gesture detection modules at intervals along the length of the range hood, the detection range of each gesture detection module covers and overlaps the length of the range hood. This allows at least one gesture detection module to capture the reflected light signal of the user's hand when the user performs gesture operations at different lateral positions on the range hood, further improving the convenience of range hood operation and the accuracy of gesture recognition.

[0009] According to one embodiment of this application, the distance between adjacent gesture detection modules satisfies:

[0010] in, This indicates the distance between adjacent gesture detection modules. Represents the speed of light. The minimum effective duration of the gesture is indicated by , and k represents a coefficient related to the installation height of the range hood.

[0011] In this embodiment, the distance between adjacent gesture detection modules takes into account the propagation characteristics of the speed of light, the temporal characteristics of gesture movements, and the impact of the installation height of the smoke machine on the detection range. This makes the detection area of ​​adjacent gesture detection modules more reasonably covered in the length direction of the smoke machine, reducing both the problem of blind spots in gesture recognition caused by excessive spacing and the waste of resources and signal interference caused by insufficient spacing.

[0012] According to one embodiment of this application, the value of k is calculated according to the following formula:

[0013] Where h represents the actual installation height of the range hood. This indicates the standard installation height of the range hood.

[0014] In this embodiment, through the calculation of the above-mentioned k value, the spacing between adjacent gesture detection modules can be dynamically adjusted according to the change of the actual installation height of the smoke machine relative to the standard installation height, so that the detection range of the gesture detection module matches the user operation area in the actual installation scenario, providing sufficient spatiotemporal sampling density and redundancy for the recognition of user gestures.

[0015] According to one embodiment of this application, the distance between adjacent gesture detection modules is 5-30 cm.

[0016] In this embodiment, by limiting the distance between adjacent gesture detection modules to 5–30 cm, a high-density, low-blind-zone detection array can be formed along the length of the cigarette machine. This allows the laser fields of view of adjacent gesture detection modules to overlap sufficiently, reducing signal gaps caused by excessive spacing. Even if the user's hand moves quickly and with small amplitude, it can be continuously captured by at least two modules, thereby improving the accuracy of gesture timing feature acquisition.

[0017] According to one embodiment of this application, the emission angle of the laser emitter of each gesture detection module satisfies:

[0018] in, Indicates the emission angle of the laser emitter. This indicates the distance between adjacent gesture detection modules. The value represents the overlap width of the detection areas of adjacent gesture detection modules, and L represents the vertical distance from the smoke machine to the preset gesture detection area.

[0019] In this embodiment, the emission angle of the laser emitter is calculated in the above manner, so that the laser fan-shaped fields of adjacent gesture detection modules exactly form a field-of-view overlap band with a width of Omin at a distance L. This allows the user's hand to seamlessly sample signals when crossing the boundary of adjacent gesture detection modules, further improving the accuracy of gesture recognition.

[0020] According to one embodiment of this application, the emission angle of the laser emitter is 10°-35°.

[0021] In this embodiment, by limiting the emission angle of the laser emitter to the range of 10°–35°, a detection zone with a width of about 10–25 cm and adjacent fields of view that exactly overlap can be formed in front of the smoke machine. This reduces the problem of insufficient effective detection area caused by the fan being too narrow, and also reduces the problem of energy dispersion caused by the fan being too wide, thereby further improving the accuracy of gesture recognition.

[0022] According to one embodiment of this application, user gestures are identified based on the time difference between the reflected light signal and the laser signal corresponding to each gesture detection module, including: A depth map, including the user's hand, is generated based on the time difference between the laser signal and the reflected light signal. The user's gestures are obtained by recognizing the depth maps at multiple consecutive time points corresponding to each gesture detection module.

[0023] In this embodiment, by acquiring depth maps at multiple consecutive moments, the spatial position and shape changes of the user's hand at different points in time can be captured, and the dynamic change process of the hand can be reconstructed from the time dimension. Furthermore, by combining the depth maps at multiple consecutive moments corresponding to multiple gesture detection modules, the geometric shape and motion trajectory of the hand from different perspectives can be integrated, thereby improving the accuracy of user gesture recognition.

[0024] Secondly, this application provides a method for controlling a range hood, the range hood including multiple gesture detection modules and a controller, each gesture detection module including at least one laser emitter and at least one receiver; the method includes: The laser emitter of each gesture detection module emits a laser signal toward the target direction of the cigarette machine, and the receiver receives the reflected light signal formed by the laser signal after being reflected by the user's hand. User gestures are identified based on the time difference between the reflected light signal and the laser signal corresponding to each gesture detection module. Generate control commands corresponding to user gestures to control the operation of the range hood.

[0025] According to the range hood control method of this application, by configuring a collaborative control architecture consisting of multiple gesture detection modules and a controller in the range hood, each gesture detection module integrates at least one laser emitter and at least one receiver, the method can perform unified instruction scheduling and signal processing for each gesture detection module, drive the laser emitter to emit laser signals in the target direction of the range hood, and collect the reflected light signals formed by the user's hand reflection through the receiver. Then, based on the time difference between the laser signals and reflected light signals of each gesture detection module, the spatial position information of the hand under the viewpoint of different gesture detection modules is calculated, thereby realizing the recognition of the user's gestures and generating corresponding control commands to adjust the operating state of the range hood. This achieves non-contact control of the range hood, reduces the problem of oil and grease from the user's hands contaminating the range hood components during cooking, and improves the convenience of range hood operation and the accuracy of gesture recognition.

[0026] Thirdly, this application provides a smoke hood control device, the smoke hood including multiple gesture detection modules and a controller, each gesture detection module including at least one laser emitter and at least one receiver; the device includes: The control module is used to control the laser emitters of each gesture detection module to emit laser signals in the target direction of the smoke machine, and to receive the reflected light signal formed by the laser signal after being reflected by the user's hand through the receiver; The recognition module is used to identify user gestures based on the time difference between the reflected light signal and the laser signal corresponding to each gesture detection module; The generation module is used to generate control commands corresponding to user gestures to control the operating status of the range hood.

[0027] According to the range hood control device of this application, by configuring a collaborative control architecture consisting of multiple gesture detection modules and a controller in the range hood, each gesture detection module integrates at least one laser emitter and at least one receiver, the device can perform unified instruction scheduling and signal processing for each gesture detection module, drive the laser emitter to emit laser signals in the target direction of the range hood, and collect the reflected light signals formed by the user's hand reflection through the receiver. Then, based on the time difference between the laser signals and reflected light signals of each gesture detection module, the spatial position information of the hand under the viewpoint of different gesture detection modules is calculated, thereby realizing the recognition of the user's gestures and generating corresponding control commands to adjust the operating state of the range hood. This achieves non-contact control of the range hood, reduces the problem of oil stains from the user's hands contaminating the range hood components during cooking, and improves the convenience of range hood operation and the accuracy of gesture recognition.

[0028] Fourthly, this application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the smoke hood control method as described in the second aspect above.

[0029] Fifthly, this application provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the smoke machine control method as described in the second aspect above.

[0030] The above-described one or more technical solutions in the embodiments of this application have at least one of the following technical effects: According to the range hood of this application, by configuring a collaborative control architecture consisting of multiple gesture detection modules and a controller, each gesture detection module integrates at least one laser emitter and at least one receiver. The controller can uniformly schedule and process signals for each gesture detection module, drive the laser emitter to emit laser signals in the target direction of the range hood, and collect the reflected light signals formed by the user's hand reflection through the receiver. Then, based on the time difference between the laser signals and reflected light signals of each gesture detection module, the spatial position information of the hand under the viewpoint of different gesture detection modules is calculated, thereby realizing the recognition of the user's gestures and generating corresponding control commands to adjust the operating state of the range hood. This achieves non-contact control of the range hood, reduces the problem of oil stains from the user's hands contaminating the range hood components during cooking, and improves the convenience of operating the range hood and the accuracy of gesture recognition.

[0031] In some embodiments, by arranging multiple gesture detection modules at intervals along the length of the range hood, the detection range of each gesture detection module covers and overlaps the length of the range hood. This allows at least one gesture detection module to capture the reflected light signal of the user's hand when the user performs gesture operations at different lateral positions on the range hood, further improving the convenience of range hood operation and the accuracy of gesture recognition.

[0032] In some embodiments, the distance between adjacent gesture detection modules takes into account the propagation characteristics of the speed of light, the temporal characteristics of gesture actions, and the impact of the installation height of the smoke machine on the detection range. This makes the coverage area of ​​the detection area of ​​adjacent gesture detection modules in the length direction of the smoke machine more reasonable, which reduces the problem of gesture recognition blind spots caused by excessive spacing, and also reduces the waste of resources and signal interference caused by insufficient spacing.

[0033] In some embodiments, through the calculation of the above-mentioned k value, the spacing between adjacent gesture detection modules can be dynamically adjusted as the actual installation height of the range hood changes relative to the standard installation height, so that the detection range of the gesture detection module matches the user operation area in the actual installation scenario, providing sufficient spatiotemporal sampling density and redundancy for the recognition of user gestures.

[0034] In some embodiments, by limiting the distance between adjacent gesture detection modules to 5–30 cm, a high-density, low-blind-zone detection array can be formed along the length of the cigarette machine, so that the laser fields of view of adjacent gesture detection modules can overlap sufficiently, reducing signal gaps caused by excessive spacing. Even if the user's hand moves quickly and with small amplitude, it can be continuously captured by at least two modules, thereby improving the accuracy of gesture timing feature acquisition.

[0035] In some embodiments, the emission angle of the laser emitter is calculated in the manner described above, so that the laser fan surfaces of adjacent gesture detection modules form a field of view overlap band with a width of Omin at a distance L. This allows the user's hand to seamlessly sample signals when crossing the boundary of adjacent gesture detection modules, further improving the accuracy of gesture recognition.

[0036] In some embodiments, by limiting the emission angle of the laser emitter to the range of 10°–35°, a detection zone with a width of about 10–25 cm and adjacent fields of view exactly overlapping can be formed in front of the smoke machine. This reduces the problem of insufficient effective detection area caused by the fan being too narrow, and also reduces the problem of energy dispersion caused by the fan being too wide, thereby further improving the accuracy of gesture recognition.

[0037] In some embodiments, by acquiring depth maps at multiple consecutive moments, the spatial position and shape changes of the user's hand at different points in time can be captured, the dynamic change process of the hand can be reconstructed from the time dimension, and the depth maps at multiple consecutive moments corresponding to multiple gesture detection modules can be analyzed to integrate the geometric shape and motion trajectory from different perspectives, thereby improving the accuracy of user gesture recognition.

[0038] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0039] The above and / or additional aspects and advantages of this application will become apparent and readily understood in conjunction with the following description of the embodiments in conjunction with the accompanying drawings, wherein: Figure 1 This is a schematic diagram of the structure of the range hood provided in the embodiments of this application; Figure 2 This is a flowchart illustrating the smoke hood control method provided in an embodiment of this application; Figure 3 This is a schematic diagram of the structure of the smoke machine control device provided in the embodiments of this application; Figure 4 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0040] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0041] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such use of data can be interchanged where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and the number of objects is not limited; for example, a first object can be one or more. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0042] The following description, in conjunction with the accompanying drawings, details the range hood, range hood control method, and device provided in this application through specific embodiments and application scenarios.

[0043] A range hood, also known as a kitchen exhaust hood, is an essential piece of equipment in the kitchen used to remove cooking fumes and exhaust gases, maintaining fresh air in the kitchen. A range hood can include components such as a fan system, exhaust duct, control panel, air inlet, and air outlet. The air inlet is the part of the range hood that absorbs cooking fumes and exhaust gases; it is usually located at the bottom or side of the range hood, close to the stove, to capture the fumes generated during cooking. The air outlet is located at the top or rear of the range hood, expelling the absorbed fumes and exhaust gases outdoors through the exhaust duct. The fan system, as the core power component of the range hood, consists of a motor and an impeller. When the motor drives the impeller to rotate at high speed, a negative pressure area is created inside the fan. This pressure difference draws the cooking fumes into the machine and then exhausts them outdoors through the air outlet and exhaust duct. The control panel allows users to interact with the range hood. Users can control the range hood's on / off function, fan speed adjustment, lighting, and other functions through physical buttons or a touch interface on the control panel. In this embodiment, users can also control the range hood's on / off function, fan speed adjustment, lighting, and other functions through gestures. like Figure 1 As shown, the smoke hood 100 in this embodiment of the application includes a plurality of gesture detection modules 110 and a controller 120, and each gesture detection module includes at least one laser emitter 101 and at least one receiver 102; The controller 120 is used to control the laser emitter 101 of each gesture detection module 110 to emit laser signals in the target direction of the smoke machine 100, and to receive the reflected light signal formed by the laser signal after being reflected by the user's hand through the receiver 102; to identify the user's gesture based on the time difference between the reflected light signal and the laser signal corresponding to each gesture detection module 110, and to generate control commands corresponding to the user's gesture to control the operating status of the smoke machine.

[0044] In this embodiment, the gesture detection module 110 is a sensing unit for the range hood to achieve gesture recognition and control, mainly including a laser emitter 101 and a receiver 102. The laser emitter 101 is a device capable of emitting laser signals of a specific wavelength, such as a vertical-cavity surface-emitting laser (VCSEL). The laser emitter 101 can emit laser pulses at a pulse repetition frequency under the modulation of the driving circuit. It should be noted that the peak pulse power of the laser emitter 101 has undergone safety assessment and meets human eye safety standards, ensuring no optical radiation hazard to users in daily use scenarios of the range hood.

[0045] The receiver 102 works in conjunction with the laser emitter 101 to receive the reflected light signal after being reflected by the target object. The receiver 102 includes an array of photosensitive elements capable of sensing the corresponding laser wavelength, such as CCD (Charge-Coupled Device), CMOS (Complementary Metal-Oxide-Semiconductor), SPAD (Single Photon Avalanche Diode), etc.

[0046] The gesture detection module 110 can be integrated or installed on the main body of the range hood 100, such as in the control panel area, the middle or upper part of the front of the range hood, or the area around the air inlet of the range hood. This allows users to make gestures in a natural operating range, such as above the stove, below the range hood, or in front of the range hood, without having to change their body posture significantly during cooking, so that the gesture detection module can capture the gestures.

[0047] In some embodiments, the laser emitter 101 and receiver 102 in the gesture detection module 110 can be arranged coplanarly or approximately coplanarly behind the same optical window on the inner side of the front panel of the smoke hood 100. The optical window can be closed by a narrow-band filter with high transmittance and low transmittance in the visible light band to suppress ambient light interference. Specifically, the laser emitter 101 is located 10mm–20mm to the left of the horizontal center line of the optical window, and the receiver 102 is located symmetrically to the right of the center line. Of course, the laser emitter 101 and receiver 102 can also be set in other positions, such as the lower edge of the smoke hood, facing directly in front of the smoke hood 100. This application embodiment does not limit the position of the laser emitter 101 and receiver 102.

[0048] In some embodiments, multiple gesture detection modules 110 can be spaced apart on the range hood 100. For example, gesture detection modules 110 can be respectively arranged at different positions in the direction of the front panel of the range hood 100. Multiple gesture detection modules 110 can also be arranged spaced apart along the length of the range hood, so that the gesture sensing area can cover the main range of hand movement when the user is standing. Gesture detection modules 110 can also be arranged on the side walls of the range hood 100, so that the user can perform gesture control on the range hood 100 from the side. This application embodiment does not limit the arrangement position of these multiple gesture detection modules 110.

[0049] In this embodiment, by arranging multiple gesture detection modules at intervals along the length of the range hood, the detection range of each gesture detection module covers and overlaps the length of the range hood. This allows at least one gesture detection module to capture the reflected light signal of the user's hand when the user performs gesture operations at different lateral positions on the range hood, further improving the convenience of range hood operation and the accuracy of gesture recognition.

[0050] When the range hood 100 enters a gesture recognition control mode, the controller 120 of the range hood 100 triggers the laser emitter 101 to start working, emitting a laser signal in the target direction of the range hood 100. The target direction is a pre-set and calibrated effective area for user gesture operations. For example, the target direction is directly in front of the range hood 100, and is the approximate area where the user's hands might appear when cooking in front of the stove. This could be a certain space under the smoke collection hood of the range hood 100 with the stove as the center, thus facilitating the recognition of the user's gestures in the target direction.

[0051] When a laser signal propagates to the user's hand, it is reflected, forming a reflected light signal. When the reflected light signal reaches the receiver 102, it forms a detectable electrical signal. Taking the receiver 102 as a single-photon avalanche diode as an example, when the laser signal propagates to the user's hand, it is reflected, forming a reflected light signal. When the reflected light signal reaches the photosensitive area of ​​the single-photon avalanche diode, photons are absorbed, generating electron-hole pairs. Under the influence of a strong reverse bias electric field, these initially generated electron-hole pairs undergo an avalanche multiplication effect, thereby forming a detectable electrical signal.

[0052] In this embodiment, when the controller 120 issues a command to control the laser transmitter 101 to emit a laser signal, a high-precision timer, such as a time-to-digital converter or a high-frequency counter, can be started simultaneously. The laser signal propagates towards the target direction. When the laser signal shines on the user's hand, part of the light signal is reflected back by the hand surface, forming a reflected light signal. When the receiver 102 receives the reflected light signal, it immediately generates an electrical signal, which triggers the timer to stop. The time difference between the laser signal and the reflected light signal is the time interval between the timer starting (corresponding to the laser signal emission time) and the timer stopping (corresponding to the reflected light signal being received).

[0053] Based on the time difference between the laser signal and the reflected light signal, the one-way distance of the laser signal propagation, i.e., the distance from the user's hand to the receiver 102, can be calculated. The calculation process is as follows:

[0054] Where D represents the one-way distance of the laser signal propagation, and c represents the speed of light. This represents the time difference between the laser signal and the reflected light signal.

[0055] In this embodiment of the application, the positions of receiver 102 and laser emitter 101 are usually fixed. Therefore, a coordinate system can be established based on the positions of receiver 102 and laser emitter 101, and the one-way distance of laser signal propagation can be mapped to the coordinate system as a pixel. The pixels in one frame period constitute a depth map including the user's hand.

[0056] In the embodiments of this application, user gestures are actions or postures made by the hands that have specific meanings and patterns, such as waving, hovering, clicking, swiping, drawing circles, etc.

[0057] Since kitchen walls and cabinets can also reflect light, the depth map will include pixels corresponding to the user's hand, as well as pixels corresponding to walls and cabinets. Therefore, it is necessary to segment the area containing the user's hand from the area containing walls and cabinets in the depth map, and analyze the area containing the user's hand to identify the user's gesture.

[0058] In some embodiments, a distance threshold range can be set to identify regions in the depth map that are close to the receiver 102 and conform to hand size characteristics as the region where the user's hand is located. Alternatively, region growing or deep learning models (such as semantic segmentation models based on convolutional neural networks) can be used to extract the region where the user's hand is located from the depth map.

[0059] After extracting the area where the user's hand is located, features representing the gesture type can be further extracted, such as the center point coordinates, outline, area, aspect ratio, number and posture of fingers (extended, bent), and palm orientation. For example, the "hover" gesture is characterized by the center point of the hand area remaining basically unchanged for a period of time, and the outline shape being stable; the "click" gesture is characterized by a rapid contraction and expansion of the hand outline within a short period of time.

[0060] The extracted features can be input into a classification model, which then determines which predefined user gesture the gesture belongs to. The classification model can employ classic machine learning algorithms such as Support Vector Machines, Decision Trees, and Random Forests, or it can use deep learning algorithms. Alternatively, the extracted features can be compared with the features corresponding to predefined user gestures to calculate similarity and thus determine the type of user gesture.

[0061] In some embodiments, after calculating the distance from the user's hand to the receiver 102 based on the time difference between the laser signal and the reflected light signal, a depth map may not be constructed; instead, the motion trajectory of the user's hand may be constructed based on the distance. Specifically, since multiple gesture detection modules 110 are deployed from different spatial angles according to a preset layout, the gesture detection modules 110 can simultaneously detect the distance to different reflection points of the same user's hand. Based on the known spatial coordinate positions of each gesture detection module 110, the controller 120 can perform fusion calculations on multiple sets of distance data using the principle of triangulation to construct the real-time coordinate information of the user's hand in three-dimensional space. After multiple sets of continuous three-dimensional coordinate information are arranged in a time sequence, a motion trajectory that changes with the movement of the user's hand is formed. This motion trajectory is a time-series set of coordinate points, reflecting information such as the path, direction, and speed of the hand movement.

[0062] In this method, the similarity between the motion trajectory and each gesture in a preset template library can be calculated, and the gesture with the highest similarity is identified as the user's gesture. Specifically, the template library stores standard gesture motion trajectory templates corresponding to various control functions of the range hood 100, such as "horizontal wave (used to control the range hood to start / stop)," "vertical swipe up (used to control the range hood to increase airflow)," "vertical swipe down (used to control the range hood to decrease airflow)," "clockwise rotation (used to control the range hood to turn on the lighting)," and "counterclockwise rotation (used to control the range hood to turn off the lighting)," etc. Each standard gesture motion trajectory template is motion trajectory data collected from a large number of user samples and standardized.

[0063] Trajectory features can be extracted from the motion trajectory, such as the shape of the trajectory, the direction of motion, the distance of motion, the changes in speed and acceleration, and the positional relationship between the starting and ending points of the trajectory. Trajectory features corresponding to each gesture are extracted from a template library. The similarity between the extracted trajectory features and the trajectory features corresponding to each gesture is calculated, for example, using Euclidean distance or cosine similarity. The calculated similarities are then ranked, and the gesture with the highest similarity is identified as the user's gesture.

[0064] Control commands may include power on / off, speed adjustment, lighting switch, delayed shutdown, etc. In this embodiment, the controller 120 of the range hood 100 may store a gesture command mapping table, which defines the correspondence between each user gesture and the corresponding control command. The mapping relationship may be one-to-one, one-to-many, or many-to-one. For example, a user gesture of "waving from left to right" may uniquely correspond to the command of "increasing the fan speed by one level"; a user gesture of "hovering for two seconds" may correspond to either a "power on" or "power off" command, depending on the current operating state of the range hood. For example, when the range hood is in standby mode, a user gesture of "hovering for two seconds" corresponds to the power on control command, and when the range hood is running, a user gesture of "hovering for two seconds" corresponds to the power off control command.

[0065] After determining the user's gesture, the controller 120 can match the control command corresponding to the user's gesture through the gesture command mapping table, and control the operation status of the range hood according to the control command.

[0066] According to the range hood of this application, by configuring a collaborative control architecture consisting of multiple gesture detection modules and a controller, each gesture detection module integrates at least one laser emitter and at least one receiver. The controller can uniformly schedule and process signals for each gesture detection module, drive the laser emitter to emit laser signals in the target direction of the range hood, and collect the reflected light signals formed by the user's hand reflection through the receiver. Then, based on the time difference between the laser signals and reflected light signals of each gesture detection module, the spatial position information of the hand under the viewpoint of different gesture detection modules is calculated, thereby realizing the recognition of the user's gestures and generating corresponding control commands to adjust the operating state of the range hood. This achieves non-contact control of the range hood, reduces the problem of oil stains from the user's hands contaminating the range hood components during cooking, and improves the convenience of operating the range hood and the accuracy of gesture recognition.

[0067] In some embodiments, the distance between adjacent gesture detection modules 110 satisfies:

[0068] in, This indicates the distance between adjacent gesture detection modules 110. Represents the speed of light. The minimum effective duration of the gesture is indicated by , and k represents a coefficient related to the installation height of the range hood.

[0069] In this embodiment, the minimum duration of an effective gesture It is the minimum time threshold required for a user to complete a valid gesture that can be recognized by the range hood. The value can be determined by combining the user's usual operating habits with the response characteristics of the range hood gesture recognition algorithm. Specifically, a large number of experiments can be conducted to statistically test different user gestures, collecting time data for users to complete different gestures such as "swiping up and down" and "waving left and right". The average or minimum value is used as the initial reference value, and then the initial reference value is corrected by combining the signal sampling frequency of receiver 102 and the calculation time of controller 120 in recognizing user gestures. For example, if the minimum time data for users to complete different gestures is 0.07 seconds, and controller 120 can correctly recognize user gestures with a completion time of 0.07 seconds, then the value can be adjusted accordingly. If the controller 120 cannot correctly recognize a user gesture with a completion time of 0.07 seconds, it can be tested to determine the minimum completion time at which the controller 120 can correctly recognize the user gesture, for example, 0.08 seconds. The time was set at 0.08 seconds.

[0070] The value of k ranges from (0, 1] and is related to the installation height of the range hood 100. It is used to compensate for the difference in the relative position between the user's hand operation area and the gesture detection module 110 under different installation heights. When the installation height of the range hood 100 is high, the vertical distance between the user's hand operation area and the gesture detection module increases, and the value of k is greater than 1; when the installation height of the range hood is low, the user's hand operation area is closer to the gesture detection module, and the value of k is less than 1.

[0071] It should be noted that the gesture detection module 110 can be fixedly installed on the range hood 100 or movably installed on the range hood 100. If the gesture detection module 110 is movably installed on the range hood 100, after the range hood 100 is actually installed in the kitchen, the k value can be determined according to the actual installation height of the range hood, and the distance between adjacent gesture detection modules 110 can be adjusted. If the gesture detection module 110 is fixedly installed on the range hood 100, a standard installation height for the range hood can be predetermined, and then the k value can be determined according to the standard installation height, thereby calculating the distance between adjacent gesture detection modules 110.

[0072] by Taking 0.08 seconds and k = 0.8 as an example, the speed of light =3×10 8 Meters per second (m / s) Substituting into the above formula, we calculate d = 0.096 meters, meaning the distance between adjacent gesture detection modules is 9.6 centimeters.

[0073] In this embodiment, the distance between adjacent gesture detection modules takes into account the propagation characteristics of the speed of light, the temporal characteristics of gesture movements, and the impact of the installation height of the smoke machine on the detection range. This makes the detection area of ​​adjacent gesture detection modules more reasonably covered in the length direction of the smoke machine, reducing both the problem of blind spots in gesture recognition caused by excessive spacing and the waste of resources and signal interference caused by insufficient spacing.

[0074] In some embodiments, the value of k is calculated according to the following formula:

[0075] Where h represents the actual installation height of the range hood. This indicates the standard installation height of the range hood.

[0076] In this embodiment, through the calculation of the above-mentioned k value, the spacing between adjacent gesture detection modules can be dynamically adjusted according to the change of the actual installation height of the smoke machine relative to the standard installation height, so that the detection range of the gesture detection module matches the user operation area in the actual installation scenario, providing sufficient spatiotemporal sampling density and redundancy for the recognition of user gestures.

[0077] In some embodiments, the distance between adjacent gesture detection modules is 5-30 cm.

[0078] In this embodiment, by limiting the distance between adjacent gesture detection modules to 5–30 cm, a high-density, low-blind-zone detection array can be formed along the length of the cigarette machine. This allows the laser fields of view of adjacent gesture detection modules to overlap sufficiently, reducing signal gaps caused by excessive spacing. Even if the user's hand moves quickly and with small amplitude, it can be continuously captured by at least two modules, thereby improving the accuracy of gesture timing feature acquisition.

[0079] In some embodiments, the emission angle of the laser emitter of each gesture detection module satisfies:

[0080] in, Indicates the emission angle of the laser emitter. This indicates the distance between adjacent gesture detection modules. The value represents the overlap width of the detection areas of adjacent gesture detection modules, and L represents the vertical distance from the smoke machine to the preset gesture detection area.

[0081] The overlap width of the detection areas of adjacent gesture detection modules It can be preset, for example, 5 cm to 10 cm, so that the user's hand movements can be captured by two gesture detection modules within the overlapping area.

[0082] The vertical distance from the range hood to the preset gesture detection area can be preset. For example, the range hood can be preset to detect gestures within 1 meter of the range hood, and the vertical distance L from the range hood to the preset gesture detection area can be set to 1 meter.

[0083] In this embodiment, the emission angle of the laser emitter The angle between the central optical axis of the laser emitter and the vertical direction of the smoke hood panel. In determining... , After adding L, the launch angle can be calculated using the formula above. .

[0084] With a distance d between adjacent gesture detection modules of 0.1 meters and the overlap width of the detection areas of adjacent gesture detection modules... Taking a distance of 0.05 meters and a vertical distance L of 1 meter from the range hood to the preset gesture detection area as an example, .

[0085] In this embodiment, the emission angle of the laser emitter is calculated in the above manner, so that the laser fan-shaped fields of adjacent gesture detection modules exactly form a field-of-view overlap band with a width of Omin at a distance L. This allows the user's hand to seamlessly sample signals when crossing the boundary of adjacent gesture detection modules, further improving the accuracy of gesture recognition.

[0086] In some embodiments, the emission angle of the laser emitter is 10°-35°.

[0087] In this embodiment, by limiting the emission angle of the laser emitter to the range of 10°–35°, a detection zone with a width of about 10–25 cm and adjacent fields of view that exactly overlap can be formed in front of the smoke machine. This reduces the problem of insufficient effective detection area caused by the fan being too narrow, and also reduces the problem of energy dispersion caused by the fan being too wide, thereby further improving the accuracy of gesture recognition.

[0088] In some embodiments, recognizing a user's gesture based on the time difference between the reflected light signal and the laser signal corresponding to each gesture detection module 110 includes: A depth map, including the user's hand, is generated based on the time difference between the laser signal and the reflected light signal. The user's gesture is obtained by recognizing the depth maps of multiple consecutive time points corresponding to each gesture detection module 110.

[0089] In this embodiment, the distance D from each position of the user's hand to the receiver 102 can be calculated based on the time difference between the laser signal and the reflected light signal. The positions of the receiver 102 and the laser transmitter 101 are usually fixed. Therefore, the one-way distance of the laser signal propagation can be mapped to points in the three-dimensional world coordinate system as points of point cloud data by combining the positions of the receiver 102 and the laser transmitter 101.

[0090] Specifically, to construct the three-dimensional coordinates of the point cloud data, taking receiver 102 as a single-photon avalanche diode as an example, the inherent position information of each pixel can be combined. Specifically, each pixel has predefined two-dimensional coordinates (u, v), which typically have the top-left corner of the single-photon avalanche diode array as the origin, with the u-axis pointing horizontally to the right and the v-axis pointing vertically downwards. These coordinates can be the row and column indices of the pixel; for example, the pixel in the i-th row and j-th column can have coordinates represented as (i, j), or they can be calibrated physical coordinates, for example, in millimeters, representing the horizontal and vertical offset of the pixel center relative to the array origin.

[0091] Using the two-dimensional coordinates (u, v) of a pixel and the corresponding distance d, and combining the intrinsic parameters of a single-photon avalanche diode, the coordinates (X, Y, Z) of the reflection point corresponding to each pixel in the three-dimensional world coordinate system are calculated through geometric transformation. The intrinsic parameters may include, but are not limited to: the physical size of the pixel (such as pixel pitch), effective focal length, principal point coordinates (the intersection of the optical axis and the sensor plane), etc., and can be obtained in advance through a pre-calibration process.

[0092] In one example, point cloud data can be calculated based on the following simplified geometric transformation model: assuming that the origin of the 3D world coordinate system coincides with the optical center of the single-photon avalanche diode array, the Z-axis is perpendicular to the array plane and points in the user direction (i.e., the depth direction), the X-axis is horizontal to the right, and the Y-axis is vertically downward.

[0093] X = ((u - c_u) × s_x ) × D / f Y = ( (v - c_v) × s_y ) × D / f Z = D Where: (c_u, c_v) represent the principal point coordinates; s_x and s_y represent the physical dimensions of the pixel in the u-axis and v-axis directions, respectively; f represents the effective focal length; and D represents the radial distance from the point on the user's hand surface to the single-photon avalanche diode.

[0094] Through the above transformation, the pixels in the single-photon avalanche diode array can be converted into points (X, Y, Z) in three-dimensional space. The set of all three-dimensional points constitutes point cloud data that can characterize the position, contour and shape of the user's hand in three-dimensional space.

[0095] The 3D point cloud data can be orthogonally projected onto an X–Y reference plane parallel to the front panel of the range hood, and voxelized using a grid of preset size. The Z-axis mean value of each point within the grid is calculated to generate an 8-bit grayscale depth map. The grayscale values ​​in the depth map correspond to the depth range, and the area where the user's hand is located can be highlighted in the image. In the above manner, depth maps of multiple consecutive time points corresponding to each gesture detection module 110 can be obtained, that is, each gesture detection module 110 corresponds to a depth map time series.

[0096] After obtaining the depth image time series, the positional changes of the user's hand can be extracted and tracked from the depth image time series, thereby identifying the motion trajectory.

[0097] Specifically, for each frame of the depth map in a depth image time series, the hand region can be located using a hand detection algorithm. For example, the depth map provides distance information, and the hand region appears as a connected region with a significant depth difference from the background. Analyzing the distance information in the depth map allows for the location of the hand region. After detecting the hand region, the coordinates of its center point can be extracted as the representative position of the hand in that frame's depth map. Tracking algorithms, such as Kalman filtering, particle filtering, or deep learning-based tracking models, can be used to associate the hand region detected in the current frame's depth map with the hand region tracked in the previous frame's depth map, thereby tracking the same hand in consecutive frame depth maps.

[0098] In addition to tracking the overall center point of the hand, feature points such as fingertips and knuckles can be extracted within the hand region. By matching these feature points across consecutive depth maps, the movement and posture changes of the hand can be described more accurately. By recording the coordinates of the hand's center point or other feature points in multiple consecutive depth maps and connecting these coordinates in chronological order, the user's hand's motion trajectory in space can be generated. This trajectory is a temporal set of coordinate points that reflects information such as the path, direction, and speed of the hand's movement.

[0099] It can calculate the similarity between the motion trajectory and each gesture in the preset template library. The template library stores standard gesture motion trajectory templates corresponding to all control functions of the range hood, such as "horizontal wave (for controlling the range hood to start / stop)," "vertical swipe up (for controlling the range hood to increase airflow)," "vertical swipe down (for controlling the range hood to decrease airflow)," "clockwise rotation (for controlling the range hood to turn on the lights)," and "counterclockwise rotation (for controlling the range hood to turn off the lights)," etc. Each standard gesture motion trajectory template is motion trajectory data collected from a large number of user samples and standardized.

[0100] Trajectory features can be extracted from the motion trajectory, such as the shape of the trajectory, the direction of motion, the distance of motion, the changes in speed and acceleration, and the positional relationship between the starting and ending points of the trajectory. Trajectory features corresponding to each gesture are extracted from a template library. The similarity between the extracted trajectory features and the trajectory features corresponding to each gesture is calculated, for example, using Euclidean distance or cosine similarity. Thus, based on the depth map time series corresponding to different gesture detection modules 110, the similarity between different gesture detection modules 110 can be calculated. The user gesture recognition result is obtained by combining the similarity scores from different gesture detection modules 110.

[0101] For example, the similarity of all gesture detection modules 110 can be compared, and the gesture with the highest similarity in the template library can be identified as the user gesture. Alternatively, the similarity of different gesture detection modules 110 can be weighted and summed to calculate the comprehensive similarity, and the gesture with the highest comprehensive similarity can be identified as the user gesture.

[0102] In some embodiments, depth maps at multiple consecutive time points corresponding to the gesture detection module can be input into the gesture recognition model to obtain the user gestures output by the gesture recognition model.

[0103] In this embodiment, the gesture recognition model is pre-built based on deep learning algorithms. For example, convolutional neural networks, recurrent neural networks, long short-term memory networks (LSTM) can be used to build the gesture recognition model. Then, the gesture recognition model is trained so that the trained gesture recognition model can complete the task of recognizing user gestures.

[0104] During the training phase, a large number of depth image time series samples labeled with user gesture categories can be used for training. For example, different user gesture actions can be performed, and depth maps at multiple consecutive time points can be generated based on the time difference between laser signals and reflected light signals to form depth image time series samples. For each depth image time series, a label representing the user gesture category can be established.

[0105] During training, the loss value between the predicted value of the user's gesture output and the label is calculated. Based on the loss value, the internal parameters of the gesture recognition model are continuously adjusted through the backpropagation algorithm to minimize the error between its predicted output and the label. After sufficient training, the gesture recognition model has the ability to analyze and recognize user gestures from new and unseen depth image time series.

[0106] In this embodiment, depth maps from multiple consecutive time points corresponding to the gesture detection module can be input into the trained gesture recognition model. The gesture recognition model processes the time series of the depth image layer by layer and outputs the user's gesture. For example, the gesture recognition model can extract spatial features through structures such as convolutional layers to capture local features and shape information in the depth map; then, it can capture the temporal dynamic information in the time series of the depth map through structures such as recurrent layers to understand the temporal features of hand movements. Finally, the output layer of the gesture recognition model outputs a probability distribution, where each probability value corresponds to a user gesture, and the user gesture with the highest probability can be selected as the recognition result of the gesture recognition model.

[0107] In this embodiment, by acquiring depth maps at multiple consecutive moments, the spatial position and shape changes of the user's hand at different points in time can be captured, and the dynamic change process of the hand can be reconstructed from the time dimension. Furthermore, by combining the depth maps at multiple consecutive moments corresponding to multiple gesture detection modules, the geometric shape and motion trajectory of the hand from different perspectives can be integrated, thereby improving the accuracy of user gesture recognition.

[0108] This application also provides a method for controlling a range hood. The subject executing the method can be an electronic device or a functional module or entity in an electronic device that can implement the method. For example, the electronic devices mentioned in this application include, but are not limited to, a range hood controller, a gesture detection module, and a server. The following description uses an electronic device as the subject of execution to illustrate the method for controlling a range hood provided in this application.

[0109] like Figure 2 As shown, the smoke hood includes multiple gesture detection modules and a controller. Each gesture detection module includes at least one laser emitter and at least one receiver. The smoke hood control method includes steps 210, 220 and 230.

[0110] Step 210: Control the laser emitter of each gesture detection module to emit laser signals in the target direction of the cigarette machine, and receive the reflected light signal formed by the laser signal after being reflected by the user's hand through the receiver; Step 220: Identify user gestures based on the time difference between the reflected light signal and the laser signal corresponding to each gesture detection module; Step 230: Generate control commands corresponding to user gestures to control the operating status of the range hood.

[0111] According to the range hood control method of this application, by configuring a collaborative control architecture consisting of multiple gesture detection modules and a controller in the range hood, each gesture detection module integrates at least one laser emitter and at least one receiver, the method can perform unified instruction scheduling and signal processing for each gesture detection module, drive the laser emitter to emit laser signals in the target direction of the range hood, and collect the reflected light signals formed by the user's hand reflection through the receiver. Then, based on the time difference between the laser signals and reflected light signals of each gesture detection module, the spatial position information of the hand under the viewpoint of different gesture detection modules is calculated, thereby realizing the recognition of the user's gestures and generating corresponding control commands to adjust the operating state of the range hood. This achieves non-contact control of the range hood, reduces the problem of oil and grease from the user's hands contaminating the range hood components during cooking, and improves the convenience of range hood operation and the accuracy of gesture recognition.

[0112] The exhaust fan control method provided in this application can be executed by an exhaust fan control device. This application uses an exhaust fan control device executing the exhaust fan control method as an example to illustrate the exhaust fan control device provided in this application.

[0113] This application also provides a range hood control device, which includes multiple gesture detection modules and a controller. Each gesture detection module includes at least one laser emitter and at least one receiver.

[0114] like Figure 3 As shown, the smoke hood control device includes: The control module 310 is used to control the laser emitters of each gesture detection module to emit laser signals toward the target direction of the cigarette machine, and to receive the reflected light signal formed by the laser signal after being reflected by the user's hand through the receiver; The recognition module 320 is used to recognize user gestures based on the time difference between the reflected light signal and the laser signal corresponding to each gesture detection module. The generation module 330 is used to generate control commands corresponding to user gestures to control the operating status of the range hood.

[0115] According to the range hood control device of this application, by configuring a collaborative control architecture consisting of multiple gesture detection modules and a controller in the range hood, each gesture detection module integrates at least one laser emitter and at least one receiver, the device can perform unified instruction scheduling and signal processing for each gesture detection module, drive the laser emitter to emit laser signals in the target direction of the range hood, and collect the reflected light signals formed by the user's hand reflection through the receiver. Then, based on the time difference between the laser signals and reflected light signals of each gesture detection module, the spatial position information of the hand under the viewpoint of different gesture detection modules is calculated, thereby realizing the recognition of the user's gestures and generating corresponding control commands to adjust the operating state of the range hood. This achieves non-contact control of the range hood, reduces the problem of oil stains from the user's hands contaminating the range hood components during cooking, and improves the convenience of range hood operation and the accuracy of gesture recognition.

[0116] The control device for the range hood in this application embodiment can be an electronic device or a component within an electronic device, such as an integrated circuit or a chip. The electronic device can be a terminal or other devices besides a terminal. For example, the electronic device can be a mobile phone, tablet computer, laptop computer, PDA, robot, wearable device, ultra-mobile personal computer (UMPC), netbook, or personal digital assistant (PDA), etc., and can also be a server, gesture detection module, controller in the range hood, functional module, etc. This application embodiment does not specifically limit the specific implementation.

[0117] The smoke hood control device in this application embodiment can be a device with an operating system. This operating system can be a Microsoft (Windows) operating system, an Android operating system, an embedded system, or other possible operating systems; this application embodiment does not specifically limit it.

[0118] In some embodiments, such as Figure 4 As shown, this application embodiment also provides an electronic device 400, including a processor 401, a memory 402, and a computer program stored in the memory 402 and executable on the processor 401. When the program is executed by the processor 401, it implements the various processes of the above-described smoke machine control method embodiment and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0119] It should be noted that the electronic devices in the embodiments of this application include the mobile electronic devices and non-mobile electronic devices described above.

[0120] This application also provides a non-transitory computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it implements the various processes of the above-described smoke machine control method embodiments and achieves the same technical effect. To avoid repetition, it will not be described again here.

[0121] The processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0122] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described smoke machine control method.

[0123] The processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0124] This application embodiment also provides a chip, which includes a processor and a communication interface. The communication interface and the processor are coupled. The processor is used to run programs or instructions to implement the various processes of the above-described smoke machine control method embodiment and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0125] It should be understood that the chip mentioned in the embodiments of this application may also be referred to as a system-on-a-chip, system chip, chip system, or system-on-a-chip, etc.

[0126] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0127] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a computer software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0128] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

[0129] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "illustrative embodiment," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0130] Although embodiments of this application have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of this application, the scope of which is defined by the claims and their equivalents.

Claims

1. A range hood, characterized in that, The smoke hood includes multiple gesture detection modules and a controller, and each gesture detection module includes at least one laser emitter and at least one receiver; The controller is used to control the laser emitters of each gesture detection module to emit laser signals toward the target direction of the smoke machine, and to receive the reflected light signal formed by the laser signal after being reflected by the user's hand through the receiver; to identify the user's gesture based on the time difference between the reflected light signal corresponding to each gesture detection module and the laser signal, and to generate control commands corresponding to the user's gesture to control the operating state of the smoke machine.

2. The range hood according to claim 1, characterized in that, Multiple gesture detection modules are arranged at intervals along the length of the cigarette machine.

3. The smoke hood according to claim 1, characterized in that, The distance between adjacent gesture detection modules satisfies: in, This indicates the distance between adjacent gesture detection modules. Represents the speed of light. The minimum effective duration of the gesture is indicated by k, which is a coefficient related to the installation height of the range hood.

4. The range hood according to claim 3, characterized in that, Calculate the value of k using the following formula: Where h represents the actual installation height of the range hood. This indicates the standard installation height of the range hood.

5. The range hood according to claim 1, characterized in that, The distance between adjacent gesture detection modules is 5-30 centimeters.

6. The range hood according to claim 1, characterized in that, The emission angle of the laser emitter of each gesture detection module satisfies: in, Indicates the emission angle of the laser emitter. This indicates the distance between adjacent gesture detection modules. L represents the overlap width of the detection areas of adjacent gesture detection modules, and L represents the vertical distance from the smoke machine to the preset gesture detection area.

7. The smoke hood according to claim 1, characterized in that, The laser emitter has an emission angle of 10°-35°.

8. The range hood according to claim 1, characterized in that, The step of recognizing user gestures based on the time difference between the reflected light signal corresponding to each gesture detection module and the laser signal includes: A depth map including the user's hand is generated based on the time difference between the laser signal and the reflected light signal; The user's gesture is obtained by recognizing the depth maps at multiple consecutive time points corresponding to each gesture detection module.

9. A method for controlling a smoke hood, characterized in that, The smoke hood includes multiple gesture detection modules and a controller, each gesture detection module including at least one laser emitter and at least one receiver; the method includes: The laser emitter of each gesture detection module is controlled to emit a laser signal toward the target direction of the cigarette machine, and the receiver receives the reflected light signal formed by the laser signal after being reflected by the user's hand; User gestures are identified based on the time difference between the reflected light signal and the laser signal corresponding to each gesture detection module. The system generates control commands corresponding to the user's gestures to control the operating status of the range hood.

10. A smoke machine control device, characterized in that, The smoke hood includes multiple gesture detection modules and a controller, each gesture detection module including at least one laser emitter and at least one receiver; the device includes: The control module is used to control the laser emitters of each gesture detection module to emit laser signals toward the target direction of the cigarette machine, and to receive the reflected light signal formed by the laser signal after being reflected by the user's hand through the receiver; The recognition module is used to recognize user gestures based on the time difference between the reflected light signal corresponding to each gesture detection module and the laser signal; The generation module is used to generate control commands corresponding to the user's gestures in order to control the operating status of the smoke machine.

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