Intelligent closestool control system and method

Abstract

The invention relates to the field of smart home, and discloses an intelligent closestool control system and method.The actual distance between a user and a closestool is converted into horizontal distance information relative to a preset reference plane through an information acquisition module; the triggering wake-up module judges whether a user is within a preset triggering distance in front of the closestool, if yes, the closestool is switched to a low-power-consumption monitoring mode, and an image acquisition starting instruction is output; the image acquisition module acquires image data, extracts moving direction features, and extracts actual feature information when moving towards the closestool; the comparison and analysis module compares the actual feature information with a standard feature database, confirms the type of a user, and generates a deep wake-up signal if the comparison succeeds; and the execution control module generates a driving control signal according to the signal to control the position adjustment and the overturning of the toilet seat. The whole analysis process can intelligently judge and automatically regulate and control the toilet seat action, convenient use experience and efficient intelligent management are achieved, and the defecation comfort and the equipment automation level are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of smart home, more particularly to a smart toilet control system and method. BACKGROUND

[0002] The existing smart toilet control system is usually equipped with various sensors, such as infrared human sensor or microwave radar, for detecting the presence of the user to realize the basic functions of automatic cover turning, automatic flushing and seat heating; some high-end systems further integrate image acquisition devices, which can capture the visual information around the toilet and combine with the central processing unit for data analysis to assist in completing more complex interactive control; in addition, with the development of smart home technology, the related system has network communication capability, which can receive the instructions of external terminal or upload device status data, thereby building a remote monitoring and management system.

[0003] However, the prior art still has the following disadvantages:

[0004] Firstly, the existing smart toilet usually only relies on infrared or microwave radar to detect the presence of the human body, and once the presence is detected, the action is triggered, which cannot distinguish between the passer-by (such as just walking around the toilet) and the real use intention (really walking to the toilet), resulting in false opening of the cover, false flushing, and interference with the normal life of the user;

[0005] Secondly, the existing smart toilet can usually only provide unified standardized services, i.e. regardless of men, women, old or young, master or guest, the cover turning angle, seat temperature and opening mode of the toilet are fixed, which cannot meet the specific use habits of different family members;

[0006] Thirdly, the existing control logic is usually a simple "sensing-execution" open-loop control, which lacks accurate calculation and feedback of the final execution state, resulting in harsh and inaccurate seat cover turning action, which is difficult to match the complex user demand. SUMMARY

[0007] In order to overcome the above-mentioned defects of the prior art, the present application provides a smart toilet control system and method to solve the problems in the above background.

[0008] The present application provides the following technical solutions: a smart toilet control system, comprising:

[0009] An information acquisition module: for the actual distance information between the user and the toilet, and converting the actual distance information into horizontal distance information of the user relative to a preset reference plane;

[0010] The trigger wake-up module: according to the horizontal distance information, it is judged whether the user is in the preset trigger distance range in front of the closestool, if it is judged that the user is in the preset trigger distance range, the closestool is switched from the sleep mode to the low-power monitoring mode, and the starting image acquisition instruction is output;

[0011] The image acquisition module: according to the starting image acquisition instruction, the image data of the user is collected, and the horizontal distance information between the current user and the closestool is synchronously received, the moving direction feature of the user is extracted through the time sequence change of the horizontal distance information, and when it is determined that the moving direction feature is moving towards the closestool, the actual feature information of the user is extracted from the image data;

[0012] The comparison and analysis module: for comparing and analyzing the actual feature information with the standard feature information in the preset standard feature database, confirming the user type, if the comparison is successful, a deep wake-up signal is generated, and the closestool seat ring is driven to perform a preparation action;

[0013] The execution control module: according to the deep wake-up signal and the comparison and analysis result, a final driving control signal is generated to control the closestool seat ring to perform position adjustment and overturning action.

[0014] Preferably, the information acquisition module collects the original actual distance data between the user and the closestool in real time through the ranging sensor, and uses the built-in coordinate transformation algorithm to process the original actual distance data through trigonometric function, and converts the original actual distance data into the horizontal distance information of the user's body relative to the preset reference plane of the closestool seat ring; wherein the detection area of the ranging sensor covers the preset activity area in front of the closestool.

[0015] Preferably, the trigger wake-up module receives the horizontal distance information output by the information acquisition module, constructs distance sequence data based on time dimension, and calculates the real-time distance and distance change rate of the user based on the sequence data; when it is determined that the real-time distance is in the preset trigger distance range, and the distance change rate represents the trend of moving towards the closestool, the closestool is switched from the sleep mode to the low-power monitoring mode, and the starting image acquisition instruction is output.

[0016] Preferably, after receiving the starting image acquisition instruction, the image acquisition module activates the image acquisition unit to obtain the original image data containing the user, and synchronously couples the real-time horizontal distance information output by the information acquisition module to construct the distance-time continuous monitoring sequence;

[0017] The approaching trend index is used to indicate the moving direction of the user relative to the toilet seat and the approaching posture by performing trend fitting analysis on the horizontal distance information.

[0018] The approaching trend index is compared with a preset effective approaching threshold in real time, and when the approaching trend index is greater than the preset effective approaching threshold, it is confirmed that the user is moving towards the toilet seat, and then a feature extraction algorithm is started to segment and identify the actual feature information of the user from the original image data; wherein the actual feature information includes human body contour features, facial features, clothing texture features and human body posture features.

[0019] Preferably, the comparison and analysis module is used to receive the actual feature information of the user extracted by the image acquisition module, and perform multi-dimensional feature matching analysis on the actual feature information and each standard feature information in the preset standard feature database, to calculate a feature matching degree, and identify the identity attribute and category of the user based on the feature matching degree; and when the feature matching degree is greater than or equal to a preset feature matching threshold, it is confirmed that the comparison is successful, and then a deep wake-up signal is generated; the deep wake-up signal is used to drive the toilet seat to perform preparation actions including automatic turning up or heating to a preset temperature, to realize personalized service response based on the user.

[0020] Preferably, the execution control module is used to receive the deep wake-up signal and the identity attribute and category of the user output by the comparison and analysis module, and according to a preset identity-action mapping table, analyze the target seat state parameter corresponding to the current user identity attribute, and perform difference calculation on the target seat state parameter and the current real-time state parameter of the toilet seat to generate a displacement deviation; and based on the displacement deviation, a closed-loop motion control algorithm is solved to output a final drive control signal, the drive control signal is used to control the operation of the toilet seat motor to drive the toilet seat to perform position adjustment and turning actions including position zero, angle turning and posture keeping, so as to realize control matching the personalized needs of the user.

[0021] To achieve the above purpose, the present application provides the following technical scheme: an intelligent toilet control method using the above-mentioned intelligent toilet control system, comprising the following steps:

[0022] Step 1: for the actual distance information between the user and the toilet, and convert the actual distance information into horizontal distance information of the user relative to a preset reference plane;

[0023] Step 2: According to the horizontal distance information, it is judged whether the user is in the preset trigger distance range in front of the toilet, and if it is judged that the user is in the preset trigger distance range, the toilet is switched from the sleep mode to the low-power monitoring mode, and an image acquisition instruction is output;

[0024] Step 3: According to the start image acquisition instruction, the image data of the user is collected, and the horizontal distance information between the current user and the toilet is synchronously received, the moving direction feature of the user is extracted through the time sequence change of the horizontal distance information, and when the moving direction feature is determined to be moving towards the toilet, the actual feature information of the user is extracted from the image data;

[0025] Step 4: The actual feature information is compared and analyzed with the standard feature information in the preset standard feature database to confirm the user type, and if the comparison is successful, a deep wake-up signal is generated to drive the toilet seat to perform a preparation action;

[0026] Step 5: According to the deep wake-up signal and the comparison and analysis result, a final driving control signal is generated to control the toilet seat to perform position adjustment and overturning action.

[0027] The technical effects and advantages of the present application are:

[0028] (1) The information acquisition module acquires accurate horizontal distance information, and the trigger wake-up module combines the preset trigger distance range for preliminary judgment; the image acquisition module extracts the moving direction feature of the user by synchronously receiving the time sequence change of the horizontal distance information, and only extracts the actual feature information when the moving direction feature is determined to be moving towards the toilet. This double determination mechanism based on distance change trend and moving direction effectively filters the moving interference of non-use direction, thereby avoiding the false opening of the cover or false flushing caused by passers-by.

[0029] (2) The comparison and analysis module compares and analyzes the collected actual feature information with the preset standard feature database to confirm the user type (such as distinguishing family members or men and women). If the comparison is successful, the system generates a targeted deep wake-up signal, and the corresponding driving control signal is generated through the execution control module, so that the toilet seat can perform position adjustment and overturning action according to the identified user type, thereby realizing differentiated and personalized service response.

[0030] (3) Through the execution control module, the final driving control signal is generated by combining the target seat ring state parameters and the current real-time state parameters for difference calculation and closed loop calculation according to the deep wake-up signal and the comparison analysis result. Through the accurate control of the motor operation, the system can drive the seat ring to perform accurate position adjustment, angle turning and posture keeping, thereby solving the problems of rough action and inaccurate position and meeting the complex use requirements. BRIEF DESCRIPTION OF DRAWINGS

[0031] Figure 1 The figure is a system structure diagram of the present application.

[0032] Figure 2 The figure is a method step diagram of the present application. DETAILED DESCRIPTION

[0033] The technical solutions in the present application will be described clearly and completely in combination with the drawings in the present application. In addition, the forms of each structure described in the following embodiments are only examples, and the intelligent toilet control system and method involved in the present application are not limited to each structure described in the following embodiments. All other embodiments obtained by those skilled in the art without making creative efforts belong to the scope of protection of the present application.

[0034] As shown in the present embodiment, an intelligent toilet control system is provided, which comprises: Figure 1

[0035] The information acquisition module is used for the actual distance information between the user and the toilet, and converts the actual distance information into the horizontal distance information of the user relative to the preset reference plane.

[0036] In the present embodiment, the information acquisition module collects the original actual distance data between the user and the toilet in real time through the ranging sensor, and utilizes the built-in coordinate transformation algorithm to combine the preset toilet installation height parameter and the spatial position relationship of the sensor relative to the seat ring plane of the toilet to perform trigonometric function calculation processing on the original actual distance data, so as to convert the original actual distance data into the orthographic horizontal distance information of the user's body relative to the preset reference plane of the seat ring of the toilet. The detection area of the ranging sensor covers the preset active area in front of the toilet.

[0037] ​It should be specifically explained that the coordinate transformation algorithm constructs a spatial rectangular coordinate system with the center point of the ranging sensor as the origin and the toilet seat plane as the reference plane. The trigonometric function calculation process is as follows: First, based on the sensor's built-in attitude parameters, the pitch angle of the ranging optical axis relative to the horizontal plane and the azimuth angle relative to the toilet's central axis are obtained. When the original actual distance data is collected, it is used as the hypotenuse length. Combined with the pitch angle, the cosine theorem is used to calculate the user's height projection component in the vertical direction and the preliminary distance component in the horizontal plane relative to the sensor center. Then, the height projection component is corrected by combining the installation height difference between the sensor and the toilet seat plane to determine the three-dimensional spatial coordinate point of the user's body. Finally, based on the geometric relationship between this three-dimensional spatial coordinate point and the preset reference plane, the vertical height data is removed, and the horizontal distance information of the orthographic projection of the user's body onto the preset reference plane of the toilet seat is extracted, thereby converting the radar ranging value with spatial angular deviation into a precise horizontal straight-line distance.

[0038] Trigger wake-up module: Based on the horizontal distance information, determine whether the user is within the preset trigger distance range in front of the toilet. If the user is within the preset trigger distance range, switch the toilet from sleep mode to low power monitoring mode and output a command to start image acquisition.

[0039] In this embodiment, the trigger wake-up module receives the horizontal distance information of the orthographic projection output by the information acquisition module, constructs distance sequence data based on the time dimension, and calculates the user's real-time distance and distance change rate based on the sequence data; when it is determined that the real-time distance is within the preset trigger distance range, and the distance change rate represents a trend of moving towards the toilet, the toilet is switched from sleep mode to low power monitoring mode, and a command to start image acquisition is output.

[0040] It should be specifically noted that the distance sequence data based on the time dimension specifically includes the horizontal distance value D(t) at the current time and the horizontal distance value D(t-1) at the previous sampling time. Therefore, the formula for calculating the rate of change of distance is: Where Δt is the sampling time interval; then, the calculated distance change rate V is numerically determined. When the value of V is less than zero, it indicates that the distance between the user and the toilet is decreasing, that is, the user's movement direction is determined to be a trend of moving towards the toilet; at this time, the system further verifies whether the current horizontal distance value D(t) falls within the preset trigger distance interval [D]. min D max If D(t) satisfies the interval condition and V is continuously less than the preset negative threshold duration, then the effective wake-up condition is confirmed, the toilet is controlled to switch from sleep mode to low power monitoring mode, and an image acquisition start command is immediately output.

[0041] Image acquisition module: Based on the image acquisition start command, it acquires the user's image data and simultaneously receives the horizontal distance information between the current user and the toilet. It extracts the user's movement direction features through the time series changes of the horizontal distance information. When it is determined that the movement direction features are moving towards the toilet, it extracts the user's actual feature information from the image data.

[0042] In this embodiment, after receiving the command to start image acquisition, the image acquisition module activates the image acquisition unit to obtain raw image data containing the user, and synchronously couples the real-time horizontal distance information output by the receiving information acquisition module to construct a distance-time continuous monitoring sequence.

[0043] By performing trend fitting analysis on the horizontal distance information, a proximity trend index is calculated, which is used to indicate the user's direction of movement and proximity relative to the toilet seat.

[0044] The proximity trend index is compared with a preset effective proximity threshold in real time. When the proximity trend index is greater than the preset effective proximity threshold, it is confirmed that the user is moving towards the toilet seat. Then, the feature extraction algorithm is activated to segment and identify the user's actual feature information from the original image data. The actual feature information includes human body contour features, facial features, clothing texture features, and human posture features.

[0045] It should be specifically noted that the trend fitting analysis employs the least squares method to linearly fit the distance-time continuous monitoring sequence within a preset time window, calculating the slope parameter of the fitted line. This slope parameter is defined as the proximity trend index. When the proximity trend index is negative and its absolute value is greater than a preset effective proximity threshold, it indicates that the horizontal distance between the user and the toilet seat exhibits a monotonically decreasing trend and the rate meets the proximity condition, thus confirming that the user is moving towards the toilet seat. The feature extraction algorithm first uses background subtraction or optical flow to segment the original image data into moving targets, obtaining the region of interest (ROI). Then, a convolutional neural network model is used to perform multi-scale feature detection within this region. A high-dimensional feature vector is output through a fully connected layer, from which actual feature information, including the coordinates of the human body contour boundaries, the positions of facial key points, the gray-level co-occurrence matrix of clothing texture, and joint angle information, is parsed and extracted.

[0046] The comparison and analysis module is used to compare and analyze the actual feature information with the standard feature information in the preset standard feature database to confirm the user type. If the comparison is successful, a deep wake-up signal is generated to drive the toilet seat to perform preparation actions.

[0047] In this embodiment, the comparison and analysis module receives the actual feature information of the user extracted by the image acquisition module, performs multi-dimensional feature matching analysis on the actual feature information and each standard feature information in the preset standard feature database, calculates the feature matching degree, and identifies the user's identity attributes and category based on the feature matching degree; and when the feature matching degree is greater than or equal to the preset feature matching threshold, the comparison is confirmed to be successful, and a deep wake-up signal is generated; the deep wake-up signal is used to drive the toilet seat to perform preparation actions including automatically opening or heating to a preset temperature, so as to realize personalized service response based on the user.

[0048] It should be specifically noted that the multi-dimensional feature matching analysis employs a weighted similarity fusion algorithm. First, the Euclidean distance or cosine similarity between the facial features, human contour features, and clothing texture features in the actual feature information and their corresponding templates in the standard feature database is calculated, yielding facial sub-matching values, contour sub-matching values, and clothing sub-matching values. Then, preset dynamic weight coefficients are assigned based on the recognition stability of different feature categories; for example, facial features have a higher weight than clothing features. The weighted summation is achieved using the formula S = ∑(W i ×S i ) Calculate the overall feature matching degree S, where W i S is the weight of the i-th feature. i The sub-matching value of the i-th feature is used. Finally, the calculated feature matching degree S is compared with the preset feature matching threshold θ. If S≥θ, the identity attribute and category corresponding to the standard feature information with the highest matching degree are locked, the matching is confirmed to be successful, and a deep wake-up signal containing user ID and personalized parameters is generated.

[0049] Execution control module: Based on the deep wake-up signal and the comparison analysis results, it generates the final drive control signal to control the toilet seat to perform position adjustment and flipping actions.

[0050] In this embodiment, the execution control module receives the deep wake-up signal and the user identity attributes and category output by the comparison and analysis module. Based on a preset identity-action mapping table, it parses out the target seat ring state parameters corresponding to the current user identity attributes. It calculates the difference between the target seat ring state parameters and the current real-time state parameters of the toilet seat ring to generate a displacement deviation. Then, based on the displacement deviation, it performs a closed-loop motion control algorithm to output the final drive control signal. The drive control signal is used to control the operation of the toilet seat ring motor to drive the toilet seat ring to perform position adjustment and flipping actions, including position zeroing, angle flipping, and posture maintenance, thereby achieving control that matches the user's personalized needs.

[0051] It should be specifically noted that the closed-loop motion control algorithm employs a PID (Proportional-Integral-Derivative) control algorithm. The calculation process is as follows: First, the displacement deviation e(t) is used as the input to the PID controller, and the proportional term K is calculated... p ×e(t), integral term K i ×∫e(t)dt and the differential term K d ×de(t) / dt, where K p K i K d The control parameters are pre-tuned according to the characteristics of the motor. Then, the above three calculation results are linearly superimposed to obtain the control output u(t). The control output u(t) is converted into a pulse width modulation (PWM) signal or voltage analog signal with a corresponding duty cycle to form the final drive control signal. By adjusting the amplitude of the drive control signal in real time, the seat ring motor is driven to operate at the corrected speed and torque until the displacement deviation e(t) converges to the preset dead zone range, thereby realizing precise closed-loop control of the seat ring position and flipping action.

[0052] like Figure 2 The present embodiment provides a smart toilet control method, including the following steps:

[0053] Step 1: Use the actual distance information between the user and the toilet, and convert the actual distance information into the horizontal distance information of the user relative to the preset reference plane;

[0054] Step 2: Based on the horizontal distance information, determine whether the user is within the preset trigger distance range in front of the toilet. If the user is within the preset trigger distance range, switch the toilet from sleep mode to low power monitoring mode and output a command to start image acquisition.

[0055] Step 3: According to the image acquisition start command, the image data of the user is acquired, and the horizontal distance information between the current user and the toilet is received synchronously. The user's movement direction feature is extracted by the time series change of the horizontal distance information. When the movement direction feature is determined to be moving towards the toilet, the actual feature information of the user is extracted from the image data.

[0056] Step 4: This step compares and analyzes the actual feature information with the standard feature information in the preset standard feature database to confirm the user type. If the comparison is successful, a deep wake-up signal is generated to drive the toilet seat to perform preparation actions.

[0057] Step 5: Based on the deep wake-up signal and the comparison analysis results, generate the final drive control signal to control the toilet seat to perform position adjustment and flipping actions.

[0058] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

[0059] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A smart toilet control system, characterized in that, include: Information acquisition module: used to obtain the actual distance information between the user and the toilet, and convert the actual distance information into the horizontal distance information of the user relative to the preset reference plane; Trigger wake-up module: Based on the horizontal distance information, determine whether the user is within the preset trigger distance range in front of the toilet. If the user is within the preset trigger distance range, switch the toilet from sleep mode to low power monitoring mode and output a command to start image acquisition. Image acquisition module: Based on the image acquisition start command, it acquires the user's image data and simultaneously receives the horizontal distance information between the current user and the toilet. It extracts the user's movement direction features through the time series changes of the horizontal distance information. When it is determined that the movement direction features are moving towards the toilet, it extracts the user's actual feature information from the image data. Comparison and analysis module: It is used to compare and analyze the actual feature information with the standard feature information in the preset standard feature database to confirm the user type. If the comparison is successful, a deep wake-up signal is generated to drive the toilet seat to perform preparation actions. Execution control module: Based on the deep wake-up signal and the comparison analysis results, it generates the final drive control signal to control the toilet seat to perform position adjustment and flipping actions.

2. The intelligent toilet control system according to claim 1, characterized in that, The information acquisition module collects the raw actual distance data between the user and the toilet in real time through a distance sensor. Using a built-in coordinate transformation algorithm, combined with preset toilet installation height parameters and the spatial position relationship of the sensor relative to the toilet seat plane, the module performs trigonometric function calculations on the raw actual distance data, converting it into the horizontal distance information of the user's body projected onto a preset reference plane of the toilet seat. The detection area of ​​the distance sensor covers a preset activity area in front of the toilet.

3. The intelligent toilet control system according to claim 2, characterized in that, The trigger wake-up module receives the horizontal distance information of the orthographic projection output by the information acquisition module, constructs distance sequence data based on the time dimension, and calculates the user's real-time distance and distance change rate based on the sequence data; when it is determined that the real-time distance is within the preset trigger distance range, and the distance change rate represents a trend of moving towards the toilet, the toilet is switched from sleep mode to low power monitoring mode, and a command to start image acquisition is output.

4. The intelligent toilet control system according to claim 3, characterized in that, Upon receiving a command to start image acquisition, the image acquisition module activates the image acquisition unit to acquire raw image data containing the user, and synchronously couples the real-time horizontal distance information output by the receiving information acquisition module to construct a distance-time continuous monitoring sequence. By performing trend fitting analysis on the horizontal distance information, a proximity trend index is calculated, which is used to indicate the user's direction of movement and proximity relative to the toilet seat. The proximity trend index is compared with a preset effective proximity threshold in real time. When the proximity trend index is greater than the preset effective proximity threshold, it is confirmed that the user is moving towards the toilet seat. Then, the feature extraction algorithm is activated to segment and identify the user's actual feature information from the original image data. The actual feature information includes human body contour features, facial features, clothing texture features, and human posture features.

5. The intelligent toilet control system according to claim 4, characterized in that, The comparison and analysis module receives the user's actual feature information extracted by the image acquisition module, performs multi-dimensional feature matching analysis with the standard feature information in the preset standard feature database, calculates the feature matching degree, and identifies the user's identity attributes and category based on the feature matching degree. When the feature matching degree is greater than or equal to the preset feature matching threshold, the comparison is confirmed to be successful, and a deep wake-up signal is generated. The deep wake-up signal is used to drive the toilet seat to perform preparatory actions, including automatically opening or heating to a preset temperature, to achieve personalized service response based on the user.

6. The intelligent toilet control system according to claim 5, characterized in that, The execution control module receives the deep wake-up signal and the user identity attributes and category output by the comparison and analysis module. Based on a preset identity-action mapping table, it parses the target seat state parameters corresponding to the current user identity attributes. It calculates the difference between the target seat state parameters and the current real-time state parameters of the toilet seat to generate a displacement deviation. Then, based on the displacement deviation, it performs a closed-loop motion control algorithm to output the final drive control signal. The drive control signal is used to control the operation of the toilet seat motor to drive the toilet seat to perform position adjustment and flipping actions, including position zeroing, angle flipping, and posture maintenance, thereby achieving control that matches the user's personalized needs.

7. A method for controlling an intelligent toilet, using an intelligent toilet control system as described in any one of claims 1-6, characterized in that, Includes the following steps: Step 1: Use the actual distance information between the user and the toilet, and convert the actual distance information into the horizontal distance information of the user relative to the preset reference plane; Step 2: Based on the horizontal distance information, determine whether the user is within the preset trigger distance range in front of the toilet. If the user is within the preset trigger distance range, switch the toilet from sleep mode to low power monitoring mode and output a command to start image acquisition. Step 3: According to the image acquisition start command, the image data of the user is acquired, and the horizontal distance information between the current user and the toilet is received synchronously. The user's movement direction feature is extracted by the time series change of the horizontal distance information. When the movement direction feature is determined to be moving towards the toilet, the actual feature information of the user is extracted from the image data. Step 4: This step compares and analyzes the actual feature information with the standard feature information in the preset standard feature database to confirm the user type. If the comparison is successful, a deep wake-up signal is generated to drive the toilet seat to perform preparation actions. Step 5: Based on the deep wake-up signal and the comparison analysis results, generate the final drive control signal to control the toilet seat to perform position adjustment and flipping actions.

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