Intelligent closestool automatic control method based on millimeter wave induction

Abstract

The invention provides an intelligent closestool automatic control method based on millimeter wave induction, and the method comprises the steps: transmitting an intermediate frequency signal through a radar, receiving a reflected signal, and achieving the precise capturing and recognition of a user behavior, and firstly obtaining the distance information of a target through fast Fourier transform; then, the speed weight and the track speed weight of the target are calculated to judge the gesture of the user, speed weight data are smoothed through Kalman filtering, the gesture recognition accuracy is improved, and when the gesture of the user is successfully matched with preset gesture template data, the intelligent closestool executes corresponding actions such as automatic uncovering or flushing; in addition, the system also records the result of each gesture recognition and the response condition of the closestool, so that the gesture recognition algorithm and the closestool control logic are continuously optimized and improved, and the intelligent level and the user experience of the intelligent closestool are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent sanitary ware, and more specifically, to an automatic control method of an intelligent toilet based on millimeter wave sensing. Background Art

[0002] With the development of science and technology and the improvement of living standards, people have higher and higher requirements for the comfort and intelligence of home life. As an important product to enhance the bathroom experience, smart toilets have developed from simple warm water washing functions to multiple intelligent functions such as automatic lid opening, seat heating, warm air drying, etc. However, most of the existing smart toilets rely on traditional technologies such as infrared sensing and touch control. These technologies have certain limitations in user experience and function realization. For example, infrared sensing technology may misjudge or fail to accurately identify user behavior under complex light or large environmental changes. Touch control requires direct contact from users, which is insufficient in terms of hygiene and convenience. In addition, with the increasing attention paid to personal health data, the potential of smart toilets in health monitoring has not been fully utilized. Millimeter wave radar technology, as an emerging sensor technology, has been widely used in the fields of automobile collision avoidance and drone obstacle avoidance due to its advantages of high precision, high sensitivity and strong anti-interference ability. Applying millimeter wave radar technology to smart toilets can accurately capture and identify user behavior, thereby providing more intelligent and personalized services.

[0003] The existing technology has a non-contact control method, and cannot accurately judge user behavior in complex light or environment, resulting in inaccurate recognition. Summary of the invention

[0004] In order to overcome the above technical defects of the prior art, the present invention designs an intelligent toilet automatic control method based on millimeter wave sensing, which can effectively solve the above technical problems.

[0005] In order to solve the above technical problems, the technical solution of the present invention is as follows:

[0006] A method for automatically controlling a smart toilet based on millimeter wave sensing comprises the following steps:

[0007] The radar transmits an intermediate frequency signal and receives the reflected intermediate frequency signal, and calculates and determines whether there is a target approaching according to the reflected intermediate frequency signal;

[0008] Calculating the target speed weight in the current frame according to the reflected intermediate frequency signal;

[0009] Repeat the calculation of the target speed weight in the current frame according to the reflected intermediate frequency signal for several times, obtain the target speed weight of multiple frames, calculate and obtain the target trajectory speed weight according to the target speed weight of multiple frames, and determine whether there is a user gesture;

[0010] Calculate user gesture data and determine whether the user gesture data matches the gesture template data, and if so, control the smart toilet to perform corresponding actions;

[0011] After identifying the user gesture data and controlling the smart toilet to perform corresponding actions, the results of the user gesture recognition and the response of the smart toilet are recorded, and the gesture recognition algorithm and smart toilet control logic are continuously optimized and improved.

[0012] Preferably, the determining whether a target is approaching includes:

[0013] The radar transmitter transmits an intermediate frequency signal, wherein the intermediate frequency signal is composed of a series of chirp signals, each of which has a specific frequency modulation characteristic;

[0014] The radar receiver receives the intermediate frequency signal reflected by the target;

[0015] Performing a fast Fourier transform on each received chirp signal to obtain distance information of the target;

[0016] According to the FFT results of multiple chirp signals, the distance and speed information of the target are calculated using the range-speed resolution algorithm;

[0017] Based on the distance and speed information of the target and a preset approach judgment threshold, it is determined whether there is a target approaching the smart toilet.

[0018] Preferably, the acquiring the distance information of the target includes:

[0019] Sampling each chirp signal to obtain discrete signal data;

[0020] Performing FFT operation on the sampled signal data to obtain a representation in the frequency domain;

[0021] The distance information of the target is extracted according to the representation in the frequency domain.

[0022] Preferably, the speed weight of the target includes:

[0023] For the reflected intermediate frequency signal of the current frame, calculate the target amplitude of each target;

[0024] Calculating the variance of the target amplitude based on the target amplitude of a plurality of consecutive frames;

[0025] The calculated variance is compared with a preset first threshold value. When the variance is greater than the first threshold value, it is determined that the target is approaching the smart toilet, and the target speed weight of the target in the current frame is calculated.

[0026] Preferably, judging whether there is a user gesture according to the trajectory speed weight of the target includes:

[0027] Repeating the calculation of the target speed weight in the current frame several times according to the reflected intermediate frequency signal to obtain the target speed weights of multiple frames;

[0028] Kalman filtering is used to smooth the multi-frame target velocity weights;

[0029] Calculating the target trajectory speed weight based on the target speed weight after smoothing;

[0030] The target trajectory speed weight is compared with a preset gesture judgment threshold to determine whether a specific user gesture exists.

[0031] Preferably, the determining whether the user gesture data matches the gesture template data, and if so, controlling the smart toilet to perform a corresponding action comprises:

[0032] For the recognized user gesture, calculate the user gesture data;

[0033] Matching the user gesture data with preset gesture template data;

[0034] If the user gesture data matches the gesture template data successfully, the smart toilet is controlled to perform corresponding actions according to the matching result.

[0035] An electronic device, comprising:

[0036] A memory storing executable program code;

[0037] a processor coupled to the memory;

[0038] The processor calls the executable program code stored in the memory to execute the above-mentioned intelligent toilet automatic control method based on millimeter wave sensing.

[0039] A computer storage medium stores computer instructions, which, when called, are used to execute the above-mentioned intelligent toilet automatic control method based on millimeter wave sensing.

[0040] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention uses the intermediate frequency signal emitted by the radar and the received reflected signal to accurately determine whether the target is close to the smart toilet. This process does not depend on light conditions, so the user's presence and approach behavior can still be accurately identified in a complex or dim light environment. Secondly, the received chirp signal is processed by fast Fourier transform to extract the distance information of the target, and the distance and speed information of the target are further calculated by combining the distance-speed resolution algorithm, which provides accurate user behavior data for the smart toilet. In addition, by calculating the target speed weight and trajectory speed weight, the present method can identify The user's gestures, such as waving and approaching, trigger corresponding actions of the smart toilet, such as automatic opening of the lid and flushing. This intelligent control based on user behavior not only improves the user experience, but also makes the operation of the smart toilet more hygienic and convenient. The application of Kalman filtering further optimizes data processing, reduces noise interference, and improves the accuracy of gesture recognition. Finally, the gesture recognition algorithm and smart toilet control logic are continuously optimized and improved. By recording and analyzing the user gesture recognition results and the response of the smart toilet, this self-learning and optimization ability enables the smart toilet to better adapt to the needs of different users and provide more personalized services.

[0041] In order to more clearly illustrate the implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other implementation drawings can be derived based on the provided drawings without paying any creative work.

[0042] Figure 1 This is a step-by-step diagram of an automatic control method for a smart toilet based on millimeter wave sensing. DETAILED DESCRIPTION

[0043] The drawings are for illustrative purposes only and should not be construed as limiting the present patent;

[0044] In order to better illustrate the present embodiment, some parts in the drawings may be omitted, enlarged or reduced, and do not represent the size of the actual product;

[0045] It is understandable to those skilled in the art that some well-known structures and their descriptions may be omitted in the drawings.

[0046] The technical solution of the present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0047] Example

[0048] A method for automatically controlling a smart toilet based on millimeter wave sensing, such as Figure 1As shown, the following steps are included:

[0049] The radar (millimeter wave radar sensor) transmits an intermediate frequency signal and receives the reflected intermediate frequency signal, and calculates and determines whether a target is approaching based on the reflected intermediate frequency signal;

[0050] Calculating the target speed weight in the current frame according to the reflected intermediate frequency signal;

[0051] Repeat the calculation of the target speed weight in the current frame according to the reflected intermediate frequency signal for several times, obtain the target speed weight of multiple frames, calculate and obtain the target trajectory speed weight according to the target speed weight of multiple frames, and determine whether there is a user gesture;

[0052] Calculate user gesture data and determine whether the user gesture data matches the gesture template data, and if so, control the smart toilet to perform corresponding actions;

[0053] After identifying the user gesture data and controlling the smart toilet to perform corresponding actions, the results of the user gesture recognition and the response of the smart toilet are recorded, and the gesture recognition algorithm and smart toilet control logic are continuously optimized and improved.

[0054] The determining whether a target is approaching includes:

[0055] The radar transmitter transmits an intermediate frequency signal, wherein the intermediate frequency signal is composed of a series of chirp signals, each of which has a specific frequency modulation characteristic;

[0056] Chirp signal, also known as Linear Frequency Modulation (LFM) signal, is a signal commonly used in radar, sonar and other wireless communication systems. It is a time-varying signal whose frequency increases or decreases linearly over time, and its shape is similar to the "chirp" sound in bird song, hence the name.

[0057] Characteristics of Chirp signal:

[0058] Time-frequency characteristics: The frequency of the Chirp signal changes linearly with time, which can be rising (frequency increases with time) or falling (frequency decreases with time).

[0059] Bandwidth: Since the frequency varies with time, the Chirp signal usually has a wider bandwidth, which gives it advantages in frequency resolution and distance resolution.

[0060] Resolution: In radar systems, the wide bandwidth of the chirp signal can provide high range resolution, which is very important for accurately measuring target distance and speed.

[0061] Anti-interference ability: Due to its special frequency characteristics, Chirp signal is highly resistant to interference in some cases.

[0062] Flexibility: The parameters of the Chirp signal, such as bandwidth, duration, and frequency change rate, can be adjusted as needed to adapt to different application scenarios.

[0063] The radar receiver receives the intermediate frequency signal reflected by the target;

[0064] Performing a fast Fourier transform (FFT) on each of the received chirp signals to obtain distance information of the target;

[0065] According to the FFT results of multiple chirp signals, the distance and speed information of the target are calculated using the range-speed resolution algorithm;

[0066] Based on the distance and speed information of the target and in combination with a preset proximity judgment threshold, it is determined whether a target (such as a user) is approaching the smart toilet.

[0067] The acquiring of the distance information of the target includes:

[0068] Sampling each chirp signal to obtain discrete signal data;

[0069] Performing FFT operation on the sampled signal data to obtain a representation in the frequency domain;

[0070] According to the representation in the frequency domain, the distance information of the target is extracted. The distance information is usually expressed as a peak position in the FFT result.

[0071] The speed weights of the targets include:

[0072] For the reflected intermediate frequency signal of the current frame, calculate the target amplitude of each target;

[0073] Based on the target amplitude of multiple consecutive frames, calculating the variance of the target amplitude; the variance reflects the change of the target speed;

[0074] The calculated variance is compared with a preset first threshold. When the variance is greater than the first threshold, it is determined that the target is approaching the smart toilet, and the target speed weight of the target in the current frame is calculated. The target speed weight is related to the approach speed and stability of the target.

[0075] When the variance is greater than the first threshold, the trend of the target amplitude change is further analyzed to determine the target's approach speed and direction. Based on the approach speed and direction, the target speed weight of the target in the current frame is calculated. The weight reflects the urgency and stability of the target approaching the smart toilet. The calculated target speed weight is compared with the preset weight threshold to further confirm whether the target's approach behavior is valid.

[0076] The determining whether there is a user gesture according to the target trajectory speed weight includes:

[0077] Repeating the calculation of the target speed weight in the current frame several times according to the reflected intermediate frequency signal to obtain the target speed weights of multiple frames;

[0078] Kalman filtering is used to smooth the multi-frame target velocity weights;

[0079] The multi-frame target velocity weights are preprocessed, such as denoising and normalization, to establish a Kalman filter model, set state variables, observation variables and noise parameters, and smooth the target velocity weights according to the prediction-update cycle of the Kalman filter to obtain a more stable and accurate target trajectory velocity weight.

[0080] Based on the target speed weight after smoothing, the target trajectory speed weight is calculated; the weight reflects the stability of the target's moving trajectory and speed change;

[0081] The target trajectory speed weight is compared with a preset gesture judgment threshold to determine whether there is a specific user gesture, such as waving, clicking, etc.

[0082] The determining whether the user gesture data matches the gesture template data, and if so, controlling the smart toilet to perform a corresponding action includes:

[0083] For the recognized user gesture, calculate the user gesture data, including the shape, direction, speed, etc. of the gesture;

[0084] Matching the user gesture data with preset gesture template data; the gesture template data includes various gestures recognizable by the smart toilet and their corresponding control commands;

[0085] The gesture template data matching also includes the following steps: preprocessing the calculated user gesture data, such as smoothing, normalization, feature extraction, etc., comparing the preprocessed user gesture data with the data in the gesture template database one by one, calculating the similarity, and judging whether the user gesture data is successfully matched with the gesture template data based on the similarity and a preset matching threshold.

[0086] If the user gesture data matches the gesture template data successfully, the smart toilet will be controlled to perform corresponding actions according to the matching results, such as flushing, seat heating, deodorization, etc.

[0087] In the specific implementation, the hardware is configured first, including a smart toilet with functions such as automatic opening, automatic flushing, and automatic closing of the lid; a millimeter-wave radar sensor installed on the side or front of the smart toilet, which is used to transmit and receive intermediate frequency signals to detect the approach and gestures of the target; a controller includes a processor: responsible for processing the data collected by the millimeter-wave radar sensor, executing the gesture recognition algorithm, and controlling the action of the smart toilet; a memory: storing executable program code, gesture template data, historical records, etc., for the processor to call.

[0088] Computer storage medium: stores computer instructions, which, when called, are used to execute the intelligent toilet automatic control method based on millimeter wave sensing described in this embodiment.

[0089] Working process: The millimeter-wave radar sensor emits a series of chirp signals (frequency modulation signals) with specific frequency modulation characteristics. When the user approaches the smart toilet, these signals will be reflected back by the user and received by the radar receiver. The controller performs a fast Fourier transform (FFT) on each received chirp signal to obtain the distance information of the target. The controller calculates the distance and speed information of the target based on the FFT results of multiple chirp signals and uses the distance-speed resolution algorithm. If the distance and speed information of the target meet the preset proximity judgment threshold, the controller determines that a target is approaching the smart toilet.

[0090] Target speed weight calculation: For the reflected intermediate frequency signal of the current frame, the controller calculates the target amplitude of each target. Based on the target amplitudes of multiple consecutive frames, the controller calculates the variance of the target amplitudes. If the variance is greater than the preset first threshold, the controller determines that the target is approaching the smart toilet and calculates the target speed weight of the target in the current frame. The controller repeats the above process several times to obtain the target speed weights of multiple frames.

[0091] Target trajectory speed weight calculation and gesture judgment, the controller uses Kalman filtering to smooth the target speed weights of multiple frames to reduce noise and errors. Based on the smoothed target speed weights, the controller calculates the target trajectory speed weights. The controller compares the target trajectory speed weights with the preset gesture judgment threshold to determine whether there is a specific user gesture.

[0092] Gesture recognition and smart toilet control. If the controller recognizes a specific user gesture, it will calculate the user gesture data. The controller will match the user gesture data with the preset gesture template data. If the user gesture data matches the gesture template data successfully, the controller will control the smart toilet to perform corresponding actions based on the matching results. For example, if the user makes a lid opening gesture, the controller will send a signal to the lid opening mechanism of the smart toilet to automatically open the toilet lid.

[0093] Recording and optimization: After identifying the user gesture data and controlling the smart toilet to perform corresponding actions, the controller will record the results of the user gesture recognition and the response of the smart toilet. The controller will continuously optimize and improve the gesture recognition algorithm and smart toilet control logic based on the recorded data to improve the recognition accuracy and the response speed of the smart toilet.

[0094] Specific implementation scenario: suppose a user approaches a smart toilet and is ready to use it. When the user approaches, the millimeter-wave radar sensor detects the user's approach and sends a signal to the controller. The controller calculates the user's distance and speed information, and determines that the user is approaching the toilet. Then, the controller starts to detect the user's gestures. If the user makes a lid-opening gesture, such as waving, the controller will recognize the gesture and control the smart toilet to automatically open the toilet lid. After the user finishes using it, he can make another gesture, such as waving again. The controller will recognize the gesture and control the smart toilet to automatically flush and close the toilet lid.

[0095] The same or similar reference numerals correspond to the same or similar components;

[0096] The terms used in the drawings to describe positional relationships are only used for illustrative purposes and should not be construed as limiting this patent;

[0097] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not limitations on the implementation methods of the present invention. For ordinary technicians in the relevant field, other different forms of changes or modifications can be made on the basis of the above description. It is not necessary and impossible to list all the implementation methods here. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the claims of the present invention.

Claims

1. A smart toilet automatic control method based on millimeter wave sensing, characterized in that: The following steps are involved: The radar transmits an intermediate frequency signal and receives the reflected intermediate frequency signal, and calculates and determines whether there is a target approaching according to the reflected intermediate frequency signal; Calculating the target speed weight in the current frame according to the reflected intermediate frequency signal; Repeat the calculation of the target speed weight in the current frame according to the reflected intermediate frequency signal for several times, obtain the target speed weight of multiple frames, calculate and obtain the target trajectory speed weight according to the target speed weight of multiple frames, and determine whether there is a user gesture; Calculate user gesture data and determine whether the user gesture data matches the gesture template data, and if so, control the smart toilet to perform corresponding actions; After identifying the user gesture data and controlling the smart toilet to perform corresponding actions, the results of the user gesture recognition and the response of the smart toilet are recorded, and the gesture recognition algorithm and smart toilet control logic are continuously optimized and improved.

2. The method for automatic control of a smart toilet based on millimeter wave sensing according to claim 1, characterized in that: The determining whether a target is approaching includes: The radar transmitter transmits an intermediate frequency signal, wherein the intermediate frequency signal is composed of a series of chirp signals, each of which has a specific frequency modulation characteristic; The radar receiver receives the intermediate frequency signal reflected by the target; Performing a fast Fourier transform on each received chirp signal to obtain distance information of the target; According to the FFT results of multiple chirp signals, the distance and speed information of the target are calculated using the range-speed resolution algorithm; Based on the distance and speed information of the target and a preset approach judgment threshold, it is determined whether there is a target approaching the smart toilet.

3. The method for automatic control of a smart toilet based on millimeter wave sensing according to claim 2 is characterized in that: The acquiring of the distance information of the target includes: Sampling each of the chirp signals to obtain discrete signal data; Performing FFT operation on the sampled signal data to obtain a representation in the frequency domain; The distance information of the target is extracted according to the representation in the frequency domain.

4. The method for automatic control of a smart toilet based on millimeter wave sensing according to claim 1, characterized in that: The speed weights of the targets include: For the reflected intermediate frequency signal of the current frame, calculate the target amplitude of each target; Calculating the variance of the target amplitude based on the target amplitude of a plurality of consecutive frames; The calculated variance is compared with a preset first threshold value. When the variance is greater than the first threshold value, it is determined that the target is approaching the smart toilet, and the target speed weight of the target in the current frame is calculated.

5. The method for automatic control of a smart toilet based on millimeter wave sensing according to claim 1, characterized in that: The determining whether there is a user gesture according to the target trajectory speed weight includes: Repeating the calculation of the target speed weight in the current frame several times according to the reflected intermediate frequency signal to obtain the target speed weights of multiple frames; Kalman filtering is used to smooth the multi-frame target velocity weights; Calculating the target trajectory speed weight based on the target speed weight after smoothing; The target trajectory speed weight is compared with a preset gesture judgment threshold to determine whether a specific user gesture exists.

6. The method for automatic control of a smart toilet based on millimeter wave sensing according to claim 1, characterized in that: The determining whether the user gesture data matches the gesture template data, and if so, controlling the smart toilet to perform a corresponding action includes: For the recognized user gesture, calculate the user gesture data; Matching the user gesture data with preset gesture template data; If the user gesture data matches the gesture template data successfully, the smart toilet is controlled to perform corresponding actions according to the matching result.

7. An electronic device, characterized in that: The electronic device comprises: A memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the smart toilet automatic control method based on millimeter wave sensing as described in any one of claims 1-6.

8. A computer storage medium, characterized in that: The computer storage medium stores computer instructions, which, when called, are used to execute the intelligent toilet automatic control method based on millimeter wave sensing as described in any one of claims 1-6.

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