Intelligent closestool water column detection system based on millimeter wave radar

Abstract

The invention provides an intelligent closestool water column detection system based on a millimeter wave radar, and the system comprises a millimeter wave radar processing module and an intelligent closestool, the millimeter wave radar processing module is installed on the intelligent closestool, and the millimeter wave radar processing module comprises a millimeter wave radio frequency receiving and transmitting unit, a micro-control unit, a transmitting antenna, and a receiving antenna. The micro-control unit is used for giving a water column detection result according to a plurality of characteristic values in the water column signal data; the mainboard software of the intelligent closestool is used for outputting a corresponding control instruction according to the water column detection result returned by the millimeter-wave radar processing module in combination with the cover opening and closing state of the intelligent closestool; according to the water column detection algorithm adopted by the invention, points of a water column of a tester are collected based on a millimeter wave radar, statistics is carried out on power, speed and related characteristic values of the collected points in combination with related knowledge of physics, and whether the water column exists in the intelligent closestool or not is judged. The system provided by the invention can improve the water column detection efficiency and accuracy of the intelligent closestool.

Description

Technical Field

[0001] This article belongs to the technical field of smart toilets, and specifically relates to a smart toilet water column detection system based on millimeter wave radar. Background Art

[0002] In the field of human-computer interaction, dynamic and static target recognition based on sensors is an important part. Wireless object detection is a contactless technology, and wireless signals can penetrate materials such as plastic, walls or clothes. Wireless object detection can work at night and its performance is not affected by visible light. Compared with solutions based on visible light, wireless solutions have greater advantages in privacy protection. Millimeter wave radar is a wireless technology with good prospects. Millimeter wave radar has a power-saving system chip sensor that can simultaneously perform signal feature extraction and classification.

[0003] However, in the field of smart homes (such as smart toilets), the user's intelligent experience during use needs to be improved. For example, how to efficiently identify the user's status when using a smart toilet (such as men urinating) so as to quickly perform intelligent operations is a technical problem that needs to be solved urgently. In particular, there is little research on millimeter-wave radar for water column detection (mainly used to identify men's urination). Therefore, how to quickly and efficiently accurately identify users on smart toilets is a technical problem that needs to be solved urgently. Summary of the invention

[0004] In view of the above-mentioned problems of the prior art, the purpose of this article is to provide a smart toilet water column detection system based on millimeter-wave radar to solve the problems that the existing millimeter-wave radar water column detection is less used in the field of smart homes and lacks a more mature and comprehensive system for more accurate water column detection. It can improve the efficiency and accuracy of water column detection when identifying a person standing in front of a smart toilet.

[0005] In order to solve the above technical problems, the specific technical solutions of this article are as follows:

[0006] On the one hand, this article provides a smart toilet water column detection system based on millimeter wave radar, the system comprising: a millimeter wave radar processing module and a smart toilet:

[0007] The millimeter wave radar processing module is installed on the smart toilet, and the millimeter wave radar processing module includes a millimeter wave radio frequency transceiver unit, a micro control unit, a transmitting antenna and a receiving antenna. The micro control unit is connected to the millimeter wave radio frequency transceiver unit, the transmitting antenna and the receiving antenna respectively, and controls the millimeter wave radio frequency transceiver unit, the transmitting antenna and the receiving antenna to work according to preset instructions to obtain water column signal data of a user standing at a preset position of the smart toilet; the micro control unit is also used to give a water column detection result according to multiple characteristic values ​​in the water column signal data;

[0008] The mainboard software of the smart toilet is used to output corresponding control instructions based on the water column detection results returned by the millimeter wave radar processing module and the state of the smart toilet lid switch.

[0009] Furthermore, the micro control unit performs water column detection through the following steps:

[0010] Determine a water column detection start condition and a water column detection range, wherein the start condition at least includes that a user stands at a designated position of the smart toilet and the smart toilet is in an open lid state, and the water column detection range at least includes an internal range of the smart toilet body and a range extending upward from the smart toilet body;

[0011] When the water column detection start condition is met, a water column detection instruction is received, and the millimeter wave radio frequency transceiver unit, the transmitting antenna and the receiving antenna are controlled to obtain water column signal data within the water column detection range;

[0012] Based on the collected water column signal data, multiple statistical initial characteristic values ​​of single-frame point cloud data are obtained through multiple dimension screening;

[0013] A plurality of signal features are calculated by taking a plurality of statistical initial feature values ​​of 10 consecutive frames of point cloud data as a group;

[0014] During the water column detection process, multiple signal features of each group are used to determine whether a water column exists through preset judgment rules, and the water column detection result is output to the smart toilet.

[0015] Furthermore, the dimensions for screening each acquisition point in the single-frame point cloud data include at least the following three:

[0016] The collection point is within the water column detection range;

[0017] The absolute value of the speed of the acquisition point exceeds the preset speed, and the moving direction is toward the millimeter wave radar processing module;

[0018] The acquisition point is within a preset angle range of the radar beam center.

[0019] Furthermore, the multiple statistical initial eigenvalues ​​include at least the following:

[0020] The number of collection points with a speed less than 0 in the filtered single-frame point cloud data minus_V_Num;

[0021] The speed Max_v with the largest absolute value among the collection points whose speed is less than 0 in the filtered single-frame point cloud data;

[0022] The number of selected collection points within the water column detection range, TargetNum;

[0023] Whether the single frame point cloud data is valid after screening within the water column detection range, Valid_Sign, when TargetNum>1, Valid_Sign=1, otherwise Valid_Sign=0;

[0024] The maximum power Max_Pow, the maximum Y coordinate value Y_max, the minimum Y coordinate value Y_min, and the average Y coordinate value Y_mean of the collected points in the single-frame point cloud data after screening within the water column detection range;

[0025] The minimum value R_min of the distance from the acquisition point to the radar within the water column detection range.

[0026] Among them, the X-axis is parallel to the ground and parallel to the midline of the smart toilet. The positive direction of the X-axis is on the side of the radar board facing the user. The Y-axis is parallel to the ground. When the user faces the radar, the left side is the negative direction of the Y-axis and the right side is the positive direction of the Y-axis. The Z-axis is perpendicular to the ground, the upward direction is the negative direction of the Z-axis, and the downward direction is the positive direction of the Z-axis.

[0027] Furthermore, multiple signal features corresponding to 10 consecutive frames of point cloud data include the following:

[0028] The sum of Valid_Sign in all single-frame point cloud data is Sum_Valid_Sign;

[0029] The sum of Y_mean in all single-frame point cloud data is divided by Sum_Valid_Sign to get Total_Y_Mean;

[0030] When Valid_sign=1, if the deviations of Y_max and Y_min from Total_Y_Mean are within a certain distance, the Y of the single frame is valid, and the number of all valid Ys in all 10 frames, sum_valid_y, is calculated;

[0031] The number of frames with R_min exceeding 0.4m in all single-frame point cloud data, sum_r_min_far;

[0032] The number of frames with R_min exceeding 0.5m in all single-frame point cloud data sum_r_min_further;

[0033] If the maximum Max_Pow of one frame in all single-frame point cloud data exceeds a certain threshold, max_pow_flag=1 is defined, otherwise max_pow_flag=0;

[0034] If the number of points in one frame of all single-frame point cloud data exceeds a certain threshold after screening, point_num_flag=1 is defined, otherwise point_num_flag=0;

[0035] The velocity value max_v_inBuff which is less than 0 and has the largest absolute value among all single-frame point cloud data;

[0036] The total number of points after screening in all single-frame point cloud data is sum_point_num, the sum of the points with speed less than 0 in the past 10 frames is sum_minus_v_num, and the number of valid frames in the past 10 frames is sum_valid_num.

[0037] Furthermore, the presence of a water column is determined by at least one of the following preset judgment rules:

[0038] If sum_valid_num>=4, sum_minus_v_num=sum_point_num, max_pow_flag==0, sum_r_min_further>=sum_valid_num, max_v_inBuff<-1.2m / s, sum_valid_y==sum_valid_num, it is determined that there is a water column; or

[0039] If sum_valid_num>=5, sum_minus_v_num>=0.9*sum_point_num, max_pow_flag==0, sum_r_min_further>=sum_valid_num-1, max_v_inBuff<-1.2m / s, sum_valid_y>=sum_valid_num-1, it is determined that there is a water column; or

[0040] If sum_valid_num>=6, sum_minus_v_num>=0.9*sum_point_num, max_pow_flag==0, sum_r_min_far>=(sum_valid_num-1)), then if point_num_flag is not 0, it is determined that there is a water column; otherwise, if point_num_flag==0 and sum_valid_y>=(sum_valid_num-1), it is determined that there is a water column; or

[0041] If sum_valid_num>=8, sum_minus_v_num>=0.95*sum_point_num, max_pow_flag==0, then if point_num_flag is not 0, it is determined that there is a water column; otherwise, if point_num_flag=0 and sum_valid_y>=8, it is determined that there is a water column.

[0042] Furthermore, when the smart toilet receives a signal indicating the presence of a water column, it outputs an instruction to continue water column detection. When the smart toilet receives a signal indicating the absence of a water column and the user is not standing at a designated position of the smart toilet, it closes the lid and performs flushing.

[0043] On the other hand, this article also provides a smart toilet water column detection method, which is applied to a smart toilet equipped with a millimeter wave radar processing module, wherein the millimeter wave radar processing module includes a millimeter wave radio frequency transceiver unit, a micro control unit, a transmitting antenna and a receiving antenna, and the micro control unit is respectively connected to the millimeter wave radio frequency transceiver unit, the transmitting antenna and the receiving antenna, and the method includes the following steps:

[0044] Determine a water column detection start condition and a water column detection range, wherein the start condition at least includes that a user stands at a designated position of the smart toilet and the smart toilet is in an open lid state, and the water column detection range at least includes an internal range of the smart toilet body and a range extending upward from the smart toilet body;

[0045] When the water column detection start condition is met, a water column detection instruction is received, and the millimeter wave radio frequency transceiver unit, the transmitting antenna and the receiving antenna are controlled to obtain water column signal data within the water column detection range;

[0046] Based on the collected water column signal data, multiple statistical initial characteristic values ​​of single-frame point cloud data are obtained through multiple dimension screening;

[0047] A plurality of signal features are calculated by taking a plurality of statistical initial feature values ​​of 10 consecutive frames of point cloud data as a group;

[0048] During the water column detection process, multiple signal features of each group are used to determine whether a water column exists through preset judgment rules, and the water column detection results are output.

[0049] On the other hand, this article also provides a smart toilet, which has the smart toilet water column detection system based on millimeter wave radar as described in any of the above items.

[0050] On the other hand, the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method described above is implemented as follows.

[0051] By adopting the above technical scheme, a millimeter-wave radar-based smart toilet water column detection system described in this article comprises: a millimeter-wave radar processing module and a smart toilet: the millimeter-wave radar processing module is installed on the smart toilet, and the millimeter-wave radar processing module comprises a millimeter-wave radio frequency transceiver unit, a microcontroller unit, a transmitting antenna and a receiving antenna, and the microcontroller unit is respectively connected to the millimeter-wave radio frequency transceiver unit, the transmitting antenna and the receiving antenna, and controls the millimeter-wave radio frequency transceiver unit, the transmitting antenna and the receiving antenna to work according to preset instructions to obtain water column signal data of a user standing in a preset position of the smart toilet; the microcontroller unit is also used to give a water column detection result according to multiple characteristic values ​​in the water column signal data; the mainboard software of the smart toilet is used to output corresponding control instructions according to the water column detection result returned by the millimeter-wave radar processing module, combined with the switch cover status of the smart toilet. The system provided in this article can improve the efficiency and accuracy of water column detection by the smart toilet.

[0052] In order to make the above and other purposes, features and advantages of this article more obvious and easy to understand, the following specifically cites preferred embodiments and describes them in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the technical solutions in the embodiments of this article or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of this article. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0054] Figure 1 This is the basic block diagram of a smart toilet equipped with a millimeter-wave radar in the embodiments of this specification.

[0055] Figure 2 This is the basic block diagram of the millimeter wave radar in the embodiments of this specification.

[0056] Figure 3This is a basic block diagram of the water column detection algorithm in the embodiments of this specification.

[0057] Figure 4 This is a schematic diagram of the hardware structure of the smart toilet provided in the embodiments of this specification. DETAILED DESCRIPTION

[0058] The following will be combined with the drawings in the embodiments of this article to clearly and completely describe the technical solutions in the embodiments of this article. Obviously, the described embodiments are only part of the embodiments of this article, not all of the embodiments. Based on the embodiments of this article, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this article.

[0059] It should be noted that the terms "first", "second", etc. in the specification and claims of this article and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of this article described here can be implemented in an order other than those illustrated or described here. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, device, product or equipment that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or equipment.

[0060] The present invention proposes a smart toilet water column detection system based on millimeter wave radar, wherein the installation position and angle of the millimeter wave radar in the smart toilet are as follows: Figure 1 As shown. Here, the X-axis is defined to be parallel to the ground and parallel to the center line of the smart toilet, and the positive direction of the X-axis is on the side of the radar board facing the person. The Y-axis is parallel to the ground. When a person faces the radar, the left hand is in the negative direction of the Y-axis and the right hand is in the positive direction of the Y-axis. The Z-axis is perpendicular to the ground, with the positive direction of the Z-axis upward and the negative direction of the Z-axis downward. Β is the angle between the target point and the horizontal plane, and α is the angle between the short side of the radar board and the horizontal plane. Note that the RF chip of the radar module must be on top. Since the beam angle range of the radar is approximately (-60°, 60°), the effective target point above the horizontal plane satisfies β<60-α. That is, the radar collects the most points on the target within this range, and the effect is best.

[0061] Millimeter wave radar processing module such as Figure 2As shown, it includes a millimeter wave radio frequency transceiver unit, a micro control unit, a transmitting antenna and a receiving antenna, etc., which are installed behind the intelligent toilet lid. The micro control unit is connected to the millimeter wave radio frequency transceiver unit, the transmitting antenna and the receiving antenna respectively, and controls the millimeter wave radio frequency transceiver unit, the transmitting antenna and the receiving antenna to work according to preset instructions, so as to obtain water column signal data of a user standing at a preset position of the intelligent toilet; generates a corresponding millimeter wave radar signal according to the radar waveform parameters, processes the signal reflected back by the user (such as a tester), and gives a water column detection result;

[0062] The mainboard software of the smart toilet responds according to the relevant software protocol based on the water column detection results returned by the millimeter-wave radar processing module.

[0063] In the embodiment of this specification, the micro control unit performs water column detection through the following steps:

[0064] Determine a water column detection start condition and a water column detection range, wherein the start condition at least includes that a user stands at a designated position of the smart toilet and the smart toilet is in an open lid state, and the water column detection range at least includes an internal range of the smart toilet body and a range extending upward from the smart toilet body;

[0065] When the water column detection start condition is met, a water column detection instruction is received, and the millimeter wave radio frequency transceiver unit, the transmitting antenna and the receiving antenna are controlled to obtain water column signal data within the water column detection range;

[0066] Based on the collected water column signal data, multiple statistical initial characteristic values ​​of single-frame point cloud data are obtained through multiple dimension screening;

[0067] A plurality of signal features are calculated by taking a plurality of statistical initial feature values ​​of 10 consecutive frames of point cloud data as a group;

[0068] During the water column detection process, multiple signal features of each group are used to determine whether a water column exists through preset judgment rules, and the water column detection result is output to the smart toilet.

[0069] For example, Figure 3 As shown, the specific steps include:

[0070] Step 1: The tester needs to stand in the sensing area in front of the toilet with the smart toilet lid open:

[0071] The basis for determining the standing area of ​​a smart toilet is as follows:

[0072] The sensing area is a rectangular area of ​​a specified size in front of the smart toilet. The width of the rectangular area is the same as that of the smart toilet, and the length range is usually 0.4m to 0.5m.

[0073] The opening of the water column detection can be controlled by the main board. When a person is not standing or the smart toilet is in the closed state, the water column detection is closed;

[0074] The standing state can be determined by measuring the center of mass and power of the human body through radar. Taking the 60G millimeter-wave radar as an example, when the tester stands in front of the toilet (about 50-100cm away from the radar), the signal strength value is usually above 2000. The detection of the center of mass of the human body can be achieved by implementing clustering and tracking algorithms based on the various points of the human body collected by the millimeter-wave radar.

[0075] S2.1, the clustering algorithm steps are as follows:

[0076] S2.1.1. Find the maximum power point by traversing and searching each frame of point cloud data acquired by the millimeter wave radar, and record its power value MaxPow and serial number index MaxPowIdx;

[0077] S2.1.2, select the point cloud data with power greater than 0.4*MaxPow within the second preset radius neighborhood of the maximum power point, then classify these points together with the maximum power point into a class, and update the weighted average coordinates and weighted energy values ​​of all point cloud data in the class as the clustering result returned by the algorithm;

[0078] S2.2. According to the clustering results of each frame of point cloud obtained by the clustering algorithm, the motion trajectory of the test person in the plane parallel to the ground is tracked and predicted. The corresponding iterative calculation process is as follows:

[0079] S2.2.1. Initialize the tester's tracking position (t_x, t_y) and tracking speed (t_vx, t_vy):

[0080] t_x=0m, t_y=0m, t_vx=0m / s, t_vy=0m / s

[0081] S2.2.2. According to the tracking position (t_x, t_y) and tracking speed (t_vx, t_vy) of the tester in the previous frame, the frame interval Frame_T, and the clustering position (xCenter, yCenter) obtained by clustering algorithm B in the current frame, calculate the predicted position (x_predict, y_predict) and prediction deviation (delta_x, delta_y) of the tester in the current frame:

[0082] x_predict=t_x+t_vx*Frame_T;

[0083] y_predict=t_y+t_vx*Frame_T;

[0084] delta_x=xCenter-x_predict;

[0085] delta_y=yCenter-y_predict;

[0086] S2.2.3. Update the tracking position (t_x, t_y) and tracking speed (t_vx, t_vy) of the current frame:

[0087] t_x=x_predict+λ*delta_x;

[0088] t_y=y_predict+λ*delta_y;

[0089] t_vx=t_vx+ω / Frame_T*delta_x;

[0090] t_vy=t_vx+ω / Frame_T*delta_y;

[0091] Among them, λ and ω take values ​​between 0 and 1 and are adjusted according to actual needs. The main function of the tracking algorithm is to prevent errors caused by position jumps caused by the maximum power point collected by the millimeter-wave radar.

[0092] Step 2: Define the water column detection range. The microcontroller unit obtains the position, speed and energy information of multiple points within the water column detection range based on the echo signal:

[0093] Water column detection range: The water column detection range is 20cm on both sides of the toilet center line, 30cm above and below the plane where the toilet lid is when the toilet lid is closed, and within 50cm in front of the radar board;

[0094] The millimeter-wave radar collects and processes the relevant information of multiple points in the water column of the tester within the water column detection range, including

[0095] (1) Current frame number frameNow;

[0096] (2) The distance r from the point cloud collected in the current frame to the radar center;

[0097] (3) The three-dimensional rectangular coordinates (x, y, z) of the point cloud collected in the current frame;

[0098] (4) The point cloud motion speed vel collected in the current frame;

[0099] (5) Point cloud power pow collected in the current frame;

[0100] (6) TargetNum, the number of valid point clouds collected in the current frame after millimeter-wave radar processing;

[0101] Step 3: Filter the collected water column microwave data and calculate the relevant statistical characteristic values ​​of the single frame after filtering:

[0102] The conditions for screening points within the water column detection range are:

[0103] (1) The selected point is within the designated water column detection range;

[0104] (2) The absolute value of the speed of the selected point should be greater than 0.5 m / s and the speed direction should be toward the millimeter wave radar processing module;

[0105] (3) The selected point should be within 15 degrees above the center of the radar beam;

[0106] The process of calculating the statistical eigenvalues ​​of a single frame is as follows:

[0107] (1) Calculate the number of points minus_V_Num whose velocity is less than 0 after screening in the water column detection area;

[0108] (2) Calculate the velocity Max_v with the largest absolute value among the points with a velocity less than 0 in the water column detection area after screening;

[0109] (3) Calculate the number of screened points TargetNum within the water column detection area;

[0110] (4) Calculate whether the frame is valid after screening in the water column detection area. If TargetNum>1, Valid_Sign=1, otherwise Valid_Sign=0;

[0111] (5) Calculate the maximum power Max_Pow, the maximum Y coordinate value Y_max, the minimum Y coordinate value Y_min, and the average Y coordinate value Y_mean of the screened points in the water column detection area;

[0112] (6) Calculate the minimum value R_min of the distance from a point in the water column detection area to the radar;

[0113] Step 4: Define the cache structure array WaterBuff, which is used to store the relevant statistical feature values ​​of each frame in the past 10 frames, and further calculate the relevant statistical feature values ​​of all elements of WaterBuff (i.e., the past 10 frames):

[0114] For the defined WaterBuff structure array, the calculation process of the relevant eigenvalues ​​of all elements WaterBuff[i] (i=0,1,2,...,9) is as follows:

[0115] (1) Calculate the sum of all Valid_Sign elements in WaterBuff, that is, the number of valid frames in the past 10 frames;

[0116] (2) Calculate the sum of Y_mean of all elements in WaterBuff and divide it by Sum_Valid_Sign to get Total_Y_Mean;

[0117] (3) When WaterBuff[i].valid_sign=1, if the deviation of WaterBuff[i].y_max and WaterBuff[i].y_min from Total_Y_Mean is within a certain distance (usually 0.1m to 0.15m) of 0, then the frame y is valid, and the number of all valid y in the WaterBuff in the past 10 frames, sum_valid_y, is calculated;

[0118] (4) Calculate the number of frames in the WaterBuff whose r_min exceeds 0.4m in the past 10 frames, sum_r_min_far;

[0119] (5) Calculate the number of frames in the WaterBuff whose r_min exceeds 0.5m in the past 10 frames, sum_r_min_further;

[0120] (6) If the maximum Max_Pow of one frame in the last 10 frames, i.e. WaterBuff, exceeds a certain threshold (usually 3000-3500), then define max_pow_flag = 1, otherwise max_pow_flag = 0;

[0121] (7) If the number of points in one of the last 10 frames, i.e. WaterBuff, exceeds a certain threshold (usually 8 to 10) after screening, point_num_flag=1 is defined, otherwise point_num_flag=0;

[0122] (8) Calculate the velocity value max_v_inBuff which is less than 0 and has the largest absolute value in WaterBuff in the last 10 frames;

[0123] (9) Calculate the total number of points after screening in the WaterBuff in the last 10 frames, sum_point_num (the sum of the points after screening in the last 10 frames), the sum of the points with a speed less than 0 in the last 10 frames, sum_minus_v_num, and the number of valid frames in the last 10 frames, sum_valid_num;

[0124] Step 5: Determine whether there is a water column in the current water column detection range based on the calculated relevant statistical characteristic values. If yes, send a water column instruction to the smart toilet, otherwise, still send a standing instruction:

[0125] According to the calculated relevant statistical characteristic values, it is judged whether there is a water column in the current water column detection range. The specific judgment conditions are as follows:

[0126] (1) If sum_valid_num>=4, sum_minus_v_num=sum_point_num, max_pow_flag==0, sum_r_min_further>=sum_valid_num, max_v_inBuff<-1.2m / s, sum_valid_y==sum_valid_num are satisfied at the same time, it is judged that there is a water column, and WaterBuff is cleared;

[0127] (2) If the condition in (1) is not satisfied and

[0128] If sum_valid_num>=5, sum_minus_v_num>=0.9*sum_point_num, max_pow_flag==0, sum_r_min_further>=sum_valid_num-1, max_v_inBuff<-1.2m / s, sum_valid_y>=sum_valid_num-1 are satisfied at the same time, it is judged that there is water column, and WaterBuff is cleared;

[0129] (3) If neither of the conditions (1) or (2) is satisfied,

[0130] sum_valid_num>=6, sum_minus_v_num>=0.9*sum_point_num, max_pow_flag==0, sum_r_min_far>=(sum_valid_num-1)) are satisfied at the same time, then if point_num_flag is not 0, it is judged that there is a water column, and WaterBuff is cleared, otherwise if point_num_flag==0 and sum_valid_y>=(sum_valid_num-1), it is judged that there is a water column, and WaterBuff is cleared;

[0131] (4) If the conditions in (1), (2), and (3) are not met,

[0132] If sum_valid_num>=8, sum_minus_v_num>=0.95*sum_point_num, max_pow_flag==0 are satisfied at the same time, then if point_num_flag is not 0, it is judged that there is a water column and WaterBuff is cleared; otherwise, if point_num_flag==0 and sum_valid_y>=8, it is judged that there is a water column and WaterBuff is cleared;

[0133] (1)(2)(3)(4) If any one of the above is met, it is determined that there is a water column and a water column instruction is sent to the smart toilet; otherwise, a standing instruction is still sent.

[0134] In the embodiment of the present specification, when the smart toilet receives a signal indicating the presence of a water column, it outputs an instruction to continue water column detection. When it receives a signal indicating the absence of a water column and the user is not standing at a designated position of the smart toilet, it closes the lid and performs flushing.

[0135] The system provided in the embodiments of this specification aims to solve the problems that the existing millimeter-wave radar water column detection is less used in the field of smart homes, and there is a lack of more mature and comprehensive systems for more accurate water column detection. The water column (such as urine column) detection algorithm used is mainly based on the millimeter-wave radar to collect urine column points of the tester and combine the relevant knowledge of physics to collect the power, speed and related characteristic values ​​of the collected points to determine whether there is a water column in the smart toilet. On the other hand, water column detection requires the tester to be in front of the toilet and in a standing state. The system has an accuracy rate of more than 95% for water column recognition, which can ensure that at least one water column is detected during the entire process of a man's urination. In addition, the system-related devices are easy to integrate and install, have low power consumption, and have good privacy protection. It can identify whether there is a water column when a person is standing in front of the smart toilet, thereby improving the efficiency and accuracy of detection.

[0136] Based on the system provided above, the embodiment of this specification also provides a smart toilet water column detection method, which is applied to a smart toilet equipped with a millimeter wave radar processing module, wherein the millimeter wave radar processing module includes a millimeter wave radio frequency transceiver unit, a micro control unit, a transmitting antenna and a receiving antenna, and the micro control unit is respectively connected to the millimeter wave radio frequency transceiver unit, the transmitting antenna and the receiving antenna, and the method includes the following steps:

[0137] Determine a water column detection start condition and a water column detection range, wherein the start condition at least includes that a user stands at a designated position of the smart toilet and the smart toilet is in an open lid state, and the water column detection range at least includes an internal range of the smart toilet body and a range extending upward from the smart toilet body;

[0138] When the water column detection start condition is met, a water column detection instruction is received, and the millimeter wave radio frequency transceiver unit, the transmitting antenna and the receiving antenna are controlled to obtain water column signal data within the water column detection range;

[0139] Based on the collected water column signal data, multiple statistical initial characteristic values ​​of single-frame point cloud data are obtained through multiple dimension screening;

[0140] A plurality of signal features are calculated by taking a plurality of statistical initial feature values ​​of 10 consecutive frames of point cloud data as a group;

[0141] During the water column detection process, multiple signal features of each group are used to determine whether a water column exists through preset judgment rules, and the water column detection results are output.

[0142] The effects achieved by the method and system provided above are consistent.

[0143] This embodiment provides a smart toilet, which has any of the above-mentioned smart toilet water column detection systems based on millimeter wave radar, and its internal structure diagram can be shown as follows: Figure 4 As shown. The computer device includes a processor, a memory and a network interface connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal through a network connection.

[0144] Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0145] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0146] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0147] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0148] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0149] It should also be understood that in the embodiments of this article, the term "and / or" is only a description of the association relationship of the associated objects, indicating that three relationships may exist. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0150] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this article.

[0151] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0152] In the several embodiments provided herein, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of the units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, or can be electrical, mechanical or other forms of connection.

[0153] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiments of this article.

[0154] Specific embodiments are used in this article to illustrate the principles and implementation methods of this article. The description of the above embodiments is only used to help understand the methods and core ideas of this article. At the same time, for general technicians in this field, according to the ideas of this article, there will be changes in the specific implementation methods and application scopes. In summary, the content of this specification should not be understood as a limitation on this article.

Claims

1. An intelligent toilet water column detection system based on millimeter wave radar, characterized in that: The system includes: a millimeter wave radar processing module and a smart toilet: The millimeter wave radar processing module is installed on the smart toilet, and the millimeter wave radar processing module includes a millimeter wave radio frequency transceiver unit, a micro control unit, a transmitting antenna and a receiving antenna. The micro control unit is connected to the millimeter wave radio frequency transceiver unit, the transmitting antenna and the receiving antenna respectively, and controls the millimeter wave radio frequency transceiver unit, the transmitting antenna and the receiving antenna to work according to preset instructions to obtain water column signal data of a user standing at a preset position of the smart toilet; The micro control unit is also used to provide a water column detection result according to a plurality of characteristic values ​​in the water column signal data; The mainboard software of the smart toilet is used to output corresponding control instructions based on the water column detection results returned by the millimeter wave radar processing module and the state of the smart toilet lid switch.

2. The system according to claim 1, characterized in that The microcontroller unit performs water column detection through the following steps: Determine a water column detection start condition and a water column detection range, wherein the start condition at least includes that a user stands at a designated position of the smart toilet and the smart toilet is in an open lid state, and the water column detection range at least includes an internal range of the smart toilet body and a range extending upward from the smart toilet body; When the water column detection start condition is met, a water column detection instruction is received, and the millimeter wave radio frequency transceiver unit, the transmitting antenna and the receiving antenna are controlled to obtain water column signal data within the water column detection range; Based on the collected water column signal data, multiple statistical initial characteristic values ​​of single-frame point cloud data are obtained through multiple dimension screening; A plurality of signal features are calculated by taking a plurality of statistical initial feature values ​​of 10 consecutive frames of point cloud data as a group; During the water column detection process, multiple signal features of each group are used to determine whether a water column exists through preset judgment rules, and the water column detection result is output to the smart toilet.

3. The system according to claim 2, characterized in that The dimensions for screening each acquisition point in a single-frame point cloud data include at least the following three: The collection point is within the water column detection range; The absolute value of the speed of the acquisition point exceeds the preset speed, and the moving direction is toward the millimeter wave radar processing module; The acquisition point is within a preset angle range of the radar beam center.

4. The system according to claim 2, characterized in that The multiple statistical initial eigenvalues ​​include at least the following: The number of collection points with a speed less than 0 in the filtered single-frame point cloud data minus_V_Num; The speed Max_v with the largest absolute value among the collection points whose speed is less than 0 in the filtered single-frame point cloud data; The number of selected collection points within the water column detection range, TargetNum; Whether the single frame point cloud data is valid after screening within the water column detection range, Valid_Sign, when TargetNum>1, Valid_Sign=1, otherwise Valid_Sign=0; The maximum power Max_Pow, the maximum Y coordinate value Y_max, the minimum Y coordinate value Y_min, and the average Y coordinate value Y_mean of the collected points in the single-frame point cloud data after screening within the water column detection range; The minimum value R_min of the distance from the acquisition point to the radar within the water column detection range.

5. Among them, The X-axis is parallel to the ground and parallel to the center line of the smart toilet. The positive direction of the X-axis is on the side of the radar board facing the user. The Y-axis is parallel to the ground. When the user faces the radar, the left side is the negative direction of the Y-axis and the right side is the positive direction of the Y-axis. The Z-axis is perpendicular to the ground, with the negative direction of the Z-axis pointing upward and the positive direction of the Z-axis pointing downward. The system according to claim 4, characterized in that the plurality of signal features corresponding to 10 consecutive frames of point cloud data include the following: The sum of Valid_Sign in all single-frame point cloud data is Sum_Valid_Sign; The sum of Y_mean in all single-frame point cloud data is divided by Sum_Valid_Sign to get Total_Y_Mean; When Valid_sign=1, if the deviations of Y_max and Y_min from Total_Y_Mean are within a certain distance, the Y of the single frame is valid, and the number of all valid Ys in all 10 frames, sum_valid_y, is calculated; The number of frames with R_min exceeding 0.4m in all single-frame point cloud data, sum_r_min_far; The number of frames with R_min exceeding 0.5m in all single-frame point cloud data sum_r_min_further; If the maximum Max_Pow of one frame in all single-frame point cloud data exceeds a certain threshold, max_pow_flag=1 is defined, otherwise max_pow_flag=0; If the number of points in one frame of all single-frame point cloud data exceeds a certain threshold after screening, point_num_flag=1 is defined, otherwise point_num_flag=0; The velocity value max_v_inBuff which is less than 0 and has the largest absolute value among all single-frame point cloud data; The total number of points after screening in all single-frame point cloud data is sum_point_num, the sum of the points with speed less than 0 in the past 10 frames is sum_minus_v_num, and the number of valid frames in the past 10 frames is sum_valid_num.

6. The system according to claim 1, characterized in that The presence of a water column is determined by at least one of the following preset judgment rules: If sum_valid_num>=4, sum_minus_v_num=sum_point_num, max_pow_flag==0, sum_r_min_further>=sum_valid_num, max_v_inBuff<-1.2m / s, sum_valid_y==sum_valid_num, it is determined that there is a water column; or If sum_valid_num>=5, sum_minus_v_num>=0.9*sum_point_num, max_pow_flag==0, sum_r_min_further>=sum_valid_num-1, max_v_inBuff<-1.2m / s, sum_valid_y>=sum_valid_num-1, it is determined that there is a water column; or If sum_valid_num>=6, sum_minus_v_num>=0.9*sum_point_num, max_pow_flag==0, sum_r_min_far>=(sum_valid_num-1)), then if point_num_flag is not 0, it is determined that there is a water column; otherwise, if point_num_flag==0 and sum_valid_y>=(sum_valid_num-1), it is determined that there is a water column; or If sum_valid_num>=8, sum_minus_v_num>=0.95*sum_point_num, max_pow_flag==0, then if point_num_flag is not 0, it is determined that there is a water column; otherwise, if point_num_flag=0 and sum_valid_y>=8, it is determined that there is a water column.

7. The system according to claim 1, characterized in that When the smart toilet receives a signal indicating that a water column exists, the smart toilet outputs an instruction to continue water column detection. When the smart toilet receives a signal indicating that a water column does not exist and the user is not standing at a designated position of the smart toilet, the smart toilet closes the lid and performs flushing.

8. A method for detecting water column in an intelligent toilet, characterized in that: The method is applied to a smart toilet equipped with a millimeter wave radar processing module, wherein the millimeter wave radar processing module includes a millimeter wave radio frequency transceiver unit, a micro control unit, a transmitting antenna and a receiving antenna, wherein the micro control unit is connected to the millimeter wave radio frequency transceiver unit, the transmitting antenna and the receiving antenna respectively, and the method includes the following steps: Determine a water column detection start condition and a water column detection range, wherein the start condition at least includes that a user stands at a designated position of the smart toilet and the smart toilet is in an open lid state, and the water column detection range at least includes an internal range of the smart toilet body and a range extending upward from the smart toilet body; When the water column detection start condition is met, a water column detection instruction is received, and the millimeter wave radio frequency transceiver unit, the transmitting antenna and the receiving antenna are controlled to obtain water column signal data within the water column detection range; Based on the collected water column signal data, multiple statistical initial characteristic values ​​of single-frame point cloud data are obtained through multiple dimension screening; A plurality of signal features are calculated by taking a plurality of statistical initial feature values ​​of 10 consecutive frames of point cloud data as a group; During the water column detection process, multiple signal features of each group are used to determine whether a water column exists through preset judgment rules, and the water column detection results are output.

9. A smart toilet, characterized in that: The smart toilet has the smart toilet water column detection system based on millimeter wave radar as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to claim 8 is implemented.

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