Method for monitoring activities of old people in toilet and related equipment

Abstract

The invention belongs to the technical field of elderly activity monitoring, and discloses a toilet elderly activity monitoring method and related equipment, two passive infrared sensors are used for detecting original infrared radiation signals of a human body and infrared radiation intensity data reflected by a mirror surface respectively, and a water vapor sensor is used for detecting water vapor concentration data; interference of mirror reflection and water vapor to the environment is comprehensively considered, the sensitivity threshold value of the sensor is adjusted based on the interference intensity, human body activity judgment is conducted by comparing the original infrared radiation signal of the human body with the sensitivity threshold value, and therefore environment interference can be effectively restrained, and the method has the advantage of improving the accuracy of activity monitoring of the old in the toilet.

Description

Technical Field

[0001] The present application relates to the technical field of elderly activity monitoring, and in particular to a method for monitoring elderly activities in a bathroom and related equipment. Background Art

[0002] With the increasing popularity of home-based elderly care, the issue of safety monitoring for elderly people living alone is particularly important. As an important place for the daily activities of the elderly at home, the bathroom has special environment, such as relatively small space, high humidity, and usually installed with mirrors. In scenes such as showering, the bathroom is filled with water vapor. These factors make the bathroom a high-incidence area for accidents such as falls of the elderly. In order to effectively ensure the safety of elderly people living alone in the bathroom, the use of low-cost and non-contact passive infrared sensors for human activity monitoring has become a common technical means. Passive infrared sensors sense human activities by detecting infrared radiation emitted by the human body. This technology does not require users to wear any equipment, can effectively protect user privacy, and is easily accepted by the elderly.

[0003] However, the unique environmental factors of the bathroom have brought many technical challenges to the application of passive infrared sensors in this scenario. On the one hand, the mirrors commonly found in the bathroom will reflect infrared radiation from the human body and other objects in the environment, resulting in complex infrared signal components received by the sensor, making it difficult to effectively distinguish between real human radiation signals and interference signals generated by mirror reflection. On the other hand, the water vapor generated during showering will absorb and scatter infrared radiation, which will further weaken the intensity of human radiation signals and reduce the signal-to-noise ratio. Especially in a relatively small space such as the bathroom, mirror reflection interference and water vapor interference are easily superimposed, making the environmental interference problem more complicated and difficult to handle. Under the influence of the above complex environmental interference, traditional passive infrared sensors are very prone to misjudgment and cannot accurately identify the state of human activity, which in turn leads to problems such as false alarms or missed alarms in the monitoring system, seriously affecting the reliability of the monitoring system.

[0004] Therefore, how to effectively suppress environmental interference in a bathroom environment with mirror reflection and water vapor, thereby improving the accuracy of human activity monitoring by passive infrared sensors, has become a technical problem that needs to be urgently solved by technicians in this field.

[0005] In view of the above problems, the existing technology needs to be improved urgently. Summary of the invention

[0006] The purpose of this application is to provide a method and related equipment for monitoring the activities of the elderly in the bathroom, which can improve the accuracy of monitoring the activities of the elderly in the bathroom.

[0007] In a first aspect, the present application provides a method for monitoring elderly people's activities in a bathroom, which is used to monitor elderly people's activities in a water vapor environment of a bathroom equipped with a mirror. The method comprises the following steps: A1. Receive the original infrared radiation signal of the human body detected by the first passive infrared sensor, the infrared radiation intensity data of the mirror reflection detected by the second passive infrared sensor, and the water vapor concentration data detected by the water vapor sensor; the detection field of the first passive infrared sensor avoids the mirror area of ​​the bathroom, and the detection field of the second passive infrared sensor faces the mirror area of ​​the bathroom; A2. Calculate the comprehensive interference intensity of the mirror reflection and water vapor on the environment according to the infrared radiation intensity data of the mirror reflection and the water vapor concentration data; A3 based on the evaluation of the comprehensive interference intensity, nonlinearly adjusting the sensitivity threshold of the first passive infrared sensor to obtain an adjusted sensitivity threshold; A4. Compare the original infrared radiation signal of the human body with the adjusted sensitivity threshold, combine with the human activity duration judgment mechanism, determine whether human activity occurs and output an alarm signal in a timely manner.

[0008] This method can effectively suppress environmental interference by comprehensively considering the interference of mirror reflection and water vapor on the environment and adjusting the sensor sensitivity threshold based on the interference intensity. It has the advantage of improving the accuracy of monitoring the activities of the elderly in the bathroom.

[0009] Preferably, a plurality of water vapor sensors are provided, and the plurality of water vapor sensors are distributed at different positions of the bathroom mirror area; Step A2 includes: Performing weighted averaging on the water vapor concentration data detected by each of the water vapor sensors to obtain an average water vapor concentration; The comprehensive interference intensity of the specular reflection and the water vapor on the environment is calculated according to the infrared radiation intensity data of the specular reflection and the average water vapor concentration.

[0010] Through the above method, the accuracy of the comprehensive interference intensity calculation results can be improved. As a result, the subsequent sensitivity threshold adjustment and human activity determination can be based on more accurate interference assessment, thereby improving the reliability of elderly activity monitoring.

[0011] Preferably, the step A2 further comprises: Monitor the status of bathroom lighting fixtures in real time. If a change in the status of the lighting fixture is detected, the time of the change will be recorded. Collecting the infrared radiation intensity data reflected by the mirror in a preset time window before and after the state of the lamp changes, and calculating the infrared radiation intensity change rate in the time window; Determine whether the infrared radiation intensity change rate exceeds a preset change rate threshold, and if so, determine the interference intensity adjustment parameter according to the lamp state change type; According to the interference intensity adjustment parameter, the calculation result of the comprehensive interference intensity of specular reflection and water vapor on the environment is adjusted.

[0012] The interference of the state change of bathroom lighting fixtures on infrared radiation is considered, and the influence of the state change of lighting fixtures is added to the calculation of comprehensive interference intensity, making the assessment of environmental interference intensity more comprehensive and accurate. This helps to more accurately adjust the sensitivity threshold of the first passive infrared sensor, thereby improving the accuracy of monitoring the activities of the elderly in the water vapor environment of the bathroom and reducing the false alarm rate.

[0013] Preferably, step A3 comprises: A301. Obtain the individual infrared radiation intensity levels of multiple elderly people and divide them into multiple sensitivity adjustment intervals; A302. According to the comprehensive interference intensity, determine the sensitivity adjustment parameter, the sensitivity adjustment parameter includes an adjustment amplitude and an adjustment direction; A303. Calculate the sensitivity threshold adjustment amount of the first passive infrared sensor according to the sensitivity adjustment interval of the current infrared radiation intensity level of the elderly individual and the sensitivity adjustment parameter; A304. Add the sensitivity threshold adjustment amount to the initial sensitivity threshold of the first passive infrared sensor to obtain an adjusted sensitivity threshold.

[0014] Preferably, a plurality of water vapor sensors are provided, and the plurality of water vapor sensors are distributed at different positions of the bathroom mirror area; Step A302 includes: E1. Dividing the mirror area into a plurality of sub-areas, and calculating the water vapor concentration of each sub-area according to the water vapor concentration data detected by each water vapor sensor; E2. Calculate the infrared radiation absorption rate of each sub-region according to the water vapor concentration of each sub-region; E3. Calculate the weighted average infrared radiation absorption rate based on the infrared radiation absorption rate of each sub-region and the area ratio of each sub-region; E4. Determine a sensitivity adjustment parameter based on the weighted average infrared radiation absorption rate and the comprehensive interference intensity, wherein the sensitivity adjustment parameter includes an adjustment amplitude and an adjustment direction.

[0015] Preferably, step A303 includes: C1. Collect the infrared radiation intensity of the elderly in real time, and use the Kalman filter algorithm to perform smoothing to obtain the smoothed infrared radiation intensity value; C2. According to the smoothed infrared radiation intensity value, dynamically adjust the upper and lower limits of the sensitivity adjustment interval to ensure that the current infrared radiation intensity level of the elderly individual is located in the middle of the adjustment interval; C3. According to the sensitivity adjustment interval of the infrared radiation intensity level of the elderly individual and the sensitivity adjustment parameter, the sensitivity threshold adjustment amount of the first passive infrared sensor is calculated by a piecewise linear interpolation algorithm.

[0016] Preferably, step A4 comprises: A401. Compare the original infrared radiation signal of the human body with the adjusted sensitivity threshold to obtain a comparison result; A402. If the comparison result shows that the original infrared radiation signal of the human body exceeds the adjusted sensitivity threshold, monitor the duration of the original infrared radiation signal of the human body exceeding the adjusted sensitivity threshold; A403. If the duration exceeds the preset time threshold, it is determined that human activity has occurred and an alarm signal is output.

[0017] In a second aspect, the present application provides a device for monitoring elderly people's activities in a bathroom, which is used to monitor elderly people's activities in a water vapor environment of a bathroom equipped with a mirror, and the device comprises: A signal receiving module is used to receive the original infrared radiation signal of the human body detected by the first passive infrared sensor, the infrared radiation intensity data of the mirror reflection detected by the second passive infrared sensor, and the water vapor concentration data detected by the water vapor sensor; the detection field of the first passive infrared sensor avoids the mirror area of ​​the bathroom, and the detection field of the second passive infrared sensor faces the mirror area of ​​the bathroom; An interference assessment module, used to calculate the comprehensive interference intensity of the mirror reflection and water vapor on the environment according to the infrared radiation intensity data of the mirror reflection and the water vapor concentration data; A threshold adjustment module, configured to nonlinearly adjust the sensitivity threshold of the first passive infrared sensor based on the evaluated comprehensive interference intensity to obtain an adjusted sensitivity threshold; The activity determination module is used to compare the original infrared radiation signal of the human body with the adjusted sensitivity threshold, and combine the human activity duration determination mechanism to determine whether human activity occurs and output an alarm signal in a timely manner.

[0018] In a third aspect, the present application provides an electronic device including a processor and a memory, wherein the memory stores a computer program executable by the processor, and when the processor executes the computer program, it runs the steps in the method for monitoring activities of the elderly in the bathroom as described above.

[0019] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps in the method for monitoring activities of elderly people in bathrooms as described above are performed.

[0020] Beneficial effect: The present application provides a method and related equipment for monitoring the activities of the elderly in the bathroom. By comprehensively considering the interference of mirror reflection and water vapor on the environment and adjusting the sensor sensitivity threshold based on the interference intensity, it can effectively suppress environmental interference and has the advantage of improving the accuracy of monitoring the activities of the elderly in the bathroom. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 Flow chart of the method for monitoring elderly people's activities in the bathroom provided in an embodiment of the present application.

[0022] Figure 2 This is a schematic diagram of the structure of the device for monitoring the activities of the elderly in the bathroom provided in an embodiment of the present application.

[0023] Figure 3 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0024] Explanation of reference numerals: 1. Model acquisition module; 2. Parameter determination module; 3. Microstructure preparation module; 4. Coating processing module; 301. Processor; 302. Memory; 303. Communication bus. DETAILED DESCRIPTION

[0025] The technical solutions in the present application will be clearly and completely described below in conjunction with the drawings in the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The components of the present application generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the present application for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0026] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0027] refer to Figure 1This application proposes a method for monitoring elderly people's activities in a bathroom, which is used to monitor elderly people's activities in a water vapor environment of a bathroom equipped with a mirror. The steps of the method include: A1. Receive the original infrared radiation signal of the human body detected by the first passive infrared sensor, the infrared radiation intensity data of the mirror reflection detected by the second passive infrared sensor, and the water vapor concentration data detected by the water vapor sensor; the detection field of the first passive infrared sensor avoids the mirror area of ​​the bathroom, and the detection field of the second passive infrared sensor faces the mirror area of ​​the bathroom; A2. Calculate the comprehensive interference intensity of specular reflection and water vapor on the environment based on the infrared radiation intensity data of specular reflection and water vapor concentration data; A3. Based on the evaluated comprehensive interference intensity, nonlinearly adjusting the sensitivity threshold of the first passive infrared sensor to obtain an adjusted sensitivity threshold; A4. Compare the original infrared radiation signal of the human body with the adjusted sensitivity threshold, and combine it with the human activity duration judgment mechanism to determine whether human activity has occurred and output an alarm signal in a timely manner.

[0028] By comprehensively considering the interference of mirror reflection and water vapor on the environment and adjusting the sensor sensitivity threshold based on the interference intensity, environmental interference can be effectively suppressed, which has the advantage of improving the accuracy of monitoring the activities of the elderly in the bathroom.

[0029] Among them, in step A1, the first passive infrared sensor and the second passive infrared sensor are installed at appropriate locations in the bathroom to ensure that the detection area of ​​the first passive infrared sensor is free from the influence of the mirror and focuses on detecting the original infrared radiation emitted by the human body. The second passive infrared sensor is adjusted so that its detection area is aimed at the bathroom mirror, specifically for capturing the infrared radiation reflected by the mirror. The water vapor sensor is placed in the bathroom to monitor the water vapor concentration in the bathroom air in real time; for example, it can be set on a wall near the mirror or on the mirror.

[0030] In step A2, the calculation of the comprehensive interference intensity can adopt a variety of mathematical models. For example, a function relationship can be established, which takes the infrared radiation intensity data of mirror reflection and the water vapor concentration data as input and outputs the comprehensive interference intensity value. The function relationship can be nonlinear to more accurately reflect the impact of complex environmental interference.

[0031] Among them, in step A3, the nonlinear adjustment of the sensitivity threshold can adopt a lookup table method. A lookup table between the comprehensive interference intensity and the sensitivity threshold adjustment amount is pre-established, and the table records the specific values ​​of the sensitivity threshold that need to be adjusted under different interference intensities. The adjustment method is nonlinear. For example, under low interference intensity, the threshold adjustment amount is small; under high interference intensity, the threshold adjustment amount is large, and the adjustment amplitude may not increase linearly.

[0032] Among them, in step A4, the human activity duration judgment mechanism can be set to, only when the original infrared radiation signal of the human body exceeds the adjusted sensitivity threshold and the duration exceeds the set time threshold (for example, 2 seconds), it is finally determined that human activity has occurred and an alarm signal is issued. The setting of the time threshold can effectively filter out short-term interference signals and avoid false alarms. The alarm signal can be used to trigger the subsequent human activity abnormality judgment program, so as to enter the human activity abnormality monitoring process according to the real-time changes in the original infrared radiation signal of the human body. The human activity abnormality monitoring process may include: preliminarily judging whether the elderly have an abnormality according to the real-time changes in the original infrared radiation signal of the human body (the existing technology can be used for judgment), when it is preliminarily judged that an abnormality has occurred, the voice device set in the bathroom can be turned on, and the elderly’s state can be finally confirmed by voice interaction with the elderly. When the elderly are finally determined to be abnormal, an alarm message is sent to the monitoring terminal.

[0033] Specifically, the working principle of the method for monitoring the activities of the elderly in the bathroom is as follows: first, the original infrared radiation signal of the human body is directly collected by the first passive infrared sensor as the basic signal for judging the human activity. At the same time, the second passive infrared sensor and the water vapor sensor are used to collect the infrared radiation intensity data and the water vapor concentration data of the mirror reflection respectively, which are used to evaluate the environmental interference intensity. Then, based on the comprehensive interference intensity obtained by the evaluation, the sensitivity threshold of the first passive infrared sensor is nonlinearly and dynamically adjusted. When the environmental interference is strong, the sensitivity threshold is increased to reduce the sensitivity of the sensor to the interference signal; when the environmental interference is weak, the sensitivity threshold is reduced to improve the sensitivity of the sensor to the human activity signal. Finally, the original infrared radiation signal of the human body is compared with the adjusted sensitivity threshold, and combined with the human activity duration judgment mechanism, it is accurately determined whether the human activity occurs, and an alarm signal is output. Therefore, the method can effectively suppress the interference of the bathroom mirror reflection and water vapor on the monitoring of the elderly activity, and improve the accuracy and reliability of the monitoring of the elderly activity in a complex environment. Furthermore, the alarm signal can be used to trigger the subsequent abnormal human activity judgment program, so that the elderly abnormality recognition is performed only when it is determined that the elderly are active in the bathroom, so as to reduce the unnecessary recognition calculation burden.

[0034] In some embodiments, in step A2, the comprehensive interference intensity can be calculated by the following formula: comprehensive interference intensity=K1*mirror reflection infrared intensity+K2*water vapor concentration^2, where K1 and K2 are preset weight coefficients.

[0035] In some possible implementations, in step A3, nonlinear adjustment is implemented through a piecewise function, when the comprehensive interference intensity is less than threshold T1, the threshold adjustment amount is 0; when the comprehensive interference intensity is greater than or equal to T1 and less than T2, the threshold adjustment amount is C1; when the comprehensive interference intensity is greater than or equal to T2, the threshold adjustment amount is C2, where T1, T2, C1, and C2 are preset constants.

[0036] Among them, only one water vapor sensor can be set, or multiple water vapor sensors can be set. When only one water vapor sensor is set, the water vapor concentration data measured by the single water vapor sensor can be substituted into the water vapor concentration in the above-mentioned comprehensive interference intensity calculation formula to perform comprehensive interference intensity calculation. When multiple water vapor sensors are set, the comprehensive interference intensity can be calculated in step A2 according to the mean or weighted average of the water vapor concentration data measured by each water vapor sensor.

[0037] For example, in some possible implementations, a plurality of water vapor sensors are provided, and the plurality of water vapor sensors are distributed at different positions of the bathroom mirror area; Step A2 includes: A201. Perform weighted averaging on the water vapor concentration data detected by each water vapor sensor to obtain an average water vapor concentration; A202. Based on the infrared radiation intensity data of mirror reflection and the average water vapor concentration, calculate the comprehensive interference intensity of mirror reflection and water vapor on the environment.

[0038] Among them, multiple water vapor sensors can be set at different positions of the bathroom mirror area, such as the upper, middle and lower parts of the mirror, to cover a wider area and collect water vapor concentration data at different positions more comprehensively. As a preferred embodiment, the water vapor concentration data collected by each sensor can be weighted averaged according to the representativeness of each water vapor sensor in the mirror area. For example, the data of the water vapor sensor located in the center area of ​​the mirror can be assigned a higher weight, while the data of the water vapor sensor located in the edge area can be assigned a lower weight. The weighted average calculation can use arithmetic mean, geometric mean or a more complex weighting algorithm to more accurately reflect the overall water vapor concentration level of the mirror area.

[0039] Among them, the comprehensive interference intensity of mirror reflection and water vapor on the environment is calculated according to the infrared radiation intensity data of mirror reflection and the average water vapor concentration. The following formula can be used for calculation: comprehensive interference intensity = K1*mirror reflection infrared intensity + K2*average water vapor concentration^2.

[0040] Specifically, in the water vapor environment of the bathroom, due to the uneven distribution of water vapor, relying solely on a single water vapor sensor may not be able to accurately evaluate the overall water vapor interference in the mirror area. In order to solve this problem, the present application uses multiple water vapor sensors and distributes them at different positions in the mirror area. These sensors work together to collect water vapor concentration data at their respective positions at the same time. By weighted averaging these data, a comprehensive average water vapor concentration value can be obtained, which can more accurately represent the water vapor concentration level of the entire mirror area. Subsequently, based on this average water vapor concentration and the infrared radiation intensity data of the mirror reflection, the comprehensive interference intensity of the mirror reflection and water vapor on the environment can be more accurately calculated. As a result, the subsequent sensitivity threshold adjustment and human activity determination can be based on a more accurate interference assessment, thereby improving the reliability of elderly activity monitoring.

[0041] In some specific embodiments, the bathroom mirror area is divided into three sub-areas: upper, middle, and lower, and a water vapor sensor is provided in each sub-area, for a total of three water vapor sensors. When performing weighted average calculation, the water vapor sensor data in the middle area is given a weight of 0.5, and the water vapor sensor data in the upper and lower areas are both given a weight of 0.25. In this way, the water vapor concentration in the middle area has a greater impact on the average water vapor concentration, which is more in line with the actual water vapor distribution. Using the weighted average water vapor concentration data to calculate the comprehensive interference intensity can improve the accuracy of the interference intensity assessment, thereby improving the performance of the elderly activity monitoring system.

[0042] In some preferred embodiments, step A2 further comprises: A203. Real-time monitoring of the status of bathroom lighting fixtures. If a change in the status of the lighting fixture is detected, the time of the change in the status of the lighting fixture is recorded; A204. Collect the infrared radiation intensity data of mirror reflection in the preset time window before and after the lamp state changes, and calculate the infrared radiation intensity change rate in the time window; A205. Determine whether the infrared radiation intensity change rate exceeds a preset change rate threshold. If it exceeds the preset change rate threshold, determine the interference intensity adjustment parameter according to the type of lamp state change; A206. Adjust the parameters according to the interference intensity to adjust the calculation results of the comprehensive interference intensity of mirror reflection and water vapor on the environment.

[0043] Among them, in step A203, real-time monitoring of the state of the bathroom lighting fixture can be achieved by a lamp state sensor. The lamp state sensor is configured to detect the current state of the bathroom lighting fixture, for example, whether the lamp is on or off. The lamp state sensor can be a light sensor arranged to detect the light intensity emitted by the lighting fixture. When the light intensity detected by the light sensor changes significantly, the system determines that the lamp state has changed. The moment when the lamp state changes is recorded as a time reference point for the subsequent calculation of the infrared radiation intensity change rate.

[0044] Among them, in step A204, the preset time window is set to a time range before and after the moment when the lamp state changes, for example, a time period from 10 seconds before the moment when the lamp state changes to 10 seconds after the moment when the lamp state changes. In this time window, the infrared radiation intensity data of the mirror reflection collected by the second passive infrared sensor is collected. The infrared radiation intensity change rate is calculated by analyzing the infrared radiation intensity data collected in the time window. Specifically, the change rate can be the difference between the maximum and minimum values ​​of the infrared radiation intensity in the time window, divided by the duration of the time window.

[0045] Among them, in step A205, the preset change rate threshold is a pre-set value used to determine whether the change in infrared radiation intensity is significant. The preset change rate threshold can be adjusted according to the actual application scenario and experimental data. If the calculated infrared radiation intensity change rate exceeds the preset change rate threshold, it indicates that the change in the lamp state has caused significant interference to the infrared radiation. The interference intensity adjustment parameter is a value used to adjust the comprehensive interference intensity. The determination of the interference intensity adjustment parameter depends on the type of lamp state change, and the type of lamp state change includes turning on and off the light. For example, when the lamp changes from the off state to the on state (i.e., turning on the light), the infrared radiation intensity usually increases, and the interference intensity adjustment parameter can be set to a positive value to increase the comprehensive interference intensity. Conversely, when the lamp changes from the on state to the off state (i.e., turning off the light), the infrared radiation intensity usually decreases, and the interference intensity adjustment parameter can be set to a negative value to reduce the comprehensive interference intensity.

[0046] In step A206, the comprehensive interference strength calculation result is adjusted after obtaining the interference strength adjustment parameter. The adjustment method may be addition adjustment, that is, the interference strength adjustment parameter is directly added to the original comprehensive interference strength calculation result to obtain the final comprehensive interference strength.

[0047] In some specific embodiments, the monitoring of bathroom lighting fixture state changes is not limited to the monitoring of the switch state of the fixture, but may also include the monitoring of the brightness adjustment state of the fixture. The fixture state sensor may be a brightness sensor, which is used to detect the brightness level of the lighting fixture. When the brightness sensor detects a change in the brightness level of the fixture, the system records the moment of the fixture brightness change and the type of brightness change (for example, the brightness is increased or decreased). The determination of the interference intensity adjustment parameter may be associated with the amplitude of the fixture brightness change. The greater the amplitude of the fixture brightness change, the greater the absolute value of the interference intensity adjustment parameter. For example, corresponding interference intensity adjustment parameters may be set for different lamp brightness change amplitude ranges to form an interference intensity adjustment parameter query table, and the corresponding interference intensity adjustment parameters may be obtained by querying the interference intensity adjustment parameter query table according to the actual amplitude of the lamp brightness change.

[0048] In some possible implementations, step A3 includes: A301. Obtain the individual infrared radiation intensity levels of multiple elderly people and divide them into multiple sensitivity adjustment intervals; A302. According to the comprehensive interference intensity, determine the sensitivity adjustment parameters, the sensitivity adjustment parameters include adjustment amplitude and adjustment direction; A303. Calculate the sensitivity threshold adjustment amount of the first passive infrared sensor according to the sensitivity adjustment interval and the sensitivity adjustment parameter of the current infrared radiation intensity level of the elderly individual; A304. Add the sensitivity threshold adjustment amount to the initial sensitivity threshold of the first passive infrared sensor to obtain an adjusted sensitivity threshold.

[0049] Among them, in step A301, the acquisition of the infrared radiation intensity levels of multiple elderly individuals can be achieved by pre-collecting a large amount of infrared radiation intensity data of elderly people of different ages and physiques, and performing statistical analysis to divide them into multiple levels. For example, the infrared radiation intensity of the elderly individuals can be divided into three levels: high, medium, and low according to the mean and standard deviation of the infrared radiation intensity. The division of the sensitivity adjustment interval can be based on the infrared radiation intensity level, and different sensitivity adjustment ranges are preset. For example, for elderly people with a high infrared radiation intensity level, the sensitivity adjustment interval can be set to be relatively narrow, and vice versa.

[0050] Among them, in step A302, the higher the comprehensive interference intensity, the greater the adjustment amplitude can be, and the adjustment direction can be to reduce the sensitivity threshold to avoid misjudgment. The determination of the sensitivity adjustment parameter can be achieved by establishing a mapping relationship between the comprehensive interference intensity and the sensitivity adjustment parameter, for example, using function fitting or a lookup table.

[0051] Among them, in step A303, the sensitivity threshold adjustment amount can be calculated by linear interpolation, nonlinear interpolation or piecewise function. For example, the sensitivity threshold adjustment amount can be calculated by piecewise linear interpolation algorithm according to the relative position of the current individual infrared radiation intensity level of the elderly (determined according to the division rules of the original infrared radiation signal of the human body and the individual infrared radiation intensity level of the elderly) in the sensitivity adjustment interval, and the sensitivity adjustment parameter.

[0052] In step A304, the initial sensitivity threshold may be a fixed value pre-set based on experience or experiment, or a dynamic value adjusted according to the environment. By adding the sensitivity threshold adjustment amount to the initial sensitivity threshold, the final adjusted sensitivity threshold may be obtained for subsequent human activity determination.

[0053] Therefore, by considering the individual differences in infrared radiation intensity among the elderly, the sensitivity threshold adjustment can be made more personalized and accurate, which can effectively improve the monitoring accuracy of the system in complex environments.

[0054] Specifically, in order to solve the problem of monitoring error caused by the difference in the intensity of individual infrared radiation of different elderly people, step A3 nonlinearly adjusts the sensitivity threshold of the first passive infrared sensor based on the evaluated comprehensive interference intensity to obtain the adjusted sensitivity threshold. In this process, it is necessary to consider the situation that there are differences in the intensity of individual infrared radiation of different elderly people. Steps A301-A304 are set to solve the problem of monitoring error caused by the difference in the intensity of individual infrared radiation of different elderly people. First, step A301 completes the classification of individual infrared radiation intensity levels and the setting of sensitivity adjustment intervals. This means that the system pre-analyzes the individual infrared radiation characteristics of multiple elderly people, divides the elderly into different levels, and sets corresponding sensitivity adjustment intervals for each level. This preset interval takes into account individual differences. Next, step A302 uses the comprehensive interference intensity evaluation result and determines the sensitivity adjustment parameter based on this result, including the adjustment amplitude and adjustment direction (such as increase or decrease). The sensitivity adjustment parameter determines the specific impact of environmental interference on sensitivity adjustment. Then, step A303 combines the two factors of individual infrared radiation intensity level and environmental interference to calculate the sensitivity threshold adjustment amount. The system finds the corresponding sensitivity adjustment interval according to the infrared radiation intensity level of the elderly, and then determines the sensitivity adjustment parameter in combination with step A302, and calculates the specific threshold adjustment amount within the interval. Finally, step A304 applies the calculated adjustment amount to the initial sensitivity threshold to complete the threshold update. Through the above steps, the individual differences of the elderly are further considered, so that the sensitivity threshold adjustment not only depends on the intensity of environmental interference, but also makes personalized adjustments based on the infrared radiation characteristics of the elderly themselves, thereby improving the accuracy of the system's monitoring of different elderly activities.

[0055] In some specific embodiments, in step A301, the infrared radiation intensity data of multiple elderly people can be collected in advance, and the infrared radiation intensity of the elderly can be divided into three levels using a clustering algorithm: low radiation level, medium radiation level, and high radiation level. The sensitivity adjustment interval is also divided into three intervals accordingly: the sensitivity adjustment interval corresponding to the low radiation level, the sensitivity adjustment interval corresponding to the medium radiation level, and the sensitivity adjustment interval corresponding to the high radiation level. In step A302, the comprehensive interference intensity is divided into five levels: no interference, slight interference, moderate interference, strong interference, and strong interference. The corresponding adjustment amplitude and adjustment direction are preset for each comprehensive interference intensity level, and the corresponding adjustment amplitude and adjustment direction are determined according to the level to which the comprehensive interference intensity belongs. In step A303, it is assumed that the sensitivity adjustment interval corresponding to the current individual infrared radiation intensity level of the elderly is [a1, b1], and the adjustment amplitude in the sensitivity adjustment parameter is c1. Then, the sensitivity threshold adjustment amount is calculated using a linear interpolation algorithm. Assuming that the relative position of the current individual infrared radiation intensity of the elderly in the level interval in which it is located is d, the sensitivity threshold adjustment amount = c1 + (b1-a1) * d = 0.3. In step A304, assuming that the initial sensitivity threshold of the first passive infrared sensor is e, the adjusted sensitivity threshold = e + sensitivity threshold adjustment amount. Thus, through the specific implementation method, the complete process of sensitivity threshold adjustment can be clearly demonstrated, and the setting of parameters and the calculation of adjustment amount are both operable, which can ensure the effective implementation of the technical solution.

[0056] In some embodiments, a plurality of water vapor sensors are provided, and the plurality of water vapor sensors are distributed at different positions of the bathroom mirror area; Step A302 includes: E1. Divide the mirror area into multiple sub-areas, and calculate the water vapor concentration of each sub-area according to the water vapor concentration data detected by each water vapor sensor; E2. Calculate the infrared radiation absorption rate of each sub-region according to the water vapor concentration of each sub-region; E3. Calculate the weighted average infrared radiation absorption rate based on the infrared radiation absorption rate of each sub-region and the area ratio of each sub-region; E4. Determine the sensitivity adjustment parameters based on the weighted average infrared radiation absorption rate and the comprehensive interference intensity. The sensitivity adjustment parameters include the adjustment amplitude and adjustment direction.

[0057] The difference in local water vapor concentration in the bathroom can easily lead to inaccurate sensitivity adjustment. Specifically, the uneven distribution of water vapor in the bathroom causes the comprehensive interference intensity detected by the second passive infrared sensor to be unable to accurately reflect the local water vapor concentration, affecting the sensitivity adjustment. Steps E1 to E4 are intended to solve this problem.

[0058] Among them, the mirror area is divided into multiple smaller areas. For example, a grid division method can be used to evenly divide the mirror into several rectangular sub-areas. Water vapor sensors are set at different positions of the mirror area in order to collect water vapor concentration data of each sub-area. Specifically, a water vapor sensor can be set at the center or corner of each sub-area to monitor the water vapor concentration of the sub-area. The water vapor concentration of each sub-area can be determined based on the water vapor concentration data directly detected by the water vapor sensor set in the sub-area. If multiple water vapor sensors are set in a sub-area, the water vapor concentration of the sub-area can be calculated by the average value of the water vapor concentration data detected by these water vapor sensors. Water vapor sensors can also be set only in some sub-areas. The water vapor concentration of the sub-area with a water vapor sensor can be determined by referring to the method described above. For the sub-area without a water vapor sensor, the water vapor concentration of the corresponding sub-area can be calculated by interpolation based on the water vapor concentration of the sub-area with a water vapor sensor.

[0059] The infrared radiation absorptivity reflects the absorption capacity of water vapor to infrared radiation. The higher the water vapor concentration, the higher the infrared radiation absorptivity. The infrared radiation absorptivity of each sub-region can be calculated based on the water vapor concentration data through a preset mathematical model or a lookup table. For example, an empirical formula or experimental data can be used to establish a mapping relationship between water vapor concentration and infrared radiation absorptivity.

[0060] When calculating the weighted average infrared radiation absorption rate, the area proportion of each sub-region needs to be considered. Sub-regions with larger areas have higher weights in the weighted average, while sub-regions with smaller areas have lower weights. By using area-weighted average, the water vapor interference of the entire mirror area can be more accurately evaluated.

[0061] The sensitivity adjustment parameter includes an adjustment amplitude and an adjustment direction, which are used to adjust the sensitivity threshold of the first passive infrared sensor. The adjustment amplitude indicates the size of the sensitivity threshold adjustment, and the adjustment direction indicates whether the sensitivity threshold is adjusted up or down. The determination of the sensitivity adjustment parameter needs to comprehensively consider the weighted average infrared radiation absorption rate and the comprehensive interference intensity. The weighted average infrared radiation absorption rate reflects the degree of water vapor interference in the mirror area, and the comprehensive interference intensity comprehensively considers the interference of mirror reflection and water vapor on the environment.

[0062] Take the difference in local water vapor concentration into consideration, accurately adjust the sensitivity, and avoid false alarms and missed alarms. According to the weighted average infrared radiation absorption rate and the comprehensive interference intensity, comprehensively evaluate the degree of environmental interference, determine the sensitivity adjustment parameters, and enable the system to adaptively adjust the sensitivity according to the actual situation to improve the accuracy of human activity monitoring. By determining the sensitivity adjustment parameters based on the weighted average infrared radiation absorption rate and the comprehensive interference intensity, the difference in local water vapor concentration and the overall interference intensity can be comprehensively considered to make the sensitivity adjustment more accurate. For example, an adjustment amplitude coefficient can be preset, and the correction coefficient of the adjustment amplitude can be obtained by multiplying the weighted average infrared radiation absorption rate by the adjustment amplitude coefficient. An initial adjustment amplitude is determined according to the comprehensive interference intensity (refer to the adjustment amplitude determination method in the previous article), and then the initial adjustment amplitude is multiplied by the correction coefficient to obtain the final adjustment amplitude.

[0063] Specifically, the water vapor distribution in the mirror area of ​​the bathroom may be uneven. If only a comprehensive interference intensity is used to represent the interference situation of the entire mirror area, it may not be accurate enough. In order to more accurately evaluate the water vapor interference, the mirror area is divided into multiple sub-areas, and water vapor sensors are set at different positions. The advantage of this is that the water vapor concentration data of each sub-area can be collected, thereby reflecting the uneven distribution of water vapor. Step E1 calculates the water vapor concentration of each sub-area, and step E2 calculates the infrared radiation absorptivity of each sub-area based on the water vapor concentration of the sub-area. The infrared radiation absorptivity is related to the water vapor concentration. The higher the water vapor concentration, the higher the infrared radiation absorptivity. By calculating the infrared radiation absorptivity of each sub-area, the degree of interference of water vapor on infrared radiation can be more finely evaluated. Step E3 considers the area proportion of each sub-area and calculates the weighted average infrared radiation absorptivity. This can comprehensively consider the water vapor interference situation of sub-areas of different sizes and obtain an average level that is more representative of the water vapor interference of the entire mirror area. Step E4 uses the weighted average infrared radiation absorptivity and the comprehensive interference intensity to determine the sensitivity adjustment parameter. Compared with directly using the comprehensive interference intensity, the weighted average infrared radiation absorption rate is used, and the uneven distribution of water vapor in the mirror area is taken into account, so that the determination of the sensitivity adjustment parameters is more accurate, so that the sensitivity threshold of the infrared sensor can be adjusted more effectively and the accuracy of human activity monitoring can be improved. Therefore, the water vapor interference can be evaluated more finely, thereby improving the reliability of the elderly activity monitoring method.

[0064] In some specific embodiments, the bathroom mirror is divided into four rectangular sub-areas of equal size, which are located at the upper left corner, upper right corner, lower left corner and lower right corner of the mirror respectively. A water vapor sensor is set at the center of each sub-area, and a total of four water vapor sensors are set. In step E1, the water vapor concentration of each sub-area directly uses the water vapor concentration data detected by the water vapor sensor of the corresponding sub-area. In step E2, assuming that the infrared radiation absorption rate is proportional to the water vapor concentration, a proportional coefficient is set, and the infrared radiation absorption rate of each sub-area is calculated by multiplying the water vapor concentration of each sub-area by the proportional coefficient. In step E3, since the areas of the four sub-areas are equal, the area proportion of each sub-area is 25%. The weighted average infrared radiation absorption rate is obtained by multiplying the infrared radiation absorption rates of the four sub-areas by 0.25 respectively, and then summing them. In step E4, the adjustment amplitude of the sensitivity adjustment parameter is proportional to the weighted average infrared radiation absorption rate, and the adjustment direction is to increase the sensitivity threshold. Specifically, an adjustment amplitude coefficient can be preset, and the correction coefficient of the adjustment amplitude can be obtained by multiplying the weighted average infrared radiation absorption rate by the adjustment amplitude coefficient, and an initial adjustment amplitude is determined according to the comprehensive interference intensity (refer to the adjustment amplitude determination method in the previous text), and then the initial adjustment amplitude is multiplied by the correction coefficient to obtain the final adjustment amplitude. Through the above specific implementation method, the water vapor interference can be more accurately evaluated according to the uneven distribution of water vapor in the mirror area, and the sensitivity threshold of the infrared sensor can be adjusted accordingly to improve the accuracy of human activity monitoring.

[0065] In some implementations, step A303 includes: C1. Collect the infrared radiation intensity of the elderly in real time, and use the Kalman filter algorithm to perform smoothing to obtain the smoothed infrared radiation intensity value; C2. According to the smoothed infrared radiation intensity value, dynamically adjust the upper and lower limits of the sensitivity adjustment range to ensure that the current infrared radiation intensity level of the elderly individual is in the middle of the adjustment range; C3. According to the sensitivity adjustment interval of the infrared radiation intensity level of the elderly individual and the sensitivity adjustment parameter, the sensitivity threshold adjustment amount of the first passive infrared sensor is calculated by a piecewise linear interpolation algorithm.

[0066] Among them, in step C1, the Kalman filter algorithm is used to smooth the real-time collected infrared radiation intensity of the elderly individual, so as to reduce the random fluctuation of the infrared radiation intensity signal and obtain a stable and reliable infrared radiation intensity value. The specific implementation of the Kalman filter algorithm can include two stages: state prediction and update. In the state prediction stage, based on the state estimation value and state transition model of the previous moment, the state value and covariance matrix of the current moment are predicted. In the update stage, the predicted state value is corrected by the Kalman gain using the observed value at the current moment to obtain the optimal state estimation value at the current moment. By iteratively executing the two stages of state prediction and update, smooth filtering of the infrared radiation intensity signal is achieved.

[0067] Among them, in step C2, the dynamic adjustment of the sensitivity adjustment interval is performed according to the smoothed infrared radiation intensity value. The upper and lower limits of the dynamic adjustment of the sensitivity adjustment interval are aimed at making the infrared radiation intensity level of the current elderly individual always located in the middle of the adjustment interval, thereby ensuring that the sensitivity adjustment interval can adapt to the differences in infrared radiation intensity of different elderly individuals, as well as the changes in the infrared radiation intensity of the elderly individuals over time. The dynamic adjustment of the sensitivity adjustment interval can be implemented using a sliding average algorithm. For example, a time window can be set to calculate the average value of the smoothed infrared radiation intensity value within the time window, adjust the center position of the sensitivity adjustment interval according to the average value, and adjust the upper and lower limits of the sensitivity adjustment interval according to a preset adjustment range.

[0068] Among them, in step C3, the piecewise linear interpolation algorithm is used to calculate the sensitivity threshold adjustment amount of the first passive infrared sensor according to the dynamic adjustment interval of the current individual infrared radiation intensity level of the elderly and the interference intensity adjustment parameter. The specific implementation of the piecewise linear interpolation algorithm may include the following steps: first, according to the sensitivity adjustment interval, the infrared radiation intensity level is divided into multiple segments; then, a corresponding sensitivity threshold adjustment amount calculation formula is preset for each segment, and the calculation formula can be a linear function; finally, according to the segment where the current individual infrared radiation intensity level of the elderly is located, the corresponding calculation formula is selected, and the interference intensity adjustment parameter is substituted to calculate the sensitivity threshold adjustment amount.

[0069] Specifically, in view of the problem that the sensitivity adjustment interval is fixed, a technical solution for dynamically adjusting the sensitivity adjustment interval is proposed. First, through step C1, the infrared radiation intensity of the elderly individual collected in real time is smoothed by using the Kalman filter algorithm to reduce the noise interference of the infrared radiation intensity signal and obtain an accurate data basis. Then, in step C2, according to the smoothed infrared radiation intensity value, the upper and lower limits of the sensitivity adjustment interval are dynamically adjusted so that the infrared radiation intensity level of the current elderly individual is always located in the middle of the adjustment interval. This dynamic adjustment mechanism ensures that the sensitivity adjustment interval can always cover the infrared radiation intensity range of the elderly individual, and improves the adaptability of the sensitivity adjustment. Finally, step C3 calculates the sensitivity threshold adjustment amount by a piecewise linear interpolation algorithm based on the dynamically adjusted sensitivity adjustment interval, combined with the interference intensity adjustment parameter, to achieve refined adjustment of the sensitivity threshold. Through the steps of smoothing the infrared radiation intensity by Kalman filtering, dynamically adjusting the sensitivity adjustment interval, and calculating the sensitivity threshold adjustment amount by piecewise linear interpolation, the dynamic adaptive adjustment of the sensitivity adjustment interval is realized, the problem of poor adaptability of the fixed sensitivity adjustment interval is solved, and the monitoring accuracy and reliability of the human activity monitoring system are improved.

[0070] In some specific embodiments, in step C1, the state transition model of the Kalman filter algorithm can be set to a constant speed motion model, and the observation model can be set to a linear model. The parameters of the Kalman filter algorithm, such as the process noise covariance matrix and the observation noise covariance matrix, can be adjusted according to the actual application scenario. In step C2, the initial range of the sensitivity adjustment interval can be set according to the historical data or empirical value of the individual infrared radiation intensity of the elderly. The time window length and adjustment amplitude of the sliding average algorithm can be adjusted according to the system sensitivity and stability requirements. In step C3, the number of segments and segment boundaries of the piecewise linear interpolation algorithm can be set according to the accuracy requirements of the sensitivity adjustment. The linear function parameters of each segment can be determined according to experimental data or theoretical analysis. For example, it is assumed that the sensitivity adjustment interval is divided into three segments: a low infrared radiation intensity level segment, a medium infrared radiation intensity level segment, and a high infrared radiation intensity level segment. For the low infrared radiation intensity level segment, the sensitivity threshold adjustment amount can be set to a smaller value; for the medium infrared radiation intensity level segment, the sensitivity threshold adjustment amount can be set to a medium value; for the high infrared radiation intensity level segment, the sensitivity threshold adjustment amount can be set to a larger value. Through the piecewise linear interpolation algorithm, a nonlinear mapping relationship between the sensitivity threshold adjustment amount and the individual infrared radiation intensity level of the elderly can be achieved, thereby improving the flexibility and accuracy of sensitivity adjustment.

[0071] In fact, the movement of the elderly body causes the infrared radiation intensity value to fluctuate, which may cause the Kalman filter algorithm to be difficult to converge quickly, and the smoothing effect is reduced. Specifically, the change in the amplitude of the elderly's movement causes a sharp change in the infrared radiation intensity. The traditional Kalman filter algorithm cannot quickly adapt to this change, resulting in distortion of the smoothed infrared radiation intensity value, affecting the accuracy of subsequent sensitivity adjustment. To solve this problem, in some possible implementations, step C1 includes: Acquire multiple infrared radiation intensity values ​​collected by the first passive external sensor when the elderly person's body moves; Calculate the rate of change of infrared radiation intensity and determine whether the rate of change exceeds a rate threshold; If the rate of change exceeds the rate threshold, the convergence speed of the Kalman filter algorithm is reduced, and the infrared radiation intensity value is smoothed using the reduced convergence speed to obtain a smoothed infrared radiation intensity value.

[0072] Among them, a plurality of infrared radiation intensity values ​​collected by the first passive external sensor when the elderly person's body moves are obtained as input data of the Kalman filter algorithm. The rate of change of the infrared radiation intensity is obtained by calculating the difference between two or more adjacent infrared radiation intensity values. The rate threshold is a pre-set value used to determine whether the change in infrared radiation intensity is drastic. The reduction of the convergence speed of the Kalman filter algorithm can be achieved by adjusting the relevant parameters in the Kalman filter algorithm. For example, the value of the process noise covariance matrix can be increased, or the value of the observation noise covariance matrix can be reduced to reduce the convergence speed of the Kalman filter algorithm. Smoothing the infrared radiation intensity value using the reduced convergence speed means that the Kalman filter algorithm filters the infrared radiation intensity value when the convergence speed is reduced to obtain the smoothed infrared radiation intensity value.

[0073] Specifically, during the monitoring of the elderly's activities, the first passive infrared sensor collects the infrared radiation intensity value of the elderly's body in real time. The system will continuously receive these infrared radiation intensity values ​​and calculate the rate of change of the infrared radiation intensity. When the calculated rate of change exceeds the preset rate threshold, the system determines that the elderly's body moves too fast and the infrared radiation intensity changes dramatically. As a result, the system will dynamically adjust the parameters of the Kalman filter algorithm to reduce its convergence speed. After the convergence speed of the Kalman filter algorithm decreases, the algorithm will focus more on the newly collected infrared radiation intensity value and weaken the smoothing effect, so that the smoothed infrared radiation intensity value can quickly follow the changes in the original infrared radiation intensity value, and more timely and accurately reflect the rapid movement of the elderly's body. On the contrary, when the rate of change of the infrared radiation intensity does not exceed the rate threshold, the Kalman filter algorithm maintains the original convergence speed to ensure the smoothing effect when the elderly's body moves slowly or is stationary.

[0074] In some specific embodiments, the process noise covariance matrix value corresponding to the initial convergence speed of the Kalman filter algorithm is Q1, and the observation noise covariance matrix value is R1. When the rate of change of the infrared radiation intensity exceeds the rate threshold, the process noise covariance matrix value is adjusted to Q2, and the observation noise covariance matrix value is adjusted to R2, wherein Q2 is greater than Q1, and R2 is less than R1, thereby reducing the convergence speed of the Kalman filter algorithm. In this way, the Kalman filter algorithm can adaptively adjust the degree of smoothing according to the speed of the elderly's body movement, while ensuring the smoothing effect, taking into account the sensitivity to rapid movement. The technical means of dynamically adjusting the convergence speed of the Kalman filter algorithm can improve the sensitivity and accuracy of the infrared radiation intensity smoothing process when the elderly move rapidly, so that the monitoring system can more reliably identify the activity status of the human body.

[0075] In some embodiments, step C2 comprises: Get the current bathroom ambient temperature; Calculate the difference between the current bathroom ambient temperature and the preset standard temperature to obtain the temperature deviation value; According to the temperature deviation value, the adjustment range of the sensitivity adjustment range is determined. The larger the temperature deviation value, the smaller the adjustment range. According to the smoothed infrared radiation intensity value and the adjustment amplitude, the sliding average algorithm is used to dynamically adjust the upper and lower limits of the sensitivity adjustment interval to ensure that the current infrared radiation intensity level of the elderly individual is in the middle of the adjustment interval.

[0076] Among them, the acquisition of ambient temperature can be completed by a temperature sensor, and the temperature sensor is installed in the bathroom to monitor the ambient temperature in real time. The preset standard temperature is pre-set, for example, it can be set to the normal surface temperature of the human body or the appropriate ambient temperature in the bathroom. The temperature deviation value is calculated by subtracting the preset standard temperature from the current bathroom ambient temperature. The adjustment amplitude of the sensitivity adjustment interval is associated with the temperature deviation value. The larger the temperature deviation value, the smaller the adjustment amplitude. This negative correlation can be achieved by means of a mathematical function or a lookup table. The sliding average algorithm is used to smooth the infrared radiation intensity value, reduce noise interference, and ensure the stability of the sensitivity adjustment interval. The dynamic adjustment of the upper and lower limits of the sensitivity adjustment interval is centered on the smoothed infrared radiation intensity value and adjusted according to the adjustment amplitude, thereby ensuring that the individual infrared radiation intensity level of the elderly is always in the middle of the adjustment interval, ensuring the effectiveness and accuracy of the sensitivity adjustment.

[0077] Specifically, the above technical solution aims to solve the impact of changes in bathroom ambient temperature on the accuracy of elderly activity monitoring. When the bathroom ambient temperature changes, the elderly's body surface temperature and infrared radiation intensity will also change accordingly. If the sensitivity adjustment interval is fixed, it may lead to misjudgment or missed judgment. Here, by dynamically adjusting the sensitivity adjustment interval, the sensitivity adjustment interval can adapt to changes in ambient temperature and changes in individual infrared radiation intensity of the elderly, ensuring that the system can accurately monitor the activity status of the elderly at different ambient temperatures. First, the bathroom ambient temperature is obtained in real time through a temperature sensor to provide a temperature basis for subsequent sensitivity adjustment. Then, the deviation value between the current ambient temperature and the preset standard temperature is calculated, and the deviation value reflects the degree of change in ambient temperature. Next, the adjustment range of the sensitivity adjustment interval is determined according to the temperature deviation value. The larger the temperature deviation, the smaller the adjustment range. This setting can avoid frequent adjustments to the sensitivity adjustment interval when the ambient temperature changes drastically, and ensure the stability of the system. Afterwards, combined with the smoothed infrared radiation intensity value and the adjustment range, the sliding average algorithm is used to dynamically adjust the upper and lower limits of the sensitivity adjustment interval. The sliding average algorithm ensures the smoothness of the adjustment process, avoids mutations, and further improves the stability of the system. By dynamically adjusting the sensitivity adjustment range and ensuring that the individual infrared radiation intensity level of the elderly is always in the middle of the adjustment range, the adjustment of the sensitivity threshold can more accurately adapt to the changes in the elderly and the environment, thereby improving the accuracy and reliability of elderly activity monitoring.

[0078] In some specific embodiments, the preset standard temperature can be set to 25 degrees Celsius. The temperature deviation value can be calculated by the formula: temperature deviation value = current bathroom environment temperature - 25 degrees Celsius. The adjustment amplitude of the sensitivity adjustment interval can be determined by a functional relationship according to the temperature deviation value, for example, the adjustment amplitude = reference amplitude / (1 + k * | temperature deviation value |), wherein the reference amplitude is a preset fixed value, and k is a constant greater than 0, which is used to control the degree of influence of the temperature deviation value on the adjustment amplitude. The sliding average algorithm can use a sliding window of 10 sampling points. Whenever a new smoothed infrared radiation intensity value is obtained, the sliding window is updated and the upper and lower limits of the sensitivity adjustment interval are recalculated. The upper limit of the sensitivity adjustment interval is set to the smoothed infrared radiation intensity value plus the adjustment amplitude, and the lower limit is set to the smoothed infrared radiation intensity value minus the adjustment amplitude. Through the above specific implementation, the dynamic adjustment of the sensitivity adjustment interval can be achieved, thereby improving the accuracy and stability of the activity monitoring of the elderly in the bathroom.

[0079] In some embodiments, step A4 comprises: A401. Compare the original infrared radiation signal of the human body with the adjusted sensitivity threshold to obtain a comparison result; A402. If the comparison result shows that the original infrared radiation signal of the human body exceeds the adjusted sensitivity threshold, monitor the duration of the original infrared radiation signal of the human body exceeding the adjusted sensitivity threshold; A403. If the duration exceeds the preset time threshold, it is determined that human activity has occurred and an alarm signal is output.

[0080] Among them, in step A401, the comparison between the original infrared radiation signal of the human body and the adjusted sensitivity threshold can be completed by a comparator to compare the signal amplitude, and the comparison result can output two states of high and low levels. For example, when the original infrared radiation signal of the human body is greater than the adjusted sensitivity threshold, the comparator outputs a high level, otherwise it outputs a low level.

[0081] Among them, in step A402, the duration of monitoring the original infrared radiation signal of the human body exceeding the adjusted sensitivity threshold can be achieved by using a timer. When the comparator outputs a high level, the timer starts timing, and when the comparator outputs a low level, the timer stops timing. The duration recorded by the timer is the duration of the original infrared radiation signal of the human body exceeding the adjusted sensitivity threshold.

[0082] Among them, in step A403, the preset time threshold can be set according to the actual application scenario, for example, set to 1 second, 2 seconds or 3 seconds, etc. To determine whether human activity has occurred, the duration recorded by the timer can be compared with the preset time threshold. If the duration recorded by the timer exceeds the preset time threshold, it is determined that human activity has occurred and an alarm signal is output. Otherwise, it is determined that no human activity has occurred and no alarm signal is output. The alarm signal can be used to trigger a subsequent human activity abnormality judgment program, thereby entering the human activity abnormality monitoring process; the alarm signal can also be sent to the monitoring terminal to remind the guardian to pay close attention to the activities of the elderly.

[0083] Furthermore, after entering the abnormal human activity monitoring process, the first passive infrared sensor is used to obtain the original infrared radiation signal of the elderly in real time, and a preliminarily judgment is made whether the elderly has any abnormality based on the real-time changes of the original infrared radiation signal of the human body. When it is preliminarily judged that an abnormality has occurred, the voice device installed in the bathroom can be turned on, and voice interaction with the elderly can be used to finally confirm whether the elderly's state is abnormal. When it is finally determined that the elderly has an abnormality, an alarm message is sent to the monitoring terminal to notify the guardian to take timely countermeasures.

[0084] Among them, the preliminary judgment of whether the elderly person has an abnormality based on the real-time changes of the original infrared radiation signal of the human body can be performed in the following manner: extract the original infrared radiation signal of the human body with the first preset time length (which can be set according to actual needs) with the current moment as the end time point, perform normalization processing, and obtain a normalized original infrared radiation signal segment of the human body, and then slide the window to intercept multiple window data from the normalized original infrared radiation signal segment of the human body in a sliding window manner, and calculate the average value of each window data, arrange the average values ​​of each window data in chronological order to obtain a feature sequence, and input the feature sequence into a pre-trained abnormal recognition model to obtain the recognition result output by the abnormal recognition model. However, the specific abnormality judgment method is not limited to this, and other existing technologies can also be used.

[0085] Specifically, in the application scenario of monitoring the activities of the elderly in the bathroom, in order to avoid misjudgment caused by environmental interference factors such as water vapor or mirror reflection, step A4 adopts a complete human activity determination mechanism of signal comparison, duration monitoring and time threshold judgment. First, in step A401, the original infrared radiation signal of the human body from the first passive infrared sensor is compared in real time with the sensitivity threshold adjusted by environmental interference. The purpose of the comparison is to preliminarily determine whether there is infrared radiation beyond the normal range, which may be a sign of human activity. Then, step A402 is executed, and the system will only start duration monitoring when the comparison result of step A401 shows that the original infrared radiation signal of the human body exceeds the adjusted sensitivity threshold. The activation of duration monitoring is to distinguish between short-term environmental interference and continuous human activity. For example, the instantaneous fluctuation of water vapor in the bathroom may cause a short change in the infrared radiation signal, but the infrared radiation change caused by human activity is usually continuous. Finally, in step A403, the system compares the duration monitored in step A402 with the preset time threshold. The preset time threshold is used as a time filter to filter out interference signals with shorter duration. Only when the duration of the infrared radiation signal exceeding the threshold exceeds the preset time threshold, the system finally determines that real human activity has occurred and sends an alarm signal. In this way, step A4 effectively combines the intensity and duration information of the infrared radiation signal, reduces the probability of misjudgment caused by environmental interference, and improves the accuracy and reliability of elderly activity monitoring in complex bathroom environments.

[0086] refer to Figure 2 The present application provides a device for monitoring elderly people's activities in a bathroom, which is used to monitor elderly people's activities in a water vapor environment of a bathroom equipped with a mirror. The device comprises: Signal receiving module 1, used to receive the original infrared radiation signal of the human body detected by the first passive infrared sensor, the infrared radiation intensity data of the mirror reflection detected by the second passive infrared sensor, and the water vapor concentration data detected by the water vapor sensor; the detection field of the first passive infrared sensor avoids the mirror area of ​​the bathroom, and the detection field of the second passive infrared sensor faces the mirror area of ​​the bathroom (the specific process can be referred to step A1 above); Interference assessment module 2, used to calculate the comprehensive interference intensity of specular reflection and water vapor on the environment according to the infrared radiation intensity data of specular reflection and the water vapor concentration data (the specific process can be referred to step A2 above); A threshold adjustment module 3 is used to nonlinearly adjust the sensitivity threshold of the first passive infrared sensor based on the evaluated comprehensive interference intensity to obtain an adjusted sensitivity threshold (the specific process can refer to step A3 above); The activity determination module 4 is used to compare the original infrared radiation signal of the human body with the adjusted sensitivity threshold, and combine the human activity duration determination mechanism to determine whether human activity occurs and output an alarm signal in a timely manner (the specific process can be referred to step A4 above).

[0087] Please refer to Figure 3 , Figure 3 This is a structural diagram of an electronic device provided in an embodiment of the present application. The present application provides an electronic device, including: a processor 301 and a memory 302. The processor 301 and the memory 302 are interconnected and communicate with each other through a communication bus 303 and / or other forms of connection mechanisms (not shown). The memory 302 stores a computer program executable by the processor 301. When the electronic device is running, the processor 301 executes the computer program to perform the bathroom elderly activity monitoring in any optional implementation of the above embodiment to achieve the following functions: receiving the original infrared radiation signal of the human body detected by the first passive infrared sensor, the mirror reflection signal detected by the second passive infrared sensor, and the infrared radiation signal of the human body detected by the second passive infrared sensor. The infrared radiation intensity data of the emitted light and the water vapor concentration data detected by the water vapor sensor are collected; the detection field of view of the first passive infrared sensor avoids the mirror area of ​​the bathroom, and the detection field of view of the second passive infrared sensor faces the mirror area of ​​the bathroom; according to the infrared radiation intensity data of the mirror reflection and the water vapor concentration data, the comprehensive interference intensity of the mirror reflection and water vapor on the environment is calculated; based on the evaluated comprehensive interference intensity, the sensitivity threshold of the first passive infrared sensor is nonlinearly adjusted to obtain the adjusted sensitivity threshold; the original infrared radiation signal of the human body is compared with the adjusted sensitivity threshold, and combined with the human activity duration judgment mechanism, it is determined whether human activity occurs and an alarm signal is output in a timely manner.

[0088] An embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the elderly activity monitoring in the bathroom in any optional implementation method of the above-mentioned embodiment is performed to achieve the following functions: receiving the original infrared radiation signal of the human body detected by a first passive infrared sensor, the infrared radiation intensity data of the mirror reflection detected by a second passive infrared sensor, and the water vapor concentration data detected by a water vapor sensor; the detection field of the first passive infrared sensor avoids the mirror area of ​​the bathroom, and the detection field of the second passive infrared sensor faces the mirror area of ​​the bathroom; according to the infrared radiation intensity data of the mirror reflection and the water vapor concentration data, the comprehensive interference intensity of the mirror reflection and water vapor on the environment is calculated; based on the evaluated comprehensive interference intensity, the sensitivity threshold of the first passive infrared sensor is nonlinearly adjusted to obtain the adjusted sensitivity threshold; the original infrared radiation signal of the human body is compared with the adjusted sensitivity threshold, and combined with the human activity duration judgment mechanism, it is determined whether human activity occurs and an alarm signal is output in a timely manner.

[0089] Among them, the computer-readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (Static Random Access Memory, referred to as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), erasable programmable read-only memory (Erasable Programmable Read-Only Memory, referred to as EPROM), programmable read-only memory (Programmable Red-Only Memory, referred to as PROM), read-only memory (Read-Only Memory, referred to as ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0090] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0091] In addition, 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, and 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 solution of this embodiment.

[0092] Furthermore, the functional modules in the various embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.

[0093] In this document, relational terms such as first and second, etc. are used merely to distinguish one entity or operation from another entity or operation, but do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0094] The above description is only an embodiment of the present application and is not intended to limit the protection scope of the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for monitoring elderly people's activities in a bathroom, which is used to monitor elderly people's activities in a water vapor environment of a bathroom equipped with a mirror, and is characterized in that: The steps of the method include: A1. Receive the original infrared radiation signal of the human body detected by the first passive infrared sensor, the infrared radiation intensity data of the mirror reflection detected by the second passive infrared sensor, and the water vapor concentration data detected by the water vapor sensor; the detection field of the first passive infrared sensor avoids the mirror area of ​​the bathroom, and the detection field of the second passive infrared sensor faces the mirror area of ​​the bathroom; A2. Calculate the comprehensive interference intensity of the mirror reflection and water vapor on the environment according to the infrared radiation intensity data of the mirror reflection and the water vapor concentration data; A3. Based on the evaluated comprehensive interference intensity, nonlinearly adjusting the sensitivity threshold of the first passive infrared sensor to obtain an adjusted sensitivity threshold; A4. Compare the original infrared radiation signal of the human body with the adjusted sensitivity threshold, combine with the human activity duration judgment mechanism, determine whether human activity occurs and output an alarm signal in a timely manner.

2. A method for monitoring activities of elderly people in bathrooms according to claim 1, characterized in that: There are multiple water vapor sensors, and the multiple water vapor sensors are distributed at different positions of the bathroom mirror area; Step A2 includes: Performing weighted averaging on the water vapor concentration data detected by each of the water vapor sensors to obtain an average water vapor concentration; The comprehensive interference intensity of the specular reflection and the water vapor on the environment is calculated according to the infrared radiation intensity data of the specular reflection and the average water vapor concentration.

3. A method for monitoring activities of elderly people in bathrooms according to claim 1, characterized in that: The step A2 further comprises: Monitor the status of bathroom lighting fixtures in real time. If a change in the status of the lighting fixture is detected, the time of the change will be recorded. Collecting the infrared radiation intensity data reflected by the mirror in a preset time window before and after the state of the lamp changes, and calculating the infrared radiation intensity change rate in the time window; Determine whether the infrared radiation intensity change rate exceeds a preset change rate threshold, and if so, determine the interference intensity adjustment parameter according to the lamp state change type; According to the interference intensity adjustment parameter, the calculation result of the comprehensive interference intensity of specular reflection and water vapor on the environment is adjusted.

4. A method for monitoring activities of elderly people in bathrooms according to claim 1, characterized in that: Step A3 includes: A301. Obtain the individual infrared radiation intensity levels of multiple elderly people and divide them into multiple sensitivity adjustment intervals; A302. According to the comprehensive interference intensity, determine the sensitivity adjustment parameter, the sensitivity adjustment parameter includes an adjustment amplitude and an adjustment direction; A303. Calculate the sensitivity threshold adjustment amount of the first passive infrared sensor according to the sensitivity adjustment interval of the current infrared radiation intensity level of the elderly individual and the sensitivity adjustment parameter; A304. Add the sensitivity threshold adjustment amount to the initial sensitivity threshold of the first passive infrared sensor to obtain an adjusted sensitivity threshold.

5. A method for monitoring activities of elderly people in bathrooms according to claim 4, characterized in that: There are multiple water vapor sensors, and the multiple water vapor sensors are distributed at different positions of the bathroom mirror area; Step A302 includes: E1. Dividing the mirror area into a plurality of sub-areas, and calculating the water vapor concentration of each sub-area according to the water vapor concentration data detected by each water vapor sensor; E2. Calculate the infrared radiation absorption rate of each sub-region according to the water vapor concentration of each sub-region; E3. Calculate the weighted average infrared radiation absorption rate based on the infrared radiation absorption rate of each sub-region and the area ratio of each sub-region; E4. Determine a sensitivity adjustment parameter based on the weighted average infrared radiation absorption rate and the comprehensive interference intensity, wherein the sensitivity adjustment parameter includes an adjustment amplitude and an adjustment direction.

6. A method for monitoring activities of elderly people in bathrooms according to claim 4, characterized in that: Step A303 includes: C1. Collect the infrared radiation intensity of the elderly in real time, and use the Kalman filter algorithm to perform smoothing to obtain the smoothed infrared radiation intensity value; C2. According to the smoothed infrared radiation intensity value, dynamically adjust the upper and lower limits of the sensitivity adjustment interval to ensure that the current infrared radiation intensity level of the elderly individual is located in the middle of the adjustment interval; C3. According to the sensitivity adjustment interval of the infrared radiation intensity level of the elderly individual and the sensitivity adjustment parameter, the sensitivity threshold adjustment amount of the first passive infrared sensor is calculated by a piecewise linear interpolation algorithm.

7. A method for monitoring activities of elderly people in bathrooms according to claim 1, characterized in that: Step A4 includes: A401. Compare the original infrared radiation signal of the human body with the adjusted sensitivity threshold to obtain a comparison result; A402. If the comparison result shows that the original infrared radiation signal of the human body exceeds the adjusted sensitivity threshold, monitor the duration of the original infrared radiation signal of the human body exceeding the adjusted sensitivity threshold; A403. If the duration exceeds the preset time threshold, it is determined that human activity has occurred and an alarm signal is output.

8. A device for monitoring elderly people's activities in a bathroom, used for monitoring elderly people's activities in a water vapor environment of a bathroom equipped with a mirror, characterized in that: The device includes: A signal receiving module is used to receive the original infrared radiation signal of the human body detected by the first passive infrared sensor, the infrared radiation intensity data of the mirror reflection detected by the second passive infrared sensor, and the water vapor concentration data detected by the water vapor sensor; the detection field of the first passive infrared sensor avoids the mirror area of ​​the bathroom, and the detection field of the second passive infrared sensor faces the mirror area of ​​the bathroom; An interference assessment module, used to calculate the comprehensive interference intensity of the mirror reflection and water vapor on the environment according to the infrared radiation intensity data of the mirror reflection and the water vapor concentration data; A threshold adjustment module, configured to nonlinearly adjust the sensitivity threshold of the first passive infrared sensor based on the evaluated comprehensive interference intensity to obtain an adjusted sensitivity threshold; The activity determination module is used to compare the original infrared radiation signal of the human body with the adjusted sensitivity threshold, and combine the human activity duration determination mechanism to determine whether human activity occurs and output an alarm signal in a timely manner.

9. An electronic device, characterized in that: It comprises a processor and a memory, wherein the memory stores a computer program executable by the processor, and when the processor executes the computer program, it runs the steps in the method for monitoring activities of the elderly in the bathroom as described in any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, the steps of the method for monitoring activities of elderly people in the bathroom are performed as described in any one of claims 1-7.

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