Self-adaptive low-power-consumption monitoring method for indoor environment monitor

Abstract

The invention relates to a self-adaptive low-power-consumption monitoring method for an indoor environment monitor, and the method comprises the steps: jointly detecting a personnel activity signal in a monitoring region through a millimeter-wave radar and an infrared sensor, and carrying out the comprehensive judgment of the signals of the millimeter-wave radar and the infrared sensor through a data fusion algorithm; independently calculating the delay time of the next sampling for each sensor according to the currently judged personnel state and the real-time reading of each environmental parameter; and independent sensing timing power supply control and data acquisition. According to the invention, power consumption is greatly reduced when there is no person, sampling resources are distributed according to needs when there is a person, the better the environment is, the more energy is saved, the worse the environment is, the more sensitive the environment is, unification of low power consumption and high responsiveness is realized, and the method is very suitable for indoor environment monitoring scenes such as smart homes, offices and warehouses which are powered by batteries and need long-term unattended operation.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of intelligent terminals, in particular to a self-adaptive low-power monitoring method for an indoor environment monitor. BACKGROUND

[0002] With the improvement of public health and safety awareness, the monitoring demand for indoor air quality, especially the concentration of formaldehyde and VOC in newly renovated rooms, and the safety hazards caused by excessive CO concentration due to incomplete combustion, etc. is increasing. In existing indoor environment monitoring products, such as air purifiers, some environmental data can be collected, but the collection method is single, and only the environmental factors at the location of the air purifier can be reflected. Therefore, various types of indoor environment monitoring products need an indoor environment monitor that can collect different areas and collect various types of indoor sensitive environmental data. The current indoor environment detection products either need to be plugged in for use, which has many limitations for deployment, or are handheld for detection, which can only test the indoor environmental data at the current time. The core problem is that the high sampling rate of various environmental sensors will increase power consumption, leading to a decrease in overall endurance, and cannot complete long-term environmental monitoring. SUMMARY

[0003] The purpose of the present application is to overcome the shortcomings of the prior art and provide a self-adaptive low-power monitoring method for an indoor environment monitor, which solves the problems existing in the prior art.

[0004] The purpose of the present application is achieved by the following technical solution: a self-adaptive low-power monitoring method for an indoor environment monitor, the monitoring method comprising:

[0005] S1, detecting personnel activity signals in the monitoring area by a millimeter wave radar and an infrared sensor, and comprehensively determining the signals of the millimeter wave radar and the infrared sensor by a data fusion algorithm;

[0006] S2, independently calculating the delay time of the next sampling of each sensor according to the current determined personnel state and the real-time readings of each environmental parameter;

[0007] S3, independent sensor timing power supply control and data acquisition.

[0008] The comprehensive determination of the signals of the millimeter wave radar and the infrared sensor by the data fusion algorithm comprises:

[0009] When the initial state is that the indoor environment is unoccupied, only the infrared sensor monitors the area, and the millimeter wave radar is in a low-power sleep or low-frequency detection mode without reaching the trigger threshold state;

[0010] When the infrared sensor reaches the trigger threshold state, the millimeter wave radar turns to the normal working mode, and the full power monitors whether there is personnel activity in the room, if there is personnel activity, the infrared sensor turns to the low power consumption mode, the millimeter wave radar provides the current personnel position information, and the state is marked as the person state.

[0011] The environmental parameters include CO, CO2, VOC, PM2.5, PM10, temperature, humidity and formaldehyde.

[0012] The real-time readings of the current determined personnel state and each environmental parameter are used to independently calculate the delay time of the next sampling of each sensor, and the delay time of the next sampling of each sensor is specifically:

[0013] When in the unattended state, all sensors adopt a preset baseline low frequency for sampling, and the delay time of the next sampling of each sensor is specifically: , wherein, is a fixed long delay in the unattended state;

[0014] When the system is in the person state and any environmental parameter does not exceed the preset baseline, for the environmental parameter of each sensor i, the delay time of the next sampling of the sensor i is dynamically calculated according to the ratio of the current measurement value of the sensor i to the corresponding safety threshold of the sensor i through a nonlinear function, and the delay time of the next sampling of the sensor i is specifically: , wherein, represents the adaptive delay time of the sensor i, represents a preset minimum delay time, represents a basic delay time in the person state, and k is a sensitivity adjustment coefficient greater than 0, represents the normalized concentration level of the current environmental parameter; In any state, when the environmental parameter exceeds the preset baseline, the sensor i enters a real-time response mode, and the delay time of the next sampling of the sensor i is specifically:

[0015] .

[0016] The independent sensor timing power supply control and data acquisition specifically includes the following contents:

[0017] When in the unattended state, data sampling is performed once every time;

[0018] When in the person state and the environmental parameter does not exceed the preset baseline, all sensors collect data once every , and the single adjustment period time of the timer is , , wherein the minimum step in is , and the adjusted is obtained by performing an integer operation on all ;​

[0019] After completing a data collection, the sensor cuts off the power supply or is placed in a low-power mode;

[0020] After the collection is completed, the above process is repeated, thereby realizing independent and accurate control of each sensor working period.

[0021] The sensor cuts off the power supply or is placed in a low-power mode after completing a data collection, which comprises:

[0022] An independent power supply control circuit and a timer are adapted for each environmental sensor, and the single adjustment period time of the timer is The next time adjustment data refers to the current The lowest interval of each sensor data in the current period is the reference adjustment sampling rate, and when the millimeter wave radar monitors that there is no one in the room, the next adjustment period time is converted into a low-power mode.

[0023] At any time, when the environmental parameter exceeds the preset baseline, that is, The i-th sensor does not sleep until The next adjustment period time restores the interval data sampling.

[0024] The present application has the following advantages: a self-adaptive low-power monitoring method for an indoor environmental monitor, which solves the problems of high power consumption and unintelligent strategy of existing environmental monitors by fusing personnel perception and environmental quality dual-mode information and dynamically allocating sampling frequency for each sensor using a nonlinear function. The method greatly reduces power consumption when there is no one, and "distributes" sampling resources on demand when there is someone, so that the better the environment, the more energy-saving, and the worse the environment, the more sensitive, thereby realizing the unity of low power consumption and high responsiveness, and being very suitable for indoor environmental monitoring scenes such as intelligent home, office and warehouse, which are powered by batteries and need to be unattended for a long time. BRIEF DESCRIPTION OF DRAWINGS

[0025] Figure 1 The flowchart of the present application is shown;

[0026] Figure 2 The hardware connection diagram is shown;

[0027] Figure 3 The curve diagram of the delay time of each sensor changing with the measurement value is shown;

[0028] Figure 4 The timing diagram of each sensor in a single period time is shown. DETAILED DESCRIPTION

[0029] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the detailed description of the embodiments of this application provided below with reference to the accompanying drawings is not intended to limit the scope of protection of the claimed application, but merely represents selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application. The present invention will be further described below with reference to the accompanying drawings.

[0030] This invention specifically relates to an adaptive low-power monitoring method for indoor environmental monitoring instruments. The aim is to overcome the shortcomings of existing indoor environmental monitoring equipment, such as high power consumption, rigid detection strategies, and the inability to dynamically optimize power consumption based on personnel presence and environmental quality. This invention provides an adaptive low-power monitoring method based on dual-modal feedback of personnel perception and environmental quality. By intelligently adjusting the sensor sampling frequency, this method significantly extends the device's battery life while ensuring environmental safety early warning capabilities.

[0031] like Figure 1 and Figure 2 As shown, it specifically includes the following:

[0032] This embodiment comprises four parts, corresponding to data sampling, data processing, power control, and human presence monitoring. The data sampling part includes various air quality sensors; in this embodiment, these sensors include temperature and humidity sensors, PM2.5 / PM10 sensors, VOCs, CO, CO2, and formaldehyde sensors. The data processing controller is an STMicroelectronics STM32F407VET6, and the power control controller is an STMicroelectronics STM32L010F4P6 and a clock module. The human presence monitoring sensors are a 24G millimeter-wave radar and an infrared sensor. In this embodiment, the default initial state is assumed to be unmanned; except for the STM32L010F4P6 and the infrared sensor, all devices are in a low-power or power-off state. In this embodiment, the clock module uses the DS1802Z chip, which provides timing in low-power mode and the specific time of the sampled data for aligning the overall data axis.

[0033] S1. Monitoring of personnel presence is achieved through the collaboration of infrared sensors, 24G millimeter-wave radar, and STM32L010F4P6 and STM32F407VET6 microcontrollers. The system initially defaults to an "unmanned" state, where only the STM32L010F4P6 microcontroller and infrared sensors are in continuous operation, responsible for low-power periodic scanning of the monitored area. The 24G millimeter-wave radar, STM32F407VET6, and other environmental sensors are either powered off or in deep sleep mode. When the infrared sensor detects a signal that reaches a preset trigger threshold, the STM32L010F4P6 will initiate a state switching process: First, it powers on the 24G millimeter-wave radar and the STM32F407VET6 main controller. Then, it transfers the personnel monitoring task to the STM32F407VET6 and shuts down the infrared sensor to reduce system power consumption. The STM32F407VET6 drives the millimeter-wave radar into full-power mode to accurately confirm and locate personnel presence and marks the system's global status as "occupied". In the "manned" state, the STM32F407VET6 continuously processes radar data and tracks personnel activities in real time. When the radar continuously determines that no personnel are present in the area, the STM32F407VET6 notifies the STM32L010F4P6 to prepare to resume the low-power monitoring mode. The latter restarts the infrared sensor, and then the STM32F407VET6 controls the cutting off of power to the radar and itself. The system control is returned to the STM32L010F4P6, and the whole system is restored to the initial "unmanned" low-power monitoring state.

[0034] S2. Calculation of adaptive sampling frequency based on environmental quality.

[0035] Based on the current assessment of personnel status and real-time readings of various environmental parameters (including CO, CO2, VOC, PM2.5, PM10, temperature, humidity, and formaldehyde), the delay time for the next sampling is independently calculated for each sensor. .

[0036] When the system is in an "unmanned" state, all sensors sample at a preset baseline low frequency, with a delay time of [missing information]. ,in In this embodiment, the fixed long delay is for unattended operation. .

[0037] In the "unmanned" state, that is Under normal circumstances, the STM32L010F4P6 activates all sensors every 30 minutes (1800 seconds), performs data sampling, and determines whether any data is present. This situation has occurred.

[0038] In the state of "someone" and In this case, for each environmental parameter i, based on its current measurement value Its corresponding security threshold The ratio is used to dynamically calculate the delay time using a nonlinear function. ,in, This represents the adaptive delay time of sensor i; This indicates the preset shortest delay time, corresponding to the highest sampling frequency; This represents the base delay time in the "occupied" state; k is a sensitivity adjustment coefficient greater than 0, used to control the rate at which the frequency increases as the environment deteriorates; This represents the normalized concentration level of the current environmental parameters.

[0039] In temperature and humidity measurement, higher temperatures are not necessarily more comfortable. Therefore, in this embodiment, a Gaussian function is introduced as the formula for calculating the adaptive delay time:

[0040] ,

[0041] Where μ is the comfort midpoint. This is the comfort range width coefficient, used to adjust the comfort range.

[0042] In this embodiment, there are six sensors: temperature and humidity, PM2.5 / PM10, VOC, CO, CO2, and formaldehyde, which correspond to sensor 0 to sensor 1 in sequence. The sampling rate of sensor 0 and sensor 1 is adjusted with the lowest interval as a reference. Figure Three By selecting the current sampling point, it can be seen that , , , , , , , , .

[0043] In this embodiment, the sensors are classified as follows: Sensors 0-1 (temperature, humidity, PM2.5 / PM10 sensors) are real-time response sensors. For real-time response sensors, there is almost no delay after power-on, allowing them to instantly capture changes in environmental parameters with a response speed of ≤1 second. These sensors can capture changes in environmental parameters instantly upon power-on, therefore pre-starting is not required before data acquisition. Sensors 2-4 (VOC, CO, CO2) are fast-response sensors, capable of stably outputting accurate data within tens of seconds after power-on, quickly reflecting changes in gas concentration in the environment with a fast response speed. For sensors of this type, a short pre-start is required (3-30 seconds). In this embodiment, according to the sensor datasheet, the pre-start time is 3 seconds. Sensor 5 (formaldehyde) has a medium-speed response, requiring approximately 30 seconds to stabilize after power-on. Due to the diffusion of formaldehyde molecules and the chemical detection principle of the sensor, the response is slightly slower, ranging from 30-90 seconds. This type of sensor obtains a stable reading after 30 seconds of power-on and requires a pre-start. In this embodiment, according to the sensor datasheet, the pre-start time is 30 seconds. Therefore, different minimum delay times should be set for the three different types of sensors. as well as ,like Figure 3 The figure shows a preset curve of the delay time of each sensor as a function of the measured value. The actual curve can be adjusted according to different environments.

[0044] S3, Independent sensor timing power control and data acquisition.

[0045] When the system is in an "unattended" state, the system... Data is sampled once at regular intervals.

[0046] When the system is in "occupied" state All sensors each The timer's single adjustment cycle time is [time missing] for each data collection. , The minimum step size is In this embodiment, For all Perform a rounding operation, where... This represents the floor function (taking the largest integer not greater than x), thus obtaining the adjusted... .

[0047] ,

[0048] like Figure 3 As shown in the sampling points, , , , , , .

[0049] After rounding: , , , , , Based on this delay time, data can be obtained within the corresponding time period.

[0050] In this example, the sensors are divided into three categories: real-time response, fast response, and medium-speed response. The power supply scheme in this embodiment uses three power chips (EN pins) with enable pins for each of the three sensor types. These pins can be controlled to switch on and off by transmitting high and low levels through the main control chip. Therefore, for real-time response sensors, the pre-start time is 1 second, and the duration is 1 second. Data is collected after the pre-start time. If the sampling interval between multiple sensors is less than 3 seconds, the duration is extended by 3 seconds (i.e., the duration is 4 seconds). For fast response sensors, the pre-start time is 3 seconds, and the duration is 6 seconds. Data is collected after the pre-start time. If the sampling interval between multiple sensors is less than 10 seconds, the duration is extended by 10 seconds. For example, in this embodiment, the three delay times... , , The power is turned on at 45s and off at 64s to reduce the power switching frequency and optimize sampling efficiency. For medium-speed response sensors, the pre-start time is 30s and the duration is 10s. Data is collected after the pre-start time. If the sampling interval of multiple sensors is less than 30s, the duration is extended by 30s. After completing one data acquisition, the sensor is powered off or put into low-power mode. The system configures an independent power control circuit and timer for each environmental sensor. The adjustment cycle of a single timer is [missing information]. When the 24G millimeter-wave radar detects that no one is indoors, the next adjustment cycle will switch to low-power mode.

[0051] like Figure 4 The figure shows the timing diagram of each sensor in a single clock cycle. During this clock cycle, power supply 1 reduces power consumption by 75.2%, power supply 2 reduces power consumption by 34.0%, power supply 3 reduces power consumption by 61.3%, and the overall power consumption is reduced by 56.8%.

[0052] At any given time, when environmental parameters exceed the preset baseline, i.e. The i-th sensor does not go into sleep mode until... At that time, resume interval data sampling.

[0053] When environmental parameters exceed the preset baseline, i.e. The i-th sensor does not go into sleep mode until... At that time, resume interval data sampling.

[0054] After data acquisition is complete, repeat the above process to achieve independent and precise control of each sensor's working cycle.

[0055] The above description is merely a preferred embodiment of the present invention. It should be understood that the present invention is not limited to the forms disclosed herein and should not be construed as excluding other embodiments. It can be used in various other combinations, modifications, and improvements, and can be altered within the scope of the concept described herein through the above teachings or related technologies or knowledge. Modifications and variations made by those skilled in the art that do not depart from the spirit and scope of the present invention should be within the protection scope of the appended claims.

Claims

1. An adaptive low power monitoring method for an indoor environmental monitor, characterized by: The monitoring method comprises: S1, detecting personnel activity signals in a monitoring area through a millimeter wave radar and an infrared sensor, and comprehensively determining the signals of the millimeter wave radar and the infrared sensor through a data fusion algorithm; S2, independently calculating a delay time of next sampling of each sensor according to a current determined personnel state and real-time readings of each environmental parameter; S3, independently controlling a timing power supply and data acquisition.

2. The self-adaptive low-power monitoring method for indoor environment monitor according to claim 1, wherein: The comprehensive determination of the signals of the millimeter wave radar and the infrared sensor through the data fusion algorithm comprises: When the infrared sensor reaches a trigger threshold state, the millimeter wave radar is switched to a normal working mode, and full-power monitoring is performed on whether there is personnel activity in the room, if there is personnel activity, the infrared sensor is switched to a low-power mode, and the millimeter wave radar provides current personnel position information, and the state is marked as a person state. The environmental parameters comprise CO, CO2, VOC, PM2.5, PM10, temperature, humidity and formaldehyde.

3. The self-adaptive low-power monitoring method for indoor environment monitor according to claim 1, wherein: The independent calculation of the delay time of next sampling of each sensor according to the current determined personnel state and the real-time readings of each environmental parameter comprises:

4. The self-adaptive low-power monitoring method for indoor environment monitor according to claim 1, wherein: The independent control of the timing power supply and data acquisition of the sensor comprises the following contents: When in unattended state, all sensors are sampled at a preset baseline low frequency with a delay time wherein, is a fixed long delay in unattended state; When the system is in the presence state and any environmental parameter does not exceed the preset baseline, for each sensor i, the environmental parameter is dynamically calculated according to the ratio of the current measurement value of the environmental parameter of the sensor i to the corresponding safety threshold value of the environmental parameter of the sensor i through a nonlinear function fitting different sensors and its corresponding safety threshold value , the delay time is dynamically calculated by a nonlinear function fitting different sensors , wherein represents the adaptive delay time of the sensor i, represents the preset minimum delay time, represents the basic delay time in the presence state, k is a sensitivity adjustment coefficient greater than 0, represents the normalized concentration level of the current environmental parameter; At any state, when the environmental parameter exceeds the preset baseline, the sensor i enters the real-time response mode, at which time .

5. The self-adaptive low power consumption monitoring method for indoor environment monitor according to claim 1, wherein: After completing one data acquisition, the sensor is cut off power supply or placed in a low-power mode; When in unattended mode, data sampling is performed once every time. When in the presence of a person and the environmental parameters do not exceed the preset baseline, all sensors collect data once every adjustment period time of the timer is , the minimum step is , and all are rounded to obtain the adjusted ; The above process is repeated after the acquisition is completed, so as to realize independent and accurate control of the working cycle of each sensor. The independent control of the timing power supply and data acquisition of the sensor comprises the following contents:

6. The self-adaptive low-power monitoring method for indoor environment monitor according to claim 5, wherein: ​ Adapt independent power control circuit and timer for each environment sensor, the single adjustment period time of the timer is , the next time adjustment data reference the lowest interval of each sensor data in the current period is the reference adjustment sampling rate, when the millimeter wave radar monitors that there is no one in the room, the next adjustment period time turns into low power consumption mode.

7. The self-adaptive low-power monitoring method for indoor environment monitor according to claim 5, wherein: At any time, when the environmental parameter exceeds a preset baseline, i.e. The ith sensor does not sleep until The next adjustment period time recovery interval data sampling.

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