Joint occupancy behavior and air pollution adaptive control method for bathroom space exhaust

Abstract

This application relates to the field of smart home and building environment control technology, and discloses an adaptive control method for bathroom ventilation that combines human behavior and air pollution. It collects and preprocesses multi-source environmental data and human status data of the bathroom space through a multi-source environmental information fusion sensing system. A scene recognition and control logic core system performs dimensionless processing and scene pattern recognition on the multi-source environmental data and human status data, classifying the bathroom space status into several typical scene patterns. The scene recognition and control logic core system executes a behavior-environment coupling weighted method to calculate the target value of the environmental pollution index. Based on the target value of the environmental pollution index, the scene recognition and control logic core system outputs control commands to the variable frequency airflow execution system to adjust the speed of the variable frequency exhaust fan. This invention avoids the problems of insufficient ventilation or energy waste caused by fixed airflow control, achieving a balance between spatial environmental quality control and equipment operating energy efficiency.

Description

Technical Field

[0001] This invention relates to the field of smart home and building environment control technology, specifically to an adaptive control method for bathroom ventilation based on a combination of human behavior and air pollution. Background Technology

[0002] The bathroom is the area in the indoor environment where humidity and pollutant concentration fluctuate most dramatically. Maintaining good air quality is crucial for improving living comfort. Existing bathroom ventilation control systems typically rely on a single environmental parameter threshold or a simple infrared sensor signal to trigger the ventilation equipment. This single-sensor data acquisition and judgment logic cannot accurately identify complex actual usage scenarios such as washing, bathing, and excretion. It is prone to false triggering or delayed response due to fluctuations in single environmental data, making it impossible to accurately classify and grasp the actual usage status of the bathroom space.

[0003] Existing exhaust systems lack a comprehensive quantitative assessment mechanism for the degree of air pollution in the space. Conventional equipment typically operates at a preset fixed airflow rate or only roughly adjusts its speed based on the concentration of a single pollutant. These control methods fail to effectively couple multi-dimensional environmental parameters with behavioral characteristics such as the presence and duration of people in the bathroom. Consequently, the control commands output by the system cannot accurately reflect the actual usage needs and overall pollution level of people in the bathroom space, making it difficult to achieve targeted and accurate calculation of exhaust volume.

[0004] At the airflow regulation level, traditional variable frequency exhaust systems mostly employ a step-by-step speed control logic. When environmental parameters reach a set threshold, the exhaust fan directly jumps to the corresponding fixed speed setting. This rigid airflow switching process causes sudden changes in exhaust fan speed and airflow velocity, not only generating significant mechanical and airflow noise during equipment operation state switching but also causing unnecessary energy consumption. It fails to meet the requirements of reducing equipment operating noise and energy consumption while ensuring air quality in the bathroom space. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides an adaptive control method for bathroom ventilation that combines human behavior and air pollution. This method solves the problems of existing bathroom ventilation control systems that rely on a single sensor, leading to equipment malfunctions or delayed responses; lack of effective coupling between multi-dimensional environmental parameters and human behavior characteristics, resulting in inaccurate calculation of ventilation volume; and sudden changes in exhaust fan speed and equipment operating noise caused by step-like airflow switching.

[0006] To achieve the above objectives, the present invention provides the following technical solution: The first aspect of this invention provides a bathroom space exhaust ventilation adaptive control method that combines human behavior and air pollution, applied to a bathroom space exhaust ventilation adaptive intelligent control system. The bathroom space exhaust ventilation adaptive intelligent control system includes a bathroom space environment multi-source information fusion perception system, a scene recognition and control logic core system, and a variable frequency air volume execution system.

[0007] Adaptive control methods for bathroom exhaust ventilation that combine human behavior and air pollution include: The system collects and preprocesses multi-source environmental data and personnel status data of the bathroom space through a multi-source information fusion and perception system for the bathroom space environment. The core system of scene recognition and control logic performs dimensionless processing and scene pattern recognition on multi-source environmental data and personnel status data, and divides the bathroom space status into a variety of typical scene patterns. The target value of the environmental pollution index is calculated by weighting the execution behavior and environment of the core system of scene recognition and control logic. The core system of scene recognition and control logic outputs control commands to the variable frequency air volume execution system based on the target value of the environmental pollution index, thereby adjusting the speed of the variable frequency exhaust fan included in the variable frequency air volume execution system.

[0008] In the execution of the behavior-environment coupled weighted method, the scene recognition and control logic core system retrieves the relative humidity weight, odor weight, and particulate matter weight from its internal storage based on the identified typical scene patterns, and determines the behavior gain coefficient based on the duration of personnel stay. The scene recognition and control logic core system multiplies the normalized dimensionless environmental data with the corresponding environmental weight coefficients and sums them, then multiplies the sum by the behavior gain coefficient to calculate the target value of the environmental pollution index.

[0009] In the step of outputting control commands, the scene recognition and control logic core system establishes a linear mapping mechanism between the target value of the environmental pollution index and the target pulse width modulation duty cycle. It determines the corresponding pulse width modulation duty cycle control range based on the current typical scene mode, generates the target pulse width modulation duty cycle, and uses a PID control algorithm to perform closed-loop fine-tuning of the output pulse width modulation duty cycle.

[0010] The second aspect of the present invention provides an adaptive intelligent control system for bathroom ventilation that combines human behavior and air pollution, for executing the adaptive control method for bathroom ventilation that combines human behavior and air pollution provided in the first aspect of the present invention.

[0011] The bathroom space exhaust ventilation adaptive intelligent control system, which integrates human behavior and air pollution, includes: The bathroom space environment multi-dimensional information fusion sensing system includes a composite sensor array module and an environmental data preprocessing and transmission module. The composite sensor array module integrates temperature and humidity sensors, hydrogen sulfide sensors, ammonia sensors, particulate matter sensors, and a human infrared sensor module to collect multi-dimensional environmental parameters and personnel status information within the bathroom space. The environmental data preprocessing and transmission module performs noise reduction and analog-to-digital conversion on the collected signals.

[0012] The core system for scene recognition and control logic is connected to the environmental data preprocessing and transmission module and the variable frequency air volume execution system, respectively. It is used to receive preprocessed multi-source environmental data and personnel status data, perform environmental pollution index calculation and scene pattern recognition, and generate target pulse width modulation duty cycle signal.

[0013] The variable frequency air volume control system includes a variable frequency control circuit and a variable frequency exhaust fan. The variable frequency control circuit is used to receive the target pulse width modulation duty cycle signal and adjust the operating speed of the variable frequency exhaust fan.

[0014] This invention provides an adaptive control method for bathroom ventilation based on combined human behavior and air pollution. It offers the following advantages: 1. This invention integrates personnel presence status, dwell time, and multi-dimensional air pollution data to perform dimensionless processing on the collected relative humidity, hydrogen sulfide concentration, ammonia concentration, and particulate matter concentration. The core system of scene recognition and control logic compares the processed dimensionless data with set dynamic thresholds to accurately classify the bathroom space status into standby or short-term mode, high humidity defogging mode, odor forced exhaust mode, and vacant space mode. The bathroom space exhaust adaptive control method that combines personnel behavior and air pollution improves the accuracy of scene recognition and solves the problem of false triggering caused by single sensor judgment.

[0015] 2. This invention employs a behavior-environment coupled weighted method to dynamically calculate the target value of the environmental pollution index. The core system of scene recognition and control logic, based on identified typical scene patterns, calls upon corresponding relative humidity weights, odor weights, and particulate matter weights, and performs multiplication and summation operations using a behavior gain coefficient dynamically adjusted according to the duration of personnel stay. This adaptive ventilation control method for bathroom spaces, combining personnel behavior and air pollution, ensures that the output control commands accurately reflect the usage needs and pollution levels of personnel within the bathroom space, enabling targeted calculation of exhaust volume.

[0016] 3. This invention establishes a linear mapping mechanism between the target value of the environmental pollution index and the target pulse width modulation duty cycle, and combines it with a PID control algorithm for closed-loop fine-tuning. The core system of scene recognition and control logic sends continuously changing pulse signals to the variable frequency air volume execution system to drive the variable frequency exhaust fan. The speed of the variable frequency exhaust fan smoothly transitions with the rate of change of environmental parameters, avoiding sudden changes in airflow during air volume switching, and reducing equipment operating noise and energy consumption while ensuring air quality in the bathroom space. Attached Figure Description

[0017] Figure 1 This is a flowchart of the method of the present invention; Figure 2 This is a system architecture diagram of the present invention. Detailed Implementation

[0018] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Please see the appendix Figure 1 - Appendix Figure 2 This invention provides an adaptive intelligent control system for bathroom ventilation that integrates the perception of human behavior and air pollution. The system includes a multi-dimensional information fusion perception system for the bathroom environment, a scene recognition and control logic core system, and a variable frequency air volume execution system.

[0020] The bathroom space environment multi-dimensional information fusion sensing system communicates with the scene recognition and control logic core system to collect multi-dimensional environmental parameters and personnel status information within the bathroom space, and sends the processed signals to the scene recognition and control logic core system. The bathroom space environment multi-dimensional information fusion sensing system includes a composite sensor array module and an environmental data preprocessing and transmission module. The composite sensor array module integrates a temperature and humidity sensor, a hydrogen sulfide sensor, an ammonia sensor, a particulate matter sensor, and a human infrared sensor module. Specifically, the temperature and humidity sensor uses the DHT11 model, the hydrogen sulfide sensor uses the MQ136 model, the ammonia sensor uses the MQ137 model, the particulate matter sensor uses the GP2Y1014AU0F model, and the human infrared sensor module uses the HC-SR505 model. The environmental data preprocessing and transmission module is connected to both the composite sensor array module and the scene recognition and control logic core system, and is used to filter and convert the collected analog signals to digital. For the specific circuit structure of multi-channel sensor signal filtering and analog-to-digital conversion, those skilled in the art can use conventional RC low-pass filter circuits and general-purpose ADC digital-to-analog conversion chips. The specific construction method of multi-channel sensor signal filtering and analog-to-digital conversion is a well-known technology in this field and will not be described in detail here.

[0021] The scene recognition and control logic core system is connected to the environmental data preprocessing and transmission module and the variable frequency air volume execution system, respectively. The main control chip of the scene recognition and control logic core system adopts the STM32F103C8T6 microcontroller. The scene recognition and control logic core system receives preprocessed multi-dimensional environmental data, executes internally preset algorithm programs to perform feature extraction and scene recognition, and calculates and generates target exhaust commands to be sent to the variable frequency air volume execution system.

[0022] The variable frequency air volume control system includes a variable frequency control circuit and an exhaust fan that supports PWM speed regulation. The variable frequency control circuit receives PWM pulse width modulation signals from the main control chip, changes the drive voltage or frequency output to the exhaust fan, and thus adjusts the actual speed of the exhaust fan.

[0023] Based on the above system hardware architecture, this embodiment provides an adaptive intelligent control method for bathroom exhaust ventilation that jointly senses human behavior and air pollution. The overall workflow of the adaptive intelligent control method for bathroom exhaust ventilation that jointly senses human behavior and air pollution is divided into the following steps.

[0024] S100 collects and preprocesses multi-source environmental and personnel status data in the bathroom space.

[0025] The S110 uses a human infrared sensor module to capture signals of people entering the bathroom space, monitoring their presence and duration of stay in real time. The effective sensing distance of the human infrared sensor module is set to be less than or equal to 3 meters.

[0026] The S120 continuously acquires real-time sampling data of relative humidity, hydrogen sulfide concentration, ammonia concentration, and particulate matter concentration inside the bathroom space through temperature and humidity sensors, hydrogen sulfide sensors, ammonia sensors, and particulate matter sensors.

[0027] S130, the environmental data preprocessing and transmission module performs noise reduction and conversion processing on the real-time sampled data, and the converted digital signal is transmitted to the scene recognition and control logic core system via the communication bus.

[0028] The S200 main control chip performs dimensionless processing and scene pattern recognition on multi-source environmental data.

[0029] S210, the main control chip normalizes the acquired sampling data in different physical units, such as relative humidity, hydrogen sulfide concentration, ammonia concentration, and particulate matter concentration. Based on the preset baseline values ​​of each environmental parameter under clean air conditions and the preset saturation values ​​under severely polluted or extremely high humidity conditions, the main control chip calculates the difference between the real-time sampling value and the preset baseline value, and divides it by the difference between the preset saturation value and the preset baseline value, thus uniformly mapping the current real-time sampling value to a dimensionless range of 0 to 1.

[0030] The S220 main control chip, based on preset dynamic condition judgment logic, divides the current bathroom space status into four typical scenario modes: standby or short-time mode (S0), high humidity defogging mode (S1), odor extraction mode (S2), and odor removal mode (S3). The specific judgment rules of the main control chip are as follows: when someone is detected entering and staying for a short time, and the concentrations of various environmental parameters do not change abruptly and do not exceed the set thresholds, it is judged as standby or short-time mode (S0). When the detected relative humidity is greater than 80% and someone is detected, it is judged as high humidity defogging mode (S1). When the detected ammonia concentration is greater than 0.20 mg / m³, it is judged as... 3 Or the hydrogen sulfide concentration is greater than 0.01 mg / m³ 3 When the odor is detected as being in strong exhaust mode S2, and the human infrared sensor module detects that a person has left, and the real-time value of any environmental parameter has not yet dropped to the corresponding baseline value, then it is determined to be in vacant clearance mode S3.

[0031] The S300 uses a weighted method that couples behavior and environment to calculate the target value of the environmental pollution index.

[0032] In S310, the main control chip retrieves the corresponding environmental weight coefficients from its internal storage based on the current scene mode identified in S220. The system presets relative humidity weight, odor weight, and particulate matter weight. The odor weight is further subdivided into ammonia weight and hydrogen sulfide weight, each accounting for half of the total odor weight. In standby or short-term mode S0, the relative humidity weight is 0.0, the odor weight is 0.0, and the particulate matter weight is 0.0; in high humidity defogging mode S1, the relative humidity weight is 0.6, the odor weight is 0.1, and the particulate matter weight is 0.3; in odor forced exhaust mode S2, the relative humidity weight is 0.1, the odor weight is 0.6, and the particulate matter weight is 0.3; in pedestrian-free air purification mode S3, the relative humidity weight is 0.3, the odor weight is 0.3, and the particulate matter weight is 0.4.

[0033] In the S320, the main control chip determines the behavior gain coefficient based on the duration of personnel stay recorded by an internal timer. When a person is present and the stay time continues to increase, the main control chip dynamically increases the behavior gain coefficient from 1.0 to 1.2; when the person leaves the sensing area, the main control chip reduces the behavior gain coefficient to 0.8.

[0034] The S330 main control chip multiplies the normalized dimensionless environmental data with their corresponding environmental weight coefficients and sums them. Then, it multiplies the summation result with the behavior gain coefficient to calculate the target value of the environmental pollution index used to quantitatively assess the current spatial state.

[0035] The S400 main control chip outputs control commands to the frequency converter control circuit based on the environmental pollution index to adjust the exhaust fan speed.

[0036] In S410, the main control chip maps the calculated environmental pollution index to a target PWM duty cycle. Specifically, in S0 mode, the PWM duty cycle is set to 0% to 20%. In S1 mode, the PWM duty cycle is set to 50% to 70%. In S2 mode, the PWM duty cycle is set to 80% to 100%. In S3 mode, the system maintains medium speed operation until all sensor values ​​return to the baseline, after which the output is turned off.

[0037] The S420 main control chip employs a PID control algorithm to perform millisecond-level closed-loop fine-tuning of the output PWM duty cycle. The main control chip uses the target PWM duty cycle as the target setpoint for the PID controller and outputs a continuously changing PWM duty cycle signal to the frequency converter control circuit. The exhaust fan smoothly adjusts its speed according to the rate of change in odor or humidity. The specific parameter tuning and calculation logic of the PID control algorithm are well-known technologies in the field and will not be elaborated upon here.

[0038] In the aforementioned step S110, the human infrared sensing module captures the signal of personnel intervention in the bathroom space, and monitors the presence status and specific duration of personnel in real time, which specifically includes the following subordinate steps.

[0039] S111 uses a human infrared sensor module to detect changes in infrared radiation emitted by the human body within the bathroom space. The specific human infrared sensor module used is the HC-SR505 model. The effective sensing distance of the HC-SR505 model human infrared sensor module is set to be less than or equal to 3 meters.

[0040] S112, the human infrared sensor module is placed at the center of the ceiling of the bathroom or directly above the entrance. This placement ensures that the sensor's detection range covers the washbasin area, shower area, and toilet area. When the sensor detects a moving human body, it outputs a high-level pulse as a human intervention signal, providing the main control chip with the basis for calculating the person's presence and dwell time.

[0041] In the aforementioned step S120, real-time sampling data of relative humidity, hydrogen sulfide concentration, ammonia concentration and particulate matter concentration inside the bathroom space are continuously acquired through temperature and humidity sensors, hydrogen sulfide sensors, ammonia sensors and particulate matter sensors, specifically including the following sub-steps.

[0042] The S121 acquires real-time digital signals of relative humidity using a temperature and humidity sensor. The temperature and humidity sensor is a DHT11 model. The DHT11 sensor is installed on the side wall of the bathroom, avoiding direct spray from the shower head and areas directly exposed to water vapor, to accurately reflect changes in the overall relative humidity of the bathroom environment.

[0043] S122 acquires real-time sampling data of odor gas concentration using hydrogen sulfide and ammonia sensors. The hydrogen sulfide sensor is model MQ136, and the ammonia sensor is model MQ137. The MQ136 hydrogen sulfide sensor and the MQ137 ammonia sensor are installed above the excrement facilities in the bathroom space. The deployment location of the hydrogen sulfide and ammonia sensors is designed to capture the concentration data of hydrogen sulfide and ammonia diffusing upwards during excretion.

[0044] S123 acquires real-time sampling data of suspended particulate matter concentration using a particulate matter sensor. The particulate matter sensor is model GP2Y1014AU0F. The GP2Y1014AU0F particulate matter sensor continuously monitors the concentration of airborne suspended particles in the bathroom space and converts the monitored changes in light intensity into a continuous analog voltage signal for output.

[0045] S124, the aforementioned DHT11 temperature and humidity sensor, MQ136 hydrogen sulfide sensor, MQ137 ammonia sensor, and GP2Y1014AU0F particulate matter sensor remain in the normally open state after the system is powered on, and continuously sample the air inside the bathroom space in real time at a fixed sampling frequency.

[0046] In the aforementioned step S130, the environmental data preprocessing and transmission module performs noise reduction and conversion processing on the real-time sampled data, specifically including the following sub-steps.

[0047] S131, the environmental data preprocessing and transmission module receives multiple electrical signals output by the composite sensor array module. For analog voltage signals, the environmental data preprocessing and transmission module filters out high-frequency noise using its internally integrated hardware filtering circuit.

[0048] S132, the environmental data preprocessing and transmission module converts the noise-reduced analog voltage signal into a digital signal through an analog-to-digital converter circuit, and transmits the converted digital signal along with the original digital signal to the main control chip via the communication bus.

[0049] For the peripheral driving circuits, power supply voltage configurations, and specific wiring methods of the analog-to-digital conversion chips of the above-mentioned types of sensors, those skilled in the art can assemble them according to the datasheets of each component. The design of the relevant peripheral driving circuits and communication interfaces is a well-known technology in this field and will not be described in detail here.

[0050] In this embodiment, the specific execution process of the environmental data preprocessing and transmission module performing noise reduction and conversion processing on real-time sampled data in the aforementioned step S130 is described in detail, including the following sub-steps.

[0051] S131, the environmental data preprocessing and transmission module receives the sampling signals output in real time by the composite sensor array module. The input terminals of the environmental data preprocessing and transmission module are connected to each sensor in the composite sensor array module, and the received signals include the digital signals output by the temperature and humidity sensor, the level signals output by the human infrared sensor module, and the analog voltage signals output by the hydrogen sulfide sensor, ammonia sensor, and particulate matter sensor.

[0052] S132, the environmental data preprocessing and transmission module uses a hardware filtering circuit to filter out high-frequency noise from the analog voltage signal. Addressing electromagnetic interference caused by the start-up and shutdown of motors in the bathroom space, the environmental data preprocessing and transmission module employs a resistor-capacitor low-pass filter circuit to process the analog voltage signals output by the hydrogen sulfide sensor, ammonia sensor, and particulate matter sensor, filtering out high-frequency noise and electromagnetic interference in the signal transmission link.

[0053] S133, the environmental data preprocessing and transmission module converts the noise-reduced analog voltage signal into a digital signal through an analog-to-digital converter circuit. The environmental data preprocessing and transmission module uses an analog-to-digital converter chip to sample and quantize the analog voltage signal output from the hardware filtering circuit, generating a digital concentration value that can be read by the main control chip.

[0054] In step S134, the environmental data preprocessing and transmission module sends digital signals to the scene recognition and control logic core system via the communication bus. The environmental data preprocessing and transmission module packages the odor gas and particulate matter digital concentration values ​​obtained in step S133, along with the temperature and humidity digital signals output by the temperature and humidity sensor and the personnel presence level signal output by the human infrared sensor module, and transmits this data to the main control chip via the communication bus for scene recognition and environmental pollution index calculation.

[0055] For the specific topology and cutoff frequency calculation of the RC low-pass filter circuit, as well as the selection of the analog-to-digital converter chip and the configuration of the communication protocol of the communication bus, those skilled in the art can implement them in a standardized manner according to conventional electronic circuit design specifications. The relevant hardware wiring and driver code are well-known technologies in this field and will not be described in detail here.

[0056] In some embodiments of the present invention, the specific execution process of the main control chip performing dimensionless processing and scene pattern recognition on multi-source environmental data in the aforementioned step S200 is described in detail, specifically including the following subordinate steps.

[0057] The S211 main control chip sets dynamic thresholds for key pollutants and environmental parameters based on the "Indoor Air Quality Standard" (GB / T18883-2022) and a human comfort model. Key pollutants include ammonia, hydrogen sulfide, and particulate matter, while environmental parameters include relative humidity.

[0058] The S212 main control chip's internal registers store preset baseline values ​​and preset saturation values ​​for various environmental parameters. The preset baseline value represents the lower limit of the parameter when the bathroom space is in a clean air state, and the preset saturation value represents the upper limit of the parameter when the bathroom space is in a state of pollutant concentration saturation or humidity upper limit.

[0059] S213, the main control chip normalizes the sampled data of relative humidity, hydrogen sulfide concentration, ammonia concentration, and particulate matter concentration in different physical units, mapping them uniformly to the dimensionless interval [0,1]. The specific normalization formula executed by the main control chip is as follows: in, It represents the dimensionless value of a certain environmental parameter after normalization calculation; This indicates the current real-time sampled value of the corresponding environmental parameter; This indicates the preset baseline value for the corresponding environmental parameter; This indicates the preset saturation value of the corresponding environmental parameter.

[0060] S214: The main control chip compares real-time sampled values ​​with set dynamic thresholds to determine the scene. When the relative humidity is detected to be greater than 80% and the presence of a person is detected, the main control chip determines that the triggering conditions for the high humidity defogging mode S1 are met. When the ammonia concentration is detected to be greater than 0.20 mg / m³... 3 Or the hydrogen sulfide concentration is greater than 0.01 mg / m³ 3 At that time, the main control chip determines that the current conditions for triggering the odor exhaust mode S2 are met.

[0061] For the addressing and calling mechanism of the internal memory of the main control chip and the configuration of the underlying registers for floating-point arithmetic, those skilled in the art can compile the program according to the hardware architecture manual of the microcontroller. The conventional data storage and arithmetic logic unit calling involved in the microcontroller are well known technologies in this field and will not be described in detail here.

[0062] In some embodiments of the present invention, the specific execution process of the main control chip dividing the current bathroom space state into four typical scene modes according to the preset dynamic condition discrimination logic in the aforementioned step S220 is described in detail, specifically including the following subordinate steps.

[0063] S221, the main control chip receives signals from the human infrared sensor module in real time. When the human infrared sensor module detects a person entering, the main control chip wakes up and enters a pre-sensing state. The main control chip starts an internal timer to record the person's stay time and simultaneously acquires various real-time sampling data sent by the environmental data preprocessing and transmission module.

[0064] S222, the main control chip executes the logic for determining standby or short-time mode S0. After entering the pre-sensing state, the main control chip continuously monitors for a preset time period. The preset time period is set to 10 seconds. If the main control chip detects no sudden changes in environmental parameters within 10 seconds, and the real-time sampled values ​​do not exceed the corresponding set thresholds, the main control chip determines that the current bathroom space is in standby or short-time mode S0. Standby or short-time mode S0 corresponds to a washing scenario where people stay for a short period of time and do not cause pollution exceeding the standard.

[0065] S223, the main control chip executes the judgment logic for high humidity defogging mode S1. The main control chip continuously compares the real-time sampled value of relative humidity with the set humidity threshold. When the main control chip detects that the real-time sampled value of relative humidity is greater than 80%, and simultaneously receives a person presence signal output by the human infrared sensor module, the main control chip determines that the current bathroom space is in high humidity defogging mode S1. High humidity defogging mode S1 corresponds to the showering scenario.

[0066] S224, the main control chip executes the judgment logic of the odor forced exhaust mode S2. The main control chip continuously compares the real-time sampled values ​​of ammonia and hydrogen sulfide concentrations with the set odor threshold. When the main control chip detects that the real-time sampled value of ammonia concentration is greater than 0.20 mg / m³... 3 Or, the real-time sampling value of hydrogen sulfide concentration is greater than 0.01 mg / m³. 3 At this time, the main control chip determines that the current bathroom space is in the odor exhaust mode S2. Odor exhaust mode S2 corresponds to the human excretion scenario.

[0067] S225, the main control chip executes the judgment logic of the "leaving-person clearance mode" S3. When the human infrared sensor module does not detect human activity, the main control chip determines that the person has left the sensing area. The main control chip compares the real-time sampled values ​​of various environmental parameters with the corresponding preset baseline values ​​stored in the internal register. If the real-time sampled values ​​of some environmental parameters have not returned to the preset baseline values, the main control chip determines that the current bathroom space is in the "leaving-person clearance mode" S3 and executes a delayed ventilation strategy.

[0068] The configuration and interrupt triggering mechanism of the internal timer of the main control chip, as well as the logic code for multi-condition branch judgment, can be implemented by those skilled in the art in accordance with conventional embedded C language programming specifications. The specific implementation methods of the configuration and logic judgment instructions of the internal timer of the main control chip are well-known technologies in this field and will not be described in detail here.

[0069] In some embodiments of the present invention, the specific process of calculating the target value of the environmental pollution index using the weighted method of the main control chip's execution behavior and the environment in the aforementioned step S300 is described in detail, specifically including the following subordinate steps.

[0070] The S310 main control chip retrieves the internally stored environmental weight matrix based on the identified scene mode. The main control chip's internal registers contain a weight matrix that includes relative humidity weight, odor weight, and particulate matter weight. The main control chip divides the odor weight into ammonia weight and hydrogen sulfide weight, with each weight accounting for half of the total odor weight.

[0071] In standby or short-term mode S0, the main control chip executes a silent-priority control strategy. The main control chip retrieves the corresponding values ​​from the weight matrix, setting the relative humidity weight to 0.0, the odor weight to 0.0, and the particulate matter weight to 0.0.

[0072] In high-humidity defogging mode S1, the main control chip executes a dehumidification priority control strategy. The main control chip sets the relative humidity weight to 0.6, the odor weight to 0.1, and the particulate matter weight to 0.3.

[0073] In S313, under the odor-forced exhaust mode S2, the main control chip executes a deodorization-priority control strategy. The main control chip sets the relative humidity weight to 0.1, the odor weight to 0.6, and the particulate matter weight to 0.3.

[0074] In S314, under the S3 mode of air purification away from people, the main control chip executes a balanced purification control strategy. The main control chip sets the relative humidity weight to 0.3, the odor weight to 0.3, and the particulate matter weight to 0.4.

[0075] The S320 main control chip uses internal timer data to set the behavior gain coefficient. The behavior gain coefficient is dynamically adjusted based on the duration of human presence detected by the human infrared sensor module.

[0076] S321, when the human infrared sensor module detects the presence of a person and the dwell time recorded by the timer inside the main control chip increases, the main control chip dynamically increases the behavior gain coefficient from 1.0 to 1.2.

[0077] In S322, when the human infrared sensor module detects that a person has left the sensing area, the main control chip reduces the behavior gain coefficient to 0.8. The main control chip uses this reduction in behavior gain coefficient to put the system into energy-saving mode.

[0078] The S330 main control chip quantifies environmental conditions by establishing an environmental pollution index calculation model. The main control chip multiplies the normalized dimensionless environmental data with their corresponding environmental weight coefficients and sums the results. The sum is then multiplied by the behavior gain coefficient to obtain the target PWM duty cycle. The formula for calculating the environmental pollution index is: In the formula, This represents the target value output by the environmental pollution index calculation model; Indicates the behavioral gain coefficient; Indicates relative humidity weight; Indicates the weight of ammonia; Indicates the weight of hydrogen sulfide; Indicates particulate matter weight; This represents the dimensionless value of relative humidity after normalization. This represents the dimensionless value of the ammonia concentration after normalization. The dimensionless value representing the hydrogen sulfide concentration after normalization. This represents the dimensionless value of the particulate matter concentration after normalization.

[0079] For the calling of floating-point multiplication and addition instructions and the allocation of multidimensional array matrix storage space in the main control chip, those skilled in the art can configure the registers according to the microcontroller's datasheet. The arithmetic logic operations and memory read and write operations at the microcontroller's underlying level are well-known technologies in the field and will not be described in detail here.

[0080] In some embodiments of the present invention, the specific process of the main control chip mapping the calculated environmental pollution index to the target PWM duty cycle in the aforementioned step S410 is described in detail, specifically including the following lower-level steps.

[0081] S411, the main control chip establishes a linear mapping relationship between the environmental pollution index and the target PWM duty cycle. The main control chip constructs a linear mapping mechanism, using the calculated environmental pollution index as the control target setpoint, and determines the corresponding PWM duty cycle control range in combination with the current scenario mode, thus converting the environmental pollution index into specific drive control parameters.

[0082] S412, when it is determined that the current state is standby or short-time mode S0, the main control chip sets the control range of PWM duty cycle to 0% to 20% in order to control the exhaust fan to operate in a low-wind or silent state.

[0083] S413 When it is determined that the current high humidity defogging mode S1 is in, the main control chip sets the control range of the PWM duty cycle to 50% to 70% in order to control the exhaust fan to operate in a constant dehumidification and exhaust state.

[0084] S414 When it is determined that the current odor strong exhaust mode S2 is in, the main control chip sets the control range of the PWM duty cycle to 80% to 100% in order to control the exhaust fan to run in a strong exhaust state.

[0085] S415, when the system is determined to be in the pedestrian clearance mode S3, the main control chip maintains a medium-speed exhaust state. The main control chip continuously monitors various environmental parameters until the real-time sampling values ​​of all sensors return to the preset baseline, at which point the main control chip shuts off the exhaust fan output.

[0086] S416 The main control chip writes the calculated target PWM duty cycle value into the comparison register of the internal timer of the main control chip to generate a square wave signal with the corresponding duty cycle.

[0087] For the configuration of pulse width modulation mode of the internal timer of the microcontroller and the loading operation of the comparison register, those skilled in the art can perform register-level programming according to the microcontroller reference manual. The underlying PWM waveform generation technology of the microcontroller is a well-known technology in the field and will not be described in detail here.

[0088] In some embodiments of the present invention, the specific execution process of the main control chip using the PID control algorithm to perform millisecond-level closed-loop fine-tuning of the output PWM duty cycle in the aforementioned step S420 is described in detail, specifically including the following lower-level steps.

[0089] The S421 variable frequency air volume control system receives control parameters from the scene recognition and control logic core system. The main control chip uses the calculated environmental pollution index as the target setpoint for the PID controller.

[0090] The S422 main control chip executes PID algorithm calculations. Combining the environmental pollution index with real-time environmental data monitored by the composite sensor array module, the main control chip calculates the PWM duty cycle signal using the PID algorithm.

[0091] The S423 main control chip employs a linear mapping and PID fine-tuning mechanism. It sends the calculated PWM duty cycle signal to the frequency converter control circuit, enabling millisecond-level adjustments to the operating status of the circuit and the PWM-enabled exhaust fan.

[0092] The S424 frequency converter control circuit receives the PWM duty cycle signal and drives the frequency converter exhaust fan. The exhaust fan speed smoothly transitions with changes in odor or humidity, avoiding sudden changes in airflow speed and noise during the control process, thus achieving a balance between energy efficiency and acoustic comfort.

[0093] For the specific tuning methods of proportional, integral, and derivative parameters in the PID control algorithm, as well as the underlying code structure of the closed-loop control program in the microcontroller, those skilled in the art can compile and implement them based on conventional automatic control principles. The PID parameter tuning methods and underlying code structure are well-known technologies in this field and will not be elaborated here.

[0094] In some embodiments of the present invention, taking the operation example of a washroom scenario, i.e., standby or short-term mode S0, the specific implementation process of the bathroom space exhaust adaptive intelligent control method that jointly senses personnel behavior and air pollution is described in detail. The human infrared sensor module detects personnel entering the bathroom space and outputs a high-level pulse signal to the main control chip. After receiving the high-level pulse signal output by the human infrared sensor module, the main control chip wakes up from its sleep state, enters a pre-sensing state, and starts an internal timer. The composite sensor array module acquires real-time environmental data inside the bathroom space. The environmental data preprocessing and transmission module performs high-frequency noise filtering and analog-to-digital conversion on the analog voltage signal output by the composite sensor array module, and continuously transmits the converted digital signal to the main control chip. Within the 10-second cycle of the internal timer, the main control chip continuously monitors the received digital signals. The main control chip compares the received relative humidity data, hydrogen sulfide concentration data, and ammonia concentration data with the thresholds set in the internal register. The main control chip determines that the real-time sampled value of relative humidity is less than or equal to 80%, and the real-time sampled value of ammonia concentration is less than or equal to 0.20 mg / m³. 3 The real-time sampling value of hydrogen sulfide concentration is less than or equal to 0.01 mg / m³. 3 The main control chip determines that all environmental parameters have not exceeded the set thresholds, classifying the current bathroom space as standby or short-term mode S0. The main control chip retrieves the environmental weight matrix based on the standby or short-term mode S0. It retrieves the corresponding values, setting the relative humidity weight to 0.0, the odor weight to 0.0, and the particulate matter weight to 0.0. The main control chip substitutes these weighted values ​​into the aforementioned environmental pollution index calculation model. Since the weights for all environmental parameters are 0.0, the environmental pollution index calculated by the main control chip is zero. The main control chip determines the PWM duty cycle based on the environmental pollution index. It sets the PWM duty cycle control range under standby or short-term mode S0 to 0% to 20% and outputs a pulse signal corresponding to the duty cycle to the frequency converter control circuit. The frequency converter control circuit receives the pulse signal and drives the frequency converter exhaust fan. The frequency converter exhaust fan operates in a low-wind or silent state, maintaining basic ventilation in the bathroom space and avoiding excessive noise and energy waste caused by full-speed operation of the equipment. The timing principle of the internal timer of the microcontroller and the underlying logic of register value comparison can be programmed by those skilled in the art based on the conventional microcontroller principles. The timing and value comparison methods of the microcontroller are well-known technologies in this field and will not be elaborated here.

[0095] In some embodiments of the present invention, taking the operation of a bathing scenario, specifically the high-humidity defogging mode S1, as an example, the specific implementation process of the bathroom space exhaust adaptive intelligent control method that jointly senses human behavior and air pollution is described in detail. The human infrared sensor module detects the presence of a person and continuously outputs a high-level signal to the main control chip. The main control chip receives the high-level signal output by the human infrared sensor module and records the duration of the person's stay according to an internal timer. A temperature and humidity sensor collects relative humidity data inside the bathroom space. An environmental data preprocessing and transmission module converts the relative humidity data and transmits the converted digital relative humidity signal to the main control chip. The main control chip compares the real-time sampled value of relative humidity with the humidity threshold set in its internal register. When the main control chip determines that the real-time sampled value of relative humidity is greater than 80% and simultaneously receives the human presence signal output by the human infrared sensor module, the main control chip determines that the current bathroom space state is high-humidity defogging mode S1. The main control chip retrieves the corresponding environmental weight value according to the high-humidity defogging mode S1. The main control chip sets the relative humidity weight to 0.6, the odor weight to 0.1, and the particulate matter weight to 0.3. The main control chip performs environmental pollution index calculation. It multiplies the dimensionless values ​​of each environmental parameter after normalization with their corresponding environmental weight values ​​and sums the results. Then, it performs a multiplication operation based on the behavioral gain coefficient that dynamically increases with dwell time to calculate the target value of the environmental pollution index. The main control chip determines the PWM duty cycle based on the environmental pollution index. In the high-humidity defogging mode S1, the main control chip controls the PWM duty cycle between 50% and 70% and outputs the corresponding pulse signal to the frequency converter control circuit. The frequency converter control circuit receives the pulse signal and drives the frequency converter exhaust fan. The frequency converter exhaust fan operates in a constant dehumidification and exhaust state to prevent mold growth and avoid the air-cooling effect. For the scheduling of the multiplication unit inside the microcontroller and the configuration of the pulse width modulation signal generator, those skilled in the art can perform register assignment operations according to the microcontroller's datasheet. The microcontroller's operation and signal generation mechanisms are well-known technologies in the field and will not be elaborated here.

[0096] In some embodiments of the present invention, taking the operation of the excretion scenario, i.e., the odor-driven exhaust mode S2, as an example, the specific implementation process of the bathroom space exhaust adaptive intelligent control method that combines the perception of human behavior and air pollution is described in detail. The human infrared sensor module detects the presence of a person and continuously outputs a high-level signal to the main control chip. The main control chip receives the high-level signal output by the human infrared sensor module and starts an internal timer to record the duration of the person's stay. The composite sensor array module collects ammonia and hydrogen sulfide concentration data inside the bathroom space. The environmental data preprocessing and transmission module converts the ammonia and hydrogen sulfide concentration data and continuously transmits the converted digital signals to the main control chip. The main control chip compares the real-time sampled values ​​of the ammonia and hydrogen sulfide concentration data with the odor threshold set in the internal register. When the main control chip determines that the real-time sampled value of the ammonia concentration is greater than 0.20 mg / m³... 3 Or, the real-time sampling value of hydrogen sulfide concentration is greater than 0.01 mg / m³. 3 At this time, the main control chip determines that the current bathroom space status is Odor Exhaust Mode S2. The main control chip retrieves the corresponding environmental weight values ​​based on Odor Exhaust Mode S2. The main control chip sets the relative humidity weight to 0.1, the odor weight to 0.6, and the particulate matter weight to 0.3. The main control chip performs environmental pollution index calculation. The main control chip multiplies the dimensionless values ​​of each environmental parameter after normalization with the corresponding environmental weight values ​​and sums them. Then, it performs a multiplication operation combining the behavioral gain coefficient that dynamically increases with the duration of human stay, to calculate the target value of the environmental pollution index. The main control chip determines the PWM duty cycle based on the environmental pollution index. The main control chip controls the PWM duty cycle under Odor Exhaust Mode S2 between 80% and 100% and outputs the corresponding pulse signal to the frequency converter control circuit. The frequency converter control circuit receives the pulse signal and drives the frequency converter exhaust fan. The frequency converter exhaust fan operates in a powerful exhaust state to remove odors from the bathroom space with maximum efficiency. For the numerical determination logic of the comparator inside the microcontroller and the low-level driving code of the pulse signal, those skilled in the art can program and implement it according to the conventional microcontroller development manual. The numerical determination logic and low-level driving code of the microcontroller are well known technologies in this field and will not be described in detail here.

[0097] In some embodiments of the present invention, taking the operation example of a vacant space scenario (vacant space mode S3) as an example, the specific implementation process of the bathroom space exhaust adaptive intelligent control method that combines the perception of human behavior and air pollution is described in detail. When the human infrared sensing module does not detect a human activity signal, the main control chip determines that the person has left the sensing area of ​​the bathroom space. The main control chip reduces the value of the behavior gain coefficient to 0.8, causing the system to enter energy-saving mode. The composite sensor array module continuously collects multi-dimensional environmental data inside the bathroom space. The environmental data preprocessing and transmission module transmits the real-time collected environmental data to the main control chip. The main control chip compares the real-time sampled values ​​of various environmental parameters with the corresponding preset benchmark values ​​stored in the internal register. When the main control chip determines that the real-time sampled value of any environmental parameter has not decreased to the corresponding preset benchmark value, the main control chip determines that the current bathroom space state is vacant space mode S3. The main control chip retrieves the corresponding environmental weight values ​​according to vacant space mode S3. The main control chip sets the relative humidity weight to 0.3, the odor weight to 0.3, and the particulate matter weight to 0.4. The main control chip performs environmental pollution index calculation. It multiplies the dimensionless values ​​of each environmental parameter (after normalization) with their corresponding environmental weights, sums the results, and then multiplies this sum with a behavior gain coefficient of 0.8 to calculate the target environmental pollution index value. Based on the target value, the main control chip outputs a corresponding pulse signal to the frequency converter control circuit. The frequency converter control circuit drives the frequency converter exhaust fan to maintain medium-speed exhaust operation, implementing a balanced purification control strategy. The main control chip continuously executes the numerical comparison logic in a loop until all real-time sampled values ​​of environmental parameters return to their corresponding preset benchmark values. At this point, the main control chip shuts off the pulse signal output, automatically shutting down the frequency converter exhaust fan. The methods for storing and retrieving values ​​from the microcontroller's internal registers and the writing of the multi-condition loop comparison program can be implemented by those skilled in the art according to conventional embedded system development specifications. The methods for storing and retrieving values ​​from the microcontroller and the multi-condition loop comparison program are well-known technologies in this field and will not be elaborated upon here.

[0098] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A bathroom space exhaust ventilation adaptive control method combining human behavior and air pollution, characterized in that, An adaptive intelligent control system for bathroom ventilation is applied, comprising a multi-dimensional information fusion sensing system for the bathroom environment, a core system for scene recognition and control logic, and a variable frequency airflow execution system. The adaptive control method for bathroom ventilation, which combines human behavior and air pollution, includes: The system collects and preprocesses multi-source environmental data and personnel status data of the bathroom space through a multi-source information fusion and perception system for the bathroom space environment. The core system of scene recognition and control logic performs dimensionless processing and scene pattern recognition on multi-source environmental data and personnel status data, and divides the bathroom space status into a variety of typical scene patterns. The target value of the environmental pollution index is calculated by weighting the execution behavior and environment of the core system of scene recognition and control logic. The core system of scene recognition and control logic outputs control commands to the variable frequency air volume execution system based on the target value of the environmental pollution index, thereby adjusting the speed of the variable frequency exhaust fan included in the variable frequency air volume execution system.

2. The bathroom space exhaust ventilation adaptive control method based on combined human behavior and air pollution as described in claim 1, characterized in that, The system collects and preprocesses multi-source environmental data and personnel status data of the bathroom space through a multi-source information fusion sensing system, including: The human infrared sensor module captures signals of people entering the bathroom space, and monitors the presence and duration of people in real time. Real-time sampling data of relative humidity, hydrogen sulfide concentration, ammonia concentration and particulate matter concentration inside the bathroom space are continuously acquired through temperature and humidity sensors, hydrogen sulfide sensors, ammonia sensors and particulate matter sensors. The environmental data preprocessing and transmission module performs noise reduction and conversion on the real-time sampled data, and transmits the converted digital signal to the core system of scene recognition and control logic via the communication bus.

3. The bathroom space exhaust ventilation adaptive control method based on combined human behavior and air pollution as described in claim 1, characterized in that, The core system of scene recognition and control logic performs dimensionless processing and scene pattern recognition on multi-source environmental data and personnel status data, classifying the bathroom space status into several typical scene patterns, including: The scene recognition and control logic core system normalizes the real-time sampling data of relative humidity, hydrogen sulfide concentration, ammonia concentration and particulate matter concentration. Based on the preset baseline values ​​of each environmental parameter under clean air conditions and the preset saturation values ​​under pollutant concentration saturation or humidity upper limit conditions, the real-time sampling data is uniformly mapped to the dimensionless range to generate dimensionless environmental data. The core system of scene recognition and control logic divides the bathroom space status into standby or short-term mode, high humidity defogging mode, strong odor exhaust mode, and evacuation mode based on preset dynamic condition discrimination logic.

4. The bathroom space exhaust ventilation adaptive control method based on combined human behavior and air pollution according to claim 3, characterized in that, The core system for scene recognition and control logic classifies the bathroom space into standby or short-term mode, high humidity defogging mode, strong odor exhaust mode, and odor removal mode based on preset dynamic condition discrimination logic, including: When someone is detected entering and staying for a short time, and the concentrations of various environmental parameters do not change abruptly and do not exceed the set threshold, the bathroom space is determined to be in standby or short-term mode. When the real-time relative humidity value detected is greater than 80% and the presence of a person is detected, the bathroom space is determined to be in high humidity defogging mode. When the real-time sampling value of the detected ammonia concentration is greater than 0.20 mg / m³, or the real-time sampling value of the hydrogen sulfide concentration is greater than 0.01 mg / m³, the bathroom space is determined to be in odor exhaust mode. When no human activity signal is detected and the real-time sampling value of any environmental parameter does not drop to the corresponding preset benchmark value, the bathroom space is determined to be in the human-free clearance mode.

5. The bathroom space exhaust ventilation adaptive control method based on combined personnel behavior and air pollution according to claim 1, characterized in that, The target value of the environmental pollution index is calculated by using a weighted method that couples the execution behavior and environment of the core system of scene recognition and control logic, including: The core system of scene recognition and control logic retrieves relative humidity weight, odor weight, and particulate matter weight from internal storage based on the identified typical scene patterns. The core system of scene recognition and control logic determines the behavior gain coefficient based on the duration of personnel stay recorded by an internal timer; The core system of scene recognition and control logic multiplies the normalized dimensionless environmental data with the corresponding environmental weight coefficients and sums them. Then, it multiplies the summation result with the behavior gain coefficient to calculate the target value of the environmental pollution index.

6. The bathroom space exhaust ventilation adaptive control method based on combined personnel behavior and air pollution according to claim 5, characterized in that, The core system for scene recognition and control logic retrieves relative humidity weights, odor weights, and particulate matter weights from internal storage based on the identified typical scene patterns, including: In standby or short-term mode, the relative humidity weight is set to 0.0, the odor weight is set to 0.0, and the particulate matter weight is set to 0.

0. In high humidity defogging mode, the relative humidity weight is set to 0.6, the odor weight to 0.1, and the particulate matter weight to 0.

3. In the odor exhaust mode, the relative humidity weight is set to 0.1, the odor weight to 0.6, and the particulate matter weight to 0.

3. In the detached air purification mode, the relative humidity weight is set to 0.3, the odor weight to 0.3, and the particulate matter weight to 0.

4. The odor weight is divided into equal parts, with ammonia and hydrogen sulfide weights each accounting for half.

7. The bathroom space exhaust ventilation adaptive control method based on combined personnel behavior and air pollution according to claim 5, characterized in that, The core system for scene recognition and control logic determines the behavior gain coefficient based on the duration of personnel stay recorded by an internal timer, including: When the presence of a person is detected and the duration of their stay continues to increase, the core system of scene recognition and control logic dynamically increases the behavior gain coefficient from 1.0 to 1.

2. When a person is detected leaving the sensing area, the scene recognition and control logic core system reduces the behavior gain coefficient to 0.

8.

8. The bathroom space exhaust ventilation adaptive control method based on combined personnel behavior and air pollution according to claim 1, characterized in that, The core system of scene recognition and control logic outputs control commands to the variable frequency air volume execution system based on the target value of the environmental pollution index, adjusting the speed of the variable frequency exhaust fan included in the variable frequency air volume execution system, including: The core system of scene recognition and control logic establishes a linear mapping mechanism between the target value of the environmental pollution index and the target pulse width modulation duty cycle; The core system of scene recognition and control logic takes the target value of environmental pollution index as the control target set value, and determines the corresponding pulse width modulation duty cycle control range in combination with the current typical scene mode, and generates the target pulse width modulation duty cycle; The scene recognition and control logic core system writes the target pulse width modulation duty cycle into the comparison register of the internal timer and outputs a pulse signal containing the target pulse width modulation duty cycle to the frequency conversion control circuit included in the frequency conversion air volume execution system.

9. The bathroom space exhaust ventilation adaptive control method based on combined personnel behavior and air pollution according to claim 8, characterized in that, The core system for scene recognition and control logic determines the corresponding pulse width modulation duty cycle control range based on the typical scene mode currently in operation, including: In standby or short-time mode, the control range of the pulse width modulation duty cycle is set to 0% to 20%. In high humidity defogging mode, the control range of the pulse width modulation duty cycle is set to 50% to 70%; In the odor exhaust mode, the control range of the pulse width modulation duty cycle is set to 80% to 100%; In the evacuation mode, the variable frequency exhaust fan is controlled to maintain medium-speed exhaust operation until all real-time sampled values ​​of environmental parameters return to the corresponding preset reference values. Then, the pulse signal output is turned off to control the variable frequency exhaust fan to automatically shut down.

10. The bathroom space exhaust ventilation adaptive control method based on combined human behavior and air pollution according to claim 8, characterized in that, The core system of scene recognition and control logic outputs a pulse signal containing the target pulse width modulation duty cycle to the variable frequency control circuit included in the variable frequency air volume execution system, including: The core system of scene recognition and control logic uses a PID control algorithm to fine-tune the duty cycle of the output pulse width modulation in milliseconds. The scene recognition and control logic core system combines the target value of the environmental pollution index with real-time monitored environmental data, and calculates a continuously changing pulse width modulation signal through a PID control algorithm; The scene recognition and control logic core system sends continuously changing pulse width modulation signals to the frequency conversion control circuit, which controls the speed of the frequency conversion exhaust fan to achieve smooth transition adjustment as the relative humidity or odor concentration changes.

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