Intelligent bathroom monitoring method, server and medium

Abstract

The invention discloses an intelligent bathroom monitoring method, a server and a medium, and relates to the technical field of intelligent homes. The method comprises the following steps: acquiring a user control instruction and real-time environment data; when the user control instruction is to start the ventilation equipment, or the real-time humidity exceeds a preset humidity threshold value, or the harmful gas concentration exceeds a preset threshold value, the ventilation equipment is controlled to operate; when the ventilation equipment conducts ventilation operation, if the real-time harmful gas concentration is within the normal range, the first operation power of the warm air blower is determined; when the warm air blower operates, a first gas flowing track of warm air and the gas temperature and the wind speed of each track point are determined; predicting a second gas flow track of the moisture and the moving speed of each track point, and determining a target air outlet and second operating power of the ventilation equipment in combination with the real-time humidity; and controlling the target air outlet of the ventilation equipment to work according to the second operation power. By implementing the technical scheme, the influence of the operation of the warm air equipment on the moisture emission efficiency of the ventilation equipment is reduced.

Description

Technical Field

[0001] This application relates to the field of smart home technology, and in particular to a smart bathroom monitoring method, server, and medium. Background Technology

[0002] With the continuous advancement of technology, the smart home industry has made significant progress, and smart bathrooms, as a part of this, are gradually becoming a part of people's lives. Smart bathrooms aim to provide users with a more comfortable, convenient, and healthy bathing environment.

[0003] Currently, smart bathroom systems typically utilize various sensors and control technologies to monitor and regulate environmental parameters such as temperature, humidity, and air quality. When the bathroom's ventilation system is running, if the temperature of the newly introduced air differs significantly from the bathroom's internal temperature, the large influx of cold or hot air will rapidly alter the bathroom's temperature, causing users to experience significant temperature fluctuations during showering. To reduce these fluctuations, appropriate heating equipment can be used to raise the bathroom's temperature.

[0004] However, when heating equipment in the bathroom is running, the heat it generates causes the surrounding air to rise, creating convection circulation. This causes the airflow direction for the ventilation equipment to draw out moisture to deviate, preventing the moisture from being smoothly discharged through the ventilation ducts. At the same time, the interaction between the hot airflow and the ventilation airflow creates turbulence in the bathroom, hindering the effective diffusion of moisture and prolonging the time that moisture remains in the bathroom, thus reducing the efficiency of the ventilation equipment in removing moisture. Summary of the Invention

[0005] This application provides a smart bathroom monitoring method, server, and medium that can reduce the impact of heating equipment operation on the moisture emission efficiency of ventilation equipment.

[0006] In a first aspect, this application provides a smart bathroom monitoring method, which includes: when a user is in the bathroom, acquiring in real time user control commands and real-time environmental data within a preset range for the user, the real-time environmental data including temperature, humidity, and harmful gas concentration; when the user control command is to turn on the ventilation equipment, or the real-time humidity exceeds a preset humidity threshold, or the harmful gas concentration exceeds a preset threshold, controlling the preset exhaust vents of the ventilation equipment to operate at a preset operating power, wherein multiple exhaust vents are installed in different locations in the bathroom; when the ventilation equipment is operating, if the real-time harmful gas concentration is within a preset normal range, determining, based on the real-time temperature and the ideal temperature, to ensure that the temperature within the user's preset range reaches the ideal temperature. Temperature, the first operating power required by the heater; when the heater is operating at the first operating power, based on the preset air outlet direction of the heater and the first operating power, determine the first gas flow trajectory of the warm air blown out by the heater when it is operating at the first operating power, as well as the gas temperature and wind speed at each trajectory point; based on the first gas flow trajectory, the gas temperature and the wind speed, as well as the preset exhaust vent and the preset operating power, predict the second gas flow trajectory of the moisture in the bathroom and the moving speed of each trajectory point; based on the second gas flow trajectory, the moving speed and the real-time humidity, determine the target exhaust vent and the second operating power of the ventilation equipment; control the target exhaust vent of the ventilation equipment to operate at the second operating power.

[0007] By employing the above technical solution, real-time monitoring of user control commands and bathroom environmental data is conducted. Upon detecting user commands or excessive humidity or harmful gas levels, the system controls the operation of the ventilation equipment to ensure timely response to user operations or prompt removal of polluted air when humidity or harmful gas levels exceed limits. During ventilation operation, the operating power of the heater is dynamically adjusted based on temperature requirements, ensuring a comfortable bathroom environment. Simultaneously, the system predicts the flow trajectory of warm air based on the heater's airflow characteristics, thereby simulating the flow path of moisture. Based on this, the optimal exhaust outlet and operating power of the ventilation equipment are determined, avoiding interference from the heater's hot air on the ventilation equipment's moisture emission and reducing the impact of the heater's operation on the ventilation equipment's moisture emission efficiency.

[0008] In conjunction with some embodiments of the first aspect, in some embodiments, determining the target exhaust port and the second operating power of the ventilation equipment based on the second gas flow trajectory, the moving speed, and the real-time humidity specifically includes: determining the moisture concentration distribution data of the ventilation area corresponding to each vent based on the second gas flow trajectory; calculating the moisture concentration value that can be discharged from each vent based on the moisture concentration distribution data; if the real-time humidity is higher than a first preset threshold, selecting the vent with the moisture concentration value greater than the first preset concentration value as the target vent; determining the second operating power of the target vent based on the second gas flow trajectory and the moving speed of each trajectory point; if the real-time humidity is lower than the second preset threshold, selecting the vent with the moisture concentration value less than the second preset concentration value as the target vent, and using the preset operating power as the second operating power.

[0009] By analyzing the humidity concentration distribution data, the impact of air convection caused by the heat from the heater on humidity distribution can be captured. When the real-time humidity is higher than a first preset threshold, ventilators with humidity concentrations greater than the first preset threshold are prioritized as target vents. A suitable second operating power is determined based on the second gas flow trajectory and the movement speed of each trajectory point, ensuring that humidity in high-concentration areas can be extracted quickly and efficiently, avoiding turbulence caused by the interaction of hot and ventilated airflows that hinders humidity diffusion. When the real-time humidity is lower than the second preset threshold, ventilators with humidity concentrations less than the second preset threshold are selected as target vents, and the preset operating power is maintained. This avoids excessive ventilation leading to dry indoor air and reduces unnecessary energy consumption. This intelligent judgment and dynamic control mechanism based on real-time humidity thresholds can flexibly respond to complex airflow changes caused by the heater's operation, ensuring that the ventilation equipment's dehumidification path remains optimal, thus improving the health index and comfort of the bathroom environment.

[0010] In conjunction with some embodiments of the first aspect, in some embodiments, determining the second operating power of the target vent based on the second gas flow trajectory and the moving speed of each trajectory point specifically includes: calculating the first time it takes for moisture in each target sub-region to reach the surface of a preset material based on the second gas flow trajectory and the moving speed of each trajectory point, wherein the target sub-region is obtained by dividing the ventilation area corresponding to the target vent according to the direction of moisture flow and the area of ​​the preset region; obtaining the relative position information between the first sub-region corresponding to the minimum first time and the target vent; and determining the second operating power required by the target vent to draw moisture in the first sub-region into the ventilation duct within the minimum first time based on the relative position information.

[0011] By employing the above technical solution, the ventilation area corresponding to the target vent is divided according to the direction of moisture flow and a preset area. Combined with the second gas flow trajectory and the moving speed at each point, the time it takes for moisture to reach the surface of the preset material is calculated, thus identifying the key area most prone to condensation. Based on the relative position of this area and the vent, the operating power of the target vent is specifically determined, ensuring that moisture is drawn into the ventilation duct with optimal suction before it condenses into water droplets that are difficult to remove, preventing moisture from lingering in the bathroom due to condensation and improving moisture removal efficiency.

[0012] In conjunction with some embodiments of the first aspect, in some embodiments, after the step of controlling the preset exhaust vent of the ventilation equipment to operate at a preset operating power when the user control command is to turn on the ventilation equipment, or the real-time humidity exceeds a preset humidity threshold, or the concentration of harmful gas exceeds a preset threshold, the method further includes: when the ventilation equipment is performing ventilation operation, if the rate of change of the real-time harmful gas concentration within a preset time period is within a preset abnormal range, obtaining the first harmful gas concentration in all first areas of the room except the bathroom; determining the source location of the target harmful gas based on the first harmful gas concentration, the real-time harmful gas concentration, and the type of target harmful gas exceeding the normal range; and adjusting the operating mode of the ventilation equipment according to the source location and the rate of change.

[0013] By employing the above technical solution, and through real-time monitoring of harmful gas concentration data in various indoor areas, combined with the concentration change rate and the types of harmful gases exceeding the standard, the source of harmful gases can be accurately located. Based on the source location and concentration change rate, the operating mode of the ventilation equipment is dynamically adjusted, causing the harmful gases in the bathroom to decrease rapidly or increase at a minimum rate, thus reducing the impact of harmful gases on users' health.

[0014] In conjunction with some embodiments of the first aspect, in some embodiments, adjusting the operating mode of the ventilation device according to the source location and the rate of change specifically includes: when the source location is only located in the first area, if the rate of change is greater than zero, adjusting the operating mode of the ventilation device to a stop operating mode; when the source location is only located in the bathroom, adjusting the operating mode of the ventilation device to a preset maximum ventilation mode.

[0015] Using the above technical solution, when the source of harmful gas is only located in the first area outside the bathroom and the concentration is increasing, the ventilation equipment should be stopped in time to prevent harmful gas from being introduced into the bathroom by the ventilation airflow and reduce the rate of increase of harmful gas in the bathroom; when the source of harmful gas is inside the bathroom, the ventilation equipment should be quickly adjusted to the preset maximum ventilation mode to expel the harmful gas in the bathroom as quickly as possible, reduce its concentration in the bathroom, and reduce the potential harm of harmful gas to the user's health.

[0016] In conjunction with some embodiments of the first aspect, in some embodiments, after the step of adjusting the operating mode of the ventilation equipment according to the source location and the rate of change, the method further includes: determining a target duration required for the user to leave the bathroom based on the user's historical bathroom usage records; predicting the concentration of harmful gases at various time points between the current time point and the target time point based on the rate of change and the operating mode of the ventilation equipment, wherein the target time point is obtained by adding the target duration to the current time point; determining the physical harm value of the user when leaving the bathroom under different protective measures based on historical environmental data, the predicted concentration, and the user's physical condition, wherein the historical environmental data is the environmental data at various time points between the time the user entered the bathroom and the current time point; and if the physical harm value exceeds a preset physical harm threshold, playing a prompt message to prompt the user to immediately leave the location with high concentrations of harmful gases.

[0017] By employing the above technical solution, and combining users' historical bathroom usage habits, dynamic predictions of harmful gas concentrations, and users' personal health data, the system can intelligently assess the potential health risks to users in hazardous environments. When the system predicts that continued stay may lead to excessive levels of physical harm, it will promptly issue a warning, prompting users to quickly evacuate the danger zone and reducing the risk of acute or chronic damage to the respiratory system, skin, and other systems caused by harmful gases.

[0018] In conjunction with some embodiments of the first aspect, in some embodiments, after the step of acquiring user control commands and real-time environmental data within a preset range when the user is in the bathroom, the method further includes: when different users are detected issuing different control commands to the same smart control device within a preset time period, acquiring a set of locations of the target users issuing the commands and a set of control commands; based on the set of locations, the set of control commands, and the real-time environmental data, filtering out a set of normal commands from the set of control commands; determining a target control command based on the set of normal commands, the real-time environmental data, and the preset control logic of the smart control device; and controlling the smart control device to execute the target control command.

[0019] By employing the above technical solution, when multiple users simultaneously operate the intelligent control device and cause command conflicts, the system can quickly filter out a set of normal commands that meet the actual needs by acquiring the target user's location information and command content, combined with real-time environmental data. Simultaneously, based on the intelligent control device's preset control logic, the target control command is further determined, ensuring that the commands executed by the device are both appropriate to the current bathroom environment and meet the reasonable usage needs of most users. This avoids misoperation or ineffective operation of the device due to command conflicts, thereby improving the response accuracy and reliability of the intelligent control device.

[0020] In conjunction with some embodiments of the first aspect, in some embodiments, determining the target control instruction based on the normal instruction set, the real-time environmental data, and the preset control logic of the intelligent control device specifically includes: if the preset control logic of the intelligent control device is overall control, assigning priority to each normal instruction in the normal instruction set based on the real-time environmental data, the location set of the target user, and the bathroom usage time; and taking the normal instruction with the highest priority as the target control instruction.

[0021] By adopting the above technical solution, when the intelligent control device uses overall control logic, it can comprehensively consider user needs and environmental conditions by combining real-time environmental data, the location set of target users, and bathroom usage time. This allows for the allocation of priorities to various normal commands, identifying the highest-priority command as the target control command. This avoids control chaos caused by multiple commands operating in parallel, ensuring the device responds promptly to critical needs. In multi-user operation scenarios, it balances the demands of different users, reduces equipment operating efficiency losses due to command conflicts, and improves the accuracy and practicality of the intelligent control device in overall control mode.

[0022] In a second aspect, embodiments of this application provide a monitoring server, including: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code including computer instructions, and the one or more processors call the computer instructions to cause the monitoring server to perform the method described in the first aspect and any possible implementation thereof.

[0023] Thirdly, embodiments of this application provide a computer-readable storage medium including instructions that, when executed on a monitoring server, cause the monitoring server to perform the method described in the first aspect and any possible implementation thereof.

[0024] Fourthly, this application provides a computer program product that, when run on a monitoring server, causes the monitoring server to perform the method described in the first aspect and any possible implementation thereof.

[0025] Understandably, the monitoring server provided in the second aspect, the storage medium provided in the third aspect, and the computer program product provided in the fourth aspect are all used to execute the method provided in this application. Therefore, the beneficial effects they can achieve can be referred to the beneficial effects in the corresponding methods, and will not be repeated here.

[0026] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages: 1. This application dynamically adjusts the operating power of the heater according to temperature requirements during the operation of the ventilation equipment, ensuring the comfort of the bathroom environment temperature. Simultaneously, it predicts the warm air flow trajectory based on the heater's air outlet characteristics, thereby simulating the moisture flow path and determining the optimal exhaust outlet and operating power of the ventilation equipment. This avoids interference from the heater's hot air on the ventilation equipment's moisture emission, reducing the impact of the heater's operation on the ventilation equipment's moisture emission efficiency.

[0027] 2. This application accurately locates the source of harmful gases by real-time monitoring of harmful gas concentration data in various indoor areas, combined with the concentration change rate and the types of harmful gases exceeding the standard. Based on the source location and concentration change rate, the operating mode of the ventilation equipment is dynamically adjusted, causing the harmful gases in the bathroom to decrease rapidly or increase at a minimum rate, thus reducing the impact of harmful gases on the user's health.

[0028] 3. When multiple users simultaneously operate the intelligent control device and command conflicts occur, this application can quickly filter out a set of normal commands that meet the actual needs by obtaining the location information and command content of the target user and combining it with real-time environmental data. Simultaneously, based on the preset control logic of the intelligent control device, the target control command is further determined, ensuring that the commands executed by the device are both appropriate to the current bathroom environment and meet the reasonable usage needs of most users. This avoids misoperation or ineffective operation of the device due to command conflicts, thus improving the response accuracy and reliability of the intelligent control device. Attached Figure Description

[0029] Figure 1 This is a schematic diagram of a system architecture to which the intelligent bathroom monitoring method in this application embodiment can be applied; Figure 2 This is a flowchart illustrating an intelligent bathroom monitoring method in an embodiment of this application; Figure 3 This is an exemplary scenario diagram of the intelligent bathroom monitoring method in the embodiments of this application; Figure 4 This is another exemplary scenario diagram of the intelligent bathroom monitoring method in the embodiments of this application; Figure 5 This is another flowchart illustrating the intelligent bathroom monitoring method in this application embodiment; Figure 6 This is a schematic diagram of an exemplary hardware structure of the monitoring server in an embodiment of this application. Detailed Implementation

[0030] The terminology used in the following embodiments of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. As used in the specification and appended claims of this application, the singular expressions “a,” “an,” “the,” “the,” “the,” and “this” are intended to include the plural expressions as well, unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in this application refers to any or all possible combinations including one or more of the listed items.

[0031] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature, and in the description of the embodiments of this application, unless otherwise stated, "multiple" means two or more.

[0032] Figure 1 This is a schematic diagram of a system architecture for which the intelligent bathroom monitoring method in this application embodiment can be applied.

[0033] Please see Figure 1 The intelligent bathroom monitoring system includes sensors, heaters, ventilation equipment, and a monitoring server.

[0034] The monitoring server, as the core component of the system, analyzes and processes environmental data collected by sensors and sends control commands to the ventilation equipment and heaters. Sensors are located throughout the bathroom, collecting environmental data such as temperature, humidity, and harmful gas concentrations, and transmitting this data to the monitoring server. The ventilation equipment, located on the bathroom ceiling, has multiple vents arranged in a specific pattern at the top. It receives control commands from the monitoring server and operates accordingly. The heaters, also located on the bathroom ceiling, receive control commands from the monitoring server and operate accordingly.

[0035] Through the above system architecture, the intelligent bathroom monitoring system can monitor the environmental data in the bathroom in real time, and dynamically adjust the working status and parameters of the heater and ventilation equipment according to changes in the environmental data, so as to realize real-time adjustment of the environmental data in the bathroom.

[0036] In related technologies, smart bathroom systems typically utilize various sensors and control technologies to monitor and regulate environmental parameters such as temperature, humidity, and air quality. When the ventilation equipment in the bathroom is running, if the temperature of the newly entered air differs significantly from the bathroom's internal temperature, the large influx of cold or hot air will rapidly alter the bathroom's temperature, causing users to experience significant temperature fluctuations during bathing. To reduce these fluctuations, heating equipment can be used to raise the bathroom temperature. However, when the heating equipment is running, the heat generated causes the surrounding air to rise, creating convection currents. This causes the airflow direction for the ventilation equipment to draw out moisture to deviate, preventing moisture from being effectively expelled through the ventilation ducts. Simultaneously, the interaction between the hot and ventilated airflows creates turbulence within the bathroom, hindering effective moisture diffusion and prolonging the time moisture remains in the bathroom, thus reducing the ventilation equipment's efficiency in removing moisture.

[0037] The intelligent bathroom monitoring method in this application embodiment dynamically adjusts the operating power of the heater according to the temperature requirement when the ventilation equipment is running, and predicts the flow trajectory of the warm air by combining the air outlet characteristics of the heater, thereby simulating the flow path of the moisture. Based on this, the optimal exhaust port and operating power of the ventilation equipment are determined, avoiding the interference of the hot air from the heater on the moisture emission of the ventilation equipment and reducing the impact of the operation of the heater on the moisture emission efficiency of the ventilation equipment.

[0038] The following is combined Figure 2 The method of the embodiments of this application will be described below.

[0039] Please see Figure 2 This is a flowchart illustrating a smart bathroom monitoring method in an embodiment of this application.

[0040] S201. When the user is in the bathroom, the system acquires the user's control commands and real-time environmental data within the user's preset range.

[0041] The real-time environmental data includes temperature, humidity, and concentrations of harmful gases. Harmful gas concentrations include those of carbon monoxide, carbon dioxide, methane, hydrogen sulfide, formaldehyde, and ammonia. User control commands include voice commands and button commands.

[0042] Specifically, regarding the acquisition of user control commands, when a user operates the smart bathroom control panel via button commands, the microcontroller within the panel converts the electrical signal from the pressed button into a corresponding command code and transmits the command code to the server. Upon receiving the command data packet, the server first verifies the data to confirm its integrity and accuracy, then matches the command code against a pre-set operation library to parse the user's control command content. When a user uses voice commands, the smart speaker's built-in microphone array collects sound signals. After preprocessing such as noise reduction and amplification, the built-in speech recognition chip converts the analog audio signal into a digital signal and extracts features to generate a speech feature vector. Subsequently, the smart speaker transmits the speech feature vector to the server via the network. The server calls a pre-trained speech recognition model (such as a deep learning-based DNN or RNN model) to match the speech feature vector with the acoustic and language models within the model, converting the speech content into text information. Then, the server uses natural language processing technology to perform semantic analysis on the text information, understand the user's intent, and determine the corresponding control command content. The control commands include, but are not limited to, equipment switch commands, equipment mode adjustment commands, equipment operating parameter adjustment commands, commands to trigger and deactivate voice alarms, and commands to query equipment status and environmental parameters.

[0043] To acquire real-time environmental data within a user-preset range, the user's location is first determined using infrared sensors or sound data. When using infrared sensors for positioning, multiple pyroelectric infrared sensors are evenly deployed on the bathroom ceiling and walls. These sensors detect the presence of a human by detecting infrared radiation emitted by the body. When a user enters the bathroom, the sensors detect changes in the amount of infrared radiation emitted by the human body, triggering a sensing mechanism. Multiple infrared sensors work collaboratively, calculating the user's specific coordinates within the bathroom using a triangulation algorithm based on the order in which the sensors are triggered and the differences in their sensing intensity, combined with a pre-established bathroom spatial coordinate system. For sound data-based positioning, multiple smart devices with array microphones, such as smart speakers and embedded microphones, are installed in the bathroom. When a user makes a sound in the bathroom, each microphone array collects sound signals arriving at different times. After receiving these sound signals, the server uses the Time Difference of Arrival (TDOA) algorithm to calculate the time difference between the sound source and each microphone. Combined with the geometric position information of the microphone array, spatial geometric calculations are used to determine the user's location.

[0044] After determining the user's location, based on the preset locations of each sensor, real-time environmental data collected by temperature, humidity, and harmful gas concentration sensors located within the user's preset range (or closest to the user) are obtained.

[0045] S202. When the user control command is to turn on the ventilation equipment, or when the real-time humidity exceeds the preset humidity threshold, or when the concentration of harmful gases exceeds the preset threshold, the preset exhaust port of the ventilation equipment shall be controlled to operate at the preset operating power.

[0046] The bathroom has multiple exhaust vents located in different positions. The ventilation system operates in a unidirectional exhaust mode (exhausting only air from inside the bathroom).

[0047] Specifically, if the user's control command is not to turn on the ventilation equipment, a corresponding control command is generated based on the control command content and sent to the corresponding control device. After receiving the control command, the control device executes the control command content.

[0048] If the user's control command is to turn on the ventilation equipment, the system retrieves the ventilation mode (e.g., normal mode, high-power mode, silent mode, etc.) from the command and uses the preset exhaust vent corresponding to the user's location as the preset exhaust vent. If the control command includes a ventilation mode, the system sends the corresponding control parameters (e.g., motor speed, airflow angle, preset exhaust vent, etc.) to the ventilation equipment's controller. Upon receiving the command, the controller operates the preset exhaust vent according to the preset operating power, expelling air from the bathroom through the preset exhaust vent. If the control command does not include a ventilation mode, the system sets the operating parameters according to the default ventilation mode. The server queries the preset default mode configuration (e.g., operating power, standard airflow direction, etc.) and sends the corresponding parameter commands (including operating power and preset exhaust vent) to the ventilation equipment controller.

[0049] If the real-time humidity exceeds a preset humidity threshold, the preset humidity-power mapping table is first retrieved, and the target operating power of the ventilation equipment is determined based on the degree to which the current humidity exceeds the threshold. Next, based on the target operating power and the preset exhaust vents, corresponding control commands are generated and sent to the ventilation equipment's controller.

[0050] If the concentration of harmful gas exceeds a preset threshold, the system first retrieves the target operating power of the corresponding ventilation scheme from the preset safety strategy library based on the type of harmful gas (carbon monoxide, methane, etc.) and concentration level. Then, it sends a control command to the controller of the ventilation equipment, which includes a strong target operating power and a signal to fully open the exhaust vents.

[0051] S203. When the ventilation equipment is in operation, if the real-time concentration of harmful gases is within the preset normal range, the first operating power required by the heater to achieve the ideal temperature within the user's preset range shall be determined based on the real-time temperature and the ideal temperature.

[0052] Specifically, when the ventilation equipment is operating, if the real-time concentration of harmful gases is within the preset normal range, the server will first obtain the real-time temperature data within the user's preset range and the user's preset ideal temperature value, and calculate the temperature difference between the real-time temperature and the ideal temperature. At the same time, it will obtain the operating power value of the current operating status of the heater.

[0053] If the real-time temperature is lower than the ideal temperature, the built-in thermodynamic model is retrieved. This model, based on the principles of heat transfer and fluid mechanics, uses finite element analysis to divide the bathroom space into multiple computational units, simulating the conduction, convection, and radiation processes of heat in three-dimensional space. The model incorporates a dynamic parameter adjustment mechanism that automatically corrects parameters such as wall heat transfer coefficients and airflow resistance based on real-time environmental data. Simultaneously, the model integrates a machine learning module to optimize the weighting of heat transfer coefficients using historical temperature adjustment data, making the calculation results more closely resemble the actual scenario. Furthermore, the model considers the start-up delay and power response characteristics of the heater, incorporating a time delay compensation factor into the calculation to ensure the timeliness and accuracy of power adjustment.

[0054] The model incorporates parameters such as temperature difference, bathroom space volume (calculated from previously entered length, width, and height data), wall thermal conductivity (determined based on the physical properties of bathroom building materials), current ventilation volume (calculated by real-time monitoring of ventilation equipment speed and outlet cross-sectional area), air specific heat capacity (a standard physical constant), and heater heat conversion efficiency (retrieved from the equipment parameter database). Based on the principle of energy conservation, the model first calculates the basic heat required to raise the bathroom air from the real-time temperature to the ideal temperature, using the formula Q = cmΔT (where c is the air specific heat capacity, m is the bathroom air mass, and ΔT is the temperature difference). The air mass m is obtained by multiplying the air density by the bathroom space volume. Considering heat loss due to ventilation equipment operation, the model calculates the heat loss per unit time based on ventilation volume and the air inlet / outlet temperature difference, combined with the heat conduction loss from the bathroom walls (calculated using Fourier's law), to arrive at the total heat demand. Then, based on the heater heat conversion efficiency, the model reverse-engineers the total energy output required by the heater, divides it by the preset desired heating time, and obtains the first operating power.

[0055] After obtaining the initial operating power, the operating power of the heater is gradually adjusted to the initial operating power according to the preset incremental power. During the adjustment process, the server continuously collects temperature data and performs model iteration calculations every preset time interval. Based on the actual heating effect, parameters such as the heat loss coefficient and heater efficiency are corrected to ensure that the temperature rises steadily to the ideal value. When the temperature approaches the ideal temperature (the difference is within the preset range), the power fine-tuning mechanism is activated. The PID control algorithm dynamically compensates for heat loss, maintains a constant temperature, and records the heater power adjustment log.

[0056] S204. When the heater is operating at the first operating power, based on the preset air outlet direction and the first operating power of the heater, determine the first gas flow trajectory of the warm air blown out by the heater when it is operating at the first operating power, as well as the gas temperature and wind speed at each trajectory point.

[0057] Specifically, when the heater is operating at its first operating power, detailed parameter information of the heater is retrieved first, including the shape of the heater's air outlet (such as rectangular, circular, etc.), its dimensions (specific values ​​such as length, width, and diameter), and the range of air outlet angle adjustment. This parameter information is pre-stored in the device parameter database on the server.

[0058] Next, based on the preset airflow direction of the heater, determine the initial direction vector of the heat output. For example, if the preset airflow direction of the heater is vertically downward, then the initial direction vector can be represented as [0, 0, -1] (assuming a three-dimensional coordinate system of the bathroom space, where the x-axis is the horizontal direction, the y-axis is the vertical direction, and the z-axis is the vertical direction).

[0059] Then, computational fluid dynamics (CFD) was used to determine the initial gas flow trajectory of the heating system. The bathroom space was treated as a closed computational domain, which was divided into numerous tiny mesh elements using finite element analysis. Then, based on the initial operating power of the heater and the physical properties of the air (such as density and viscosity, which are standard physical constants), the initial wind speed at the heater's outlet was calculated. Generally, there is a certain correlation between the heater's operating power and the outlet wind speed; the server can determine the initial wind speed using a pre-established power-wind speed mapping model.

[0060] When calculating gas flow trajectories, the server considers the influence of various factors on gas flow. First, there's the inertial force of the air; according to Newton's second law, gas experiences an inertial force during flow, the magnitude of which depends on the gas's mass and acceleration. Second, there's the effect of gravity; since warm air is generally less dense than the surrounding cold air, it tends to rise under the influence of gravity. Third, there's the viscous force of the air, which causes internal friction during flow, affecting the gas's speed and direction. Furthermore, the server also considers the obstruction and reflection effects of bathroom walls, ceilings, floors, and other obstacles on the gas flow.

[0061] The server calculates the gas temperature at each trajectory point based on the principle of energy conservation. The warm air blown by the heater exchanges heat with the surrounding air during its flow, causing its temperature to gradually decrease. The server calculates the heat output of the heater per unit time based on its heat conversion efficiency, initial operating power, and the specific heat capacity of the gas. Then, considering heat loss during the gas flow, such as convective heat transfer with the surrounding air and radiative heat transfer with objects like walls, a heat transfer equation is established to calculate the gas temperature at each trajectory point.

[0062] To calculate the wind speed at each trajectory point, the server uses the continuity equation and Bernoulli's equation. The continuity equation states that the mass flow rate of a gas remains constant during flow in the absence of a gas source or sink. Bernoulli's equation describes the relationship between pressure, velocity, and height during gas flow. The server uses these equations, combined with the resistance encountered by the gas during flow (such as frictional resistance and local resistance), to calculate the wind speed at each trajectory point. For example, when gas flows past an obstacle in a bathroom, local resistance is generated, causing a decrease in wind speed. The server calculates the local resistance coefficient based on the shape and size of the obstacle using empirical formulas or numerical simulation methods, and then calculates the change in wind speed.

[0063] Throughout the calculation process, the server updates and calculates the gas flow trajectory, gas temperature, and wind speed at each trajectory point at regular intervals. Simultaneously, the server stores and records the calculated first gas flow trajectory and the gas temperature and wind speed data at each trajectory point.

[0064] For a more intuitive illustration of the first gas flow trajectory, please refer to [link / reference]. Figure 3 This is a schematic diagram of an exemplary scenario of the intelligent bathroom monitoring method in the embodiments of this application.

[0065] Figure 3 The image shows an interior of a bathroom. A space heater is located at the ceiling, with vents distributed around it in a specific pattern. The heater's preset airflow direction is downward, and the initial gas flow trajectory of the warm air is also downward, as shown in the image. Trajectory points are points along the flow path; multiple trajectory points form the flow trajectory. The image only shows possible gas flow trajectories under certain conditions and is for reference only. Actual gas flow trajectories are more complex than those shown in the image.

[0066] S205. Based on the first gas flow trajectory, gas temperature and wind speed, as well as the preset exhaust vent and preset operating power, predict the second gas flow trajectory of moisture in the bathroom and the moving speed of each trajectory point.

[0067] Specifically, the server first establishes a 3D computational model of the bathroom, generating a 3D coordinate system using the bathroom's geometric parameters (such as length, width, and height), and then divides the bathroom into multiple mesh elements using finite element analysis. These mesh elements are used to calculate the flow characteristics of moisture. Then, based on humidity data collected by multiple humidity sensors distributed in different locations, combined with the user's location, the initial moisture distribution is determined. The initial moisture distribution is jointly determined by the real-time humidity values ​​provided by the humidity sensors and the humidity concentration effect in the user's activity area. The server uses an interpolation algorithm to map the discrete humidity data collected by the sensors onto the 3D mesh, and sets a higher moisture concentration in the user's activity area (such as the shower area), thereby completing the construction of the initial moisture concentration field.

[0068] Next, based on current environmental data and equipment operating status, boundary conditions and driving factors for moisture flow are set. The bathroom walls, floor, and ceiling are defined as impermeable, fixed boundaries. The exhaust vent serves as the outlet boundary, its suction determined by the operating power of the exhaust equipment; the heater outlet serves as the inlet boundary, its outlet velocity and temperature provided by the first gas flow trajectory. Moisture flow is primarily driven by the following factors: the thrust of the heater's hot airflow, the suction of the exhaust equipment, the buoyancy difference between the moisture and the surrounding air, and the molecular diffusion and turbulent diffusion of the moisture. The server calculates the outlet velocity and temperature fields of the heater, combined with the intake rate and pressure distribution of the exhaust vent, to determine the main driving forces for moisture flow.

[0069] Based on the aforementioned boundary conditions and driving factors, a wet gas flow model was established using computational fluid dynamics (CFD) methods, and the relevant governing equations were solved. The flow of wet gas follows the Navier-Stokes equations, where the mass conservation equation determines the change in wet gas concentration, the momentum conservation equation calculates the velocity changes of wet gas under the influence of inertial forces, viscous forces, and buoyancy, and the energy conservation equation calculates the temperature changes caused by heat exchange between the wet gas and the surrounding air. Furthermore, the server simulates the diffusion behavior of wet gas using diffusion equations; the molecular diffusion rate is calculated using Fick's law, while turbulent diffusion is solved using turbulence models (such as the k-ε model or the large eddy simulation model). The server uses the finite volume method (FVM) to discretize these equations and iteratively solves for the velocity, concentration, and temperature distribution of wet gas within each grid cell using numerical iteration methods.

[0070] The server simulates the dynamic flow trajectory of moisture at fixed time steps. At each time step, the server predicts the flow trajectory for the next time step based on the current velocity and position of the moisture. Simultaneously, the concentration and temperature fields of the moisture are updated in real time according to the diffusion equation and the energy conservation equation. The flow trajectory of the moisture is influenced by various factors, including the pushing force of the hot airflow from the heater, the suction of the exhaust vent, the vertical movement tendency caused by buoyancy, and the interaction between the moisture and the bathroom boundary. The server progressively superimposes these influencing factors to calculate the accurate movement path and velocity of the moisture.

[0071] After the moisture flow trajectory is calculated, the results are stored and output. The moisture flow trajectory is recorded in the form of three-dimensional coordinate points, and the moving speed and concentration of each trajectory point are dynamically updated over time. The moving speed and concentration of each trajectory point are determined by the moving speed and concentration of the grid cell to which the trajectory point belongs. The server can also generate a visual image of the moisture flow, displaying the moisture flow trajectory, concentration, and speed changes as dynamic three-dimensional graphics on the smart bathroom's user interface, helping users intuitively understand the moisture diffusion situation.

[0072] For a more intuitive illustration of the second gas flow trajectory, please refer to [link / reference]. Figure 4 This is a schematic diagram of another exemplary scenario of the intelligent bathroom monitoring method in the embodiments of this application.

[0073] like Figure 4 As shown in the second gas flow trajectory, the moisture at different locations in the bathroom is affected by factors such as the first gas flow trajectory and the suction of the vents, resulting in different gas flow trajectories for moisture at different locations. The figure only shows the possible gas flow trajectories for moisture at certain locations under certain conditions and is for reference only. The actual gas flow trajectories are more complex than those shown in the figure.

[0074] S206. Based on the second gas flow trajectory, moving speed, and real-time humidity, determine the target exhaust port and second operating power of the ventilation equipment.

[0075] Specifically, firstly, based on the second gas flow trajectory, the moisture concentration distribution data of the ventilation area corresponding to each vent is determined. The ventilation area refers to the range within which each vent can actually draw in moisture under current conditions, influenced by the heater's outlet direction, airflow characteristics, and the vent's operating power. When determining the ventilation area, the server first establishes a three-dimensional geometric model of the bathroom and marks the positions of the heater and vents in the model. Then, based on the heater's operating parameters (such as outlet velocity and temperature), the server simulates the diffusion characteristics of the hot airflow and calculates the range of influence of the heater on the surrounding airflow. Next, based on the vent's rated operating power, the server calculates the intake velocity field and pressure field of the vent using Bernoulli's equation and the mass conservation equation. The vent's intake capacity guides the surrounding moisture; by analyzing the moisture velocity field and combining it with the vent's intake velocity and pressure distribution, the server determines the range within which moisture can be drawn in, thus defining the boundary of the ventilation area.

[0076] After defining the ventilation zones, the moisture concentration distribution data within each ventilation zone is determined based on the concentration at each trajectory point in the second gas flow trajectory. For each trajectory point on the second gas flow trajectory, the server determines its ventilation zone by comparing the coordinates of the trajectory point with the coordinate range of each ventilation zone in three-dimensional space. If the coordinates of the trajectory point fall within the coordinate range of a certain ventilation zone, the moisture concentration value of that trajectory point is recorded in the moisture concentration dataset of that ventilation zone.

[0077] Next, based on the moisture concentration distribution data, the moisture concentration that can be discharged from each vent is calculated. For each vent, the server first obtains a pre-built distance-weight mapping table. This table pre-sets different weight coefficients based on the distance range between the vent and each point within the ventilation area; the closer the point is to the vent, the higher the weight. Then, it iterates through all trajectory points within the ventilation area, calculates the Euclidean distance between each trajectory point and the vent, and retrieves the corresponding weight from the mapping table based on the distance. The moisture concentration of each trajectory point is multiplied by its weight, summed, and then divided by the sum of all weights to obtain the moisture concentration that can be discharged from that vent.

[0078] If the real-time humidity is higher than a first preset threshold, select ventilators with a humidity concentration greater than the first preset threshold as target ventilators. Obtain the first preset concentration value and the preset number of ventilators corresponding to the first preset threshold. Sort the humidity concentration values ​​of each ventilator from highest to lowest. After sorting, filter out ventilators with a humidity concentration greater than the first preset threshold and store them in a candidate list. If the number of ventilators in the candidate list is greater than the preset number of ventilators, select the first preset number of ventilators from highest to lowest humidity concentration as target ventilators; if the number of ventilators in the candidate list is less than the preset number of ventilators, select all ventilators as target ventilators.

[0079] Then, based on the second gas flow trajectory and the moving speed of each trajectory point, the first time it takes for the moisture in each target sub-region to reach the preset material surface is calculated. Based on the second gas flow trajectory, the ventilation area corresponding to the target vent is divided into multiple target sub-regions according to the direction of moisture flow and the area of ​​the preset region. Each sub-region is defined by a three-dimensional coordinate range, and the direction of moisture flow is consistent within each sub-region. For each target sub-region, the moving speed and position information of multiple trajectory points within the sub-region are obtained. Then, taking the trajectory point closest to the preset material surface within the sub-region as the starting point, the movement path of the moisture is simulated by numerical integration based on the moving speed and direction of that point. During the simulation, the server monitors the distance between the moisture and the preset material surface in real time. When the distance is zero, the cumulative time from the starting point is recorded, and this time is the first time it takes for the moisture in that sub-region to reach the preset material surface.

[0080] Next, the relative position information between the first sub-region corresponding to the shortest first duration and the target vent is obtained. The first durations of each target sub-region are sorted from shortest to longest, and the first sub-region corresponding to the shortest first duration in the sorted order is obtained. Then, the relative displacement vector between the geometric center coordinates of the first sub-region and the center coordinates of the target vent is calculated. This vector contains displacement components in the x, y, and z axes of three-dimensional space. Simultaneously, the server also calculates the straight-line distance and relative angle between the first sub-region and the target vent.

[0081] Finally, based on the relative position information, the second operating power required by the target vent to draw moisture from the first sub-region into the ventilation duct within the minimum first time period is determined. First, the straight-line distance and spatial angle between the first sub-region and the target vent are obtained based on their relative positions. Then, the physical parameters of the target vent, such as its length, width, and height, the shape and porosity of the grille, and the number and radius of curvature of the duct bends, are substituted into the resistance calculation model. For air viscous resistance, the fluid dynamics formula F... v =μ×A×dy / dv (where μ is the aerodynamic viscosity, A is the contact area between the humid airflow and the ventilation duct, and dydv is the velocity gradient); local resistance is calculated using the empirical formula h j =ξ×v 2 / 2g (ξ is the local drag coefficient, which can be determined by referring to tables or experimental data, v is the velocity of the moist air flow, and g is the acceleration due to gravity), calculate the drag value for different structures such as bends and grids; the pressure loss due to distance is calculated according to the Darcy-Weisberg formula ΔP=f×L / D×ρ×v 2The solution is obtained by solving for / 2 (where f is the friction coefficient, L is the transmission distance, D is the equivalent diameter of the ventilation duct, and ρ is the moisture density), and then adding the results of various resistance calculations together to obtain the total resistance value.

[0082] Next, the server calculates the volume of the first sub-region and, combined with the average moisture concentration within that region, determines the total amount of moisture in the first sub-region. Then, based on the minimum first duration, it uses the formula Q = V / t (where Q is the intake flow rate, V is the total volume of moisture, and t is the minimum first duration) to calculate the intake flow rate required to draw the moisture from the first sub-region into the ventilation duct within a specified time.

[0083] Subsequently, the server retrieves pre-stored fan performance curve data from the target ventilation equipment. This curve describes the pressure-flow relationship of the fan at different operating power levels. This is then combined with Bernoulli's equation p1 + 1 / 2 × ρ × v1. 2 +ρ×g×h1=p2+1 / 2×ρ×v2 2 +ρ×g×h2+h w (p1 and p2 represent the pressures before and after the vent, v1 and v2 represent the moisture velocities at the corresponding locations, and h1 and h2 represent the heights, h...) w (For resistance loss), an initial operating power (e.g., 30% of the rated power of the ventilation equipment) is used as the starting value, and the corresponding pressure and flow rate are calculated by substituting it into the fan performance curve. The calculated flow rate is compared with the required intake flow rate. If the calculated flow rate is less than the required flow rate, the operating power is gradually increased according to a preset power increment (e.g., 5% of the rated power), and the pressure and flow rate are recalculated. If the calculated flow rate is greater than the required flow rate and exceeds the error range (e.g., 5%), the operating power is reduced. In each iteration of the calculation, the server updates the pressure-flow rate value corresponding to the fan performance curve based on the new operating power and recalculates the pressure required to overcome resistance, determining whether the requirement to draw moisture into the ventilation duct within the minimum first time duration is met. When the calculated intake flow rate and pressure meet the requirements within the allowable error range, the operating power at this time is the second operating power required for the target ventilation opening.

[0084] If the real-time humidity is lower than the second preset threshold, select the ventilator with a humidity concentration value lower than the second preset threshold as the target ventilator, and use the preset operating power as the second operating power. Obtain the second preset concentration value corresponding to the second preset threshold, filter out the ventilators with a humidity concentration value lower than the second preset threshold as the target ventilator, and use the preset operating power as the second operating power.

[0085] S207. Control the target exhaust vent of the ventilation equipment to operate at the second operating power.

[0086] Based on the target exhaust vent and the second operating power, a corresponding control command is generated and sent to the ventilation equipment's controller. Upon receiving the command, the controller controls the target exhaust vent of the ventilation equipment to operate at the corresponding second operating power, thereby exhausting the air from the bathroom.

[0087] In this embodiment, by monitoring user control commands and bathroom environmental data in real time, the ventilation equipment is controlled to operate when user commands are detected, or when moisture or harmful gases exceed the standard, ensuring timely response to user operations or timely removal of polluted air when moisture or harmful gases exceed the standard. During ventilation operation, the operating power of the heater is dynamically adjusted according to temperature requirements, ensuring a comfortable bathroom temperature. Simultaneously, the flow trajectory of warm air is predicted based on the heater's airflow characteristics, thereby simulating the moisture flow path. Based on this, the optimal exhaust port and operating power of the ventilation equipment are determined, avoiding interference from the heater's hot air on the ventilation equipment's moisture emission and reducing the impact of the heater's operation on the ventilation equipment's moisture emission efficiency.

[0088] The following is combined Figure 5 The methods of the embodiments of this application will be further explained below.

[0089] Please see Figure 5 This is another flowchart illustrating the intelligent bathroom monitoring method in this application.

[0090] S501. When the user is in the bathroom, the system acquires the user's control commands and real-time environmental data within the user's preset range.

[0091] Step S501 and Figure 2 Step S201 in the illustrated embodiment is similar and can be found in the description of step S201, which will not be repeated here.

[0092] S502. When different users issue different control commands to the same intelligent control device within a preset time period, obtain the location set of the target users who issued the commands and the control command set.

[0093] Specifically, when a user operates the bathroom smart control panel via button commands, the location of the smart control panel is taken as the user's location, and the location, the user's control command content, and the time point when the user's command is received are associated and stored. When the user uses voice commands, the raw sound signal data collected by the microphone array in the bathroom is retrieved. Using the Time Difference of Arrival (TDOA) algorithm, based on the timestamp differences of the sound signals received by each microphone, and combined with the pre-recorded three-dimensional coordinate information of the microphone array, the location coordinates of the sound source are calculated through spatial geometric calculations. The location coordinates, the user's control command content, and the time point when the user's command is received are associated and stored.

[0094] When control commands are received from different users within a preset time period (the location of the user corresponding to the command can be compared to determine if they belong to the same user), the system identifies whether the controlled object in the command content is consistent. If so, the control parameter data in the different command contents are compared. If the comparison fails, it is determined that different users have issued different control commands to the same intelligent control device. The system then obtains the location and control command content corresponding to each target user, thus obtaining the set of target user locations and the set of control commands.

[0095] S503. Based on the location set, control command set, and real-time environmental data, filter out the normal command set from the control command set.

[0096] Specifically, firstly, the validity of each instruction in the control instruction set is checked. For the control parameter data in the instructions, the server compares it with the parameter range of the intelligent control device. The first set of instructions whose control parameter data falls within the parameter range is then selected.

[0097] Next, the rationality of the instructions is evaluated using real-time environmental data. For each instruction in the first instruction set, the server simulates the changes in environmental data after the instruction is executed. Taking a temperature control instruction as an example, if the instruction requires raising the temperature of the heater, the server uses a thermodynamic model to calculate the expected increase in bathroom temperature over a certain period of time based on parameters such as the heater's power, heat conversion efficiency, bathroom space volume, and wall thermal conductivity. Then, the expected increase is added to the current real-time temperature to obtain the simulated temperature data after the instruction is executed. The server compares the simulated environmental data after the instruction is executed with a preset reasonable range. If the temperature after the simulated execution exceeds this range, the server considers the instruction unreasonable and removes it from the first instruction set. For humidity control instructions, ventilation equipment control instructions, etc., the server also uses a similar method for simulation and evaluation, ultimately obtaining a normal instruction set.

[0098] S504. If the preset control logic of the intelligent control device is overall control, priority is assigned to each normal instruction in the normal instruction set based on real-time environmental data, the location set of the target user, and the bathroom usage time.

[0099] Specifically, if the preset control logic of the intelligent control device is overall control, it determines the specific area where the user is currently located based on the target user's location, such as a shower area, washroom area, or changing area. For each normal command, if the device corresponding to the command has a significant impact on the user's current area, the command's priority will be increased accordingly; if the impact is small, the priority will be decreased. In addition, the server will further adjust based on the distance between the user and the device, with commands that are closer to the user having higher priority.

[0100] Subsequently, the urgency of commands is assessed based on real-time environmental data. For example, commands involving turning on the ventilation system are prioritized when the humidity in the bathroom is too high, while commands with less impact from humidity changes are given lower priority. Furthermore, the priority is dynamically optimized based on bathroom usage time. For users with shorter usage times, the priority of their commands is increased to ensure a more comfortable experience within their limited usage time. For users with longer usage times, the priority of their commands is reduced or not changed.

[0101] If the preset control logic of the intelligent control device is distributed control, firstly, the target control range corresponding to the area where the target user is currently located is obtained from the control range of the control device. If multiple target users have the same target control range, the above steps are executed to determine the instruction priority. If the target control ranges of the target users are different, the control instruction content of the target user is sent to the corresponding target control range. After receiving the instruction, the control device controls the first target control range to execute the first control instruction content of the first target user, and controls the second target control range to execute the second control instruction content of the second target user.

[0102] In some embodiments, if the contents of each normal instruction in the normal instruction set are to adjust the operating parameters of the device rather than the operating status (such as turning the device on or off), the server will analyze all the operating parameters in the normal instruction set, combine real-time environmental data, the current operating status of the device, and user requirements to merge conflicting parameter data, generate new parameter data, and thus form the final target control instruction.

[0103] First, the server parses each instruction in the normal instruction set, extracting its runtime parameters and target values. Then, it performs a fusion process based on a balance of multi-user needs. The parameters are weighted and calculated according to factors such as the target user's location set, real-time environmental data, and usage duration to obtain the target parameter data. Finally, the server uses the target parameter data as the control parameter data in the target control instruction and controls the intelligent control device to execute the target control instruction.

[0104] S505: Use the highest priority normal instruction as the target control instruction.

[0105] Specifically, the normal instructions in the normal instruction set are sorted from highest to lowest priority. After sorting, the normal instruction ranked first is selected as the target control instruction.

[0106] S506. Control the intelligent control equipment to execute the target control command.

[0107] Based on the content of the target control instruction, a corresponding device control instruction is generated and sent to the appropriate smart device. Upon receiving the instruction, the smart device executes the target control instruction.

[0108] S507. When the user control command is to turn on the ventilation equipment, or the real-time humidity exceeds the preset humidity threshold, or the concentration of harmful gases exceeds the preset threshold, the preset exhaust port of the ventilation equipment shall be controlled to operate at the preset operating power.

[0109] Step S507 and Figure 2 Step S202 in the illustrated embodiment is similar and can be found in the description of step S202, which will not be repeated here.

[0110] S508. When the ventilation equipment is in operation, if the rate of change of the real-time harmful gas concentration within a preset time period is within a preset abnormal range, the first harmful gas concentration in all first areas of the room except the bathroom is obtained.

[0111] Specifically, when the ventilation equipment is operating, the server continuously monitors the rate of change of the real-time concentration of harmful gases within a preset time period. First, it acquires the current concentration value of harmful gases from the sensors, and then periodically collects the concentration data for subsequent moments at preset time intervals. After collection, the rate of change of the harmful gas concentration is calculated using the following formula: Rate of change = (Final concentration - Initial concentration) / Preset time interval × 100%.

[0112] If the calculated rate of change exceeds the preset abnormal range, it indicates an abnormality in the concentration of harmful gases in the bathroom, potentially suggesting a continuous leak of harmful gases. In this case, the server will first query pre-stored indoor area distribution information to determine the specific location and extent of all first areas except the bathroom. For each first area, it will retrieve the concentration of the first harmful gas collected by the deployed harmful gas concentration sensors within that area.

[0113] S509. Based on the concentration of the first harmful gas, the real-time concentration of the harmful gas, and the type of the target harmful gas that exceeds the normal range, determine the source location of the target harmful gas.

[0114] Specifically, the concentrations of each harmful gas in the real-time harmful gas concentration are first compared with the corresponding normal gas concentrations, and target harmful gases whose concentrations exceed the normal gas concentrations are then screened out.

[0115] Then, the operating parameters of the ventilation equipment are obtained, including real-time ventilation volume (unit: cubic meters / minute), the proportion of air flowing into the bathroom from each first zone in the ventilation path (which can be calculated from the ventilation duct layout and valve status), and the real-time concentration of the target harmful gas in each first zone. Based on these parameters, the theoretical change in the concentration of the target harmful gas in the bathroom is calculated using the principle of mass conservation. Assume the ventilation time is t minutes, the air volume in the bathroom is V cubic meters, the real-time ventilation volume is Q cubic meters / minute, and the proportion of air flowing into the bathroom from the i-th first zone is P. i The real-time concentration value of the target harmful gas in this area is C. i The initial concentration of the target harmful gas in the bathroom was C. b0 Theoretically, the expected concentration of the target harmful gas in the bathroom after ventilation for t minutes can be calculated using the following formula: After calculating the expected concentration using the formula, the difference between the actual concentration and the expected concentration is calculated. If the absolute value of the difference is less than a preset error threshold, it indicates that the change in the target harmful gas concentration in the bathroom conforms to the theoretical expectation based on the air inflow from the first area. The target harmful gas is determined to originate from the first area, and the location with the highest target harmful gas concentration in the first area is selected as the source location. If the absolute value of the difference is greater than or equal to the preset error threshold, and the first harmful gas concentrations are all within the normal range, the target harmful gas is determined to originate from the bathroom, and the location with the highest target harmful gas concentration in the bathroom is selected as the source location. If the absolute value of the difference is greater than or equal to the preset error threshold, and there is a first target harmful gas concentration exceeding the normal range, the target harmful gas is determined to originate from both the bathroom and the first area, and the locations with the highest target harmful gas concentrations in both the bathroom and the first area are selected as the source locations.

[0116] S510. When the source location is only in the first area, if the rate of change is greater than zero, adjust the working mode of the ventilation equipment to the stop working mode.

[0117] When the source location is only within the first zone, a preset stop-operation command is sent to the ventilation equipment. Upon receiving the command, the ventilation equipment stops ventilation operation.

[0118] In some embodiments, when the source location is in the first area and the bathroom, if the difference between the actual concentration change value and the theoretical change value is less than the theoretical change value, it indicates that the concentration growth rate in the bathroom is less than the concentration growth rate caused by the air entering the bathroom from the first area. In this case, for each preset ventilation mode, the expected concentration corresponding to each ventilation mode is calculated according to the calculation method in step S509, based on the preset ventilation volume corresponding to each ventilation mode. The ventilation mode corresponding to the minimum expected concentration is selected as the ventilation mode of the ventilation equipment, and the control command corresponding to this ventilation mode is sent to the ventilation equipment. After receiving the command, the ventilation equipment performs ventilation operation according to the ventilation mode.

[0119] S511. When the source is located only in the bathroom, adjust the working mode of the ventilation equipment to the preset maximum ventilation mode.

[0120] When the source of the problem is located in the bathroom, a control command corresponding to the preset maximum ventilation mode is sent to the ventilation equipment. Upon receiving the command, the ventilation equipment operates according to the maximum ventilation mode.

[0121] S512. Based on the user's historical bathroom usage records, determine the target duration required for the user to leave the bathroom.

[0122] Specifically, the system first retrieves the user's historical bathroom usage records from the user behavior database. These records include the time of each entry into the bathroom, the time of leaving the bathroom, the actions performed in the bathroom (such as showering, washing, and laundry), and the duration of each action. The server then categorizes and statistically analyzes the historical records according to action type, calculating the average duration of each action.

[0123] Next, the server further analyzes the user's current behavior data in the bathroom. It matches real-time and historical audio data collected by the device at the user's location with the audio data corresponding to each behavior in the user's historical behavior data to identify the user's current action and its start time. The average duration of this action is then obtained. Subtracting the difference between the current time and the start time from the average duration yields the target time required for the user to leave the bathroom.

[0124] S513. Based on the rate of change and the working mode of the ventilation equipment, predict the concentration of harmful gases at each time point between the current time point and the target time point.

[0125] The target time point is obtained by adding the target duration to the current time point.

[0126] Specifically, based on the real-time rate of change r and the actual ventilation volume Q of the current ventilation equipment, combined with the operating parameters and historical data of the ventilation equipment, and considering the dynamic balance between the generation and emission of harmful gases, the actual concentration growth rate r is calculated using the principle of mass conservation.actual Assuming the air volume in the bathroom is V, and the current real-time concentration of harmful gases is C0, then r actual The calculation formula is: r actual =rQ×C0 / V, where r is the natural rate of change of harmful gas concentration, and Q×C0 / V represents the reduction in harmful gas concentration per unit time due to the operation of ventilation equipment. Simultaneously, the server monitors the operating status of the ventilation equipment in real time. If equipment malfunctions or ventilation volume fluctuates due to external factors, the Q value will be updated immediately and r will be recalculated. actual .

[0127] If the ventilation equipment is in shutdown mode, based on the current real-time harmful gas concentration C0 and the real-time rate of change r actual A linear growth model is used for prediction to obtain the predicted concentration at each time point between the current time point and the target time point. From the current time point t0 to the target time point t... target (t target =t0 + target duration) at the i-th time point t i The predicted concentration C = t0+i i The calculation formula is: Ci = C0 × (1 + r actual ×i), where i = 1, 2, ..., t target -t0. Simultaneously, the server considers the impact of environmental factors on the diffusion of harmful gases, such as the size of the bathroom space and the opening / closing status of doors and windows. If doors and windows are detected to be closed, restricting the diffusion of harmful gases, the server will appropriately increase the predicted concentration increase; if doors and windows are open, the prediction model will be corrected based on the ventilation area and airflow speed to reduce the increase.

[0128] If the ventilation equipment is in other operating modes, the server predicts the concentration values ​​at each time point based on the growth rate and the preset ventilation volume Q1 corresponding to other operating modes. From the current time point t0 to the target time point t... target (t target =t0 + target duration) at the i-th time point t i The predicted concentration of t0+i is C. i Initially, C0 represents the current real-time concentration, and C... i The calculation formula is C i =C i-1 +r actual ×C i-1 -Q1×C i-1 / V, where C i-1 The predicted concentration at the previous time point is given by r in the formula. actual ×C i-1 The concentration of harmful gases that increases naturally, Q1×C i-1 / V represents the concentration of harmful gases emitted by the ventilation equipment.

[0129] S514. Based on historical environmental data, predicted concentrations, and the user's physical condition, determine the physical damage value of the user when leaving the bathroom under different protective measures.

[0130] Among them, historical environmental data refers to the environmental data at various points in time between when the user enters the bathroom and the current time.

[0131] Specifically, the system first acquires basic physical information about the user, including age, gender, height, weight, history of chronic diseases such as respiratory and cardiovascular diseases, and records of physical reactions in similar environments in the past. Simultaneously, it extracts historical environmental data for each time point between the user entering the bathroom and the current time.

[0132] Next, a health impact assessment model is established. For different types of harmful gases, corresponding concentration-health damage coefficients are set based on authoritative medical research findings, environmental health standards, and the user's health status. For example, for carbon monoxide, referring to the World Health Organization's environmental health standards, when the concentration is between 50 ppm and 100 ppm, for ordinary healthy individuals, for every 10 ppm increase, the damage coefficient to the respiratory and cardiovascular systems increases by 0.1; however, if the user has cardiovascular disease, the increase in the damage coefficient will rise to 0.2 for every 10 ppm increase, because this group has a lower tolerance to carbon monoxide and is more prone to symptoms such as arrhythmia and angina.

[0133] Then, based on the protection coefficient of the harmful gas corresponding to the preset protection measures, the first damage coefficient is subtracted from the protection coefficient to obtain the corrected second damage coefficient corresponding to each protection measure.

[0134] Finally, the server comprehensively calculates the health damage caused by historical environmental data and the health damage caused by users taking different protective measures at predicted concentrations. For historical environmental data, the cumulative health damage is calculated based on the concentration of harmful gases the user was exposed to in a specific environment at different time points and the first damage coefficient. For predicted concentrations, the expected health damage corresponding to different protective measures is calculated by adding the second damage coefficient corresponding to each protective measure and the predicted concentration. Adding the two together yields the physical damage value of the user when leaving the bathroom under different protective measures.

[0135] S515. If the physical damage value exceeds the preset physical damage threshold, a prompt message will be played.

[0136] If the level of bodily harm exceeds a preset bodily harm threshold, the system acquires a set of locations where the concentration of harmful gases exceeds the preset threshold and sends a control command containing this set of locations to a preset speaker. Upon receiving the command, the speaker plays a prompt message.

[0137] The prompt message is used to remind users to immediately leave the location with a high concentration of harmful gases (i.e., the location in the location set).

[0138] S516. When the ventilation equipment is in operation, if the real-time concentration of harmful gases is within the preset normal range, the first operating power required by the heater to achieve the ideal temperature within the user's preset range shall be determined based on the real-time temperature and the ideal temperature.

[0139] S517. When the heater is operating at the first operating power, based on the preset air outlet direction and the first operating power of the heater, determine the first gas flow trajectory of the warm air blown out by the heater when it is operating at the first operating power, as well as the gas temperature and wind speed at each trajectory point.

[0140] S518. Based on the first gas flow trajectory, gas temperature and wind speed, as well as the preset exhaust vent and preset operating power, predict the second gas flow trajectory of moisture in the bathroom and the moving speed of each trajectory point.

[0141] S519. Based on the second gas flow trajectory, determine the moisture concentration distribution data of the ventilation area corresponding to each vent.

[0142] S520. Based on the moisture concentration distribution data, calculate the moisture concentration value that can be discharged from each vent.

[0143] S521. If the real-time humidity is higher than the first preset threshold, select the ventilation opening with a humidity concentration value greater than the first preset concentration value as the target ventilation opening.

[0144] S522. Based on the second gas flow trajectory and the moving speed of each trajectory point, calculate the first time it takes for the moisture in each target sub-region to reach the preset material surface.

[0145] The target sub-region is obtained by dividing the ventilation area corresponding to the target vent according to the direction of moisture flow and the preset area area.

[0146] S523. Obtain the relative position information of the first sub-region corresponding to the minimum first duration and the target ventilation opening.

[0147] S524. Based on relative position information, determine the second operating power required by the target ventilation opening to draw moisture from the first sub-region into the ventilation duct within a minimum first time period.

[0148] S525. If the real-time humidity is lower than the second preset threshold, select the ventilation opening with a humidity concentration value lower than the second preset concentration value as the target ventilation opening.

[0149] S526. Use the preset operating power as the second operating power.

[0150] S527. Control the target exhaust vent of the ventilation equipment to operate at the second operating power.

[0151] Steps S516-S527 and Figure 2 Steps S203-S207 in the illustrated embodiment are similar and can be found in the descriptions of steps S203-S207, which will not be repeated here.

[0152] In this embodiment, by real-time monitoring of harmful gas concentration data in various indoor areas, combined with the concentration change rate and the types of harmful gases exceeding the standard, the source of harmful gases can be accurately located. The working mode of the ventilation equipment is dynamically adjusted based on the source location and concentration change rate, causing the harmful gases in the bathroom to decrease rapidly or increase at a minimum rate, thus reducing the impact of harmful gases on user health. Simultaneously, when multiple users operate the intelligent control device simultaneously, resulting in command conflicts, by acquiring the target user's location information and command content, and combining it with real-time environmental data, a set of normal commands that meet actual needs can be quickly filtered out. Furthermore, based on the preset control logic of the intelligent control device, the target control command is further determined, ensuring that the commands executed by the device are both appropriate to the current bathroom environment and meet the reasonable usage needs of most users, avoiding equipment malfunctions or ineffective operation due to command conflicts, and improving the response accuracy and reliability of the intelligent control device.

[0153] The intelligent bathroom monitoring method in the embodiments of this application has been described above. The monitoring server in the embodiments of this application will be described in detail below in conjunction with the above-described intelligent bathroom monitoring method.

[0154] Please see Figure 6 This is a schematic diagram of an exemplary hardware structure of the monitoring server in an embodiment of this application.

[0155] In some embodiments, the monitoring server 600 includes a computer device, which may be a terminal device. The computer device includes a processor 601, a memory 602, a communication module 603, an input device 604, and an output device 605 connected via a system bus. The processor 601 provides computing and control capabilities. The memory 602 includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database stores data. The communication module 603 transmits collected environmental data and sound data to the server and sends control commands to the controllers of ventilation equipment, heaters, and other intelligent devices. The input device 604 receives control commands input by the user. The output device 605 displays environmental data. When the computer program is executed by the processor 601, it implements the intelligent bathroom monitoring method of this embodiment.

[0156] Those skilled in the art will understand that Figure 6 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0157] In some embodiments of this application, a computer-readable storage medium is provided, including instructions that, when executed on the monitoring server 600, cause the monitoring server 600 to perform the smart bathroom monitoring method of the embodiments of this application.

[0158] In some embodiments of this application, a computer program product is also provided, which, when running on a monitoring server 600, causes the monitoring server 600 to execute the smart bathroom monitoring method of the embodiments of this application.

[0159] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit it. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

[0160] As used in the above embodiments, depending on the context, the term "when..." can be interpreted as meaning "if...", "after...", "in response to determining...", or "in response to detecting...". Similarly, depending on the context, the phrase "when determining..." or "if (the stated condition or event) is interpreted as meaning "if determining...", "in response to determining...", "when (the stated condition or event) is detected", or "in response to detecting (the stated condition or event)".

[0161] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state drive), etc.

[0162] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This program can be stored in a computer-readable storage medium, and when executed, it can include the processes described in the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM or random access memory (RAM), magnetic disks, or optical disks.

Claims

1. A smart bathroom monitoring method, characterized in that, include: When the user is in the bathroom, the system acquires the user's control commands and real-time environmental data within the user's preset range. The real-time environmental data includes temperature, humidity, and concentration of harmful gases. When the user control command is to turn on the ventilation equipment, or when the real-time humidity exceeds the preset humidity threshold, or when the concentration of harmful gases exceeds the preset threshold, the preset exhaust vent of the ventilation equipment is controlled to operate at the preset operating power. The bathroom is equipped with multiple exhaust vents located in different positions. When the ventilation equipment is in operation, if the real-time concentration of harmful gases is within the preset normal range, the first operating power required by the heater to bring the temperature within the user's preset range to the ideal temperature is determined based on the real-time temperature and the ideal temperature. When the heater is operating at the first operating power, based on the preset air outlet direction of the heater and the first operating power, the first gas flow trajectory of the warm air blown out by the heater when it operates at the first operating power, as well as the gas temperature and wind speed at each trajectory point, are determined. Based on the first gas flow trajectory, the gas temperature and the wind speed, as well as the preset exhaust vent and the preset operating power, predict the second gas flow trajectory of the moisture in the bathroom and the moving speed of each trajectory point; Based on the second gas flow trajectory, the moving speed, and the real-time humidity, the target exhaust port and the second operating power of the ventilation equipment are determined. The target exhaust vent of the ventilation equipment is controlled to operate at the second operating power.

2. The method according to claim 1, characterized in that, The step of determining the target exhaust port and second operating power of the ventilation equipment based on the second gas flow trajectory, the moving speed, and the real-time humidity specifically includes: Based on the second gas flow trajectory, determine the moisture concentration distribution data of the ventilation area corresponding to each ventilator; Based on the moisture concentration distribution data, calculate the moisture concentration value that can be discharged from each vent. If the real-time humidity is higher than the first preset threshold, the ventilation opening with the humidity concentration value greater than the first preset concentration value is selected as the target ventilation opening; Based on the second gas flow trajectory and the moving speed of each trajectory point, the second operating power of the target vent is determined; If the real-time humidity is lower than the second preset threshold, the ventilation opening with a humidity concentration value less than the second preset concentration value is selected as the target ventilation opening, and the preset operating power is used as the second operating power.

3. The method according to claim 2, characterized in that, Determining the second operating power of the target vent based on the second gas flow trajectory and the moving speed of each trajectory point specifically includes: Based on the second gas flow trajectory and the moving speed of each trajectory point, the first time it takes for the moisture in each target sub-region to reach the surface of the preset material is calculated. The target sub-region is obtained by dividing the ventilation area corresponding to the target vent according to the direction of moisture flow and the area of ​​the preset region. Obtain the relative position information between the first sub-region corresponding to the minimum first duration and the target ventilation opening; Based on the relative position information, a second operating power is determined for the target vent to draw moisture from the first sub-region into the ventilation duct within the minimum first time period.

4. The method according to claim 1, characterized in that, After the step of controlling the preset exhaust vent of the ventilation equipment to operate at a preset operating power when the user control command is to turn on the ventilation equipment, or the real-time humidity exceeds a preset humidity threshold, or the concentration of harmful gases exceeds a preset threshold, the method further includes: When the ventilation equipment is in operation, if the rate of change of the real-time harmful gas concentration within a preset time period is within a preset abnormal range, the first harmful gas concentration in all first areas of the room except the bathroom is obtained. Based on the first harmful gas concentration, the real-time harmful gas concentration, and the type of target harmful gas that exceeds the normal range, the source location of the target harmful gas is determined. The operating mode of the ventilation equipment is adjusted according to the source location and the rate of change.

5. The method according to claim 4, characterized in that, The step of adjusting the operating mode of the ventilation equipment based on the source location and the rate of change specifically includes: When the source location is only located in the first area, if the rate of change is greater than zero, the working mode of the ventilation equipment is adjusted to the stop working mode; When the source location is only in the bathroom, the operating mode of the ventilation equipment is adjusted to the preset maximum ventilation mode.

6. The method according to claim 4, characterized in that, After the step of adjusting the operating mode of the ventilation equipment according to the source location and the rate of change, the method further includes: Based on the user's historical bathroom usage records, determine the target duration required for the user to leave the bathroom; Based on the rate of change and the working mode of the ventilation equipment, the predicted concentration of harmful gas at each time point between the current time point and the target time point is predicted, where the target time point is obtained by adding the target duration to the current time point. Based on historical environmental data, the predicted concentration, and the user's physical condition, the physical damage value of the user when leaving the bathroom under different protective measures is determined. The historical environmental data refers to the environmental data at various time points between the time the user entered the bathroom and the current time. If the physical damage value exceeds a preset physical damage threshold, a prompt message will be played to remind the user to immediately leave the location with a high concentration of harmful gases.

7. The method according to claim 1, characterized in that, After the step of acquiring user control commands and real-time environmental data within a preset range when the user is in the bathroom, the method further includes: When different users issue different control commands to the same smart control device within a preset time period, the location set of the target user who issued the command and the control command set are obtained. Based on the location set, the control command set, and the real-time environmental data, a set of normal commands is selected from the control command set. The target control command is determined based on the normal command set, the real-time environmental data, and the preset control logic of the intelligent control device. Control the intelligent control device to execute the target control command.

8. The method according to claim 7, characterized in that, The step of determining the target control command based on the normal command set, the real-time environmental data, and the preset control logic of the intelligent control device specifically includes: If the preset control logic of the intelligent control device is overall control, priority is assigned to each normal instruction in the normal instruction set according to real-time environmental data, the location set of the target user and the bathroom usage time; The highest priority normal instruction is used as the target control instruction.

9. A monitoring server, characterized in that, include: One or more processors and memory; The memory is coupled to the one or more processors, the memory being used to store computer program code, the computer program code including computer instructions, the one or more processors invoking the computer instructions to cause the monitoring server to perform the method as described in any one of claims 1-7.

10. A computer-readable storage medium storing computer instructions, characterized in that, When the computer instructions are executed on the monitoring server, the monitoring server performs the method as described in any one of claims 1-7.

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