Air conditioning control method and system based on multi-dimensional health parameters

Abstract

The application relates to the technical field of air conditioner control, in particular to an air conditioner control method and system based on multi-dimensional health parameters. The method collects indoor multi-dimensional health parameters, identifies a current use scenario and obtains a corresponding health threshold; a cleanliness deviation index is calculated based on the health parameters and the threshold, and cleanliness control is preferentially performed when the threshold is not met; after the cleanliness threshold is met, a comfort deviation index is further calculated and comfort control is performed; health parameter data is periodically updated during the control process, and the air conditioner control strategy is dynamically adjusted according to the update result, so that the cleanliness and comfort are cooperatively and optimally controlled. The application realizes dynamic control of cleanliness priority and comfort cooperation in the control process of a duct type household air conditioner, so that the duct type household air conditioner can balance health safety, comfort experience and operation energy efficiency in different use scenarios.

Description

Technical Field

[0001] This application relates to the field of air conditioning control technology, and in particular to an air conditioning control method and system based on multidimensional health parameters. Background Technology

[0002] In related technologies, with the improvement of residents' living standards and the increasing popularity of healthy living concepts, household air conditioners have gradually evolved from traditional temperature regulation devices into indoor environmental control devices that take into account both air quality and living comfort. Especially against the backdrop of increased residential airtightness and diversified family structures, health parameters such as indoor air temperature and humidity, particulate matter concentration, carbon dioxide content, and volatile harmful gases have an increasingly prominent impact on living experience and human health. Existing household air conditioning systems typically collect environmental parameters through built-in sensors and adjust the air supply, cooling, or heating processes according to preset control logic to maintain a basically stable indoor environment.

[0003] However, existing ducted home air conditioning control technologies mostly rely on single or limited environmental parameters such as temperature and humidity as the basis for control. Their fixed control modes make it difficult to comprehensively assess multiple health parameters, including air quality, health risks, and occupant activity levels. This results in a lack of targeted control objectives across different indoor usage scenarios, failing to meet users' demands for healthy and refined environmental control. Furthermore, current technologies often fail to effectively differentiate and coordinate conflicting control objectives such as cleanliness and comfort. When air pollution loads increase or environmental conditions change rapidly, insufficient air purification or a significant decrease in comfort can easily occur, impacting the overall health level of the indoor environment. In addition, existing air conditioning control strategies often employ static or weakly adaptive methods, lacking dynamic adjustment mechanisms based on real-time environmental changes. This leads to delayed control response, over-adjustment, or unstable long-term operating results, making it difficult to consistently ensure the coordinated achievement of air cleanliness and human comfort standards in real-world home environments.

[0004] In summary, the technical problems existing in the relevant technologies need to be improved. Summary of the Invention

[0005] The main objective of this application is to propose an air conditioning control method and system based on multi-dimensional health parameters, so as to achieve dynamic control that prioritizes cleanliness and coordinates comfort during the control process of ducted household air conditioners, and enable ducted household air conditioners to take into account health and safety, comfort experience and operating efficiency in different usage scenarios.

[0006] To achieve the above objectives, one aspect of this application proposes an air conditioning control method based on multidimensional health parameters, the method comprising the following steps: Collect indoor multidimensional health parameter data; Based on the multidimensional health parameter data, calculate the cleanliness deviation index; When the cleanliness deviation index fails to meet the standard, cleanliness control is executed, and the corresponding air conditioning control action is triggered according to the cleanliness deviation index. After detecting that the cleanliness deviation index meets the compliance conditions, the comfort deviation index is calculated; Based on the comfort deviation index, comfort control is performed, triggering the corresponding air conditioning control action; During the cleanliness control or comfort control process, the multidimensional health parameter data are periodically updated, and the control strategy is dynamically adjusted based on the update results.

[0007] In some embodiments, the multidimensional health parameter data includes temperature parameters, humidity parameters, air cleanliness parameters, and air composition parameters.

[0008] In some embodiments, after collecting indoor multidimensional health parameter data, the method further includes: identifying the current indoor usage scenario based on the multidimensional health parameter data, and obtaining the health parameter compliance threshold of a multi-scenario health parameter threshold library corresponding to the indoor usage scenario. The multi-scenario health parameter threshold library includes temperature thresholds, humidity thresholds, air cleanliness thresholds, and air composition thresholds for master bedroom scene, children's room scene, elderly room scene, dining room scene, and living room scene. Based on the environmental status information of the indoor usage scenario and the multidimensional health parameter data, the health parameter compliance threshold is adaptively adjusted to generate a dynamic health parameter compliance threshold that matches the scenario. The cleanliness deviation index and the comfort deviation index are calculated based on the dynamic health parameter compliance threshold.

[0009] In some embodiments, calculating the cleanliness deviation index based on the multidimensional health parameter data includes: The validity of air cleanliness-related parameters in the multidimensional health parameter data is verified and outliers are removed to obtain a set of cleanliness calculation parameters. Based on the cleanliness calculation parameter set, the cleanliness compliance threshold corresponding to the indoor use scenario is called; Calculate the extent to which each cleanliness parameter exceeds the corresponding cleanliness compliance threshold. For parameters that do not exceed the cleanliness threshold, the corresponding exceedance range is set to zero. For parameters that exceed the cleanliness threshold, the exceedance of each cleanliness parameter is weighted and calculated according to a preset parameter weighting rule to obtain a cleanliness deviation index.

[0010] In some embodiments, the air conditioning control actions include adjusting the air supply volume, adjusting the fresh air volume, adjusting the sleep mode, and adjusting the operating power.

[0011] In some embodiments, when the cleanliness deviation index fails to meet the compliance conditions, cleanliness control is executed, and a corresponding air conditioning control action is triggered based on the cleanliness deviation index, including: Based on the current indoor usage scenario, determine the cleanliness control level corresponding to the cleanliness deviation index; Based on the cleanliness control level, trigger an air conditioning control action that matches the cleanliness control level; The air conditioning operating status is adjusted through the aforementioned air conditioning control actions; During the cleanliness control process, the multidimensional health parameter data is updated, and based on the update results, it is determined whether the cleanliness deviation index meets the compliance conditions.

[0012] In some embodiments, calculating the comfort deviation index after detecting that the cleanliness deviation index meets the compliance conditions includes: If the cleanliness deviation index continuously meets the compliance conditions, based on the current indoor usage scenario, determine the comfort parameters corresponding to the indoor usage scenario and their corresponding priority order; the comfort parameters include temperature parameters, humidity parameters, air supply intensity parameters, and fresh air volume parameters; Based on the aforementioned comfort parameters, the corresponding scenario comfort compliance thresholds are obtained, and the exceedance range of each comfort parameter relative to the corresponding comfort compliance threshold is calculated. For comfort parameters that do not exceed the aforementioned comfort threshold, the corresponding exceedance range is set to zero. Based on the priority order of the comfort parameters and a preset comfort weighting rule, the excess range of each comfort parameter is weighted and fused to obtain the comfort deviation index.

[0013] In some embodiments, the compliance conditions include: Within a preset sampling period, the cleanliness deviation index is calculated to be zero in multiple consecutive sampling periods, and the air cleanliness parameter used to calculate the cleanliness deviation index simultaneously meets the cleanliness compliance threshold corresponding to the current indoor use scenario. The air cleanliness parameters include at least PM2.5 concentration, carbon dioxide concentration, formaldehyde concentration, and bacteria concentration, and the consecutive sampling cycles are no less than three consecutive sampling cycles.

[0014] In some embodiments, the step of performing comfort control based on the comfort deviation index and triggering a corresponding air conditioning control action includes: Based on the current indoor usage scenario, determine the comfort control level corresponding to the comfort deviation index; Based on the priority order of the comfort control level and comfort parameters, trigger the air conditioning control action that matches the comfort control level; During the comfort control process, the air conditioning control action is dynamically adjusted based on the updated multidimensional health parameter data until the comfort deviation index meets the preset comfort standard conditions.

[0015] To achieve the above objectives, another aspect of this application proposes an air conditioning control system based on multidimensional health parameters, the system comprising: The data acquisition module is used to collect indoor multidimensional health parameter data; The threshold acquisition module is used to identify the current indoor usage scenario based on the multidimensional health parameter data, and to acquire the health parameter threshold corresponding to the indoor usage scenario. The first calculation module is used to calculate the cleanliness deviation index based on the multidimensional health parameter data and the health parameter compliance threshold, according to a preset weighting rule. The cleanliness control module is used to perform cleanliness control when the cleanliness deviation index does not meet the compliance conditions, and to trigger the corresponding air conditioning control action according to the cleanliness deviation index. The second calculation module is used to calculate the comfort deviation index after detecting that the cleanliness deviation index meets the standard conditions. The comfort control module is used to perform comfort control based on the comfort deviation index and trigger corresponding air conditioning control actions. The update module is used to periodically update the multidimensional health parameter data during the cleanliness control or comfort control process, and dynamically adjust the control strategy based on the update results.

[0016] To achieve the above objectives, another aspect of this application provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method.

[0017] To achieve the above objectives, another aspect of the embodiments of this application proposes a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.

[0018] To achieve the above objectives, another aspect of this application provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0019] The embodiments of this application include at least the following beneficial effects: This application provides an air conditioning control method and system based on multi-dimensional health parameters. This solution collects indoor multi-dimensional health parameter data and identifies the current indoor usage scenario, obtaining health parameter compliance thresholds that match the indoor usage scenario. This transforms the air conditioning control objective from traditional single-parameter control to scenario-based control oriented towards health needs. Furthermore, based on the multi-dimensional health parameter data and the health parameter compliance thresholds, a cleanliness deviation index is calculated according to a preset weighting rule. When the compliance conditions are not met, cleanliness control is prioritized, thereby ensuring that cleanliness indicators are prioritized to meet standards when air quality risks are high, avoiding insufficient treatment caused by interference between different control objectives. After cleanliness meets the standards, a comfort deviation index is calculated and comfort control is executed, achieving phased coordination between cleanliness and comfort, taking into account both health and safety and human comfort experience. At the same time, the multi-dimensional health parameter data is periodically updated and the control strategy is dynamically adjusted during the control process, enabling the system to adapt to changes in human activity and environmental disturbances in real time, reducing control lag and over-adjustment risks, and improving the health protection capability, control stability, and overall energy efficiency of ducted household air conditioners. Attached Figure Description

[0020] Figure 1 This is a schematic flowchart of an air conditioning control method based on multidimensional health parameters provided in an embodiment of this application; Figure 2 This is a schematic diagram of the structure of the duct-type household air conditioning equipment provided in the embodiments of this application; Figure 3 yes Figure 1 A flowchart illustrating step S3 in the process; Figure 4 yes Figure 1 A flowchart illustrating step S5 in the process; Figure 5 This is a schematic diagram of a module of an air conditioning control method based on multidimensional health parameters provided in an embodiment of this application; Attached diagram descriptions: 1. Indoor unit of air conditioner; 2. Return air surface of indoor unit; 3. Air outlet of indoor unit; 4. Fresh air inlet; 5. Return air duct; 6. Return air outlet; 7. PM2.5 sensor; 8. Temperature and humidity sensor; 9. Air monitoring sensor group; 10. Gas-liquid pipe interface of indoor unit; 11. Gas-liquid pipe interface of outdoor unit; 12. Outdoor unit of air conditioner. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit it. In the following description, when referring to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with those of this application; they are merely examples of apparatuses and methods consistent with some aspects of the embodiments of this application as detailed in the appended claims.

[0022] It is understood that the terms “first,” “second,” etc., used in this application may be used herein to describe various concepts, but unless otherwise stated, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another. For example, without departing from the scope of the embodiments of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the words “if,” “when,” or “in response to a determination” as used herein may be interpreted as “when…” or “when…” or “in response to a determination.”

[0023] As used in this application, the terms "at least one", "multiple", "each", "any", etc., "at least one" includes one, two or more, "multiple" includes two or more, "each" refers to each of the corresponding multiples, and "any" refers to any one of the multiples.

[0024] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0025] This application provides an air conditioning control method and system based on multi-dimensional health parameters. This method collects multi-dimensional health parameter data indoors and identifies the current indoor usage scenario, obtaining health parameter compliance thresholds that match the scenario. This transforms the air conditioning control objective from traditional single-parameter control to scenario-based control oriented towards health needs. Furthermore, based on the multi-dimensional health parameter data and compliance thresholds, a cleanliness deviation index is calculated according to preset weighting rules. When compliance conditions are not met, cleanliness control is prioritized, ensuring that cleanliness indicators are met first when air quality risks are high, avoiding insufficient treatment caused by interference between different control objectives. After cleanliness is achieved, a comfort deviation index is calculated and comfort control is executed, achieving phased coordination between cleanliness and comfort, balancing health and safety with human comfort. Simultaneously, the multi-dimensional health parameter data is periodically updated and the control strategy is dynamically adjusted during the control process, enabling the system to adapt to changes in human activity and environmental disturbances in real time, reducing control lag and over-adjustment risks, and improving the health assurance capability, control stability, and overall energy efficiency of ducted household air conditioners.

[0026] This application provides an air conditioning control method based on multi-dimensional health parameters, relating to the field of air conditioning control technology. This air conditioning control method based on multi-dimensional health parameters can be applied to a terminal, a server, or software running on either a terminal or a server. In some embodiments, the terminal can be a smartphone, tablet, laptop, desktop computer, smart speaker, smartwatch, or vehicle terminal, but is not limited thereto; the server can be configured as an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The server can also be a node server in a blockchain network; the software can be an application implementing an air conditioning control method based on multi-dimensional health parameters, but is not limited to the above forms.

[0027] This application can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics devices, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0028] Figure 1 This is an optional flowchart of an air conditioning control method based on multidimensional health parameters provided in an embodiment of this application. Figure 1 The method may include, but is not limited to, steps S1 to S7: S1: Collect indoor multidimensional health parameter data; among which, the multidimensional health parameter data includes temperature parameters, humidity parameters, air cleanliness parameters, and air composition parameters.

[0029] refer to Figure 2 As shown, this embodiment collects data using multi-dimensional sensors in a ducted household air conditioner. The ducted household air conditioner includes an indoor unit 1 and an outdoor unit 12, and integrates a multi-dimensional health parameter sensing and control structure inside the indoor unit and along its supply and return air paths, as detailed below: The control unit or control component installed inside the indoor unit 1 of the air conditioner is used to receive data collected by multi-dimensional health parameter sensors and generate corresponding air conditioning control commands according to preset control logic; The indoor unit return air surface 2 is used to guide air to flow inside the indoor unit along a preset path; The indoor unit's air outlet 3 is used to deliver treated air to the air outlet; Fresh air inlet 4 is used to draw fresh air from the indoor unit to the wall opening, leading to the outside. An ABS air vent is installed at the opening to allow and block outside fresh air; it can also be equipped with an internal filter to purify the fresh air. Return air duct 5 is used to house the air duct, filter components and control components; The return air vent 6 is located in the upper part of the indoor space and is used to draw in indoor return air; PM2.5 sensor 7 is located 0.5m below the air outlet of the duct to detect the coverage of clean air; The temperature and humidity sensor 8 is located 1m below the air outlet of the duct to sense the temperature of the descending airflow, which is closer to the user's body temperature. The air monitoring sensor group 9 includes a CO2 sensor, a formaldehyde sensor, and a bacteria sensor. Half of them are integrated into one unit through brackets, bayonets, and plastic parts. They are installed near the return air vent to detect return air pollution. The indoor unit gas-liquid pipe interface 10 is connected to the outdoor unit gas-liquid pipe interface 11 by drilling a hole in the wall. The outdoor unit 12 of the air conditioner is used to perform cooling, heating and power output functions, and works in conjunction with the indoor unit.

[0030] In this embodiment, the indoor unit of the air conditioner adopts an airflow organization method of top return air and bottom vertical air supply: clean air descends vertically from the air supply outlet to cover the main activity area of ​​the room, while indoor polluted air gathers upward under the action of thermal buoyancy and airflow guidance, and enters the indoor unit circulation system through the return air outlet.

[0031] Multidimensional health parameter sensors are deployed in both the supply air coverage area and the return air area to monitor changes in indoor temperature, humidity, air cleanliness, and air composition in real time. Based on the collected multidimensional health parameter data and the current usage scenario, the control unit prioritizes the air cleanliness status and adjusts the supply air volume, fresh air volume, and operating power to achieve air conditioning control that prioritizes cleanliness while also considering comfort.

[0032] Through the above-described structural and airflow organization design, this embodiment can achieve overall circulation purification and refined health control of indoor air in a duct-type household air conditioner, effectively avoiding the air pollution circulation problem caused by traditional reliance solely on temperature regulation, and improving the health and comfort of the living environment.

[0033] In this embodiment, after the ducted household air conditioner is powered on, the control unit first initiates a multi-dimensional health parameter acquisition process. The multi-dimensional health parameters are collected collaboratively by multiple sensors installed at different key locations in the air conditioning duct system, forming a three-dimensional sensing network covering the supply air area and the return air area, in order to adapt to the airflow organization characteristics of the ducted air conditioner, which is "upper return air and lower vertical air supply".

[0034] It should be noted that the sensor group and its specific requirements in this embodiment are shown in Table 1: Table 1: Sensor List;

[0035] Specifically, temperature and humidity parameters are collected by temperature and humidity sensors located at a preset height below the air supply outlet. This location corresponds to the main human activity area covered by clean air, which can more accurately reflect the user's perceived environment. Air cleanliness parameters include at least PM2.5 concentration, collected by particulate matter sensors located near the air supply outlet, to monitor the diffusion effect of clean air in the indoor space. Air composition parameters include at least CO2 concentration, formaldehyde concentration, and bacteria concentration, collected by corresponding sensors located near the return air inlet to reflect the accumulation of pollutants in the circulating air.

[0036] During data acquisition, each sensor synchronously collects data according to a preset sampling period, and the control unit summarizes and timestamps the collected results. To ensure data validity, the control unit can perform basic validity checks and outlier removal on the collected multidimensional health parameters, ensuring that subsequent scene recognition and control calculations are based on real and stable environmental data.

[0037] S2: Identify the current indoor usage scenario based on multi-dimensional health parameter data, and obtain the health parameter compliance thresholds of the multi-scenario health parameter threshold library corresponding to the indoor usage scenario; Among them, the multi-scenario health parameter threshold library includes at least the temperature threshold, humidity threshold, air cleanliness threshold and air composition threshold corresponding to the master bedroom scene, children's room scene, elderly room scene, dining room scene and living room scene; Based on the environmental status information of the indoor usage scenario and the multidimensional health parameter data, the health parameter compliance threshold is adaptively adjusted to generate a dynamic health parameter compliance threshold that matches the scenario. The cleanliness deviation index and the comfort deviation index are calculated based on the dynamic health parameter compliance threshold.

[0038] In this embodiment, after acquiring multidimensional health parameter data, the control unit determines the current indoor usage scenario based on preset scene recognition rules. The scene recognition rules can integrate the configuration of the air conditioning installation area, user preset information, and the changing characteristics of multidimensional health parameters to distinguish different family functional spaces such as the master bedroom, children's room, elderly room, dining room, or living room.

[0039] Specifically, the control unit can combine the room type information entered during the initial installation, or analyze changes in CO2 concentration, PM2.5 fluctuation characteristics, and temperature and humidity usage habits to help determine the usage scenario corresponding to the current operating environment. For example, when a rapid increase in CO2 concentration and small humidity fluctuations are detected, it can be determined to be a dining or meeting scenario where people are more concentrated in the space; when environmental parameters are stable and it is nighttime, it can be determined to be a bedroom-type usage scenario.

[0040] After identifying the usage scenario, the control unit retrieves the corresponding health parameter thresholds from a pre-stored database of scenario health parameter thresholds. These thresholds correspond to temperature, humidity, air cleanliness, and air composition parameters, defining the reasonable range for each health indicator within that scenario. By introducing differentiated scenario threshold settings, the subsequent control process can better suit the health needs and usage characteristics of different home spaces.

[0041] Specifically, the health parameter thresholds for indoor use scenarios are shown in Table 2: Table 2. Thresholds for meeting health parameters in five major scenarios.

[0042] Table 2 presents the preset health parameter compliance thresholds for five major indoor usage scenarios in this embodiment. These thresholds are used to determine and control multi-dimensional health parameters based on the identified indoor usage scenarios during air conditioning operation. The five scenarios include at least the master bedroom, children's room, elderly person's room, dining room, and living room, each corresponding to different functional spaces and usage needs within a home.

[0043] As shown in Table 2, thresholds for temperature, humidity, PM2.5, CO2, formaldehyde, and bacteria were set for different scenarios. The thresholds for each scenario were configured differently based on the characteristics of space use. Children's rooms and elderly people's rooms had relatively stricter thresholds for air cleanliness and air composition parameters, while the thresholds for the dining room and living room were set to meet health requirements while also considering the actual situation of frequent human activity and large environmental fluctuations.

[0044] During operation, after identifying the indoor usage scenario, the air conditioning control unit automatically retrieves the corresponding health parameter thresholds from Table 2 and compares the collected multidimensional health parameters with the thresholds. When the parameters are within the corresponding threshold range, the system is considered to be in a compliant state; when the parameters exceed the threshold range, the system is considered to be in a non-compliant state. These parameters serve as the basis for subsequent calculations of the cleanliness deviation index or comfort deviation index and for triggering air conditioning control actions.

[0045] S3: Calculate the cleanliness deviation index based on multidimensional health parameter data and health parameter compliance thresholds; Among them, reference Figure 3 As shown, based on multidimensional health parameter data and health parameter compliance thresholds, the cleanliness deviation index is calculated, including: S31: Perform validity verification and outlier removal on air cleanliness-related parameters in multidimensional health parameter data to obtain a set of cleanliness calculation parameters; S32: Based on the cleanliness calculation parameter set, call the cleanliness compliance threshold corresponding to the indoor use scenario; S33: Calculate the extent to which each cleanliness parameter exceeds the corresponding cleanliness compliance threshold; S34: For parameters that do not exceed the cleanliness standard threshold, set the corresponding exceedance range to zero. S35: For parameters that exceed the cleanliness standard threshold, the excess range of each cleanliness parameter is weighted and calculated according to the preset parameter weighting rules to obtain the cleanliness deviation index.

[0046] In this embodiment, after completing the collection of multi-dimensional health parameter data and the identification of indoor usage scenarios, the air conditioning control unit enters the cleanliness assessment stage. The control unit extracts parameters related to air cleanliness from the multi-dimensional health parameter data as assessment objects. The air cleanliness-related parameters include at least PM2.5 concentration, CO2 concentration, formaldehyde concentration, and bacterial concentration, which are used to reflect the comprehensive status of particulate matter, gaseous pollutants, and biological pollutants in indoor air.

[0047] Before conducting a cleanliness assessment, the control unit first verifies the validity of the aforementioned air cleanliness-related parameters and removes outliers. Specifically, the collected data is assessed for range reasonableness, continuity, and stability. When missing data, significant jumps, or values ​​exceeding the sensor's reasonable range are detected, the corresponding parameters are deemed abnormal and removed from the calculation. The parameters that pass the verification form a cleanliness calculation parameter set, ensuring that subsequent cleanliness assessments are based on reliable data.

[0048] Subsequently, the control unit, based on the identified indoor usage scenario, invokes the cleanliness compliance threshold corresponding to that scenario. The cleanliness compliance threshold is a pre-set reference standard for different indoor functional spaces, used to define the compliance range of each cleanliness parameter in the current scenario. The control unit matches each parameter in the cleanliness calculation parameter set with its corresponding cleanliness compliance threshold, providing a unified benchmark for subsequent exceedance judgments.

[0049] Based on this, the control unit evaluates the exceedance of each cleanliness parameter relative to its corresponding cleanliness compliance threshold, which characterizes the degree to which the current parameter deviates from the compliance state. For parameters that do not exceed the corresponding cleanliness compliance threshold, the control unit sets the corresponding exceedance range to zero, so that the parameter does not affect the overall cleanliness assessment result; for parameters that exceed the cleanliness compliance threshold, they are marked as exceeding the standard and participate in subsequent fusion processing.

[0050] The calculation of the exceedance range includes calculating the exceedance range of each parameter according to the formula Δ%=(actual value-compliance threshold) / compliance threshold×100%. If the result is negative, then Δ%=0.

[0051] Finally, the control unit performs weighted fusion processing on the cleanliness parameters that exceed the standard state according to preset parameter weighting rules to obtain a cleanliness deviation index. The parameter weighting rules are used to reflect the differences in health risk and control priority of different cleanliness parameters, so that multiple pollution indicators can be uniformly mapped to a single cleanliness assessment result. The obtained cleanliness deviation index serves as the decision-making basis for subsequent cleanliness control stages, triggering corresponding air conditioning control actions, thereby achieving cleanliness-priority control under multi-parameter coordination.

[0052] Specifically, the cleanliness deviation index is calculated by substituting the weighting formula: CIV1 = (PM2.5 exceedance × 0.3) + (formaldehyde exceedance × 0.3) + (bacteria exceedance × 0.2) + (CO2 exceedance × 0.2) to obtain the cleanliness deviation index.

[0053] S4: When the cleanliness deviation index does not meet the standard, cleanliness control is executed, and the corresponding air conditioning control action is triggered according to the cleanliness deviation index; the air conditioning control action includes air supply volume adjustment, fresh air volume adjustment, sleep mode adjustment and operating power adjustment.

[0054] Specifically, when the cleanliness deviation index fails to meet the compliance requirements, cleanliness control is implemented, triggering corresponding air conditioning control actions based on the cleanliness deviation index, including: S41: Based on the current indoor usage scenario, determine the cleanliness control level corresponding to the cleanliness deviation index; S42: Trigger air conditioning control actions that match the cleanliness control level, based on the cleanliness control level. S43: Adjust the air conditioner's operating status through air conditioner control actions; S44: During the cleanliness control process, update the multidimensional health parameter data and determine whether the cleanliness deviation index meets the compliance conditions based on the update results.

[0055] In this embodiment, when the cleanliness deviation index fails to meet the compliance conditions, the control unit prioritizes entering the cleanliness control process. Cleanliness control is based on the currently identified indoor usage scenario and, combined with the airflow organization characteristics of ducted air conditioning ("upward return air, downward vertical air supply"), focuses on improving the efficiency of indoor air circulation and pollutant removal, thereby rapidly improving indoor air cleanliness and air composition.

[0056] When implementing cleanliness control, the control unit first determines the level of the cleanliness deviation index based on the current indoor usage scenario, thus establishing the corresponding cleanliness control level. The cleanliness control level characterizes the severity of the deviation of the current air cleanliness from the acceptable state; different levels correspond to different control intensities and priorities. Simultaneously, the control unit can adapt and adjust the control level according to different usage scenarios. For example, in children's rooms or elderly people's rooms, a more aggressive cleanliness control strategy can be adopted to improve health protection levels.

[0057] After determining the cleanliness control level, the control unit triggers matching air conditioning control actions based on the cleanliness control level, and adjusts the air conditioning operation status through these actions. The air conditioning control actions include at least airflow adjustment, fresh airflow adjustment, sleep mode adjustment, and operating power adjustment. Specifically, increasing the fan speed can enhance the airflow, adjusting the fresh air intake can increase the fresh air intake, and adjusting the compressor or power module can change the operating power. When sleep mode or a low-noise requirement scenario is detected, an upper limit is set on the fan speed to reduce noise and airflow interference without affecting the cleanliness improvement effect.

[0058] During cleanliness control, the control unit continuously updates multidimensional health parameter data according to a preset sampling cycle, and re-evaluates whether the cleanliness deviation index meets the compliance conditions based on the updated data results. If the cleanliness deviation index still does not meet the standards, the control action corresponding to the current cleanliness control level is maintained or strengthened; if the cleanliness deviation index meets the compliance conditions and remains stable, the control unit terminates or reduces the cleanliness control intensity, providing a switching basis for the subsequent execution of comfort control, thus forming a closed-loop adjustment process for cleanliness control.

[0059] Specifically, the control range of the cleanliness control action is matched as shown in Table 3: Table 3: Cleanliness Control Action Matching Table;

[0060] Table 3 is the cleanliness control action matching table of this embodiment, used to determine the corresponding air conditioning control actions and their execution constraints according to different ranges of the Cleanliness Deviation Index (CIV1) during the cleanliness control phase. The Cleanliness Deviation Index is used to comprehensively characterize the degree to which the current indoor air cleanliness deviates from the standard state, and the control unit manages the cleanliness control intensity in a graded manner according to its numerical range.

[0061] As shown in Table 3, when the cleanliness deviation index is in the "0 (compliant)" range, it indicates that the current indoor air cleanliness meets the compliance requirements of the corresponding scenario, and the control unit maintains the current fan speed and fresh air volume unchanged; when the cleanliness deviation index is in the "0-0.3 (slight)" range, the control unit triggers a mild cleanliness control action, which accelerates the diffusion of clean air in the indoor space by slightly increasing the fan speed and appropriately increasing the fresh air volume; when the cleanliness deviation index is in the "0.3-0.6 (moderate)" range, the control unit further enhances the air supply and fresh air regulation to improve air circulation and pollutant dilution efficiency; when the cleanliness deviation index is greater than "0.6 (severe)", the control unit executes an enhanced cleanliness control action, which significantly increases the fan speed and fresh air volume within the safe operating range to quickly improve indoor air quality.

[0062] Furthermore, Table 3 specifies the operational limitations in sleep mode. When the user activates sleep mode or the system detects a need for low noise at night, the control unit, while performing the aforementioned air cleanliness control actions, sets an upper limit on the maximum fan speed. Different scenarios correspond to different speed limits; for example, the master bedroom, the elderly's room, and the children's room each have different maximum speed constraints. By establishing a synergistic constraint relationship between air cleanliness control and sleep mode limitations, this invention effectively reduces operating noise and wind fluctuations while ensuring improved air cleanliness, thus enhancing comfort and safety during nighttime use.

[0063] By introducing the cleanliness control action matching mechanism shown in Table 3, this embodiment can establish a clear mapping relationship between the cleanliness deviation index and the specific air conditioning control action, avoid control conflicts caused by independent adjustment of multiple parameters, realize graded response and stable execution of cleanliness control, and provide a clear basis for subsequent cleanliness standard determination and control stage switching.

[0064] S5: After detecting that the cleanliness deviation index meets the standard conditions, calculate the comfort deviation index; Among them, reference Figure 4 As shown, after the cleanliness deviation index is detected to meet the compliance conditions, the comfort deviation index is calculated, including: S51: Under the condition that the cleanliness deviation index continuously meets the compliance conditions, based on the current indoor usage scenario, determine the comfort parameters corresponding to the indoor usage scenario and their corresponding priority order; the comfort parameters include temperature parameters, humidity parameters, air supply intensity parameters and fresh air volume parameters; S52: Based on comfort parameters, obtain the corresponding scenario comfort compliance thresholds respectively, and calculate the exceedance range of each comfort parameter relative to the corresponding comfort compliance threshold; S53: For comfort parameters that do not exceed the comfort standard threshold, the corresponding exceedance range is set to zero. S54: Based on the priority order of comfort parameters and the preset comfort weighting rules, the excess range of each comfort parameter is weighted and fused to obtain the comfort deviation index.

[0065] Specifically, the criteria for meeting the standard include: Within the preset sampling period, the cleanliness deviation index is calculated to be zero in multiple consecutive sampling periods, and the air cleanliness parameter used to calculate the cleanliness deviation index simultaneously meets the cleanliness compliance threshold corresponding to the current indoor use scenario. The air cleanliness parameters include at least PM2.5 concentration, carbon dioxide concentration, formaldehyde concentration, and bacteria concentration, and the sampling period must be at least three consecutive sampling periods.

[0066] In this embodiment, during the cleanliness control phase, the control unit continuously updates multidimensional health parameters according to a preset sampling cycle (10 seconds per sampling cycle) and periodically calculates and determines the compliance of the cleanliness deviation index. The compliance conditions include: within the preset sampling cycle, the cleanliness deviation index is zero for at least three consecutive sampling cycles, and the air cleanliness parameters used to calculate the cleanliness deviation index simultaneously meet the cleanliness compliance threshold corresponding to the current indoor usage scenario. Specifically, the air cleanliness parameters include at least PM2.5 concentration, CO2 concentration, formaldehyde concentration, and bacteria concentration. When these parameters are within the compliance range for multiple consecutive sampling cycles, the control unit determines that the indoor air cleanliness has stably met the standards, thus allowing a switch from the cleanliness priority phase to the comfort assessment phase to avoid control conflicts caused by prematurely implementing comfort adjustments before pollution is eliminated.

[0067] After the above switching conditions are met, the control unit determines the comfort parameters and their priority order corresponding to the current indoor usage scenario. Comfort parameters include at least temperature, humidity, air supply intensity, and fresh air volume, with different priority settings for different scenarios: for example, in a children's room, humidity is prioritized to reduce dryness and discomfort, followed by temperature and air supply intensity; in an elderly person's room, temperature stability is prioritized, followed by humidity and air supply intensity; in a dining room, fresh air volume is prioritized to handle the concentration of people and the diffusion of cooking odors, followed by temperature and humidity; in a master bedroom or living room, air supply intensity can be prioritized to reduce wind and noise interference, while also considering temperature and humidity. Through scenario-based priority settings, comfort assessments are made more aligned with the usage needs of different functional spaces in a family home.

[0068] Subsequently, based on comfort parameters, the control unit obtains the corresponding scene comfort compliance thresholds and assesses the degree of deviation for each comfort parameter. Specifically, temperature and humidity can be represented by the comfort range thresholds for the current scene; air supply intensity parameters can be characterized by fan speed, air volume, or wind speed, and the corresponding scene's upper comfort limit thresholds can be used; fresh air volume parameters can be represented by the fresh air valve opening or fresh air volume setpoint, and the scene's specified reasonable range thresholds can be used. The control unit compares each comfort parameter with its threshold to obtain the degree of deviation of the parameter from the compliance state, which reflects the source and severity of the current comfort problem.

[0069] For comfort parameters that do not exceed the comfort threshold, the control unit sets the corresponding deviation to zero to prevent it from affecting the final comfort assessment result; only comfort parameters that exceed the threshold retain their deviation for subsequent fusion. Based on this, the control unit calls the preset comfort weighting rules according to the priority order of comfort parameters to perform weighted fusion of the deviation of each comfort parameter to obtain the comfort deviation index.

[0070] Specifically, the comfort deviation index is calculated by substituting the values ​​into the formula CIV2 = (excess range of level 1 comfort parameter × 0.5) + (excess range of level 2 comfort parameter × 0.3) + (excess range of level 3 comfort parameter × 0.2).

[0071] Among them, Level 1 comfort parameters have the highest impact on human comfort in the current indoor usage scenario, and can be selected as temperature parameters, humidity parameters or fresh air volume parameters depending on the usage scenario; Level 2 comfort parameters have a secondary impact on comfort and are used to further optimize the indoor environment; Level 3 comfort parameters have a relatively small impact on comfort and are mainly used to fine-tune the airflow or operating experience.

[0072] The control unit performs weighted processing on the deviation of each level of comfort parameter relative to the corresponding comfort compliance threshold according to the above priority order, so that the high priority parameters have a higher weight in the comfort deviation index calculation, thereby highlighting the comfort factors that have a more significant impact on the user's physical experience.

[0073] S6: Based on the comfort deviation index, execute comfort control and trigger the corresponding air conditioning control action; Based on the comfort deviation index, comfort control is implemented, triggering corresponding air conditioning control actions, including: S61: Based on the current indoor usage scenario, determine the comfort control level corresponding to the comfort deviation index; S62: Trigger the air conditioning control action that matches the comfort control level according to the priority order of comfort control level and comfort parameters; S63: During the comfort control process, the air conditioning control action is dynamically adjusted based on updated multi-dimensional health parameter data until the comfort deviation index meets the preset comfort standard conditions.

[0074] In this embodiment, after obtaining the comfort deviation index, the control unit enters the comfort control phase. Comfort control is based on the currently identified indoor usage scenario, and under the condition that the air cleanliness has been stably met, further optimizes the user experience of the indoor environment. The control unit comprehensively considers deviations in temperature, humidity, air supply intensity, and fresh air volume parameters to ensure that comfort adjustments do not adversely affect the already achieved air cleanliness, thereby achieving the control objective of prioritizing cleanliness and synergistically balancing comfort.

[0075] In practice, the control unit determines the level of comfort deviation index based on the current indoor usage scenario, thus establishing the corresponding comfort control level. Subsequently, the control unit triggers air conditioning control actions matching the comfort control level according to the priority order of comfort parameters: when the comfort deviation is minor, it prioritizes small adjustments to high-priority comfort parameters; when the comfort deviation is significant, it strengthens the adjustment of high-priority parameters while simultaneously compensating for secondary comfort parameters; and in sleep mode or low-noise scenarios, it limits the airflow intensity to reduce noise and wind interference.

[0076] During comfort control, the control unit continuously updates multidimensional health parameter data according to a preset sampling period and dynamically adjusts the triggered air conditioning control actions based on the update results, forming a closed-loop adjustment mechanism. If the update results indicate that the comfort deviation index still does not meet the preset comfort standard, the adjustment action corresponding to the current comfort control level is maintained or enhanced; if the comfort deviation index meets the standard and remains stable, the adjustment intensity is gradually reduced and the current operating state is maintained, thereby achieving smooth convergence of comfort control.

[0077] Specifically, the matching range of adjustment for comfort scheduling actions is shown in Table 4: Table 4: Comfort Control Priority and Action Matching Table;

[0078] Table 4 is the comfort control priority and action matching table of this embodiment. It is used to determine the corresponding comfort control actions and their execution constraints according to the size of the comfort deviation index (CIV2), the current indoor use scenario, and the priority order of comfort parameters after the cleanliness level has been stably met.

[0079] As shown in Table 4, different indoor usage scenarios correspond to different priorities for comfort parameters. These parameters include at least temperature, humidity, air supply intensity, and fresh air volume. For example, in master bedrooms and living rooms, priority is given to controlling air supply intensity to reduce drafts and noise, followed by adjusting temperature and humidity. In children's rooms and elderly people's rooms, priority is given to maintaining humidity or temperature stability to minimize the impact of dryness or temperature fluctuations on these groups. In dining rooms, priority is given to increasing fresh air volume to address issues of occupancy and odor buildup. By setting parameter priorities based on specific scenarios, comfort adjustments can be tailored to the specific needs of different spaces.

[0080] Table 4 further divides the comfort deviation index into different numerical ranges and sets graded control actions for each range. When the comfort deviation index is in a lower range, a slight comfort adjustment action is triggered, prioritizing minor corrections to high-priority parameters, such as single-level adjustment of fan speed, minor adjustment of operating frequency, or notification of humidity status via the APP. When the comfort deviation index is in a higher range, a moderate comfort adjustment action is triggered, strengthening the adjustment of high-priority parameters while coordinating control of secondary parameters, such as further adjusting operating frequency, air supply intensity, or fresh air volume, to accelerate comfort recovery.

[0081] Furthermore, Table 4 sets specific comfort parameter constraints for different scenarios to limit the boundaries of comfort adjustments. For example, in bedroom scenarios, an upper limit is set for fan speed to control nighttime noise; in dining room scenarios, a lower limit is set for fresh air volume to ensure ventilation; and in living room scenarios, a minimum operating value is set for air supply intensity to maintain basic air circulation. By combining tiered actions with specific constraints, this invention can effectively improve the perceived environment while avoiding over-adjustment or negative impacts on the user experience when performing comfort control.

[0082] Through the comfort control priority and action matching mechanism shown in Table 4, this invention achieves refined comfort adjustment on the basis of cleanliness standards, and maps multiple comfort factors into an executable hierarchical control strategy, providing a clear and implementable basis for the dynamic adjustment of comfort control actions.

[0083] S7: During cleanliness control or comfort control, periodically update multidimensional health parameter data and dynamically adjust control strategies based on the update results.

[0084] In this embodiment, the air conditioning control unit cyclically collects and updates multidimensional health parameter data of the indoor environment at a preset sampling period during cleanliness control or comfort control. The updated data includes parameters such as temperature, humidity, PM2.5, CO2, formaldehyde, and bacteria. Each sampling result is time-stamped and its validity is verified to form a continuous parameter sequence, which is used to characterize the dynamic trend of indoor environmental changes with control actions.

[0085] Within each sampling cycle, the control unit re-evaluates compliance based on the latest updated multidimensional health parameter data and updates the corresponding conflict impact value calculation results: when in the cleanliness control stage, it updates the cleanliness deviation index and adjusts control quantities such as air supply volume, fresh air volume, and operating power accordingly; when in the comfort control stage, it updates the comfort deviation index and adjusts air supply volume, operating power, or related mode parameters accordingly. Through the above-mentioned closed-loop feedback mechanism of "acquisition-calculation-execution-reacquisition," the control action can be gradually adjusted according to environmental changes, avoiding overshoot or frequent fluctuations caused by a one-time large adjustment.

[0086] Furthermore, during dynamic adjustment, the control unit maintains or switches control phases based on the update results: when cleanliness-related parameters continuously meet the compliance conditions, switching from cleanliness control to comfort control is allowed; when cleanliness indicators are detected to exceed standards or show a deteriorating trend during comfort control, the current comfort adjustment is interrupted and cleanliness control is restored first, continuing comfort adjustment only after cleanliness meets the standards again. Through this combined strategy of periodic updates and phase switching, a dynamic control effect prioritizing cleanliness and synergistically addressing comfort is achieved, improving the stability and adaptability of ducted air conditioners in different indoor scenarios.

[0087] Please see Figure 5 This application also provides an air conditioning control system based on multi-dimensional health parameters, the system comprising: The data acquisition module is used to collect indoor multidimensional health parameter data; The threshold acquisition module is used to identify the current indoor usage scenario based on multidimensional health parameter data and obtain the health parameter threshold corresponding to the indoor usage scenario. The first calculation module is used to calculate the cleanliness deviation index based on preset weighting rules, according to multidimensional health parameter data and health parameter compliance thresholds. The cleanliness control module is used to perform cleanliness control when the cleanliness deviation index does not meet the pre-acceptance conditions, and to trigger the corresponding air conditioning control action according to the cleanliness deviation index. The second calculation module is used to calculate the comfort deviation index after detecting that the cleanliness deviation index meets the standard conditions. The comfort control module is used to perform comfort control based on the comfort deviation index and trigger corresponding air conditioning control actions. The update module is used to periodically update multidimensional health parameter data during cleanliness control or comfort control, and dynamically adjust the control strategy based on the update results.

[0088] It is understood that the content of the above method embodiments is applicable to this system embodiment. The specific functions implemented in this system embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0089] This application also provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method. This electronic device can be any smart terminal, including tablet computers, in-vehicle computers, etc.

[0090] It is understood that the content of the above method embodiments is applicable to this device embodiment. The specific functions implemented by this device embodiment are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0091] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.

[0092] It is understood that the content of the above method embodiments is applicable to this storage medium embodiment. The specific functions implemented in this storage medium embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0093] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0094] It is understood that the content of the above method embodiments is applicable to the embodiments of this program product. The specific functions implemented by the embodiments of this program product are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0095] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0096] This application provides an air conditioning control method and system based on multi-dimensional health parameters. This method collects multi-dimensional health parameter data indoors and identifies the current indoor usage scenario, obtaining health parameter compliance thresholds that match the scenario. This transforms the air conditioning control objective from traditional single-parameter control to scenario-based control oriented towards health needs. Furthermore, based on the multi-dimensional health parameter data and compliance thresholds, a cleanliness deviation index is calculated according to preset weighting rules. When compliance conditions are not met, cleanliness control is prioritized, ensuring that cleanliness indicators are met first when air quality risks are high, avoiding insufficient treatment caused by interference between different control objectives. After cleanliness is achieved, a comfort deviation index is calculated and comfort control is executed, achieving phased coordination between cleanliness and comfort, balancing health and safety with human comfort. Simultaneously, the multi-dimensional health parameter data is periodically updated and the control strategy is dynamically adjusted during the control process, enabling the system to adapt to changes in human activity and environmental disturbances in real time, reducing control lag and over-adjustment risks, and improving the health assurance capability, control stability, and overall energy efficiency of ducted household air conditioners.

[0097] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.

[0098] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0099] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0100] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0101] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. An air conditioning control method based on multidimensional health parameters, characterized in that, The method includes the following steps: Collect indoor multidimensional health parameter data; Based on the multidimensional health parameter data, calculate the cleanliness deviation index; When the cleanliness deviation index fails to meet the standard, cleanliness control is executed, and the corresponding air conditioning control action is triggered according to the cleanliness deviation index. After detecting that the cleanliness deviation index meets the compliance conditions, the comfort deviation index is calculated; Based on the comfort deviation index, comfort control is performed, triggering the corresponding air conditioning control action; During the cleanliness control or comfort control process, the multidimensional health parameter data are periodically updated, and the control strategy is dynamically adjusted based on the update results.

2. The method according to claim 1, characterized in that, The multidimensional health parameter data includes temperature parameters, humidity parameters, air cleanliness parameters, and air composition parameters.

3. The method according to claim 2, characterized in that, After collecting indoor multidimensional health parameter data, the method further includes: identifying the current indoor usage scenario based on the multidimensional health parameter data, and obtaining the health parameter compliance threshold of the multi-scenario health parameter threshold library corresponding to the indoor usage scenario; The multi-scenario health parameter threshold library includes temperature thresholds, humidity thresholds, air cleanliness thresholds, and air composition thresholds for master bedroom scene, children's room scene, elderly room scene, dining room scene, and living room scene. Based on the environmental status information of the indoor usage scenario and the multidimensional health parameter data, the health parameter compliance threshold is adaptively adjusted to generate a scenario-matched dynamic health parameter compliance threshold. The cleanliness deviation index and the comfort deviation index are calculated based on the dynamic health parameter compliance threshold.

4. The method according to claim 3, characterized in that, The step of calculating the cleanliness deviation index based on the multidimensional health parameter data includes: The validity of air cleanliness-related parameters in the multidimensional health parameter data is verified and outliers are removed to obtain a set of cleanliness calculation parameters. Based on the cleanliness calculation parameter set, the cleanliness compliance threshold corresponding to the indoor use scenario is called; Calculate the extent to which each cleanliness parameter exceeds the corresponding cleanliness compliance threshold. For parameters that do not exceed the cleanliness threshold, the corresponding exceedance range is set to zero. For parameters that exceed the cleanliness threshold, the exceedance of each cleanliness parameter is weighted and calculated according to a preset parameter weighting rule to obtain a cleanliness deviation index.

5. The method according to claim 4, characterized in that, The air conditioning control actions include adjusting the air supply volume, adjusting the fresh air volume, adjusting the sleep mode, and adjusting the operating power.

6. The method according to claim 5, characterized in that, When the cleanliness deviation index fails to meet the compliance conditions, cleanliness control is executed, and corresponding air conditioning control actions are triggered based on the cleanliness deviation index, including: Based on the current indoor usage scenario, determine the cleanliness control level corresponding to the cleanliness deviation index; Based on the cleanliness control level, trigger an air conditioning control action that matches the cleanliness control level; The air conditioning operating status is adjusted through the aforementioned air conditioning control actions; During the cleanliness control process, the multidimensional health parameter data is updated, and based on the update results, it is determined whether the cleanliness deviation index meets the compliance conditions.

7. The method according to claim 6, characterized in that, After detecting that the cleanliness deviation index meets the compliance conditions, the comfort deviation index is calculated, including: If the cleanliness deviation index continuously meets the compliance conditions, based on the current indoor usage scenario, determine the comfort parameters corresponding to the indoor usage scenario and their corresponding priority order; the comfort parameters include temperature parameters, humidity parameters, air supply intensity parameters, and fresh air volume parameters; Based on the aforementioned comfort parameters, the corresponding scenario comfort compliance thresholds are obtained, and the exceedance range of each comfort parameter relative to the corresponding comfort compliance threshold is calculated. For comfort parameters that do not exceed the aforementioned comfort threshold, the corresponding exceedance range is set to zero. Based on the priority order of the comfort parameters and a preset comfort weighting rule, the excess range of each comfort parameter is weighted and fused to obtain the comfort deviation index.

8. The method according to claim 7, characterized in that, The compliance conditions include: Within a preset sampling period, the cleanliness deviation index is calculated to be zero in multiple consecutive sampling periods, and the air cleanliness parameter used to calculate the cleanliness deviation index simultaneously meets the cleanliness compliance threshold corresponding to the current indoor use scenario. The air cleanliness parameters include PM2.5 concentration, carbon dioxide concentration, formaldehyde concentration, and bacteria concentration, and the continuous multiple sampling cycles are no less than three consecutive sampling cycles.

9. The method according to claim 8, characterized in that, The step of performing comfort control based on the comfort deviation index and triggering corresponding air conditioning control actions includes: Based on the current indoor usage scenario, determine the comfort control level corresponding to the comfort deviation index; Based on the priority order of the comfort control level and comfort parameters, trigger the air conditioning control action that matches the comfort control level; During the comfort control process, the air conditioning control action is dynamically adjusted based on the updated multidimensional health parameter data until the comfort deviation index meets the preset comfort standard conditions.

10. An air conditioning control system based on multidimensional health parameters, characterized in that, The system includes: The data acquisition module is used to collect indoor multidimensional health parameter data; The threshold acquisition module is used to identify the current indoor usage scenario based on the multidimensional health parameter data, and to acquire the health parameter threshold corresponding to the indoor usage scenario. The first calculation module is used to calculate the cleanliness deviation index based on the multidimensional health parameter data and the health parameter compliance threshold, according to a preset weighting rule. The cleanliness control module is used to perform cleanliness control when the cleanliness deviation index does not meet the compliance conditions, and to trigger the corresponding air conditioning control action according to the cleanliness deviation index. The second calculation module is used to calculate the comfort deviation index after detecting that the cleanliness deviation index meets the standard conditions. The comfort control module is used to perform comfort control based on the comfort deviation index and trigger corresponding air conditioning control actions. The update module is used to periodically update the multidimensional health parameter data during the cleanliness control or comfort control process, and dynamically adjust the control strategy based on the update results.

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