Building decoration air purification quality evaluation system based on artificial intelligence

Abstract

The invention discloses a building decoration air purification quality evaluation system based on artificial intelligence, and relates to the technical field of air purification quality evaluation. The method comprises the following steps: a basic standard module for acquiring a basic purpose of building decoration and searching to obtain a corresponding basic air standard; the basic judgment module is used for acquiring purified air data and judging whether the purified air data reaches a basic air standard or not; if the basic air standard is met, the first quality module is used for obtaining the health requirement of the user and analyzing to obtain the first quality of air purification; the second quality module is used for obtaining external air data of the building, analyzing the interference degree of the purified air data to the user and obtaining the second quality of air purification according to the interference degree; and the purification quality module comprehensively obtains the evaluation quality of building decoration air purification and sends the evaluation quality to the user side. The adaptability of building decoration air purification quality evaluation based on artificial intelligence is improved.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of air purification quality evaluation, in particular to an air purification quality evaluation system for building decoration based on artificial intelligence. BACKGROUND

[0002] The air purification quality of building decoration refers to an index for quantitatively evaluating the concentration, types and influence on human health and environment of pollutants in indoor air after decoration through technical means. The advantage of evaluating the air purification quality of building decoration is that hidden pollution hazards can be found in advance through real-time monitoring and data analysis, and health damage caused by user occupancy can be avoided. For air purification of building decoration, the air quality decline caused by building decoration is relatively long-term, so even after occupancy, the air after building decoration will be purified for a long time. Purification quality evaluation of the air of building decoration is beneficial to real-time adjustment of air purification standards and provides a comfortable environment for users. However, the existing air purification quality evaluation generally sets a standard, but due to individual differences, the air purification quality cannot be accurately quantitatively evaluated by the uniformly formulated standard, and the user is not suitable. SUMMARY

[0003] The purpose of the present application is to provide an air purification quality evaluation system for building decoration based on artificial intelligence to solve the problems in the background art.

[0004] The air purification quality evaluation system for building decoration based on artificial intelligence provided by the present application adopts the following technical solution:

[0005] A basic standard module acquires the basic purpose of building decoration, and finds the corresponding air standard as a basic air standard according to the basic purpose;

[0006] A basic judgment module acquires purification air data, and judges whether the basic air standard is reached according to the purification air data;

[0007] A first quality module acquires user health needs if the basic air standard is reached, and analyzes the first quality of air purification according to the user health needs and the purification air data;

[0008] A second quality module acquires external air data of the building, analyzes the interference degree of the purification air data to the user according to the external air data and the purification air data, and obtains the second quality of air purification according to the interference degree;

[0009] A purification quality module combines the first quality and the second quality to obtain the evaluation quality of air purification of building decoration, and sends the evaluation quality to the user end.

[0010] Preferably, if the base air standard is reached, the step of obtaining the user health demand, and analyzing the first quality of air purification according to the user health demand and the purified air data, specifically comprises:

[0011] Obtaining the user health demand information, and generating the user air standard according to the user health demand information;

[0012] Comparing the purified air data with the user air standard, and judging whether the purified air data reaches the user air standard;

[0013] If the purified air data does not reach the user air standard, extracting the air factor in the user air standard, and evaluating the first quality of air purification according to the air factor;

[0014] If the purified air data reaches the user air standard, the first quality of air purification is the maximum value.

[0015] Preferably, the step of extracting the air factor in the user air standard, and evaluating the first quality of air purification according to the air factor if the purified air data does not reach the user air standard, specifically comprises:

[0016] Screening the air factor in the purified air data that does not reach the user air standard as a pollution factor;

[0017] Extracting the health information related to the air quality of the user according to the user health demand information, and recording the health information as air health information;

[0018] Finding the importance of the pollution factor affecting the air health information of the user, and obtaining the importance of the pollution factor affecting the basic physical health of the user if the pollution factor does not affect the air health information of the user;

[0019] Calculating the difference between the pollution factor and the air factor in the corresponding user air standard, and combining the importance to obtain the factor quality of the pollution factor;

[0020] Summing up the factor quality of all pollution factors to obtain the first quality of air purification.

[0021] Preferably, the step of obtaining the external air data of the building, analyzing the interference degree of the purified air data to the user according to the external air data and the purified air data, and obtaining the second quality of air purification according to the interference degree, specifically comprises:

[0022] Obtaining the personal information of the user, and analyzing the sensitivity of the user to the air according to the personal information of the user;

[0023] Analyzing the interference degree of air purification according to the purified air data and the sensitivity;

[0024] obtaining external air data of the building, and analyzing the external air data and the purified air data to obtain a fitness of the user to the external air;

[0025] combining the interference degree and the fitness to obtain a second quality of air purification.

[0026] Preferably, the step of obtaining the personal information of the user and analyzing the sensitivity of the user to the air based on the personal information of the user comprises:

[0027] extracting factors affecting the sensory perception of the user in the air as sensory air factors;

[0028] obtaining the personal information of the user, and extracting daily behavior characteristics of the user based on the personal information of the user;

[0029] extracting a change value of the sensory air factor when the user deviates from the daily behavior characteristics based on the personal information of the user;

[0030] calculating the reciprocal of the average of all change values of the sensory air factor as the sensitivity of the user to the air.

[0031] Preferably, the step of analyzing the interference degree of air purification based on the purified air data and the sensitivity comprises:

[0032] collecting historical purification data, and analyzing a first interference degree of air purification based on the historical purification data and the sensitivity;

[0033] extracting a real-time value of the sensory air factor when the user deviates from the daily behavior characteristics based on the personal information of the user;

[0034] selecting the smallest real-time value of the sensory air factor from the real-time values of the sensory air factor as a minimum value of the sensory air factor;

[0035] forming a user sensitivity standard based on all minimum values of the sensory air factor and a basic air standard;

[0036] determining whether the purified air data reaches the user sensitivity standard, and if not, extracting a real-time sensory air factor value based on the purified air data;

[0037] summing up all differences between the real-time sensory air factor values and the minimum value of the sensory air factor as a second interference degree of air purification;

[0038] superimposing the first interference degree and the second interference degree to obtain the interference degree of air purification.

[0039] Preferably, the step of collecting the historical purification data and analyzing the first interference degree of air purification based on the historical purification data and the sensitivity comprises:

[0040] According to the historical purification data, average similarity of the purified air at different time is extracted;

[0041] The first interference degree of the air purification is obtained by combining the average similarity and the sensitivity analysis.

[0042] Preferably, the step of obtaining the external air data of the building and analyzing the adaptability of the user to the external air according to the external air data and the purified air data comprises:

[0043] The external air data of the building is obtained, and similarity between the purified air data and the external air data is obtained by comparison and recorded as air similarity;

[0044] It is judged whether the similarity reaches a preset similarity threshold value, and if the preset similarity threshold value is not reached, the average duration of the user in the building is extracted according to the personal information of the user;

[0045] It is judged whether the purified air affects the adaptability of the user to the external air according to the average duration;

[0046] If the purified air affects the adaptability of the user to the external air, the tolerance interference degree of the purified air to the user is evaluated according to the personal information of the user;

[0047] The adaptability of the user to the external air is evaluated according to the air similarity and the tolerance interference degree.

[0048] Preferably, the step of evaluating the tolerance interference degree of the purified air to the user according to the personal information of the user if the purified air affects the adaptability of the user to the external air comprises:

[0049] The age of the user is extracted according to the personal information of the user, and it is judged whether the age of the user meets the demand standard of the air quality;

[0050] The environmental exposure degree after the building is decorated is obtained, and real-time purification data is estimated according to the environmental exposure degree;

[0051] The similarity between the real-time purification data and the demand standard is obtained by comparison and recorded as demand similarity;

[0052] The tolerance interference degree of the purified air to the user is obtained by combining the demand similarity and the average duration of the user in the building.

[0053] Preferably, the step of obtaining the environmental exposure degree after the building is decorated comprises:

[0054] The house type structure of the building is obtained, ventilation information is extracted, and the ventilation efficiency of the building is counted according to the ventilation information;

[0055] The average ventilation volume of the building per day is counted according to the ventilation information;

[0056] According to the average ventilation volume and ventilation efficiency analysis, the environmental exposure degree after building decoration is obtained.

[0057] In summary, the present application includes at least one of the following beneficial technical effects:

[0058] 1. According to the basis use of building decoration, the corresponding air standard is found as the basis air standard. After the building decoration purifies the air to reach the basis air standard, according to the health demand information of the user, it is evaluated whether the purified air reaches the user's demand standard. If it does not reach the user's demand standard, the first quality of the purified air is evaluated according to the health influence degree of the purified air on the user. The second quality of the purified air is further evaluated by combining the interference degree of the purified air data to the user brought by the analysis of the external air data and the purified air data. The building decoration air purification quality is obtained and sent to the user end. According to the actual demand of the user, the building decoration air purification quality is evaluated, which is helpful to obtain the air purification quality evaluation result that is more suitable for the actual situation of the user, and improves the adaptability of the building decoration air purification quality evaluation based on artificial intelligence.

[0059] 2. According to the personal information of the user, the sensitivity of the user to the air factor affecting the sensory feeling in the air is evaluated. According to the purified air and the sensitivity, the interference degree of the purified air to the daily life of the user is analyzed, and the interference degree of the air purification is confirmed. The second quality of the building decoration purified air is comprehensively evaluated by combining the adaptability of the user to the external air influenced by the purified air analyzed according to the external air data. The interference degree of the purified air to the user is analyzed, so as to evaluate the quality of the purified air, which is helpful to reduce the interference of the purified air to the user, and improves the comfort of the building decoration air purification quality evaluation based on artificial intelligence.

[0060] 3. According to the average ventilation volume and ventilation efficiency analysis, the environmental exposure degree after building decoration is obtained. According to the similarity between the demand standard of air quality obtained according to the user's age and the purified air data, the actual similarity of the purified air and the demand standard is confirmed, and then the adaptability of the user to the external air quality caused by the purified air is comprehensively obtained according to the average time of the user in the building. By analyzing and evaluating the adaptability of the user to the external air caused by the purified air, the additional inconvenience of the purified air to the user can be effectively reduced, the life of the user outside the building is covered, and the comprehensiveness of the building decoration air purification quality evaluation based on artificial intelligence is improved. BRIEF DESCRIPTION OF DRAWINGS

[0061] Figure 1 It is a module connection schematic diagram of an embodiment of the building decoration air purification quality evaluation system based on artificial intelligence. DETAILED DESCRIPTION

[0062] The following embodiments andFigure 1 The application will be further described in detail, but the embodiments of the application are not limited thereto.

[0063] The application discloses an air purification quality evaluation system for building decoration based on artificial intelligence, and specifically comprises:

[0064] The basic standard module obtains the basic use of building decoration, and finds the corresponding air standard as the basic air standard according to the basic use.

[0065] The basic use of building decoration is different, and the corresponding air standard is significantly different. For example, in civil building engineering, the limit value requirements for indoor pollutant concentration of residential buildings, hospital wards, kindergartens and other type I buildings are more stringent, according to the Indoor Environmental Pollution Control Standard for Civil Building Engineering GB 50325-2020, the limit value of formaldehyde concentration is 0.07 mg / m³, and the limit value of type II buildings (such as office buildings, shops and hotels) is relaxed to 0.08 mg / m³. This difference is due to the particularity of the population using type I buildings (such as children, patients and the elderly), whose immune systems are more fragile and need to avoid the cumulative risk of long-term exposure to low-concentration pollutants. Taking schools as an example, the Indoor Air Quality Requirements for Primary and Secondary Schools DB43 / T 1646 further stipulates that the formaldehyde limit value in classrooms should be controlled below 0.08 mg / m³. According to various standards of air quality requirements, the basic use of building decoration can be classified to obtain the corresponding specified standard as the basic air standard.

[0066] The basic judgment module obtains the purification air data and judges whether the basic air standard is reached according to the purification air data.

[0067] The air standard is not only limited to the concentration of formaldehyde, but also clearly specifies the concentration of benzene series, ammonia, radioactive gas radon, and PM2.5, ozone and other indicators. The index values in the purification air data are extracted to find out whether the index values are within the specified standard. If it is within the specified standard, it is considered to reach the basic air standard. If it is not within the specified standard, it is considered not to reach the basic air standard. If the basic air standard is not reached, the difference between the purification air data and the basic air standard for each index is calculated, and the normalized sum of the difference of each index is added to obtain the evaluation quality of the building decoration purification air, which is less than the evaluation quality of the purification air that reaches the basic air standard.

[0068] The first quality module obtains the user health demand if the basic air standard is reached, and analyzes the first quality of air purification according to the user health demand and the purification air data.

[0069] The second quality module obtains external air data of the building, analyzes an interference degree brought by the purified air data to the user according to the external air data and the purified air data, and obtains a second quality of air purification according to the interference degree.

[0070] The purification quality module combines the first quality and the second quality to obtain an evaluation quality of air purification of the building decoration, and sends the evaluation quality to the user end.

[0071] After the first quality and the second quality are normalized, an average value of the first quality and the second quality is calculated, and the average value is taken as the evaluation quality of air purification of the building decoration.

[0072] In actual application, the existing air quality evaluation system sets a threshold value based on a unified standard, and it is difficult to cover the sensitivity difference of different groups of people to pollutants, resulting in a significant deviation in the health risk perception of the same air quality data in different groups. Taking North China as an example, standardized monitoring data shows that when the PM2.5 concentration is reduced to 50 micrograms per cubic meter in the non-heating period, the satisfaction of ordinary residents is 8.7 points (full score is 10 points), and rhinitis patients will still have mucous membrane irritation symptoms at this concentration. The reason is that the nasal ciliary clearance function is impaired, and the defense ability of PM2.5 with a diameter less than 1 micrometer (such as black carbon nucleus) is only 37% of that of normal people. When the indoor TVOC concentration reaches 200 micrograms per cubic meter (in line with the GB50325 standard limit), the healthy population has no obvious discomfort, but the bronchial constriction response rate of asthma patients increases by 42%. Even if the air quality is the same, the air quality is good for ordinary users, and the air quality is poor for rhinitis patients. If the evaluation is made according to the evaluation standard of ordinary users, the air quality evaluation result received by rhinitis patients is not accurate and not suitable for rhinitis patients. At the same time, the existing purified air quality evaluation often only judges according to the numerical value of each index in the air, and does not consider the discomfort brought by the air to the user. The index is too single, which reflects the limitation of the purified air quality evaluation, and therefore brings the inaccurate evaluation result. According to the user's health needs and the interference of the purified air to the user, the purified air quality evaluation result is more comprehensive and accurate, and is more suitable for the user.

[0073] If the basic air standard is reached, the user's health needs are obtained, and the first quality of air purification is obtained according to the user's health needs and the purified air data, specifically as follows:

[0074] User health demand information is obtained, and user air standards are generated according to the user health demand information.

[0075] The health levels of different users are different, so the demand standards for air are also different. Through the user health demand information that the user has authorized, the corresponding user air standard is found, and the user health demand information includes the user's disease history, pregnancy information, etc. Taking chronic respiratory disease patients as an example, the sterilization efficiency needs to be improved to 99.9%, and the PM2.5 concentration is maintained ≤10 micrograms / cubic meter, and the humidity is adjusted to 50%-55% to relieve the mucous membrane dryness. This standard far exceeds the national standard limit (PM2.5≤75 micrograms / cubic meter) of ordinary residential. For users with allergic constitution, the PM2.5 purification efficiency reaches 99.9%, and the pollen concentration is controlled below 5 micrograms / cubic meter. If the user is not ill, a user air standard can be generated according to the user's basic physical health, for example, the basic standard stipulates that PM2.5 is less than ≤75 micrograms / cubic meter, but under this standard, it still damages the user's physical health, and then the user air standard can be further set to PM2.5 less than ≤30 micrograms / cubic meter.

[0076] By comparing the purified air data and the user air standard, it is judged whether the purified air data meets the user air standard.

[0077] The judgment mode of judging whether the purified air data meets the basic air standard can be applied for judgment.

[0078] If the purified air data does not meet the user air standard, the air factor in the user air standard is extracted, and the first quality of air purification is evaluated according to the air factor.

[0079] If the purified air data meets the user air standard, the first quality of air purification is evaluated as the maximum value.

[0080] In actual application, when the purified air meets the basic standard, it can only be said that the purified air meets the general needs of ordinary users, but for some special groups, such as patients with rhinitis and asthma, meeting the basic standard does not mean meeting the user's demand. If the user's demand is not met, the purified air will still interfere with the user, and the air purification quality is still poor for the user. For example, the pollen concentration within the standard does not affect ordinary users, but for pollen-allergic patients, the higher the pollen concentration, the higher the probability of allergy. Therefore, for pollen-allergic users, the pollen concentration in the user air standard should be lower than that in the basic air standard. If the purified air data meets the user air standard, it means that the user's health demand has been met, and the first quality is the maximum value.

[0081] If the purified air data does not meet the user air standard, the air factor in the user air standard is extracted, and the first quality of air purification is evaluated according to the air factor. The specific steps are as follows:

[0082] The air factor that does not reach the user air standard in the purified air data is recorded as a pollution factor.

[0083] According to the user health demand information, health information associated with air quality is extracted and recorded as air health information.

[0084] Since the health levels of different users are different, some respiratory diseases are related to air quality, and when the air quality is poor, it is more likely to relapse or worsen. According to the disease history in the user health demand information, the disease information associated with air quality can be found.

[0085] The importance of the pollution factor affecting the user's air health information is found out. If the pollution factor does not affect the user's air health information, the importance of the pollution factor affecting the user's basic physical health is obtained.

[0086] The health effects of specific components in air pollution on different disease patients are significantly different, and their mechanisms often have synergistic effects with the pathological characteristics of the disease itself. For example, for patients with chronic obstructive pulmonary disease (COPD), research shows that when PM2.5 concentration increases by 10 micrograms per cubic meter, the risk of hospitalization will increase by 3.1% within 0-5 days, while PM10 concentration with the same increase will lead to a 2.4% increase in hospitalization rate. For diabetic patients, long-term exposure to PM2.5 can damage the mitochondrial function of pancreatic beta cells, reducing insulin secretion by 32%, while persistent organic pollutants in particulate matter can interfere with the PPARγ signaling pathway, exacerbating insulin resistance. According to the influence degree of pollution factors on diseases, the importance can be divided into importance levels, which can be matched by setting importance levels, or the probability of disease recurrence caused by the increase of one unit of pollution factor can be used as the importance. If the user does not have a disease, there is no health information associated with air quality, and the importance of pollution factors to basic physical health is evaluated. Some substances in the air can still affect the user's physical health even if they meet the basic air standards, so even if the user does not have an air-related disease, their basic physical health will still be affected by the purified air. For example, even if the formaldehyde concentration is controlled within the 0.08mg / m³ limit of Class I buildings, the adduct formed by its combination with human glutathione can still inhibit superoxide dismutase activity, causing a 9.3% decrease in the antioxidant capacity of healthy red blood cells and accelerating the cell aging process.

[0087] The difference between the pollution factor and the air factor in the corresponding user air standard is calculated, and the importance is combined to obtain the factor quality of the pollution factor.

[0088] The reciprocal of the product of the difference and the importance is taken as the factor quality.

[0089] The sum of the factor qualities of all pollution factors is summed up to obtain the first quality of air purification.

[0090] In actual application, even if the purified air quality meets the basic air standard, it does not mean that the air quality has no damage to the human body. For some users with air-related diseases, because their demand for air quality is more stringent, some factors in the air can still cause the disease to relapse or worsen. For ordinary users who are not ill, some air factors can still affect the basic physical health of the user, for example, taking PM2.5 as an example, when the concentration is at the national standard limit of 35 micrograms per cubic meter, the polycyclic aromatic hydrocarbons it carries can still enter the blood circulation through the alveoli, activate mononuclear cells to release IL-6 and other inflammatory factors, and cause the average increase of C-reactive protein level in healthy people by 12.7%. This systemic inflammatory response will accelerate the oxidative damage of vascular endothelial cells. At the limit of 8-hour average concentration of 160 micrograms per cubic meter, ozone will react with antioxidants in the respiratory tract surface fluid to generate free radicals, inhibit the phagocytic function of alveolar macrophages, and reduce the efficiency of healthy people's lung clearance of pathogens by 18.4%. This weakening of the immune barrier may increase the susceptibility to seasonal influenza.

[0091] Obtaining external air data of the building, analyzing the interference degree brought by the purified air data to the user according to the external air data and the purified air data, and obtaining the second quality of air purification according to the interference degree, specifically comprising:

[0092] Obtaining user personal information, and analyzing the sensitivity of the user to air according to the user personal information.

[0093] The user personal information includes user-authorized behavior, age and other personal basic information.

[0094] Obtaining the interference degree of air purification according to the purified air data and the sensitivity.

[0095] Obtaining the adaptability of the user to the external air according to the external air data and the purified air data.

[0096] Combining the interference degree and the adaptability to comprehensively obtain the second quality of air purification.

[0097] In practice, weights are set for interference and adaptability, and the second quality of purified air is calculated based on these weights. For example, if the weights for interference and adaptability are set to 40% and 60%, respectively, and the interference and adaptability are 50 and 40, respectively, then the second quality of purified air is 40 × 60% - 50 × 40% = 4. Purified air quality not only affects users' health but also disrupts their daily lives. Humidity and odors in purified air can cause discomfort within the building environment and disrupt their daily lives. Therefore, a greater level of interference indicates poorer purified air quality. Furthermore, since air quality inside and outside buildings differs, and users generally do not stay inside for extended periods, a significant difference between the purified air and the outside air can easily lead to users being unable to adapt to the outside air, further impacting their health. When the level of indoor air purification differs significantly from that of the external environment, the human body's adaptive mechanisms may lower its tolerance threshold for external pollutants. For example, residents who are exposed to ultra-low PM2.5 levels (e.g., below 10 micrograms per cubic meter) using high-efficiency HEPA filters for extended periods will experience a gradual weakening of their respiratory mucociliary clearance function. In this situation, the nasal mucosa, lacking the stimulation of particulate matter for a long time, cannot produce sufficient mucus in a timely manner. This makes it easier for pollutants to penetrate the respiratory barrier, triggering severe coughing and bronchospasm. This makes it difficult for users to adapt to the air environment outside the building, which can have an impact on their health. Therefore, a greater degree of adaptation indicates better purification quality.

[0098] The steps for obtaining user personal information and analyzing the user's sensitivity to air based on the user personal information are as follows:

[0099] Factors in the air that affect the user's sensory experience are extracted as sensory air factors.

[0100] Sensory air factors in the air refer to substances that directly trigger olfactory, tactile, or stimulant responses through the human sensory system. For example, when the indoor concentration of formaldehyde reaches 0.08 mg / m³ (which meets the standards for Class I buildings), its pungent odor activates the TRPA1 ion channel in the nasal trigeminal nerve endings, causing burning eyes and nasal stinging in 48% of healthy people. Similarly, air humidity can also cause some disturbances to users.

[0101] Obtain user personal information and extract user daily behavior characteristics based on the user personal information.

[0102] Through the behaviors in the user's personal information, repeated behaviors and activity trajectories are extracted as daily behavior features.

[0103] The sensory air factor change value when the user violates the daily behavior characteristics is extracted based on the user's personal information.

[0104] The difference between the real-time value of the sensory air factor when the user violates the daily behavior characteristics each time and the last detected value is taken as the sensory air factor change value. For example, the user suddenly performs a nose-covering action, the real-time formaldehyde concentration is 0.08 mg / m3, and the last detected real-time formaldehyde concentration is 0.05 mg / m3, and the formaldehyde factor change value is 0.03 mg / m3. When it is detected that the user violates the daily behavior characteristics, it means that the user may feel uncomfortable due to the purified air.

[0105] The reciprocal of the average value of all sensory air factor change values is calculated as the user's sensitivity to air.

[0106] In actual application, when the user violates the daily behavior characteristics, it may be due to the discomfort caused by the purified air, or it may be caused by other reasons, so the abnormal values in all sensory factor change values are removed, and the average value of the remaining sensory factor change values is calculated as the user's sensitivity to air. The abnormal value can be the maximum value and the minimum value, or an abnormal value range can be set to filter out the sensory factor change values within the abnormal value range. The smaller the sensory factor change value, the higher the user's sensitivity to air, because it means that the user can feel the small air changes. Analyzing the user's sensitivity to air is beneficial to analyzing the interference degree of the purified air to the user.

[0107] According to the purified air data and the sensitivity analysis, the interference degree of the air purification is obtained. The steps are as follows:

[0108] Collect historical purification data, and analyze the first interference degree of air purification according to the historical purification data and the sensitivity.

[0109] According to the user's personal information, the real-time value of the sensory air factor when the user violates the daily behavior characteristics is extracted.

[0110] The smallest real-time value of the sensory air factor is selected from the real-time value of the sensory air factor as the minimum value of the sensory air factor.

[0111] The user's sensitive standard is formed according to all the minimum values of the sensory air factor and the basic air standard.

[0112] The value standard of the sensory air factor in the basic air standard is replaced by the minimum value of the sensory air factor, and the remaining non-sensory air factors do not need to be changed, forming a new user's sensitive standard.

[0113] It is judged whether the purified air data reaches the user's sensitive standard. If it does not reach the user's sensitive standard, the real-time sensory air factor value is extracted according to the purified air data.

[0114] If the user's sensitive standard is reached, the second interference degree is the minimum value.

[0115] The sum of the differences between the real-time sensory air factor values and the minimum value of the sensory air factor is taken as the second interference degree of air purification.

[0116] When the user sensitivity criterion is not met, the greater the difference between the real-time sensory air factor value and the minimum value of the sensory air factor, the greater the degree of interference to the user. After normalization processing of the differences between all real-time sensory air factor values and the minimum value of the sensory air factor, the sum of all the differences is taken as the second interference degree.

[0117] The first interference degree and the second interference degree are superimposed to obtain the interference degree of air purification.

[0118] In actual application, different users have different sensitivities to purified air, and thus the minimum value of the interference of the purified air to the user's life is different. Some users can feel the concentration of 0.05 mg / m³ of formaldehyde, and some users cannot feel it. For the users who can feel it, the concentration of 0.05 mg / m³ of formaldehyde still interferes with their life and makes them feel uncomfortable. However, for the users who cannot feel it, the concentration of formaldehyde does not affect their life and they do not feel uncomfortable. At the same time, the users have a higher difference sensitivity to the change of the purified air, and the interference degree of the purified air to the user's life is greater.

[0119] The first interference degree of air purification is obtained by collecting historical purification data and analyzing the historical purification data and the sensitivity, and the steps are as follows:

[0120] The average similarity of the purified air at different times is obtained by extracting the historical purification data.

[0121] The first interference degree of air purification is obtained by combining the average similarity and the sensitivity.

[0122] In actual application, the linear regression formula of the average similarity, the sensitivity, and the first interference degree is obtained by simulation through a linear regression model, and the first interference degree is calculated according to the formula. Different users have different sensitivities to the change of the purified air, and when the purified air changes, some users who are sensitive to air will quickly perceive the change of the air and have an uncomfortable reaction. Therefore, for such users, the greater the fluctuation of the purified air, the more likely it is to interfere with the user. The greater the average similarity, the smaller the fluctuation of the purified air, and the smaller the first interference degree. The greater the user sensitivity, the stronger the user's ability to perceive subtle changes in the air, and the greater the first interference degree of the change of the purified air to the user. For example, when the indoor carbon dioxide concentration suddenly increases from 500 ppm to 3000 ppm, the nasal mucosa cilia of allergic patients will reduce by 42%, and this physiological sensitization will increase the sneezing frequency by 3 times.

[0123] Obtaining external air data of the building, and analyzing the user's adaptability to the external air according to the external air data and the purified air data, specifically:

[0124] Obtaining external air data of the building, and comparing to obtain similarity between the purified air data and the external air data, and recording as air similarity.

[0125] The air similarity can be analyzed by the existing cosine similarity model, and all similarity calculations in this application can be obtained by the cosine similarity model.

[0126] Judging whether the similarity reaches a preset similarity threshold, if not, extracting the average duration of the user in the building according to the user's personal information.

[0127] When the preset similarity threshold is reached, it means that the internal and external air of the building is similar, and the user will hardly have additional discomfort to the air due to the difference between the internal and external air.

[0128] According to the average duration, judging whether the purified air affects the user's adaptability to the external air.

[0129] The average duration of long-term use of air purification equipment and the user's adaptability to the external air show significant correlation, and this correlation is manifested through the improvement of physiological regulation mechanism. Taking a city resident as an example, after using a HEPA filter air purifier for more than 180 days (daily average running time of 12 hours), the nasal mucosa cilia oscillation frequency of the resident is reduced by 27% compared with that of a person living in a naturally ventilated environment, resulting in a 40% increase in bronchial constriction reaction intensity and a 2.3 times extension of the duration compared with ordinary residents when exposed to an outdoor PM2.5 concentration of 150 micrograms per cubic meter (complying with the light pollution standard). That is, when the user stays in the building for a long time, it is more likely to be affected by the purified air. For example, the building is used for storing goods, and the average duration of the user in the building is not more than 30 minutes per day, so it is difficult for the purified air to affect the user, and it is judged that it does not affect the user's adaptability to the external air. Set an average duration threshold, and judge whether the purified air affects the user's adaptability to the external air by comparing whether the average duration reaches the average duration threshold.

[0130] If the purified air affects the user's adaptability to the external air, then according to the user's personal information, the tolerance interference degree of the purified air to the user is evaluated.

[0131] According to the air similarity and the tolerance interference degree, the user's adaptability to the external air is evaluated.

[0132] In actual application, the calculation formula (such as fitness = a x air similarity - b x interference tolerance) is simulated by addition or multiplication operation, and the fitness of the user to the external air is calculated according to the formula. The fitness of the user to the external air of the building is on the one hand from the similarity of the purified air and the external air. When the air similarity is greater, because the difference between the two is smaller, the fitness of the user to the external air is greater. When the interference tolerance is greater, it means that the purified air has greater interference on the air tolerance of the user, and therefore the fitness is smaller.

[0133] If the purified air affects the fitness of the user to the external air, the step of evaluating the interference tolerance of the purified air to the user according to the personal information of the user is as follows:

[0134] According to the personal information of the user, the age of the user is extracted, and the demand standard of the user to the air quality is judged according to the age of the user.

[0135] Studies have shown that if an adult stays in an ultra-clean environment with PM2.5<10 micrograms / cubic meter for more than 16 hours a day for 3 months, the nasal mucosa IgE (key antibody of allergic reaction) level will increase by 30%. This may cause the reaction threshold to common allergens such as pollen and dust mites to decrease, and the risk of allergy to first contact to increase. The immune system of children needs to be moderately exposed to allergens to establish a tolerance balance during the age of 3-6 years old. Studies have shown that at least 2 hours of outdoor environment containing pollen or dust mites every day can reduce the incidence of allergy by 40%. However, children who are in a HEPA filter purification environment (PM2.5<10 micrograms / cubic meter) for a long time have an allergy incidence rate 1.8 times that of ordinary children. Therefore, the demand standard of the user to the air quality is different at different ages. For children, excessive purified air is not a good thing. That is, it is not that the lower the content of some indicators in the air is, the better. The user needs to be properly exposed to allergens to establish a tolerance balance. Therefore, the air quality standard that the user needs to be exposed to can be set as the demand standard according to the age of the user.

[0136] The environmental exposure after the building decoration is obtained, and the real-time purification data is obtained according to the environmental exposure.

[0137] Because ventilation means is usually provided in the building, and different ventilation conditions will cause the environmental exposure of the building to be different, thereby affecting the purified air data. The change value of each indicator in the purified air data is obtained by estimating the environmental exposure, and the real-time purification data after ventilation is obtained according to the change value.

[0138] The similarity between the real-time purification data and the demand standard is obtained and recorded as the demand similarity.

[0139] The demand similarity can be analyzed by the existing similarity model, such as cosine similarity.

[0140] The tolerance interference degree of the purified air to the user is obtained in combination with the demand similarity and the average duration of the user in the building.

[0141] In actual application, a linear regression formula of the tolerance interference degree is simulated by a linear regression model, and the tolerance interference degree is calculated according to the formula. When the demand similarity is greater, the tolerance interference of the purified air to the user is smaller, and thus the tolerance interference degree is smaller. When the average duration of the user in the building is longer, the user stays in the purified air for a longer time, is more easily interfered by the purified air, and thus the tolerance interference degree is greater.

[0142] The step of obtaining the environmental exposure degree of the building after decoration is specifically:

[0143] The house type structure of the building is obtained, ventilation information is extracted, and the ventilation efficiency of the building is obtained according to the ventilation information.

[0144] The ventilation information includes ventilation duration, ventilation opening area and other information. The ventilation efficiency is a core index for measuring the ability of the ventilation system to effectively replace air and remove pollutants, and is usually defined as the ratio of the actual air volume for diluting pollutants to the total air volume, or is calculated by the difference in pollutant concentration distribution.

[0145] The average ventilation volume of the building after decoration is obtained according to the ventilation information.

[0146] The window opening area and the air change frequency of the naturally ventilated room need to be calculated, and the efficiency of the mechanical ventilation system needs to be evaluated.

[0147] The environmental exposure degree of the building after decoration is obtained according to the average ventilation volume and the ventilation efficiency.

[0148] In actual application, an equation formula can be established by using a linear regression model, and the environmental exposure degree is calculated according to the equation formula. When the average ventilation volume and the ventilation efficiency are greater, the environmental exposure degree is greater.

[0149] The above are preferred embodiments of the present application, and are not intended to limit the protection scope of the present application, so that: any equivalent changes made according to the structure, shape, principle of the present application should be covered within the protection scope of the present application.

Claims

1. An artificial intelligence-based building decoration air purification quality assessment system, characterized by: include: The basic standard module obtains the basic purpose of building decoration and finds the corresponding air standard based on the basic purpose as the basic air standard; The basic judgment module obtains the purified air data and determines whether the basic air quality standards are met based on the purified air data; The first quality module, if the basic air quality standard is met, obtains the user's health needs, and obtains the first quality of air purification based on the user's health needs and the purified air data analysis; The second quality module obtains the external air data of the building, analyzes the interference degree caused by the purified air data to the user based on the external air data and the purified air data, and obtains the second quality of the air purification according to the interference degree; The purification quality module combines the first quality and the second quality to obtain the evaluation quality of the building decoration air purification and sends it to the user end.

2. The building decoration air purification quality assessment system based on artificial intelligence according to claim 1 is characterized in that: If the basic air quality standard is met, the steps of obtaining the user's health needs and obtaining the first quality of air purification based on the user's health needs and the purified air data analysis are specifically as follows: Obtain user health demand information and generate user air quality standards based on the user health demand information; Compare the purified air data with the user's air standards to determine whether the purified air data meets the user's air standards; If the purified air data does not meet the user's air standard, the air factor in the user's air standard is extracted, and the first quality of air purification is obtained based on the air factor evaluation; If the purified air data reaches the user's air standard, the first quality of air purification is evaluated to be the maximum value.

3. The building decoration air purification quality assessment system based on artificial intelligence according to claim 2 is characterized in that: If the purified air data does not meet the user's air standard, the step of extracting the air factor in the user's air standard and evaluating the first quality of the air purification according to the air factor is specifically as follows: The air factors that do not meet the user's air standards in the filtered purified air data are recorded as pollution factors; Extracting the user's health information related to air quality based on the user's health demand information and recording it as air health information; Find the importance of the pollution factor in affecting the user's air health information. If the pollution factor does not affect the user's air health information, then obtain the importance of the pollution factor in affecting the user's basic physical health; Calculate the difference between the pollution factor and the air factor in the corresponding user air standard, and combine the importance to obtain the factor quality of the pollution factor; The factor masses of all pollution factors are summed to obtain the first mass of air purification.

4. The building decoration air purification quality assessment system based on artificial intelligence according to claim 1 is characterized in that: The steps of obtaining the external air data of the building, analyzing the interference degree caused by the purified air data to the user based on the external air data and the purified air data, and obtaining the second quality of air purification based on the interference degree are specifically as follows: Obtain user personal information and analyze the user's sensitivity to air based on the user's personal information; The interference degree of air purification is obtained based on the purified air data and sensitivity analysis; Obtain the building's external air data, and analyze the external air data and purified air data to determine the user's adaptability to the external air; The second quality of air purification is obtained by combining the interference degree and the adaptability.

5. The building decoration air purification quality assessment system based on artificial intelligence according to claim 4 is characterized in that: The steps of obtaining user personal information and analyzing the user's sensitivity to air based on the user personal information are specifically as follows: Extract the factors in the air that affect the user's sensory experience as sensory air factors; Obtain user personal information and extract user daily behavior characteristics based on the user personal information; Extract the sensory air factor change value when the user violates the daily behavior characteristics based on the user's personal information; The reciprocal of the average value of all sensory air factor change values ​​is calculated as the user's sensitivity to the air.

6. The building decoration air purification quality assessment system based on artificial intelligence according to claim 5 is characterized in that: The step of obtaining the interference degree of air purification based on the purified air data and sensitivity analysis is specifically as follows: Collect historical purification data, and obtain the first interference degree of air purification based on the historical purification data and sensitivity analysis; Extract the real-time value of sensory air factors when users violate their daily behavior characteristics based on their personal information; The minimum real-time value of the sensory air factor is obtained by screening out the real-time values ​​of the sensory air factor as the minimum value of the sensory air factor; Form user sensitivity standards based on the minimum values ​​of all sensory air factors and basic air standards; Determine whether the purified air data meets the user's sensitivity standard. If not, extract the real-time sensory air factor value based on the purified air data; The sum of the differences between all real-time sensory air factor values ​​and the minimum sensory air factor value is counted as the second interference degree of air purification; The first interference degree and the second interference degree are superimposed to obtain the interference degree of air purification.

7. The artificial intelligence-based building decoration air purification quality assessment system according to claim 6 is characterized in that: The step of collecting historical purification data and obtaining a first interference level of air purification based on the historical purification data and sensitivity analysis is specifically as follows: For those who have obtained historical purification data, the average similarity of purified air at different times is obtained based on the historical purification data; The first interference degree of air purification is obtained by combining the average similarity and sensitivity analysis.

8. The building decoration air purification quality assessment system based on artificial intelligence according to claim 4 is characterized in that: The steps of obtaining the building's external air data and analyzing the external air data and the purified air data to determine the user's adaptability to the external air are specifically as follows: Obtain the building's external air data, compare the purified air data with the external air data, and obtain the similarity between them, which is recorded as the air similarity. Determine whether the similarity reaches a preset similarity threshold. If not, extract the average time the user spends in the building based on the user's personal information. Determine whether air purification affects the user's adaptability to external air based on the average duration; If the purified air affects the user's adaptability to the outside air, the user's tolerance to the purified air interference is evaluated based on the user's personal information; The user's adaptability to the external air is evaluated based on the air similarity and interference tolerance.

9. The artificial intelligence-based building decoration air purification quality assessment system according to claim 8 is characterized in that: If the purified air affects the user's adaptability to the outside air, the steps of evaluating the user's tolerance to the purified air based on the user's personal information are specifically as follows: Extract the user's age based on their personal information and determine the air quality requirements based on their age; Obtain the environmental exposure after building renovation and obtain real-time purification data based on the environmental exposure estimate; Compare the similarity between the real-time purified data and the requirement standards and record it as the requirement similarity; The tolerance of purified air to user interference is obtained by combining demand similarity and the average time users spend in the building.

10. The building decoration air purification quality assessment system based on artificial intelligence according to claim 9 is characterized in that: The steps of obtaining the environmental exposure after building decoration are specifically as follows: Obtain the building's apartment structure, extract ventilation information, and calculate the building's ventilation efficiency based on the ventilation information. Calculate the average daily ventilation volume of building decoration based on ventilation information; The environmental exposure after building decoration is obtained based on the average ventilation volume and ventilation efficiency analysis.

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