An intelligent analysis method and system for public health quality control

Abstract

The present invention relates to the technical field of public health quality control, and in particular to an intelligent analysis method and system for public health quality control. The method comprises the following steps: obtaining public health facility use data, surrounding environment data of public health facilities, and public health facility feedback data, and performing sampling time series synchronization processing and sanitary air pollution index calculation to obtain the public health facility use air pollution index; extracting abnormal words of facility feedback and calculating the facility use defect score of the public health facility feedback data to obtain the public health facility use defect score; performing abnormal weighted quality control analysis and abnormal quality control decision support on the corresponding public health facilities according to the public health facility use air pollution index and the public health facility use defect score, and generating a public health facility abnormal quality control decision recommendation plan to execute the corresponding public health quality control response measures. The present invention can improve the quality control efficiency and accuracy of public health facilities.

Description

Technical Field

[0001] The present invention relates to the technical field of public health quality control, and in particular to an intelligent analysis method and system for public health quality control. Background Art

[0002] As an important public facility, the sanitary condition of public toilets directly affects people's health and safety. At the same time, the rapid development of intelligent technology in recent years has provided new solutions for the quality control of public toilet facilities. Through sensors and Internet of Things technology, the use and environmental indicators of toilets can be monitored in real time. By deploying sensors in toilet facilities, key indicators such as water flow, air quality, frequency of use and equipment status can be monitored in real time. These data are aggregated to the central management system through the Internet of Things platform to achieve real-time data update and analysis. Big data analysis technology is also used to deeply mine historical data and real-time data to identify the use patterns and potential problems of toilet facilities. A dynamic monitoring model is established by applying machine learning algorithms, which can automatically identify abnormal situations and generate early warning information, such as equipment failure or hygiene problems, to ensure timely response and processing. However, traditional quality control methods often rely on regular on-site inspections and lack effective medical and public health archive management and real-time monitoring capabilities. This method is easily affected by the subjective judgment of inspectors, resulting in an inability to fully reflect the air pollution status and facility use defects of public toilet facilities. Summary of the invention

[0003] Based on this, it is necessary for the present invention to provide an intelligent analysis method and system for public health quality control to solve at least one of the above-mentioned technical problems.

[0004] To achieve the above purpose, an intelligent analysis method for public health quality control includes the following steps:

[0005] Step S1: obtaining public health facility usage data, public health facility surrounding environment data and public health facility public feedback data, and performing sampling time series synchronization processing on the public health facility usage data, public health facility surrounding environment data and public health facility public feedback data to obtain corresponding public health facility usage data, public health facility environment data and public health facility public feedback data within the same sampling time series variation range;

[0006] Step S2: Calculate the sanitary air pollution index of the corresponding public health facilities based on the sanitary facility usage data and the sanitary facility environment data to obtain the public health facility usage air pollution index;

[0007] Step S3: extracting abnormal words of facility feedback from the public feedback data of health facilities to obtain abnormal word vectors of public health facility use feedback; calculating the facility use defect score of the corresponding public health facilities based on the abnormal word vectors of public health facility use feedback to obtain the public health facility use defect score value;

[0008] Step S4: Perform abnormal weighted quality control analysis on the corresponding public health facilities according to the air pollution index of public health facilities use and the public health facilities use defect score value to obtain the abnormal values ​​of public health facility quality control detection; perform abnormal quality control decision support on the corresponding public health facilities based on the abnormal values ​​of public health facility quality control detection, generate a public health facility abnormal quality control decision recommendation plan, and execute corresponding public health quality control response measures.

[0009] Further, step S1 includes the following steps:

[0010] Step S11: obtaining a public health planning area to be controlled, and using intelligent sensing equipment to monitor the sanitary use of corresponding public health facilities in the public health planning area to be controlled in real time, to obtain public health facility use data, wherein the public health facility use data includes the frequency of use of the health facilities and the duration of each use of the health facilities;

[0011] Step S12: using environmental monitoring sensors to monitor the surrounding environment of the corresponding public health facilities in the quality control public health planning area in real time, and obtaining the surrounding environment data of the health facilities, wherein the surrounding environment data of the health facilities includes the air flow conditions of the health facilities and the temperature and humidity changes of the health facilities;

[0012] Step S13: using the corresponding public feedback information collection channels in the public health planning area to be controlled to collect public feedback from the corresponding public health facilities in real time, and obtain public feedback data on health facilities, wherein the public feedback data on health facilities include health facility use experience, health facility use suggestions, and health facility use complaints;

[0013] Step S14: performing timestamp format standardization processing on the public health facility usage data, the surrounding environment data of the public health facilities, and the public feedback data of the public health facilities to obtain standardized data on the use of public health facilities, standardized data on the surrounding environment of public health facilities, and standardized data on the public feedback of public health facilities;

[0014] Step S15: Perform sampling time series synchronization processing on the standardized data on the use of sanitary facilities, the standardized data on the environment of sanitary facilities, and the standardized data on public feedback from sanitary facilities, and obtain the corresponding sanitary facility use data, sanitary facility environment data, and sanitary facility public feedback data within the same sampling time series variation range.

[0015] Further, step S2 includes the following steps:

[0016] Step S21: analyzing the usage behavior pattern of the corresponding public health facilities based on the usage duration of each sanitary facility in the sanitary facility usage data to obtain the public health facility usage behavior pattern, wherein the public health facility usage behavior pattern includes a long-time usage behavior pattern and a short-time usage behavior pattern;

[0017] Step S22: Based on the public health facility usage behavior pattern and the sanitary facility usage frequency in the sanitary facility usage data, an air pollution impact assessment analysis of the usage behavior of the corresponding public health facilities is performed to obtain an air pollution impact factor of the sanitary facility usage behavior;

[0018] Step S23: Based on the sanitary facility air flow conditions and sanitary facility temperature and humidity changes in the sanitary facility environmental data, an environmental air pollution impact assessment analysis is performed on the corresponding public health facilities to obtain sanitary facility environmental air pollution impact factors, wherein the sanitary facility environmental air pollution impact factors include sanitary facility air pollution ventilation efficiency impact factors, sanitary facility temperature pollution volatilization impact factors, and sanitary facility humidity pollution volatilization impact factors;

[0019] Step S24: Based on the air pollution influencing factor of sanitary facility use behavior and the air pollution influencing factor of sanitary facility environment, the sanitary air pollution index of the corresponding public health facilities is calculated using the air pollution index calculation formula to obtain the public health facility use air pollution index.

[0020] Further, step S23 includes the following steps:

[0021] Step S231: Obtain the wind speed and wind direction corresponding to the public health facility through the sanitary facility air flow conditions in the sanitary facility environmental data, and calculate the dilution and diffusion rate impact of the air pollutants in the corresponding public health facility based on the wind speed and wind direction corresponding to the public health facility, to obtain the public health facility air pollution dilution impact rate and the public health facility air pollution diffusion impact rate;

[0022] Step S232: Based on the air pollution dilution impact rate of public health facilities and the air pollution diffusion impact rate of public health facilities, an air pollution ventilation efficiency evaluation and analysis is performed on the corresponding public health facilities to obtain an air pollution ventilation efficiency impact factor of the public health facilities;

[0023] Step S233: Based on the sanitary facility temperature and humidity changes in the sanitary facility environmental data, an air pollution volatilization impact assessment analysis is performed on the air pollutants in the corresponding public health facilities to obtain the sanitary facility temperature pollution volatilization impact factor and the sanitary facility humidity pollution volatilization impact factor.

[0024] Furthermore, the air pollution index calculation formula in step S24 is specifically:

[0025] ;

[0026] In the formula, Use of air pollution index for public health facilities, is the integration start time, is the integration end time, is the integral time variable parameter, The frequency of use of sanitary facilities, Air pollution influencing factors for sanitation facility use behavior, is the sanitary facility air flow rate, is the influencing factor of ventilation efficiency of sanitary facilities air pollution, is the temperature around the sanitary facility, is the impact factor of temperature pollution volatilization in sanitary facilities, is the humidity around the sanitary facilities, is the influencing factor of humidity pollution volatilization in sanitary facilities, is the time decay constant of air pollutants, Use of air pollution index correction factors for public health facilities.

[0027] Further, step S3 includes the following steps:

[0028] Step S31: performing facility feedback semantic recognition analysis on the corresponding health facility use experience, health facility use suggestions and health facility use complaints in the health facility public feedback data to obtain health facility public use feedback semantic information;

[0029] Step S32: extracting positive and negative sentiment words from the public feedback semantic information on health facilities to obtain a positive and negative sentiment word library for public feedback semantics on health facilities;

[0030] Step S33: performing negative emotion screening analysis on each negative emotion word in the public feedback semantic positive and negative emotion word library of health facilities, and obtaining a candidate list of negative emotion words of public feedback on health facilities;

[0031] Step S34: performing context association analysis on each candidate word in the candidate list of negative emotion words for public feedback on health facilities, so as to obtain the association relationship between the context sentences of health facility feedback corresponding to each candidate word; extracting abnormal facility usage words from each candidate word in the candidate list of negative emotion words for public feedback on health facilities, based on the association relationship between the context sentences of health facility feedback corresponding to each candidate word, to obtain abnormal usage words for public feedback on health facilities; performing vectorization processing on the abnormal usage words for public feedback on health facilities, so as to obtain abnormal word vectors for public health facility usage feedback;

[0032] Step S35: Calculate the facility utilization defect score for the corresponding public health facility based on the public health facility utilization feedback abnormal word vector to obtain a public health facility utilization defect score value.

[0033] Further, step S35 includes the following steps:

[0034] Step S351: classify each abnormal facility usage word in the abnormal word vector of public health facility usage feedback into a problem type, so as to obtain a public health facility usage abnormal word sub-vector corresponding to each facility usage problem type, wherein each facility usage problem type includes sanitary conditions, facility damage, and service attitude;

[0035] Step S352: performing problem type word frequency statistics on the public health facility use abnormal word sub-vectors corresponding to each facility use problem type, and obtaining the number of public health facility use abnormal word frequencies corresponding to each facility use problem type;

[0036] Step S353: Based on the frequency of abnormal public health facility usage words corresponding to each facility usage problem type, the corresponding abnormal public health facility usage word sub-vector is evaluated and analyzed for public satisfaction and feedback experience, so as to obtain the public satisfaction with public health facility usage and the degree of impact on public health facility usage experience corresponding to each facility usage problem type;

[0037] Step S354: Based on the public satisfaction with the use of public health facilities corresponding to each facility use problem type and the degree of impact of the use experience of public health facilities, the facility use defect evaluation calculation formula is used to calculate the facility use defect score of the corresponding public health facilities to obtain the public health facility use defect score value.

[0038] Furthermore, the facility utilization defect assessment calculation formula in step S354 is specifically:

[0039] ;

[0040] In the formula, Using defect score values ​​for public health facilities, is the total number of facility usage problem types, Use the Item Index parameter of the problem type for the facility. For the The public satisfaction with the use of public health facilities corresponding to each type of facility use problem, is the satisfaction importance weight coefficient, For the The degree of impact of public health facility use experience corresponding to each facility use problem type, is the user experience importance weight coefficient, For the The cleanliness of public health facilities corresponding to each type of facility use problem, is the cleanliness importance weight coefficient, is the nonlinear impact index of public health facilities, For the The time of public health facility use corresponding to each facility use problem type, is the usage time attenuation coefficient, Use a correction factor for the deficiency score value for public health facilities.

[0041] Further, step S4 includes the following steps:

[0042] Step S41: performing abnormal weighting setting on the public health facility use air pollution index and the public health facility use defect score value to obtain the air pollution index weight and the facility use defect score weight;

[0043] Step S42: Based on the air pollution index weight and the facility use defect score weight and in combination with the public health facility use air pollution index and the public health facility use defect score, a quality control anomaly detection calculation is performed on the corresponding public health facility to obtain a public health facility quality control detection anomaly value;

[0044] Step S43: Compare and judge the quality control detection anomaly value of the public health facility according to the preset quality control detection anomaly threshold. When the quality control detection anomaly value of the public health facility is less than the preset quality control detection anomaly threshold, continue to perform quality control anomaly detection on the corresponding public health facility; when the quality control detection anomaly value of the public health facility is greater than or equal to the preset quality control detection anomaly threshold, perform abnormal quality control decision support on the corresponding public health facility, generate a public health facility abnormal quality control decision recommendation plan, and execute corresponding public health quality control response measures.

[0045] Furthermore, the present invention also provides an intelligent analysis system for public health quality control, which is used to execute the intelligent analysis method for public health quality control as described above, and the intelligent analysis system for public health quality control includes:

[0046] The public health facility data analysis module is used to obtain the public health facility usage data, the surrounding environment data of the public health facilities and the public feedback data of the public health facilities, and perform sampling time series synchronization processing on the public health facility usage data, the surrounding environment data of the public health facilities and the public feedback data of the public health facilities, so as to obtain the corresponding public health facility usage data, public health facility environment data and public health facility feedback data within the same sampling time series variation range;

[0047] The sanitary facility air pollution analysis module is used to calculate the sanitary air pollution index of the corresponding public health facilities based on the sanitary facility usage data and the sanitary facility environment data, so as to obtain the public health facility usage air pollution index;

[0048] The health facility use defect scoring module is used to extract abnormal words in the health facility feedback data to obtain abnormal word vectors for the use of public health facilities; based on the abnormal word vectors for the use of public health facilities feedback, the corresponding public health facilities are scored for the use defect to obtain the public health facility use defect score value;

[0049] The public health abnormal quality control recommendation module is used to conduct abnormal weighted quality control analysis on the corresponding public health facilities according to the air pollution index of the use of public health facilities and the defect score of the use of public health facilities, and obtain the abnormal values ​​of the quality control detection of public health facilities; based on the abnormal values ​​of the quality control detection of public health facilities, the corresponding public health facilities are supported by abnormal quality control decisions, and abnormal quality control decision-making recommendations for public health facilities are generated to implement corresponding public health quality control response measures.

[0050] Beneficial effects of the present invention:

[0051] 1. Compared with the prior art, the intelligent analysis method for public health quality control proposed by the present invention has the beneficial effect that by real-time monitoring of the sanitary use of the corresponding public health facilities, the efficiency and accuracy of public health management can be effectively improved. By collecting the frequency of use of public health facilities and the duration of each use, managers can fully understand the use of different facilities, which can reflect the utilization rate of the facilities. By using environmental monitoring sensors to monitor the surrounding environment of public health facilities in real time, important air flow conditions and temperature and humidity change data can be obtained. In addition, by collecting public feedback from the corresponding public health facilities in real time, managers can have a more comprehensive understanding of the user experience. This process can collect information such as user experience, usage suggestions and complaints, and form a comprehensive feedback data set, thereby improving the real-time monitoring capability of the public health quality control process. At the same time, by performing sampling time-series synchronization processing on the use data of public health facilities, the surrounding environment data of health facilities, and the public feedback data of health facilities, different data sets can be analyzed within the same time range. This processing step can effectively compare the correlation between various types of data and further improve the overall level of public health management. Secondly, by calculating the sanitary air pollution index of the corresponding public health facilities based on the sanitary facility usage data and sanitary facility environmental data, the corresponding sanitary air pollution index can be calculated, which will provide an important quantitative basis for the management of public health facilities. This index can not only reflect the air quality status of specific sanitary facilities, but also serve as a reference for decision-making and policy making, so as to better monitor and analyze the air pollution status of public health facilities. Then, by extracting abnormal words from the public feedback data of sanitary facilities, the abnormal words in the feedback can be extracted. This process can not only reveal the specific dissatisfaction of users with the use of facilities, but also provide specific suggestions for the improvement of facilities, so as to facilitate subsequent intelligent analysis and automated decision-making, and improve the efficiency and accuracy of feedback processing. In addition, by calculating the facility use defect score of the corresponding public health facilities based on the abnormal word vector of the public health facility use feedback, a quantitative defect score value can be provided for each public health facility. This score not only intuitively reflects the use status of the facility, but also can more comprehensively monitor and analyze the use defects of public toilet facilities. Finally, by conducting abnormal weighted quality control analysis on the corresponding public health facilities based on the air pollution index of public health facilities and the defect score of public health facilities, this step can not only monitor the operating status of public health facilities in real time, but also timely discover potential risks through weighted calculation of abnormal values, avoid public health crises caused by facility defects or environmental pollution, and greatly enhance the foresight and effectiveness of public health quality control management.In addition, by providing abnormal quality control decision support for the corresponding public health facilities based on the abnormal values ​​of quality control detection of public health facilities, it is possible to effectively distinguish between public health facilities that require emergency treatment and facilities that can be continuously observed, providing decision makers with specific action guidelines to help quickly respond to potential public health crises. This will promote the standardized management and continuous improvement of public health facilities, thereby improving the overall health level of public health quality control.

[0052] 2. The intelligent analysis system for public health quality control proposed in the present invention is generally composed of a public health facility data analysis module, a sanitary facility air pollution analysis module, a sanitary facility utilization defect scoring module and a public health abnormality quality control suggestion module. It can realize any intelligent analysis method for public health quality control described in the present invention, and is used to combine the operations between computer programs running on each module to realize the intelligent analysis method for public health quality control. The internal structures of the system cooperate with each other, which can greatly reduce duplication of work and manpower investment, and can quickly and effectively provide a more accurate and efficient intelligent analysis process for public health quality control, thereby simplifying the operating procedures of the intelligent analysis system for public health quality control. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments thereof made with reference to the following drawings:

[0054] Figure 1 A schematic diagram of the steps of the intelligent analysis method for public health quality control of the present invention;

[0055] Figure 2 for Figure 1 Detailed step flow diagram of step S1;

[0056] Figure 3 for Figure 1 Detailed step flow chart of step S2 in FIG. DETAILED DESCRIPTION

[0057] The technical method of the present invention is described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by technicians in this field without creative work are within the scope of protection of the present invention.

[0058] In addition, the accompanying drawings are only schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor methods and / or microcontroller methods.

[0059] It should be understood that, although the terms "first", "second", etc. may be used herein to describe various units, these units should not be limited by these terms. These terms are used only to distinguish one unit from another unit. For example, without departing from the scope of the exemplary embodiments, the first unit may be referred to as the second unit, and similarly the second unit may be referred to as the first unit. The term "and / or" used herein includes any and all combinations of one or more of the listed associated items.

[0060] To achieve this, please refer to Figures 1 to 3 The present invention provides an intelligent analysis method for public health quality control, the method comprising the following steps:

[0061] Step S1: obtaining public health facility usage data, public health facility surrounding environment data and public health facility public feedback data, and performing sampling time series synchronization processing on the public health facility usage data, public health facility surrounding environment data and public health facility public feedback data to obtain corresponding public health facility usage data, public health facility environment data and public health facility public feedback data within the same sampling time series variation range;

[0062] Step S2: Calculate the sanitary air pollution index of the corresponding public health facilities based on the sanitary facility usage data and the sanitary facility environment data to obtain the public health facility usage air pollution index;

[0063] Step S3: extracting abnormal words of facility feedback from the public feedback data of health facilities to obtain abnormal word vectors of public health facility use feedback; calculating the facility use defect score of the corresponding public health facilities based on the abnormal word vectors of public health facility use feedback to obtain the public health facility use defect score value;

[0064] Step S4: Perform abnormal weighted quality control analysis on the corresponding public health facilities according to the air pollution index of public health facilities use and the public health facilities use defect score value to obtain the abnormal values ​​of public health facility quality control detection; perform abnormal quality control decision support on the corresponding public health facilities based on the abnormal values ​​of public health facility quality control detection, generate a public health facility abnormal quality control decision recommendation plan, and execute corresponding public health quality control response measures.

[0065] In the embodiment of the present invention, please refer to Figure 1 FIG. 1 is a schematic diagram of the steps of the intelligent analysis method for public health quality control of the present invention. In this example, the intelligent analysis method for public health quality control includes the following steps:

[0066] Step S1: obtaining public health facility usage data, public health facility surrounding environment data and public health facility public feedback data, and performing sampling time series synchronization processing on the public health facility usage data, public health facility surrounding environment data and public health facility public feedback data to obtain corresponding public health facility usage data, public health facility environment data and public health facility public feedback data within the same sampling time series variation range;

[0067] In an embodiment of the present invention, a corresponding public health planning area to be controlled is obtained by using a geographic information system, and in the public health planning area to be controlled, intelligent sensing equipment, such as infrared sensors and RFID technology, is arranged to monitor the use of public health facilities. The equipment records the frequency of use of each sanitary facility and the duration of each use in real time, thereby obtaining the use data of public health facilities. Environmental monitoring sensors are arranged at multiple sensor nodes around the corresponding public health facilities in the public health planning area to be controlled, and real-time monitoring of the surrounding environment of the facilities is started, so that gas sensors, temperature and humidity sensors and airflow sensors are selected to continuously collect air gas flow conditions, temperature and humidity data, thereby obtaining the surrounding environment data of the sanitary facilities. In addition, public feedback information collection channels are set up, such as mobile phone applications and online questionnaires, and public feedback is facilitated in various ways. Using specially developed mobile applications, users can submit their experience, suggestions and complaints in real time after using public health facilities. The data is uploaded to the cloud service medical archive management platform through the network in real time, thereby obtaining the public feedback data of health facilities, facilitating automatic data collection, accurate analysis and real-time early warning, and innovating hospital archive management, realizing the efficiency and accuracy of public health quality control, and improving the efficiency of medical services and the level of public health safety. At the same time, by standardizing the timestamp format of the public health facility usage data, health facility surrounding environment data and health facility public feedback data previously collected in real time, the timestamps of data from different sources are unified into the ISO 8601 format by introducing data cleaning and conversion tools to ensure time consistency. Then, by synchronizing the sampling time series of the health facility usage data, health facility environment data and health facility public feedback data that have been previously standardized, it is ensured that the health facility usage data, health facility environment data and public feedback data are analyzed in the same time dimension, and time series analysis technology is used to arrange all data in chronological order, and the interpolation algorithm is used to process missing data so that various types of data are synchronized on the time axis. This process can ensure the integrity and continuity of the data, form a unified database, and finally obtain the health facility usage data, health facility environment data and health facility public feedback data corresponding to the same sampling time series variation range.

[0068] Step S2: Calculate the sanitary air pollution index of the corresponding public health facilities based on the sanitary facility usage data and the sanitary facility environment data to obtain the public health facility usage air pollution index;

[0069] In an embodiment of the present invention, by combining the duration of each use of the sanitary facilities in the sanitary facility use data obtained by previous real-time monitoring, the usage behavior pattern of the corresponding public health facilities is analyzed, and it is divided into long-term use behavior patterns and short-term use behavior patterns according to the use duration. Examples of long-term use include long hand washing time in public restrooms, while short-term use involves quick toilet visits or short hand washing behaviors, thereby forming a detailed behavior pattern report, and by combining the public health facility use behavior patterns obtained by previous identification and analysis and the sanitary facility use frequency in the sanitary facility use data, the corresponding public health facility use behavior air pollution impact assessment analysis is performed, so as to combine the use frequency data obtained previously with the use behavior patterns of public health facilities, Analyze the degree of influence of various types of usage behaviors on air pollution, so as to obtain the specific value of the air pollution influence factor of the use behavior of sanitary facilities. At the same time, by combining the air airflow conditions of sanitary facilities and the temperature and humidity changes of sanitary facilities in the sanitary facility environmental data obtained by real-time monitoring, the corresponding public health facilities are evaluated and analyzed for the impact of air pollution. This step focuses on the air airflow conditions and temperature and humidity changes of sanitary facilities, arranges air quality monitoring equipment to record air flow rate and temperature and humidity data in real time, and uses meteorological analysis software to determine the influence of ventilation efficiency and temperature and humidity on the volatilization of pollutants, so as to obtain the air pollution influence factors of sanitary facility environment, including air pollution ventilation efficiency influence factors, temperature pollution volatilization influence factors and humidity pollution volatilization influence factors. Then, by combining the air pollution influence factors of sanitary facility use behavior, the air pollution influence factors of sanitary facility environment and related parameters, a suitable air pollution index calculation formula is formed to calculate the sanitary air pollution index of the corresponding public health facilities, so as to quantitatively calculate the corresponding air pollution index, and finally obtain the air pollution index of public health facilities.

[0070] Step S3: extracting abnormal words of facility feedback from the public feedback data of health facilities to obtain abnormal word vectors of public health facility use feedback; calculating the facility use defect score of the corresponding public health facilities based on the abnormal word vectors of public health facility use feedback to obtain the public health facility use defect score value;

[0071] In an embodiment of the present invention, by collecting the public's experience, suggestions and complaints about sanitary facilities from the public feedback data on sanitary facilities, these data can be obtained through questionnaires, social media comments or online feedback forms, and using natural language processing (NLP) tools, such as word segmentation tools and part-of-speech tagging tools, the collected data is preprocessed to extract relevant keywords and phrases, and then a semantic analysis model is established, the processed data is input into the model, and a deep learning algorithm is used for semantic recognition, so as to identify the key information in the public feedback, including the positive and negative emotional expressions of the usage experience, to form structured semantic information, and by extracting positive and negative emotional vocabulary from the public feedback semantic information obtained by the previous analysis, a positive and negative emotional dictionary is established using the sentiment analysis tool, and the emotional polarity of each feedback in the public feedback semantic information is determined, so as to identify positive emotional words (such as "clean" and "convenient") and negative emotional words (such as "dirty" and "crowded") by expanding and updating the emotional dictionary, and a machine learning algorithm, such as a support vector machine (SVM), is used to classify and label the emotional words to generate a structured semantic information containing positive and negative emotions. In addition, the negative emotion vocabulary library is used to screen out negative emotions for each negative emotion vocabulary in the positive and negative emotion vocabulary library, so as to use the sentiment analysis algorithm to further screen out the negative emotion features of each negative emotion word, and build a negative emotion feature model to apply these features to the negative emotion words to evaluate their negativity. To ensure accuracy, the context of each negative emotion word can be analyzed to identify the negative emotion expression related to the word, and a candidate list of negative emotion words is generated, which contains all keywords that reflect the public's dissatisfaction with the use of sanitary facilities. For each negative emotion word, its context is analyzed to see whether there are key phrases or words pointing to specific abnormal use. Keyword extraction algorithms (such as TF-IDF or TextRank) are used to identify abnormal expressions related to the use of sanitary facilities, such as "the faucet is broken" and "the toilet has a peculiar smell". The extracted abnormal words are sorted into a list to obtain the corresponding public feedback abnormal words. The extracted public feedback abnormal words are converted into vectors by using vectorization technology (such as word embedding), and the abnormal word vector of public health facility use feedback is constructed, thereby obtaining the abnormal word vector of public health facility use feedback. Then, the defect score of the corresponding public health facility is calculated by combining the abnormal word vectors of the public health facility use feedback obtained in the previous analysis, so as to calculate the defect score value of each facility based on a pre-set scoring model (for example, based on weighted average or deep learning model) combined with the vector representation of the abnormal words. The scoring model needs to consider the number and severity of abnormal words and their frequency in the feedback. The final score is obtained by combining these factors to help identify and improve potential problems in the use of facilities, and finally obtain the public health facility use defect score value.

[0072] Step S4: Perform abnormal weighted quality control analysis on the corresponding public health facilities according to the air pollution index of public health facilities use and the public health facilities use defect score value to obtain the abnormal values ​​of public health facility quality control detection; perform abnormal quality control decision support on the corresponding public health facilities based on the abnormal values ​​of public health facility quality control detection, generate a public health facility abnormal quality control decision recommendation plan, and execute corresponding public health quality control response measures.

[0073] In an embodiment of the present invention, weighted values ​​are assigned to the public health facility use air pollution index and the public health facility use defect score values ​​obtained by previous quantitative calculations, so as to determine the weights of the air pollution index and the facility use defect score by using a statistical analysis method, such as principal component analysis (PCA), and after obtaining the air pollution index weight and the facility use defect score weight, the air pollution index and the public health facility use defect score values ​​are combined to perform a quantitative calculation of the quality control abnormality values ​​of the corresponding public health facilities using a weighted algorithm, so as to obtain a comprehensive evaluation value by multiplying the air pollution index and the defect score of each facility with their weights, for example, abnormal value = air pollution index weight × public health facility use air pollution index + facility use defect score weight × public health facility use defect score, and quantitatively calculate the abnormal values ​​of public health facility quality control detection. Then, the quality control detection anomaly values ​​of public health facilities obtained by previous quantitative calculations are compared and judged by using the preset quality control detection anomaly threshold. If the anomaly value is less than the preset threshold, the corresponding facilities will continue to be monitored and data updated to ensure that new problems that may arise are captured in a timely manner; if the anomaly value is greater than or equal to the preset threshold, the abnormal quality control decision support process will be automatically triggered. This process will involve the generation of data reports, including abnormal details, possible cause analysis and recommended response measures. At this time, the decision support system (DSS) is used to integrate historical data and case analysis to provide decision makers with specific response plans, such as equipment maintenance, structural adjustments or environmental improvement measures, to ensure the normal operation of public health facilities and the protection of public health, and finally generate a public health facility abnormal quality control decision recommendation plan to implement corresponding public health quality control response measures.

[0074] Further, step S1 includes the following steps:

[0075] Step S11: obtaining a public health planning area to be controlled, and using intelligent sensing equipment to monitor the sanitary use of corresponding public health facilities in the public health planning area to be controlled in real time, to obtain public health facility use data, wherein the public health facility use data includes the frequency of use of the health facilities and the duration of each use of the health facilities;

[0076] Step S12: using environmental monitoring sensors to monitor the surrounding environment of the corresponding public health facilities in the quality control public health planning area in real time, and obtaining the surrounding environment data of the health facilities, wherein the surrounding environment data of the health facilities includes the air flow conditions of the health facilities and the temperature and humidity changes of the health facilities;

[0077] Step S13: using the corresponding public feedback information collection channels in the public health planning area to be controlled to collect public feedback from the corresponding public health facilities in real time, and obtain public feedback data on health facilities, wherein the public feedback data on health facilities include health facility use experience, health facility use suggestions, and health facility use complaints;

[0078] Step S14: performing timestamp format standardization processing on the public health facility usage data, the surrounding environment data of the public health facilities, and the public feedback data of the public health facilities to obtain standardized data on the use of public health facilities, standardized data on the surrounding environment of public health facilities, and standardized data on the public feedback of public health facilities;

[0079] Step S15: Perform sampling time series synchronization processing on the standardized data on the use of sanitary facilities, the standardized data on the environment of sanitary facilities, and the standardized data on public feedback from sanitary facilities, and obtain the corresponding sanitary facility use data, sanitary facility environment data, and sanitary facility public feedback data within the same sampling time series variation range.

[0080] As an embodiment of the present invention, refer to Figure 2 As shown, Figure 1 Detailed step flow diagram of step S1 in FIG. 1 , in this embodiment, step S1 includes the following steps:

[0081] Step S11: obtaining a public health planning area to be controlled, and using intelligent sensing equipment to monitor the sanitary use of corresponding public health facilities in the public health planning area to be controlled in real time, to obtain public health facility use data, wherein the public health facility use data includes the frequency of use of the health facilities and the duration of each use of the health facilities;

[0082] In an embodiment of the present invention, a geographic information system is used to obtain a corresponding public health planning area to be quality controlled, and intelligent sensing equipment, such as infrared sensors and RFID technology, is arranged in the public health planning area to be quality controlled to monitor the use of public health facilities. The equipment records the frequency of use of each sanitary facility and the duration of each use in real time. In a specific implementation, when the infrared sensor detects that someone is approaching the sanitary facility, it starts timing immediately and stops automatically after the use. During this process, the system uploads real-time data to the central database to form a dynamic update of the sanitary facility usage data, ensuring that the usage records of each time node are accurate and detailed, and finally obtaining the public health facility usage data, including the frequency of use of the sanitary facility and the duration of each use of the sanitary facility.

[0083] Step S12: using environmental monitoring sensors to monitor the surrounding environment of the corresponding public health facilities in the quality control public health planning area in real time, and obtaining the surrounding environment data of the health facilities, wherein the surrounding environment data of the health facilities includes the air flow conditions of the health facilities and the temperature and humidity changes of the health facilities;

[0084] In an embodiment of the present invention, environmental monitoring sensors are arranged at multiple sensor nodes around the corresponding public health facilities in the public health planning area to be quality controlled, and real-time monitoring of the environment around the facilities is started, so as to select gas sensors, temperature and humidity sensors and airflow sensors to continuously collect air gas flow conditions, temperature and humidity data. Each sensor regularly sends data to the monitoring platform, and the Internet of Things technology is used to ensure real-time data update. The airflow sensor can monitor the air flow conditions and identify any abnormal conditions, such as odor or pollution, and issue an alarm in time. After all the data are analyzed, the environmental data around the sanitary facilities are formed, and finally the environmental data around the sanitary facilities are obtained, including the air flow conditions of the sanitary facilities and the temperature and humidity changes of the sanitary facilities.

[0085] Step S13: using the corresponding public feedback information collection channels in the public health planning area to be controlled to collect public feedback from the corresponding public health facilities in real time, and obtain public feedback data on health facilities, wherein the public feedback data on health facilities include health facility use experience, health facility use suggestions, and health facility use complaints;

[0086] In an embodiment of the present invention, by establishing a public feedback information collection channel, such as a mobile phone application and an online questionnaire, public feedback is facilitated in a variety of ways. By using a specially developed mobile application, users can submit usage experience, suggestions and complaint information in real time after using public health facilities. The data is instantly uploaded to the cloud service medical archive management platform via the network. Data mining technology is used to analyze public feedback and extract key issues and suggestions. These feedback data provide an important basis for the improvement of public health facilities and form public feedback data on health facilities. Ultimately, public feedback data on health facilities is obtained, which includes health facility usage experience, health facility usage suggestions and health facility usage complaints.

[0087] Step S14: performing timestamp format standardization processing on the public health facility usage data, the surrounding environment data of the public health facilities, and the public feedback data of the public health facilities to obtain standardized data on the use of public health facilities, standardized data on the surrounding environment of public health facilities, and standardized data on the public feedback of public health facilities;

[0088] In an embodiment of the present invention, the timestamp format of the public health facility usage data, the surrounding environment data of the health facilities, and the public feedback data of the health facilities previously collected in real time is standardized, and the timestamps of the data from different sources are unified into the ISO 8601 format by introducing data cleaning and conversion tools to ensure time consistency. During the standardization process, the data format is verified to eliminate errors and duplicate data to ensure data reliability and consistency. After processing, standardized data on the use of health facilities, standardized data on the environment of health facilities, and standardized data on public feedback from health facilities are finally obtained.

[0089] Step S15: Perform sampling time series synchronization processing on the standardized data on the use of sanitary facilities, the standardized data on the environment of sanitary facilities, and the standardized data on public feedback from sanitary facilities, and obtain the corresponding sanitary facility use data, sanitary facility environment data, and sanitary facility public feedback data within the same sampling time series variation range.

[0090] In an embodiment of the present invention, by synchronizing the sampling time series of the standardized data on the use of sanitary facilities, the standardized data on the environment of sanitary facilities, and the standardized data on public feedback from sanitary facilities that have been previously obtained after standardization processing, it is ensured that the sanitary facility use data, the sanitary facility environment data, and the public feedback data are analyzed in the same time dimension, and time series analysis technology is used to arrange all data in chronological order, and the interpolation algorithm is used to process missing data so that various types of data are synchronized on the time axis. This process can ensure the integrity and continuity of the data, form a unified database, and finally obtain the corresponding sanitary facility use data, sanitary facility environment data, and sanitary facility public feedback data within the same sampling time series variation range.

[0091] Further, step S2 includes the following steps:

[0092] Step S21: analyzing the usage behavior pattern of the corresponding public health facilities based on the usage duration of each sanitary facility in the sanitary facility usage data to obtain the public health facility usage behavior pattern, wherein the public health facility usage behavior pattern includes a long-time usage behavior pattern and a short-time usage behavior pattern;

[0093] Step S22: Based on the public health facility usage behavior pattern and the sanitary facility usage frequency in the sanitary facility usage data, an air pollution impact assessment analysis of the usage behavior of the corresponding public health facilities is performed to obtain an air pollution impact factor of the sanitary facility usage behavior;

[0094] Step S23: Based on the sanitary facility air flow conditions and sanitary facility temperature and humidity changes in the sanitary facility environmental data, an environmental air pollution impact assessment analysis is performed on the corresponding public health facilities to obtain sanitary facility environmental air pollution impact factors, wherein the sanitary facility environmental air pollution impact factors include sanitary facility air pollution ventilation efficiency impact factors, sanitary facility temperature pollution volatilization impact factors, and sanitary facility humidity pollution volatilization impact factors;

[0095] Step S24: Based on the air pollution influencing factor of sanitary facility use behavior and the air pollution influencing factor of sanitary facility environment, the sanitary air pollution index of the corresponding public health facilities is calculated using the air pollution index calculation formula to obtain the public health facility use air pollution index.

[0096] As an embodiment of the present invention, refer to Figure 3 As shown, Figure 1 Detailed step flow diagram of step S2 in FIG. 1 , in this embodiment, step S2 includes the following steps:

[0097] Step S21: analyzing the usage behavior pattern of the corresponding public health facilities based on the usage duration of each sanitary facility in the sanitary facility usage data to obtain the public health facility usage behavior pattern, wherein the public health facility usage behavior pattern includes a long-time usage behavior pattern and a short-time usage behavior pattern;

[0098] In an embodiment of the present invention, the usage behavior pattern analysis of the corresponding public health facilities is performed by combining the usage duration of each sanitary facility in the sanitary facility usage data obtained by previous real-time monitoring. First, the sanitary facility usage data is collected, including the specific duration of each use. These data will be sorted and classified, and divided into long-term usage behavior patterns and short-term usage behavior patterns according to the usage duration. Examples of long-term use include long hand washing time in public restrooms, while short-term use involves quick toilet visits or short hand washing behaviors. Statistical analysis tools, such as SPSS or the Pandas library in Python, are used for data cleaning and pattern recognition. Cluster analysis methods are used to identify the characteristics of different usage behaviors, thereby forming a detailed behavior pattern report, and finally obtaining the public health facility usage behavior pattern, which includes long-term usage behavior patterns and short-term usage behavior patterns.

[0099] Step S22: Based on the public health facility usage behavior pattern and the sanitary facility usage frequency in the sanitary facility usage data, an air pollution impact assessment analysis of the usage behavior of the corresponding public health facilities is performed to obtain an air pollution impact factor of the sanitary facility usage behavior;

[0100] In an embodiment of the present invention, an impact assessment analysis of the use behavior of corresponding public health facilities on air pollution is performed by combining the use behavior pattern of public health facilities obtained by previous identification and analysis and the frequency of use of health facilities in the use data of health facilities, so as to analyze the degree of impact of various types of use behaviors on air pollution based on the use frequency data obtained previously and in combination with the use behavior pattern of public health facilities, and to quantify the specific impact of each use behavior pattern on air quality by using a linear regression model or a multiple regression analysis, so as to obtain the specific value of the air pollution impact factor of the use behavior of health facilities, and finally obtain the air pollution impact factor of the use behavior of health facilities.

[0101] Step S23: Based on the sanitary facility air flow conditions and sanitary facility temperature and humidity changes in the sanitary facility environmental data, an environmental air pollution impact assessment analysis is performed on the corresponding public health facilities to obtain sanitary facility environmental air pollution impact factors, wherein the sanitary facility environmental air pollution impact factors include sanitary facility air pollution ventilation efficiency impact factors, sanitary facility temperature pollution volatilization impact factors, and sanitary facility humidity pollution volatilization impact factors;

[0102] In an embodiment of the present invention, the impact of air pollution on the corresponding public health facilities is evaluated and analyzed by combining the air airflow conditions of the sanitary facilities and the temperature and humidity changes of the sanitary facilities in the sanitary facility environmental data obtained by previous real-time monitoring. This step focuses on the air airflow conditions and temperature and humidity changes of the sanitary facilities, arranges air quality monitoring equipment to record the air flow rate and temperature and humidity data in real time, and uses meteorological analysis software to analyze the collected data to determine the impact of ventilation efficiency and temperature and humidity on the volatilization of pollutants. Through laboratory environmental simulation, the volatilization rate of air pollutants is tested under different temperature and humidity conditions, and finally the air pollution influencing factors of the sanitary facility environment are obtained, including air pollution ventilation efficiency influencing factors, temperature pollution volatilization influencing factors and humidity pollution volatilization influencing factors.

[0103] Step S24: Based on the air pollution influencing factor of sanitary facility use behavior and the air pollution influencing factor of sanitary facility environment, the sanitary air pollution index of the corresponding public health facilities is calculated using the air pollution index calculation formula to obtain the public health facility use air pollution index.

[0104] In an embodiment of the present invention, a suitable air pollution index calculation formula is formed by combining time variable parameters, frequency of use of sanitary facilities, air pollution influencing factors of sanitary facility use behavior, air air flow rate of sanitary facilities, air pollution ventilation efficiency influencing factors of sanitary facilities, ambient temperature of sanitary facilities, temperature pollution volatilization influencing factors of sanitary facilities, ambient humidity of sanitary facilities, humidity pollution volatilization influencing factors of sanitary facilities, time decay constant of air pollutants and related parameters to calculate the sanitary air pollution index of the corresponding public health facilities, so as to quantitatively calculate the corresponding air pollution index and finally obtain the air pollution index of the use of public health facilities.

[0105] Further, step S23 includes the following steps:

[0106] Step S231: Obtain the wind speed and wind direction corresponding to the public health facility through the sanitary facility air flow conditions in the sanitary facility environmental data, and calculate the dilution and diffusion rate impact of the air pollutants in the corresponding public health facility based on the wind speed and wind direction corresponding to the public health facility, to obtain the public health facility air pollution dilution impact rate and the public health facility air pollution diffusion impact rate;

[0107] In an embodiment of the present invention, by collecting and analyzing environmental data of public health facilities, especially air flow conditions, wind speed and wind direction are measured, and real-time monitoring is performed using high-precision anemometers and wind vanes. The data recording device uploads real-time data to a central database through the Internet of Things technology, thereby obtaining the wind speed and wind direction corresponding to the public health facilities, and based on the wind speed and wind direction information, the dilution and diffusion rates of air pollutants are analyzed and calculated using a fluid dynamics model, and an appropriate mathematical model, such as the Navier-Stokes equation, is selected. In combination with environmental meteorological data, the pollutant concentration distribution within a specific public health facility is calculated. On this basis, a comprehensive evaluation and calculation of the dilution rate and diffusion rate of air pollutants is performed, thereby obtaining the dilution impact rate and diffusion impact rate of air pollution within the facility, and ultimately obtaining the dilution impact rate of air pollution in public health facilities and the diffusion impact rate of air pollution in public health facilities.

[0108] Step S232: Based on the air pollution dilution impact rate of public health facilities and the air pollution diffusion impact rate of public health facilities, an air pollution ventilation efficiency evaluation and analysis is performed on the corresponding public health facilities to obtain an air pollution ventilation efficiency impact factor of the public health facilities;

[0109] In an embodiment of the present invention, a comprehensive evaluation is performed on the air pollution ventilation efficiency of public health facilities by combining the dilution impact rate of air pollution in public health facilities and the diffusion impact rate of air pollution in public health facilities obtained by previous analysis. Numerical simulation software, such as ANSYS Fluent, is used to construct an air flow model of the sanitary facility, and dilution and diffusion rate data are input to simulate the changes in air quality under different ventilation conditions. By setting specific boundary conditions, the removal rates of various air pollutants at different wind speeds and wind directions are analyzed, and the indicators affecting ventilation efficiency are calculated to obtain the air pollution ventilation efficiency influencing factors of the sanitary facilities. This factor will provide a basis for facility management to improve the ventilation system, and finally the air pollution ventilation efficiency influencing factors of the sanitary facilities are obtained.

[0110] Step S233: Based on the sanitary facility temperature and humidity changes in the sanitary facility environmental data, an air pollution volatilization impact assessment analysis is performed on the air pollutants in the corresponding public health facilities to obtain the sanitary facility temperature pollution volatilization impact factor and the sanitary facility humidity pollution volatilization impact factor.

[0111] In an embodiment of the present invention, the effect of temperature and humidity changes in sanitary facilities in sanitary facility environmental data obtained through previous real-time monitoring on the volatilization of air pollutants is evaluated and analyzed, so that high-precision temperature and humidity sensors are used to monitor the temperature and humidity changes in sanitary facilities in real time, and the data is transmitted to a data processing system in real time. The gas volatilization kinetic model is used in combination with the temperature and humidity data to calculate the effect of temperature and humidity on the volatilization rate of air pollutants. Specifically, the Arrhenius equation is used to analyze the degree of influence of temperature on the volatilization rate, and the empirical formula is used to analyze the degree of influence of humidity on volatilization, so as to obtain the temperature influence factor and humidity influence factor of sanitary facility pollution volatilization, and finally obtain the sanitary facility temperature pollution volatilization influence factor and the sanitary facility humidity pollution volatilization influence factor.

[0112] Furthermore, the air pollution index calculation formula in step S24 is specifically:

[0113] ;

[0114] In the formula, Use of air pollution index for public health facilities, is the integration start time, is the integration end time, is the integral time variable parameter, The frequency of use of sanitary facilities, Air pollution influencing factors for sanitation facility use behavior, is the sanitary facility air flow rate, is the influencing factor of ventilation efficiency of sanitary facilities air pollution, is the temperature around the sanitary facility, is the impact factor of temperature pollution volatilization in sanitary facilities, is the humidity around the sanitary facilities, is the influencing factor of humidity pollution volatilization in sanitary facilities, is the time decay constant of air pollutants, Use of air pollution index correction factors for public health facilities.

[0115] The present invention obtains an air pollution index calculation formula by using a specific mathematical model and verifying it, which is used to calculate the sanitary air pollution index of the corresponding public health facilities. The air pollution index calculation formula can comprehensively evaluate the changes in air quality during the use of the facilities through a comprehensive analysis of the use behavior patterns, use frequency and environmental conditions of the public health facilities. This evaluation helps to identify the air pollution levels in different time periods. The air pollution index (API) calculation formula introduces a variety of influencing factors (such as the use frequency of sanitary facilities, air flow rate, temperature and humidity, etc.), which can effectively identify which factors have a significant impact on air pollution, thereby providing a scientific basis for improving air quality. In the formula, the changes in air pollution within a specific time period can be dynamically monitored through integral calculation. This dynamic monitoring can timely reflect the fluctuations in air quality and help relevant management departments formulate effective response measures. The air pollution index obtained by calculation can provide data support for the management and optimization of public health facilities. For example, the use time of the facility can be adjusted according to the API value, the ventilation conditions can be improved, or temporary closure can be taken when the pollution is serious. The regular release and analysis of the air pollution index can increase the public's attention to the use of sanitary facilities and the quality of environmental air, enhance the public's health awareness, and promote them to take necessary preventive measures when using public health facilities. In summary, this formula fully takes into account the use of air pollution index in public health facilities , integration start time , integration end time , integral time variable parameter , frequency of use of sanitary facilities , factors affecting air pollution in sanitation facility use behavior , air flow rate of sanitary facilities , Factors affecting ventilation efficiency of air pollution in sanitary facilities , the temperature around the sanitary facilities , factors affecting the volatilization of temperature pollution in sanitary facilities , humidity around sanitary facilities , Factors affecting the volatilization of humidity pollution in sanitary facilities , air pollutant time decay constant , correction factor for the air pollution index used by public health facilities , according to the public health facilities using the air pollution index The correlation between the above parameters constitutes a functional relationship This formula can realize the calculation process of the sanitary air pollution index of the corresponding public health facilities. At the same time, the correction coefficient of the air pollution index used by public health facilities is The introduction of can be adjusted according to the errors that occur in the calculation process, thereby improving the accuracy and applicability of the air pollution index calculation formula.

[0116] Further, step S3 includes the following steps:

[0117] Step S31: performing facility feedback semantic recognition analysis on the corresponding health facility use experience, health facility use suggestions and health facility use complaints in the health facility public feedback data to obtain health facility public use feedback semantic information;

[0118] In an embodiment of the present invention, by collecting the public's experience, suggestions and complaints about sanitary facilities from the public feedback data on sanitary facilities, which can be obtained through questionnaires, social media comments or online feedback forms, the collected data are preprocessed using natural language processing (NLP) tools, such as word segmentation tools and part-of-speech tagging tools, to extract relevant keywords and phrases. Subsequently, a semantic analysis model is established, the processed data is input into the model, and semantic recognition is performed using a deep learning algorithm. The model is trained using an annotated corpus to enhance the ability to understand the content of sanitary facility feedback, thereby identifying key information in the public's feedback, including positive and negative emotional expressions of the usage experience, forming structured semantic information, and finally obtaining semantic information of the public's feedback on sanitary facilities.

[0119] Step S32: extracting positive and negative sentiment words from the public feedback semantic information on health facilities to obtain a positive and negative sentiment word library for public feedback semantics on health facilities;

[0120] In an embodiment of the present invention, positive and negative emotional vocabulary is extracted from the semantic information of public feedback on the use of sanitation facilities obtained by previous analysis, and a positive and negative emotional dictionary is established by using a sentiment analysis tool. The emotional polarity of each feedback in the semantic information of public feedback on the use of sanitation facilities is determined, and positive emotional words (such as "clean" and "convenient") and negative emotional words (such as "dirty" and "crowded") are identified by expanding and updating the emotional dictionary. A machine learning algorithm, such as a support vector machine (SVM), is used to classify and label the emotional words to generate a vocabulary library containing positive and negative emotions. In this process, a frequency analysis of the emotional words is also required to identify the most frequently occurring emotional expressions, and finally a semantic positive and negative emotional vocabulary library of public feedback on sanitation facilities is obtained.

[0121] Step S33: performing negative emotion screening analysis on each negative emotion word in the public feedback semantic positive and negative emotion word library of health facilities, and obtaining a candidate list of negative emotion words of public feedback on health facilities;

[0122] In an embodiment of the present invention, negative emotion screening and analysis is performed on each negative emotion word in the semantic positive and negative emotion vocabulary library of public feedback on sanitary facilities, so as to further screen out the negative emotion characteristics of each negative emotion word by using the sentiment analysis algorithm, and by constructing a negative emotion feature model, these features are applied to the negative emotion words to evaluate their negativity. To ensure accuracy, the context of each negative emotion word can be analyzed to identify the negative emotion expression related to the word, and a candidate list of negative emotion words is generated, which contains all keywords that reflect the public's dissatisfaction with the use of sanitary facilities, and finally a candidate list of negative emotion words for public feedback on sanitary facilities is obtained.

[0123] Step S34: performing context association analysis on each candidate word in the candidate list of negative emotion words for public feedback on health facilities, so as to obtain the association relationship between the context sentences of health facility feedback corresponding to each candidate word; extracting abnormal facility usage words from each candidate word in the candidate list of negative emotion words for public feedback on health facilities, based on the association relationship between the context sentences of health facility feedback corresponding to each candidate word, to obtain abnormal usage words for public feedback on health facilities; performing vectorization processing on the abnormal usage words for public feedback on health facilities, so as to obtain abnormal word vectors for public health facility usage feedback;

[0124] In an embodiment of the present invention, a context association analysis is performed on each candidate word in the candidate list of negative emotion words for public feedback on sanitary facilities, so as to extract complete sentences containing candidate words by applying a text association analysis tool, construct a context association model, and analyze the relationship between words and sentences, thereby obtaining the association relationship of sanitary facility feedback context sentences corresponding to each candidate word. Then, by combining the context association relationship obtained by the previous analysis, the abnormal use of facilities words are extracted for each negative emotion word. This process requires that for each negative emotion word, whether there are key phrases or words pointing to specific abnormal use in its context, and using a keyword extraction algorithm (such as TF-IDF or TextRank) to identify abnormal expressions related to the use of sanitary facilities, such as "the faucet is broken", "the toilet has a peculiar smell", etc., the extracted abnormal words are sorted into a list, thereby obtaining the abnormal use words of public feedback on sanitary facilities. Then, by using vectorization technology (such as word embedding), the extracted abnormal use words of public feedback on sanitary facilities are converted into vectors, and the abnormal word vector of public health facility use feedback is constructed. This process ensures that the high-dimensional representation of the data can reflect the similarity of different abnormal words and their importance in public feedback, and can reveal potential facility use problems, and finally obtain the abnormal word vector of public health facility use feedback.

[0125] Step S35: Calculate the facility utilization defect score for the corresponding public health facility based on the public health facility utilization feedback abnormal word vector to obtain a public health facility utilization defect score value.

[0126] In an embodiment of the present invention, a defect score is calculated for the corresponding public health facility by combining the abnormal word vectors of the public health facility use feedback obtained in the previous analysis, so as to calculate the defect score value of each facility based on a pre-set scoring model (for example, based on a weighted average or a deep learning model) combined with the vector representation of the abnormal words. The scoring model needs to consider the number and severity of abnormal words and their frequency in the feedback. The final score is obtained by combining these factors to help identify and improve potential problems in the use of facilities, and finally obtain a public health facility use defect score value.

[0127] Further, step S35 includes the following steps:

[0128] Step S351: classify each abnormal facility usage word in the abnormal word vector of public health facility usage feedback into a problem type, so as to obtain a public health facility usage abnormal word sub-vector corresponding to each facility usage problem type, wherein each facility usage problem type includes sanitary conditions, facility damage, and service attitude;

[0129] In an embodiment of the present invention, when performing abnormal word vector analysis on feedback information on the use of public health facilities, the use feedback data of each public health facility is first extracted and converted into abnormal word vectors, and these word vectors are classified by using natural language processing (NLP) technology, and they are summarized into three major types of problems: sanitary conditions, facility damage, and service attitude. In this process, word vector models (such as Word2Vec or GloVe) are used for vectorization, and the similarity between word vectors is calculated to identify various types of abnormal words. Each type of abnormal word will be classified into a corresponding sub-vector, and finally the public health facility use abnormal word sub-vector corresponding to each facility use problem type is obtained.

[0130] Step S352: performing problem type word frequency statistics on the public health facility use abnormal word sub-vectors corresponding to each facility use problem type, and obtaining the number of public health facility use abnormal word frequencies corresponding to each facility use problem type;

[0131] In an embodiment of the present invention, the frequency statistics of abnormal words in the use of public health facilities corresponding to each classified facility use problem type are performed, so as to count each type of abnormal words by using Python's Pandas library to obtain the frequency of abnormal words in each problem type. In this process, the frequency of occurrence of all abnormal words is recorded in a data frame, and summarized and analyzed. The statistical results will show the frequency of occurrence of abnormal words in each problem type, and finally the frequency of abnormal words in the use of public health facilities corresponding to each facility use problem type is obtained.

[0132] Step S353: Based on the frequency of abnormal public health facility usage words corresponding to each facility usage problem type, the corresponding abnormal public health facility usage word sub-vector is evaluated and analyzed for public satisfaction and feedback experience, so as to obtain the public satisfaction with public health facility usage and the degree of impact on public health facility usage experience corresponding to each facility usage problem type;

[0133] In an embodiment of the present invention, the impact of public satisfaction and feedback experience is evaluated and calculated on the corresponding abnormal word sub-vectors of public health facility use by combining the abnormal word frequencies of public health facility use corresponding to each facility use problem type obtained by previous statistics, so as to determine the relationship between abnormal word frequencies and public satisfaction and feedback experience by using statistical analysis tools (such as R language or Python's SciPy library) for correlation analysis. The specific method includes using regression analysis or correlation analysis to establish a model to evaluate the impact of abnormal word frequencies on public satisfaction and feedback experience. The analysis will generate an evaluation report on the public satisfaction score and the impact of feedback experience, and finally obtain the public satisfaction with public health facility use and the impact of public health facility use experience corresponding to each facility use problem type.

[0134] Step S354: Based on the public satisfaction with the use of public health facilities corresponding to each facility use problem type and the degree of impact of the use experience of public health facilities, the facility use defect evaluation calculation formula is used to calculate the facility use defect score of the corresponding public health facilities to obtain the public health facility use defect score value.

[0135] In an embodiment of the present invention, a suitable facility use defect evaluation calculation formula is constructed by combining the public satisfaction with the use of public health facilities, the degree of impact of the use experience of public health facilities, the cleanliness of public health facilities, the corresponding importance weight coefficient, the nonlinear impact index of public health facilities, the use time of public health facilities, the use time attenuation coefficient and related parameters corresponding to each facility use problem type obtained by previous evaluation and analysis to calculate the facility use defect score for the corresponding public health facilities, so as to combine parameters such as public satisfaction, abnormal word frequency and degree of impact, and use data analysis tools (such as Excel or special evaluation software) to organize the calculation results, and quantify the calculation to obtain a defect score value. The score value is used to reflect the degree of defects in the use of public health facilities, clarify the severity of various problems, and finally obtain a public health facility use defect score value.

[0136] Furthermore, the facility utilization defect assessment calculation formula in step S354 is specifically:

[0137] ;

[0138] In the formula, Using defect score values ​​for public health facilities, is the total number of facility usage problem types, Use the Item Index parameter of the problem type for the facility. For the The public satisfaction with the use of public health facilities corresponding to each type of facility use problem, is the satisfaction importance weight coefficient, For the The degree of impact of public health facility use experience corresponding to each facility use problem type, is the user experience importance weight coefficient, For the The cleanliness of public health facilities corresponding to each type of facility use problem, is the cleanliness importance weight coefficient, is the nonlinear impact index of public health facilities, For the The time of public health facility use corresponding to each facility use problem type, is the usage time attenuation coefficient, Use a correction factor for the deficiency score value for public health facilities.

[0139] The present invention obtains a facility use defect evaluation calculation formula by using a specific mathematical model and verifying it, which is used to calculate the facility use defect score for the corresponding public health facilities. The facility use defect evaluation calculation formula can obtain a more comprehensive facility use defect score by comprehensively considering multiple factors such as satisfaction, experience impact and cleanliness. The weight coefficient and nonlinear influence index are introduced into the formula, so that the influence of different factors on the score can be reflected, which can more accurately reflect the real feelings of the user. By using the time attenuation coefficient and the correction coefficient, the score is made more dynamic and can reflect the changes in the facility status in real time. In summary, the formula fully considers the public health facility use defect score value. , the total number of facility use problem types , the item index parameter of the facility usage problem type , No. Public satisfaction with public health facilities usage corresponding to each type of facility usage problem , satisfaction importance weight coefficient , No. The impact of public health facility use experience on each facility use problem type , weight coefficient of user experience importance , No. Cleanliness of public health facilities corresponding to each type of facility use problem , cleanliness importance weight coefficient , nonlinear impact index of public health facilities , No. Public health facility usage time corresponding to each facility use problem type , using the time decay coefficient , correction factor for the public health facility use deficiency score , based on the public health facility use defect score The correlation between the above parameters constitutes a functional relationship This formula can realize the calculation process of the facility utilization defect score of the corresponding public health facilities. At the same time, the correction coefficient of the public health facility utilization defect score value is The introduction of can be adjusted according to the errors that occur in the calculation process, thereby improving the accuracy and applicability of the facility utilization defect assessment calculation formula.

[0140] Further, step S4 includes the following steps:

[0141] Step S41: performing abnormal weighting setting on the public health facility use air pollution index and the public health facility use defect score value to obtain the air pollution index weight and the facility use defect score weight;

[0142] In an embodiment of the present invention, weighted values ​​are assigned to the public health facility use air pollution index and the public health facility use defect score values ​​obtained by previous quantitative calculations, so as to determine the weights of the air pollution index and the facility use defect score by using statistical analysis methods, such as principal component analysis (PCA). In this process, the collected data needs to be normalized to ensure that indicators of different dimensions are comparable, so as to obtain a reasonable weight distribution. After the weight is determined, it is applied to subsequent data analysis to highlight the influence of important indicators in quality control testing, and finally the air pollution index weight and the facility use defect score weight are obtained.

[0143] Step S42: Based on the air pollution index weight and the facility use defect score weight and in combination with the public health facility use air pollution index and the public health facility use defect score, a quality control anomaly detection calculation is performed on the corresponding public health facility to obtain a public health facility quality control detection anomaly value;

[0144] In an embodiment of the present invention, after obtaining the air pollution index weight and the facility use defect score weight, a weighted algorithm is used to quantify the quality control abnormality values ​​of the corresponding public health facilities in combination with the public health facility use air pollution index and the public health facility use defect score value, so as to multiply the air pollution index and defect score of each facility by its weight, for example, abnormal value = air pollution index weight × public health facility use air pollution index + facility use defect score weight × public health facility use defect score value, so as to obtain a comprehensive evaluation value, so as to show the evaluation distribution of each facility, and finally quantify and calculate the quality control detection abnormality value of the public health facility.

[0145] Step S43: Compare and judge the quality control detection anomaly value of the public health facility according to the preset quality control detection anomaly threshold. When the quality control detection anomaly value of the public health facility is less than the preset quality control detection anomaly threshold, continue to perform quality control anomaly detection on the corresponding public health facility; when the quality control detection anomaly value of the public health facility is greater than or equal to the preset quality control detection anomaly threshold, perform abnormal quality control decision support on the corresponding public health facility, generate a public health facility abnormal quality control decision recommendation plan, and execute corresponding public health quality control response measures.

[0146] In an embodiment of the present invention, a comparison is made with the quality control detection anomaly value of a public health facility obtained by the previous quantitative calculation by using a preset quality control detection anomaly threshold. If the anomaly value is less than the preset threshold, the corresponding facility is continued to be subsequently monitored and the data updated to ensure that new problems that may arise are captured in a timely manner; if the anomaly value is greater than or equal to the preset threshold, the abnormal quality control decision support process is automatically triggered. The process will involve the generation of a data report, including abnormal details, possible cause analysis and recommended response measures. At this time, a decision support system (DSS) is used to integrate historical data and case analysis to provide decision makers with specific response plans, such as equipment maintenance, structural adjustments or environmental improvement measures, to ensure the normal operation of public health facilities and the protection of public health, and ultimately generate a public health facility abnormal quality control decision recommendation plan to implement corresponding public health quality control response measures.

[0147] Furthermore, the present invention also provides an intelligent analysis system for public health quality control, which is used to execute the intelligent analysis method for public health quality control as described above, and the intelligent analysis system for public health quality control includes:

[0148] The public health facility data analysis module is used to obtain the public health facility usage data, the surrounding environment data of the public health facilities and the public feedback data of the public health facilities, and perform sampling time series synchronization processing on the public health facility usage data, the surrounding environment data of the public health facilities and the public feedback data of the public health facilities, so as to obtain the corresponding public health facility usage data, public health facility environment data and public health facility feedback data within the same sampling time series variation range;

[0149] The sanitary facility air pollution analysis module is used to calculate the sanitary air pollution index of the corresponding public health facilities based on the sanitary facility usage data and the sanitary facility environment data, so as to obtain the public health facility usage air pollution index;

[0150] The health facility use defect scoring module is used to extract abnormal words in the health facility feedback data to obtain abnormal word vectors for the use of public health facilities; based on the abnormal word vectors for the use of public health facilities feedback, the corresponding public health facilities are scored for the use defect to obtain the public health facility use defect score value;

[0151] The public health abnormal quality control recommendation module is used to conduct abnormal weighted quality control analysis on the corresponding public health facilities according to the air pollution index of the use of public health facilities and the defect score of the use of public health facilities, and obtain the abnormal values ​​of the quality control detection of public health facilities; based on the abnormal values ​​of the quality control detection of public health facilities, the corresponding public health facilities are supported by abnormal quality control decisions, and abnormal quality control decision-making recommendations for public health facilities are generated to implement corresponding public health quality control response measures.

[0152] Therefore, the embodiments should be regarded as illustrative and non-restrictive from all points, and the scope of the present invention is limited by the appended claims rather than the above description, and it is therefore intended that all changes falling within the meaning and range of equivalent elements of the application documents are included in the present invention.

[0153] The above description is only a specific embodiment of the present invention, so that those skilled in the art can understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but should conform to the widest scope consistent with the principles and novel features invented herein.

Claims

1. An intelligent analysis method for public health quality control, characterized in that: The following steps are involved: Step S1: obtaining public health facility usage data, public health facility surrounding environment data and public health facility public feedback data, and performing sampling time series synchronization processing on the public health facility usage data, public health facility surrounding environment data and public health facility public feedback data, to obtain the corresponding public health facility usage data, public health facility surrounding environment data and public health facility public feedback data within the same sampling time series variation range; Step S2: Calculate the sanitary air pollution index of the corresponding public health facilities based on the sanitary facility usage data and the sanitary facility surrounding environment data to obtain the public health facility usage air pollution index; Step S3: extracting abnormal words of facility feedback from the public feedback data of health facilities to obtain abnormal word vectors of public health facility use feedback; calculating the facility use defect score of the corresponding public health facilities based on the abnormal word vectors of public health facility use feedback to obtain the public health facility use defect score value; Step S4: Perform abnormal weighted quality control analysis on the corresponding public health facilities according to the air pollution index of public health facilities use and the public health facilities use defect score value to obtain the abnormal values ​​of public health facility quality control detection; perform abnormal quality control decision support on the corresponding public health facilities based on the abnormal values ​​of public health facility quality control detection, generate a public health facility abnormal quality control decision recommendation plan, and execute corresponding public health quality control response measures.

2. The intelligent analysis method for public health quality control according to claim 1, characterized in that: Step S1 includes the following steps: Step S11: obtaining a public health planning area to be controlled, and using intelligent sensing equipment to monitor the sanitary use of corresponding public health facilities in the public health planning area to be controlled in real time, to obtain public health facility use data, wherein the public health facility use data includes the frequency of use of the health facilities and the duration of each use of the health facilities; Step S12: using environmental monitoring sensors to monitor the surrounding environment of the corresponding public health facilities in the quality control public health planning area in real time, and obtaining the surrounding environment data of the health facilities, wherein the surrounding environment data of the health facilities includes the air flow conditions of the health facilities and the temperature and humidity changes of the health facilities; Step S13: using the corresponding public feedback information collection channels in the public health planning area to be controlled to collect public feedback from the corresponding public health facilities in real time, and obtain public feedback data on health facilities, wherein the public feedback data on health facilities include health facility use experience, health facility use suggestions, and health facility use complaints; Step S14: performing timestamp format standardization processing on the public health facility usage data, the surrounding environment data of the public health facilities, and the public feedback data of the public health facilities to obtain standardized data on the use of public health facilities, standardized data on the surrounding environment of public health facilities, and standardized data on public feedback of public health facilities; Step S15: Perform sampling timing synchronization processing on the standardized data on the use of sanitary facilities, the standardized data on the surrounding environment of sanitary facilities, and the standardized data on public feedback on sanitary facilities to obtain the corresponding sanitary facility use data, sanitary facility surrounding environment data, and sanitary facility public feedback data within the same sampling timing variation range.

3. The intelligent analysis method for public health quality control according to claim 2, characterized in that: Step S2 includes the following steps: Step S21: analyzing the usage behavior pattern of the corresponding public health facilities based on the usage duration of each sanitary facility in the sanitary facility usage data to obtain the public health facility usage behavior pattern, wherein the public health facility usage behavior pattern includes a long-time usage behavior pattern and a short-time usage behavior pattern; Step S22: Based on the public health facility usage behavior pattern and the sanitary facility usage frequency in the sanitary facility usage data, an air pollution impact assessment analysis of the usage behavior of the corresponding public health facilities is performed to obtain an air pollution impact factor of the sanitary facility usage behavior; Step S23: Based on the sanitary facility air flow conditions and sanitary facility temperature and humidity changes in the sanitary facility surrounding environment data, an environmental air pollution impact assessment analysis is performed on the corresponding public health facility to obtain a sanitary facility environmental air pollution impact factor, wherein the sanitary facility environmental air pollution impact factor includes a sanitary facility air pollution ventilation efficiency impact factor, a sanitary facility temperature pollution volatilization impact factor, and a sanitary facility humidity pollution volatilization impact factor; Step S24: Based on the air pollution influencing factor of sanitary facility use behavior and the air pollution influencing factor of sanitary facility environment, the sanitary air pollution index of the corresponding public health facilities is calculated using the air pollution index calculation formula to obtain the public health facility use air pollution index.

4. The intelligent analysis method for public health quality control according to claim 3, characterized in that: Step S23 includes the following steps: Step S231: Obtain the wind speed and wind direction corresponding to the public health facility through the air flow conditions of the sanitary facility in the environmental data surrounding the sanitary facility, and calculate the dilution and diffusion rate influence of the air pollutants in the corresponding public health facility based on the wind speed and wind direction corresponding to the public health facility, so as to obtain the dilution influence rate of the air pollution in the public health facility and the diffusion influence rate of the air pollution in the public health facility; Step S232: Based on the air pollution dilution impact rate of public health facilities and the air pollution diffusion impact rate of public health facilities, an air pollution ventilation efficiency evaluation and analysis is performed on the corresponding public health facilities to obtain an air pollution ventilation efficiency impact factor of the public health facilities; Step S233: Based on the sanitary facility temperature and humidity changes in the sanitary facility surrounding environment data, air pollution volatilization impact assessment and analysis is performed on the air pollutants in the corresponding public health facilities to obtain the sanitary facility temperature pollution volatilization impact factor and the sanitary facility humidity pollution volatilization impact factor.

5. The intelligent analysis method for public health quality control according to claim 3, characterized in that: The air pollution index calculation formula in step S24 is specifically: ； In the formula, Use of air pollution index for public health facilities, is the integration start time, is the integration end time, is the integral time variable parameter, The frequency of use of sanitary facilities, Air pollution influencing factors for sanitation facility use behavior, is the sanitary facility air flow rate, is the influencing factor of ventilation efficiency of sanitary facilities air pollution, is the temperature around the sanitary facility, is the impact factor of temperature pollution volatilization in sanitary facilities, is the humidity around the sanitary facilities, is the influencing factor of humidity pollution volatilization in sanitary facilities, is the time decay constant of air pollutants, Use of air pollution index correction factors for public health facilities.

6. The intelligent analysis method for public health quality control according to claim 2, characterized in that: Step S3 includes the following steps: Step S31: performing facility feedback semantic recognition analysis on the corresponding health facility use experience, health facility use suggestions and health facility use complaints in the health facility public feedback data to obtain health facility public use feedback semantic information; Step S32: extracting positive and negative sentiment words from the public feedback semantic information on health facilities to obtain a positive and negative sentiment word library for public feedback semantics on health facilities; Step S33: performing negative emotion screening analysis on each negative emotion word in the public feedback semantic positive and negative emotion word library of health facilities, and obtaining a candidate list of negative emotion words of public feedback on health facilities; Step S34: performing context association analysis on each candidate word in the candidate list of negative emotion words for public feedback on health facilities, so as to obtain the association relationship between the context sentences of health facility feedback corresponding to each candidate word; extracting abnormal facility usage words from each candidate word in the candidate list of negative emotion words for public feedback on health facilities, based on the association relationship between the context sentences of health facility feedback corresponding to each candidate word, to obtain abnormal usage words for public feedback on health facilities; performing vectorization processing on the abnormal usage words for public feedback on health facilities, so as to obtain abnormal word vectors for public health facility usage feedback; Step S35: Calculate the facility utilization defect score for the corresponding public health facility based on the public health facility utilization feedback abnormal word vector to obtain a public health facility utilization defect score value.

7. The intelligent analysis method for public health quality control according to claim 6, characterized in that: Step S35 includes the following steps: Step S351: classify each abnormal facility usage word in the abnormal word vector of public health facility usage feedback into a problem type, so as to obtain a public health facility usage abnormal word sub-vector corresponding to each facility usage problem type, wherein each facility usage problem type includes sanitary conditions, facility damage, and service attitude; Step S352: performing problem type word frequency statistics on the public health facility use abnormal word sub-vectors corresponding to each facility use problem type, and obtaining the number of public health facility use abnormal word frequencies corresponding to each facility use problem type; Step S353: Based on the frequency of abnormal public health facility usage words corresponding to each facility usage problem type, the corresponding abnormal public health facility usage word sub-vector is evaluated and analyzed for public satisfaction and feedback experience, so as to obtain the public satisfaction with public health facility usage and the degree of impact on public health facility usage experience corresponding to each facility usage problem type; Step S354: Based on the public satisfaction with the use of public health facilities corresponding to each facility use problem type and the degree of impact of the use experience of public health facilities, the facility use defect evaluation calculation formula is used to calculate the facility use defect score of the corresponding public health facilities to obtain the public health facility use defect score value.

8. The intelligent analysis method for public health quality control according to claim 7, characterized in that: The facility utilization defect evaluation calculation formula in step S354 is specifically: ； In the formula, Using defect score values ​​for public health facilities, is the total number of facility usage problem types, Use the Item Index parameter of the problem type for the facility. For the The public satisfaction with the use of public health facilities corresponding to each type of facility use problem, is the satisfaction importance weight coefficient, For the The degree of impact of public health facility use experience corresponding to each facility use problem type, is the user experience importance weight coefficient, For the The cleanliness of public health facilities corresponding to each type of facility use problem, is the cleanliness importance weight coefficient, is the nonlinear impact index of public health facilities, For the The time of public health facility use corresponding to each facility use problem type, is the usage time attenuation coefficient, Use a correction factor for the deficiency score value for public health facilities.

9. The intelligent analysis method for public health quality control according to claim 1, characterized in that: Step S4 includes the following steps: Step S41: performing abnormal weighting setting on the public health facility use air pollution index and the public health facility use defect score value to obtain the air pollution index weight and the facility use defect score weight; Step S42: Based on the air pollution index weight and the facility use defect score weight and in combination with the public health facility use air pollution index and the public health facility use defect score, a quality control anomaly detection calculation is performed on the corresponding public health facility to obtain a public health facility quality control detection anomaly value; Step S43: Compare and judge the quality control detection anomaly value of the public health facility according to the preset quality control detection anomaly threshold. When the quality control detection anomaly value of the public health facility is less than the preset quality control detection anomaly threshold, continue to perform quality control anomaly detection on the corresponding public health facility; when the quality control detection anomaly value of the public health facility is greater than or equal to the preset quality control detection anomaly threshold, perform abnormal quality control decision support on the corresponding public health facility, generate a public health facility abnormal quality control decision recommendation plan, and execute corresponding public health quality control response measures.

10. An intelligent analysis system for public health quality control, characterized in that: The intelligent analysis method for public health quality control according to claim 1, wherein the intelligent analysis system for public health quality control comprises: The public health facility data analysis module is used to obtain the public health facility usage data, the surrounding environment data of the public health facilities and the public feedback data of the public health facilities, and perform sampling time series synchronization processing on the public health facility usage data, the surrounding environment data of the public health facilities and the public feedback data of the public health facilities, so as to obtain the corresponding public health facility usage data, the surrounding environment data of the public health facilities and the public feedback data of the public health facilities within the same sampling time series variation range; The sanitary facility air pollution analysis module is used to calculate the sanitary air pollution index of the corresponding public health facilities based on the sanitary facility usage data and the sanitary facility surrounding environment data, so as to obtain the public health facility usage air pollution index; The health facility use defect scoring module is used to extract abnormal words in the health facility feedback data to obtain abnormal word vectors for the use of public health facilities; based on the abnormal word vectors for the use of public health facilities feedback, the corresponding public health facilities are scored for the use defect to obtain the public health facility use defect score value; The public health abnormal quality control recommendation module is used to conduct abnormal weighted quality control analysis on the corresponding public health facilities according to the air pollution index of the use of public health facilities and the defect score of the use of public health facilities, and obtain the abnormal values ​​of the quality control detection of public health facilities; based on the abnormal values ​​of the quality control detection of public health facilities, the corresponding public health facilities are supported by abnormal quality control decisions, and abnormal quality control decision-making recommendations for public health facilities are generated to implement corresponding public health quality control response measures.

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