Laboratory efficient disinfection method and system based on multi-source data analysis
Through multi-source data analysis, the three-dimensional space model and disinfection strategy space of laboratory are constructed, which solves the problem of low intelligence in laboratory disinfection in the existing technology, and achieves efficient and accurate laboratory disinfection effects.
Patent Information
- Application Number
- CN202411907296.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-24
- Publication Date
- 2025-02-07
AI Technical Summary
The disinfection of existing laboratories is relatively intelligent, resulting in poor disinfection effect and low disinfection efficiency.
Through multi-source data analysis methods, the spatial distribution data and operation application information of the laboratory are collected, and the spatial model of the body is constructed, and the multi-source environmental data flow is obtained through environmental sampling detection, the cleanliness standards and disinfection correlation factors are determined, and the disinfection is constructed. The strategy space is mapped and matched, the disinfection strategy parameters are determined and graded disinfection control is carried out.
It realizes intelligent disinfection in the laboratory, improves the applicability and accuracy of the disinfection strategy, and ensures the laboratory disinfection effect and disinfection efficiency.
Smart Images
Figure CN119397253A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of data processing, and in particular to a laboratory efficient disinfection method and system based on multi-source data analysis. Background Art
[0002] The disinfection process of the laboratory is an important part of laboratory management and is directly related to the environmental hygiene and microbial control inside the laboratory. Effective disinfection can reduce bacteria, viruses and other microorganisms in the laboratory, protect the health of laboratory personnel and the accuracy of experimental results, and improve the overall operating efficiency and safety of the laboratory. However, the existing laboratory disinfection technology relies on experience or fixed disinfection cycles, and the degree of disinfection intelligence is low, resulting in poor disinfection effect and low disinfection efficiency. Summary of the invention
[0003] The present application provides an efficient laboratory disinfection method and system based on multi-source data analysis, thereby solving the technical problem that the existing technology has a low level of disinfection intelligence, resulting in poor disinfection effect and low disinfection efficiency. The application achieves the technical effect of realizing intelligent laboratory disinfection through personalized analysis of multi-source data, improving the applicability and accuracy of disinfection strategies, and thus ensuring the disinfection effect and efficiency of the laboratory.
[0004] In view of the above problems, the present invention provides a laboratory efficient disinfection method and system based on multi-source data analysis.
[0005] In the first aspect, the present application provides a laboratory efficient disinfection method based on multi-source data analysis, the method comprising: collecting and acquiring spatial distribution data information of the target laboratory, and constructing a laboratory three-dimensional spatial model based on the spatial distribution data information; segmenting the laboratory three-dimensional spatial model according to laboratory operation application information, and determining a set of laboratory equivalent spatial regions; performing environmental sampling and detection on each spatial region in the laboratory equivalent spatial region set in turn, and obtaining a set of multi-source environmental data streams of equivalent spatial regions, wherein the multi-source environmental data stream set of equivalent spatial regions includes air quality data, microbial distribution data, and environmental temperature and humidity data; performing disinfection standard analysis based on the laboratory equivalent spatial region set, and determining a set of equivalent spatial region cleanliness standards; extracting disinfection-related factors from the multi-source environmental data stream set of the equivalent spatial region, and obtaining a set of regional disinfection-related factor parameters; constructing a laboratory disinfection strategy space, using the equivalent spatial region cleanliness standard set and the regional disinfection-related factor parameter set as constraint parameters, mapping and matching them with the laboratory disinfection strategy space, determining a set of laboratory disinfection strategy parameters, and performing graded disinfection control on the target laboratory based on the set of laboratory disinfection strategy parameters.
[0006] On the other hand, the present application also provides a laboratory efficient disinfection system based on multi-source data analysis, the system comprising: a laboratory space model construction module, used to collect and obtain spatial distribution data information of the target laboratory, and construct a laboratory three-dimensional space model based on the spatial distribution data information; a space model segmentation module, used to segment the laboratory three-dimensional space model according to laboratory operation application information, and determine a set of laboratory equivalent space areas; an environmental sampling and detection module, used to perform environmental sampling and detection on each space area in the laboratory equivalent space area set in turn, and obtain a multi-source environmental data stream set of equivalent space areas, wherein the multi-source environmental data stream set of equivalent space areas includes air quality data, microbial distribution data, environmental A disinfection standard analysis module is used to perform disinfection standard analysis based on the laboratory equivalent space area set, and determine the equivalent space area cleanliness standard set; a disinfection-related factor extraction module is used to extract disinfection-related factors from the equivalent space area multi-source environmental data stream set, and obtain a regional disinfection-related factor parameter set; a hierarchical disinfection control module is used to construct a laboratory disinfection strategy space, use the equivalent space area cleanliness standard set and the regional disinfection-related factor parameter set as constraint parameters, map and match them with the laboratory disinfection strategy space, determine the laboratory disinfection strategy parameter set, and perform hierarchical disinfection control on the target laboratory based on the laboratory disinfection strategy parameter set.
[0007] One or more technical solutions provided in this application have at least the following technical effects or advantages: Because the laboratory stereoscopic space model is constructed based on the spatial distribution data information of the target laboratory, and then the laboratory stereoscopic space model is segmented according to the laboratory operation application information, and then the segmented laboratory equivalent space area set is sequentially sampled and tested for environmental sampling, and a multi-source environmental data stream set of the equivalent space area is obtained; at the same time, based on the laboratory equivalent space area set, the equivalent space area cleanliness standard set is determined, and then the disinfection-related factors of the multi-source environmental data stream set of the equivalent space area are extracted to obtain a regional disinfection-related factor parameter set; the equivalent space area cleanliness standard set and the regional disinfection-related factor parameter set are used as constraint parameters, mapped and matched with the laboratory disinfection strategy space, and the laboratory disinfection strategy parameter set is determined to perform a technical solution for hierarchical disinfection control of the target laboratory. Thus, the technical effect of realizing intelligent laboratory disinfection through personalized analysis of multi-source data, improving the applicability and accuracy of disinfection strategies, and thus ensuring the laboratory disinfection effect and disinfection efficiency is achieved.
[0008] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS
[0009] Figure 1 This is a schematic diagram of the process of the laboratory efficient disinfection method based on multi-source data analysis in this application; Figure 2 A schematic diagram of a process for determining a set of laboratory equivalent space regions in a laboratory efficient disinfection method based on multi-source data analysis in this application; Figure 3 This is a schematic diagram of the structure of the laboratory efficient disinfection system based on multi-source data analysis in this application.
[0010] Explanation of the accompanying drawings: laboratory space model construction module 11, space model segmentation module 12, environmental sampling and detection module 13, disinfection standard analysis module 14, disinfection related factor extraction module 15, graded disinfection control module 16. DETAILED DESCRIPTION
[0011] The present application provides an efficient laboratory disinfection method and system based on multi-source data analysis, thereby solving the technical problem that the existing technology has a low level of disinfection intelligence, resulting in poor disinfection effect and low disinfection efficiency. The application achieves the technical effect of realizing intelligent laboratory disinfection through personalized analysis of multi-source data, improving the applicability and accuracy of disinfection strategies, and thus ensuring the disinfection effect and efficiency of the laboratory.
[0012] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.
[0013] The present application is described below in conjunction with the drawings in the present application.
[0014] Embodiment 1, as Figure 1 As shown, the present application provides a laboratory efficient disinfection method based on multi-source data analysis, the method comprising: Step S1: Acquire spatial distribution data information of a target laboratory, and construct a three-dimensional spatial model of the laboratory based on the spatial distribution data information; Specifically, the laboratory disinfection process is an important part of laboratory management and is directly related to the environmental hygiene and microbial control within the laboratory. Effective disinfection can reduce bacteria, viruses and other microorganisms in the laboratory, ensure the health of laboratory personnel and the accuracy of experimental results, and improve the overall operating efficiency and safety of the laboratory.
[0015] In order to realize intelligent laboratory disinfection analysis, the spatial distribution data information of the target laboratory to be intelligently disinfected is first collected through the laboratory management system and on-site measurement, and the spatial distribution data information includes laboratory space structure data and laboratory functional area division, experimental equipment distribution, parameters and other related information. Then, the spatial distribution data information is modeled in the laboratory three-dimensional space through the three-dimensional modeling technology to construct a three-dimensional laboratory space model. The three-dimensional laboratory space model is a laboratory space area visualization model, which can intuitively and accurately display the laboratory space distribution parameters, and provide a visualization data basis for subsequent laboratory space segmentation and disinfection parameter analysis.
[0016] Step S2: segmenting the laboratory three-dimensional space model according to the laboratory operation application information to determine a set of laboratory equivalent space regions; like Figure 2 As shown, further, the step of determining the set of laboratory equivalent space regions in this application also includes: Extracting indicators from the laboratory operation application information to construct a laboratory application segmentation indicator set, wherein the laboratory application segmentation indicator set includes laboratory space layout, experimental operation functional area, and experimental equipment application; Performing a priority level analysis according to the laboratory application segmentation indicator set to obtain segmentation indicator priority level information, and determining the laboratory application segmentation level indicator set according to the segmentation indicator priority level information; Based on the laboratory application segmentation level indicator set, the laboratory three-dimensional space model is sequentially spatially segmented and marked to obtain an indicator space segmentation region set and a segmentation region indicator feature label set; The indicator space segmentation region set is clustered and integrated according to the segmentation region indicator feature label set to determine the laboratory equivalent space region set.
[0017] Specifically, since different areas of the laboratory have different requirements for disinfection standards, the three-dimensional space model of the laboratory is segmented according to the laboratory operation application information. Specifically, the laboratory operation application information is firstly subjected to index extraction, wherein the laboratory operation application information is the relevant application function information of each area of the laboratory. By segmenting the laboratory operation application information and extracting the associated indexes, a set of laboratory application segmentation indexes is constructed. The set of laboratory application segmentation indexes is the laboratory space area segmentation basis index, including laboratory space layout, such as unit combination plane layout, double corridor plane layout, etc.; experimental operation function area, such as sample processing area, experimental operation area, rest area, etc.; experimental equipment application, such as heating equipment, metering equipment, testing instruments, etc. Priority level analysis is performed based on the set of laboratory application segmentation indexes, that is, the priority division degree of each application segmentation index is analyzed, and the priority level can be determined by the regional division fineness, so as to obtain the segmentation index priority level information, and the segmentation index priority level information is the segmentation index priority level, which is usually prioritized from large to small for laboratory space layout, experimental operation function area, and experimental equipment application.
[0018] According to the segmentation index priority level information, the laboratory application segmentation level index set is determined, and the laboratory application segmentation level index set is the segmentation index information arranged according to the priority level size. Then, based on the laboratory application segmentation level index set, the laboratory three-dimensional space model is spatially segmented in turn, and the spatial area segmented according to the level index is marked with indicator features, such as laboratory space layout type, experimental operation function area type, experimental equipment application type and other area labels, to obtain the corresponding indicator space segmentation area set after division and the marked segmentation area indicator feature label set. The indicator space segmentation area set is clustered and integrated according to the segmentation area indicator feature label set, that is, each indicator space segmentation area with the same segmentation area indicator feature label is clustered into one category, and the laboratory equivalent space area set after the same feature label sequence type classification is determined. Rapid segmentation of laboratory space areas based on multi-level indicators is achieved, the accuracy of area segmentation is improved, and the accuracy of personalized analysis of laboratory disinfection is ensured.
[0019] Step S3: performing environmental sampling and detection on each space area in the laboratory equivalent space area set in turn to obtain a multi-source environmental data stream set of the equivalent space area, wherein the multi-source environmental data stream set of the equivalent space area includes air quality data, microbial distribution data, and environmental temperature and humidity data; Furthermore, the step of obtaining a set of multi-source environmental data streams in an equivalent space region also includes: The ambient air and space surface multi-point sampling is sequentially performed on the laboratory equivalent space area set to obtain a laboratory equivalent space sample set; Formulate a sample component detection procedure, and perform component extraction and analysis on the laboratory equivalent space sample set based on the sample component detection procedure to obtain the air quality data and microbial distribution data; The environmental temperature and humidity data are obtained in real time by arranging temperature and humidity sensors in the laboratory equivalent space area set; Based on the air quality data, microbial distribution data and the environmental temperature and humidity data, a set of multi-source environmental data streams in the equivalent space region is generated.
[0020] Specifically, the spatial environment sampling and detection is carried out on each spatial area in the laboratory equivalent spatial area set in turn. Specifically, the ambient air of the laboratory equivalent spatial area set is firstly sampled in turn; and the spatial surface, including the equipment surface, the operating table surface and other multi-point sampling, so as to obtain a laboratory equivalent spatial sample set, including the ambient air samples of each spatial area and the spatial area surface samples. Then a sample component detection procedure is formulated. The sample component detection procedure is a component detection step for the spatial sample, which can be set by the laboratory test conditions, such as mass spectrometer detection, analytical extraction, etc. Based on the sample component detection procedure, the component extraction and analysis of the laboratory equivalent spatial sample set is carried out to obtain the laboratory spatial area environmental air quality data, including the types and proportions of pollutants such as air-suspended microorganisms and bacteria; and the microbial distribution data corresponding to the spatial surface samples, including the microbial distribution type, density, etc. At the same time, the temperature and humidity sensors are deployed in the laboratory equivalent spatial area set to monitor and obtain the environmental temperature and humidity data of each spatial area in real time. Based on the air quality data, microbial distribution data and the environmental temperature and humidity data, a set of multi-source environmental data streams of equivalent spatial regions is generated, which is the multi-source detection environmental data of each spatial region of the laboratory, including air quality data, microbial distribution data, and environmental temperature and humidity data. The comprehensiveness of laboratory spatial environmental data detection and acquisition is improved, and personalized collection of spatial regional environmental data is realized, thereby ensuring the applicability and accuracy of laboratory spatial area disinfection.
[0021] Step S4: performing disinfection standard analysis on the equivalent space area sets of the laboratory respectively to determine the cleanliness standard set of the equivalent space areas; Specifically, due to different requirements for experimental environment quality, the disinfection requirements for each space area in the laboratory are also different. Therefore, disinfection standard analysis is performed based on the equivalent space area set of the laboratory. According to the experimental application requirements of each laboratory space area, the regional pollutant concentration limit is determined, and then the equivalent space area cleanliness standard set is obtained. The equivalent space area cleanliness standard set is the maximum pollutant concentration limit standard for each equivalent area space. Personalized analysis of laboratory disinfection standards is achieved to ensure the applicability of disinfection effects for each space area in the laboratory and improve disinfection efficiency.
[0022] Step S5: extracting disinfection-related factors from the multi-source environmental data stream set of the equivalent space region to obtain a set of regional disinfection-related factor parameters; Furthermore, the step of obtaining the set of parameters of factors associated with regional disinfection, in this application, further includes: Evaluate the pollutant ratio of the air quality data to obtain a set of equivalent regional air pollution parameters; Based on the microbial distribution data, determining a microbial distribution type, a microbial distribution density, and a microbial distribution size; Determining a set of equivalent area microbial contamination parameters according to the microbial distribution type, microbial distribution density, and microbial distribution size; Based on the environmental temperature and humidity data, a catalytic disinfection impact analysis is performed on the equivalent area air pollution parameter set and the equivalent area microbial pollution parameter set to obtain an equivalent area air disinfection parameter set and an equivalent area microbial disinfection parameter set; The equivalent area air disinfection parameter set and the equivalent area microbial disinfection parameter set are merged to determine the area disinfection associated factor parameter set.
[0023] Furthermore, the application steps also include: Sampling and monitoring the target laboratory according to a preset time frequency to obtain a time series data stream of laboratory multi-source environmental monitoring; Conducting pollutant index evaluation on the laboratory multi-source environmental monitoring time series data stream in sequence to obtain laboratory time series pollutant index change information; Generate a pollutant distribution parameter change curve according to the laboratory time series pollutant index change information, and perform curvature analysis on the pollutant distribution parameter change curve to determine the pollutant distribution parameter increment rate information; The set of parameters of the regional disinfection-related factors is predicted and supplemented based on the pollutant distribution parameter value-added rate information.
[0024] Specifically, the disinfection-related factors are extracted from the multi-source environmental data stream set of the equivalent space area, that is, the related disinfection parameters are analyzed based on the current environmental monitoring data of the laboratory space area. First, the pollutant proportion of the air quality data in the multi-source environmental data is evaluated, and the proportion of pollutants such as microorganisms and bacteria that need to be disinfected is counted to obtain the corresponding equivalent area air pollution parameter set, which includes the type of air pollutants and air proportion parameters of each laboratory space area. At the same time, based on the microbial distribution data, the microbial distribution parameters are extracted and determined, including the microbial distribution type, microbial distribution density and microbial distribution size. According to the microbial distribution type, microbial distribution density and microbial distribution size, the surface microbial contamination information corresponding to each space area of the laboratory is determined, that is, the equivalent area microbial contamination parameter set.
[0025] Since the temperature and humidity in the laboratory have a significant impact on the reproduction and spread of pathogens, the catalytic disinfection impact analysis is performed on the equivalent area air pollution parameter set and the equivalent area microbial pollution parameter set based on the environmental temperature and humidity data. Through biological pathogen simulation, the type and concentration of pollutants and the current temperature and humidity are analyzed to promote the growth of pathogens, and the equivalent area air disinfection parameter set and the equivalent area microbial disinfection parameter set after the additive influence under the temperature and humidity environment are obtained. The equivalent area air disinfection parameter set and the equivalent area microbial disinfection parameter set are merged to determine the regional disinfection associated factor parameter set, which includes the target air pollutant parameters and surface microbial pollutant parameters that need to be disinfected in each spatial area. Improve the comprehensiveness and accuracy of the disinfection associated factor parameter analysis, thereby ensuring the disinfection effect of the laboratory space area.
[0026] In order to ensure the practical applicability of laboratory disinfection, the target laboratory is sampled and monitored according to the preset time frequency, wherein the preset time frequency is the frequency of laboratory environmental testing, which can be set according to the needs, for example, the laboratory environment sampling and testing is set every hour, and the samples of each time period are tested through the sample component detection program to obtain the environmental testing data arranged in time series, that is, the laboratory multi-source environmental monitoring time series data stream. The pollutant index of the laboratory multi-source environmental monitoring time series data stream is evaluated in sequence, that is, the pollutant concentration is determined in sequence before and after the time series, and then the index is evaluated based on the pollutant concentration. The weighted mean of the concentration of each type of pollutant can be used as the pollutant index of the time series space area, and the pollutant index is arranged in time series to obtain the corresponding laboratory time series pollutant index change information.
[0027] A curve graph is drawn based on the laboratory time series pollutant index change information to generate a pollutant distribution parameter change curve, which is used to indicate the relationship between laboratory pollutant concentration and time. The pollutant distribution parameter change curve is subjected to curvature analysis, that is, the curve is differentiated and its change rate information is calculated to determine the pollutant distribution parameter value-added rate information, which is used to indicate the distribution value growth of laboratory environmental pollutants. Based on the pollutant distribution parameter value-added rate information, the regional disinfection-related factor parameter set is predicted and supplemented to predict the growth of pollutant distribution concentrations that need to be disinfected in each spatial area over time. Realize real-time monitoring of laboratory environmental pollutants, improve the comprehensiveness of pollutant monitoring and the accuracy of distribution prediction, and thus ensure the laboratory disinfection effect.
[0028] Step S6: Construct a laboratory disinfection strategy space, use the equivalent space area cleanliness standard set and the area disinfection associated factor parameter set as constraint parameters, map and match them with the laboratory disinfection strategy space, determine the laboratory disinfection strategy parameter set, and perform graded disinfection control on the target laboratory based on the laboratory disinfection strategy parameter set.
[0029] Furthermore, the step of determining the laboratory disinfection strategy parameter set in this application also includes: According to the constraint parameters, setting spatial disinfection feature dimension information; Arrange and integrate the laboratory disinfection strategy space according to the spatial disinfection feature dimension information to obtain a laboratory disinfection feature strategy space; A similarity algorithm is used to calculate the similarity between the constraint parameter and the laboratory disinfection feature strategy space, and a laboratory disinfection feature strategy memory library is obtained by proportional screening; The disinfection effect fitness function is used to perform disinfection effect optimization analysis on the laboratory disinfection feature strategy memory library, and the laboratory disinfection strategy parameter set is output.
[0030] Furthermore, the application steps also include: The whole process of the experimenter's activities is monitored through monitoring equipment to obtain the experimenter's regional activity parameter information and experimental process operation information; Perform pollutant diffusion prediction based on the experimental personnel's regional activity parameter information and the experimental process operation information to obtain pollutant diffusion prediction parameter information; Determining the predicted cleanliness information of the laboratory space according to the pollutant diffusion prediction parameter information and the pollutant distribution parameter value-added rate information; The laboratory disinfection strategy parameter set is modified and optimized based on the predicted cleanliness information of the laboratory space.
[0031] Specifically, a laboratory disinfection strategy space can be constructed by data mining technology, etc. The laboratory disinfection strategy space is the laboratory historical disinfection data, including laboratory disinfection monitoring data, laboratory disinfection program data and disinfection effect data. The equivalent space regional cleanliness standard set and the regional disinfection associated factor parameter set are used as constraint parameters, and are mapped and matched with the laboratory disinfection strategy space to analyze the laboratory disinfection program parameters. First, according to the constraint parameters, the spatial disinfection feature dimension information is set, and the spatial disinfection feature dimension information is the disinfection data feature dimension, including and corresponding to the equivalent space regional cleanliness standard and regional disinfection associated factor parameter type. Then the laboratory disinfection strategy space is arranged and integrated according to the spatial disinfection feature dimension information, that is, the laboratory disinfection monitoring data in the strategy space is arranged according to the spatial disinfection feature dimension information, and the laboratory disinfection feature strategy space after the dimension feature arrangement is integrated to improve the subsequent program parameter analysis and matching efficiency. The constraint parameters and the laboratory disinfection feature strategy space can be similarity calculated using a similarity algorithm such as cosine similarity to determine the similarity information between each historical data in the laboratory disinfection feature strategy space and the laboratory disinfection feature. Then, the strategy space data after similarity calculation is arranged in descending order of similarity, and the screening ratio is set according to the calculation efficiency requirements. For example, historical data with similarity in the top 10% can be screened proportionally, and then a laboratory disinfection feature strategy memory library is formed to reduce the optimization range of disinfection strategy parameters and improve the efficiency of disinfection parameter optimization analysis.
[0032] The disinfection effect fitness function is used to perform a disinfection effect optimization analysis on the laboratory disinfection feature strategy memory library, wherein the disinfection effect fitness function is a disinfection effect evaluation function, which can be generated by fitting indicators such as sterilization rate and residue removal. Exemplarily, the disinfection effect fitness function is: , obtained by weighted fitting of indicators, where Characterize the sterilization rate weight, is the empirical function of sterilization rate effect, Characterize the residue removal weight, is the empirical function of residue removal effect, is the disinfection strategy parameter of the i-th group, and The sum of the weights is 1. The higher the fitness, the better the laboratory disinfection effect under the disinfection scheme parameters. The disinfection effect of each disinfection scheme parameter in the memory bank is evaluated through the disinfection effect fitness function, and the set of laboratory disinfection strategy parameters with the largest fitness is output as the optimal laboratory disinfection scheme parameters, including disinfection methods, equipment, duration, route, etc. And based on the laboratory disinfection strategy parameter set, the target laboratory is graded for disinfection control, that is, each laboratory space area is disinfected according to the applicable scheme according to the laboratory disinfection strategy parameter set, to ensure the actual disinfection effect of each space area and improve the applicability and accuracy of the disinfection strategy.
[0033] Since laboratory personnel operations and personnel flow are also important factors affecting the laboratory disinfection effect, the monitoring equipment is used to monitor the entire process of the laboratory personnel activity process, and obtain the corresponding laboratory personnel area activity parameter information, including personnel flow, personnel density, etc.; and experimental process operation information, including experimental operation type, experimental process generation of pollutants, etc. According to the experimental personnel area activity parameter information and experimental process operation information, pollutant diffusion prediction can be performed, and the prediction model can be trained by historical pollutant diffusion data to predict the current experimental personnel activity monitoring parameters, and obtain pollutant diffusion prediction parameter information, which includes the diffusion growth rate of each type of pollutant. According to the pollutant diffusion prediction parameter information and the pollutant distribution parameter value-added rate information, each laboratory space area is analyzed for pollutant growth, and the laboratory space prediction cleanliness information is determined based on the distribution parameters after the pollutant growth. The laboratory space prediction cleanliness information is the parameter information to be disinfected after the preset period of the laboratory space area. Based on the laboratory space prediction cleanliness information, the laboratory disinfection strategy parameter set is modified and optimized, such as increasing the disinfection frequency, optimizing the disinfection route, etc. Improve the applicability and practical applicability of the disinfection strategy, thereby ensuring the laboratory disinfection effect and disinfection efficiency.
[0034] In summary, the laboratory efficient disinfection method and system based on multi-source data analysis provided by this application has the following technical effects: Because the laboratory stereoscopic space model is constructed based on the spatial distribution data information of the target laboratory, and then the laboratory stereoscopic space model is segmented according to the laboratory operation application information, and then the segmented laboratory equivalent space area set is sequentially sampled and tested for environmental sampling, and a multi-source environmental data stream set of the equivalent space area is obtained; at the same time, based on the laboratory equivalent space area set, the equivalent space area cleanliness standard set is determined, and then the disinfection-related factors of the multi-source environmental data stream set of the equivalent space area are extracted to obtain a regional disinfection-related factor parameter set; the equivalent space area cleanliness standard set and the regional disinfection-related factor parameter set are used as constraint parameters, mapped and matched with the laboratory disinfection strategy space, and the laboratory disinfection strategy parameter set is determined to perform a technical solution for hierarchical disinfection control of the target laboratory. Thus, the technical effect of realizing intelligent laboratory disinfection through personalized analysis of multi-source data, improving the applicability and accuracy of disinfection strategies, and thus ensuring the laboratory disinfection effect and disinfection efficiency is achieved.
[0035] Embodiment 2, based on the same inventive concept as the laboratory efficient disinfection method based on multi-source data analysis in the above embodiment, the present invention also provides a laboratory efficient disinfection system based on multi-source data analysis, such as Figure 3 As shown, the system comprises: The laboratory space model building module 11 is used to collect and obtain the spatial distribution data information of the target laboratory, and build a three-dimensional space model of the laboratory based on the spatial distribution data information; The space model segmentation module 12 is used to segment the laboratory three-dimensional space model according to the laboratory operation application information to determine a set of laboratory equivalent space regions; The environmental sampling and detection module 13 is used to perform environmental sampling and detection on each space area in the equivalent space area set of the laboratory in turn, and obtain a multi-source environmental data stream set of the equivalent space area, wherein the multi-source environmental data stream set of the equivalent space area includes air quality data, microbial distribution data, and environmental temperature and humidity data; A disinfection standard analysis module 14 is used to perform disinfection standard analysis based on the laboratory equivalent space area set to determine the cleanliness standard set of the equivalent space area; The disinfection-related factor extraction module 15 is used to extract disinfection-related factors from the multi-source environmental data stream set of the equivalent space area to obtain a set of regional disinfection-related factor parameters; The hierarchical disinfection control module 16 is used to construct a laboratory disinfection strategy space, use the equivalent space area cleanliness standard set and the area disinfection associated factor parameter set as constraint parameters, map and match them with the laboratory disinfection strategy space, determine the laboratory disinfection strategy parameter set, and perform hierarchical disinfection control on the target laboratory based on the laboratory disinfection strategy parameter set.
[0036] Furthermore, the system also includes: A segmentation index extraction unit, used to extract indicators from the laboratory operation application information and construct a laboratory application segmentation index set, wherein the laboratory application segmentation index set includes laboratory space layout, experimental operation functional area, and experimental equipment application; A priority level analysis unit, configured to perform a priority level analysis based on the laboratory application segmentation indicator set to obtain segmentation indicator priority level information, and determine the laboratory application segmentation level indicator set based on the segmentation indicator priority level information; A space segmentation marking unit, used to sequentially perform space segmentation marking on the laboratory three-dimensional space model based on the laboratory application segmentation level indicator set, to obtain an indicator space segmentation region set and a segmentation region indicator feature label set; The equivalent space region set determination unit is used to cluster and integrate the index space segmentation region set according to the segmentation region index feature label set to determine the laboratory equivalent space region set.
[0037] Furthermore, the system also includes: A spatial multi-point sampling unit is used to sequentially perform multi-point sampling of ambient air and spatial surface on the laboratory equivalent spatial area set to obtain a laboratory equivalent spatial sample set; A component extraction and analysis unit, used to formulate a sample component detection procedure, and perform component extraction and analysis on the laboratory equivalent space sample set based on the sample component detection procedure to obtain the air quality data and microbial distribution data; An environmental temperature and humidity data acquisition unit, used to acquire the environmental temperature and humidity data in real time by arranging temperature and humidity sensors in the laboratory equivalent space area set; The multi-source environmental data stream generating unit is used to generate the multi-source environmental data stream set of the equivalent space area based on the air quality data, microbial distribution data and the environmental temperature and humidity data.
[0038] Furthermore, the system also includes: A pollutant proportion evaluation unit, used to evaluate the pollutant proportion of the air quality data and obtain an equivalent regional air pollution parameter set; a microorganism distribution parameter determination unit, for determining a microorganism distribution type, a microorganism distribution density, and a microorganism distribution size based on the microorganism distribution data; A microbial contamination parameter determination unit, used to determine a set of microbial contamination parameters of an equivalent region according to the microbial distribution type, microbial distribution density and microbial distribution size; A catalytic disinfection impact analysis unit, used to perform a catalytic disinfection impact analysis on the equivalent area air pollution parameter set and the equivalent area microbial pollution parameter set based on the environmental temperature and humidity data, to obtain an equivalent area air disinfection parameter set and an equivalent area microbial disinfection parameter set; The disinfection parameter fusion unit is used to fuse the equivalent area air disinfection parameter set and the equivalent area microbial disinfection parameter set to determine the area disinfection associated factor parameter set.
[0039] Furthermore, the system also includes: A feature dimension setting unit, used to set spatial disinfection feature dimension information according to the constraint parameters; A space arrangement and integration unit, used to arrange and integrate the laboratory disinfection strategy space according to the spatial disinfection feature dimension information to obtain a laboratory disinfection feature strategy space; A similarity calculation unit, used for performing similarity calculation on the constraint parameter and the laboratory disinfection feature strategy space by using a similarity algorithm, and proportionally screening to obtain a laboratory disinfection feature strategy memory library; The disinfection effect optimization analysis unit is used to perform disinfection effect optimization analysis on the laboratory disinfection feature strategy memory library using a disinfection effect fitness function, and output the laboratory disinfection strategy parameter set.
[0040] Furthermore, the system also includes: A laboratory sampling and monitoring unit, used to perform sampling and monitoring of the target laboratory according to a preset time frequency, and obtain a time series data stream of laboratory multi-source environmental monitoring; A pollutant index evaluation unit, used to sequentially evaluate the pollutant index of the laboratory multi-source environmental monitoring time series data stream to obtain laboratory time series pollutant index change information; A parameter increment rate determination unit, used to generate a pollutant distribution parameter change curve according to the laboratory time series pollutant index change information, and perform curvature analysis on the pollutant distribution parameter change curve to determine the pollutant distribution parameter increment rate information; The associated factor parameter prediction and supplementation unit is used to predict and supplement the regional disinfection associated factor parameter set based on the pollutant distribution parameter value-added rate information.
[0041] Furthermore, the system also includes: The laboratory full-process monitoring unit is used to monitor the activity process of the experimenter through monitoring equipment, and obtain the regional activity parameter information of the experimenter and the experimental process operation information; A pollutant diffusion prediction unit, used to perform pollutant diffusion prediction based on the experimental personnel's regional activity parameter information and the experimental process operation information to obtain pollutant diffusion prediction parameter information; A predicted cleanliness information determination unit, used to determine the predicted cleanliness information of the laboratory space according to the pollutant diffusion prediction parameter information and the pollutant distribution parameter value-added rate information; A parameter correction and optimization unit is used to correct and optimize the laboratory disinfection strategy parameter set based on the predicted cleanliness information of the laboratory space.
[0042] The foregoing Figure 1 The various variations and specific examples of the laboratory efficient disinfection method based on multi-source data analysis in Example 1 are also applicable to the laboratory efficient disinfection system based on multi-source data analysis in this embodiment. Through the above detailed description of the laboratory efficient disinfection method based on multi-source data analysis, technical personnel in this field can clearly know the implementation method of the laboratory efficient disinfection system based on multi-source data analysis in this embodiment, so for the sake of brevity of the specification, it will not be described in detail here.
[0043] This specification and the accompanying drawings are merely exemplary illustrations of the present application, but the protection scope of the present application is not limited thereto. It should be noted that any technician familiar with the technical field can easily think of changes or replacements within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. In some cases, the actions or steps recorded in the present application can be performed in an order different from that in the embodiment and the desired results can still be achieved. In addition, the process depicted in the accompanying drawings does not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
Claims
1. A highly efficient laboratory disinfection method based on multi-source data analysis, characterized in that: The method comprises: Collect and obtain spatial distribution data information of the target laboratory, and construct a three-dimensional spatial model of the laboratory based on the spatial distribution data information; Segmenting the laboratory three-dimensional space model according to the laboratory operation application information to determine a set of laboratory equivalent space regions; Performing environmental sampling and testing on each space area in the laboratory equivalent space area set in turn to obtain a multi-source environmental data stream set of the equivalent space area, wherein the multi-source environmental data stream set of the equivalent space area includes air quality data, microbial distribution data, and environmental temperature and humidity data; Based on the set of equivalent space areas of the laboratory, disinfection standard analysis is performed respectively to determine a set of cleanliness standards for equivalent space areas; Extracting disinfection-related factors from the multi-source environmental data stream set of the equivalent space region to obtain a set of regional disinfection-related factor parameters; Construct a laboratory disinfection strategy space, take the equivalent space area cleanliness standard set and the area disinfection associated factor parameter set as constraint parameters, map and match them with the laboratory disinfection strategy space, determine the laboratory disinfection strategy parameter set, and perform graded disinfection control on the target laboratory based on the laboratory disinfection strategy parameter set.
2. The method according to claim 1, characterized in that The step of determining a set of laboratory equivalent space regions comprises: Extracting indicators from the laboratory operation application information to construct a laboratory application segmentation indicator set, wherein the laboratory application segmentation indicator set includes laboratory space layout, experimental operation functional area, and experimental equipment application; Performing a priority level analysis according to the laboratory application segmentation indicator set to obtain segmentation indicator priority level information, and determining the laboratory application segmentation level indicator set according to the segmentation indicator priority level information; Based on the laboratory application segmentation level indicator set, the laboratory three-dimensional space model is sequentially spatially segmented and marked to obtain an indicator space segmentation region set and a segmentation region indicator feature label set; The indicator space segmentation region set is clustered and integrated according to the segmentation region indicator feature label set to determine the laboratory equivalent space region set.
3. The method according to claim 1, characterized in that The step of obtaining a set of multi-source environmental data streams in an equivalent space region includes: The ambient air and space surface multi-point sampling is sequentially performed on the laboratory equivalent space area set to obtain a laboratory equivalent space sample set; Formulate a sample component detection procedure, and perform component extraction and analysis on the laboratory equivalent space sample set based on the sample component detection procedure to obtain the air quality data and microbial distribution data; The environmental temperature and humidity data are obtained in real time by arranging temperature and humidity sensors in the laboratory equivalent space area set; Based on the air quality data, microbial distribution data and the environmental temperature and humidity data, a set of multi-source environmental data streams in the equivalent space region is generated.
4. The method according to claim 1, characterized in that The step of obtaining a set of parameters of factors associated with regional disinfection includes: Evaluate the pollutant ratio of the air quality data to obtain a set of equivalent regional air pollution parameters; Based on the microbial distribution data, determining a microbial distribution type, a microbial distribution density, and a microbial distribution size; Determining a set of equivalent area microbial contamination parameters according to the microbial distribution type, microbial distribution density, and microbial distribution size; Based on the environmental temperature and humidity data, a catalytic disinfection impact analysis is performed on the equivalent area air pollution parameter set and the equivalent area microbial pollution parameter set to obtain an equivalent area air disinfection parameter set and an equivalent area microbial disinfection parameter set; The equivalent area air disinfection parameter set and the equivalent area microbial disinfection parameter set are merged to determine the area disinfection associated factor parameter set.
5. The method according to claim 1, characterized in that The step of determining a set of laboratory disinfection strategy parameters includes: According to the constraint parameters, setting spatial disinfection feature dimension information; Arrange and integrate the laboratory disinfection strategy space according to the spatial disinfection feature dimension information to obtain a laboratory disinfection feature strategy space; A similarity algorithm is used to calculate the similarity between the constraint parameter and the laboratory disinfection feature strategy space, and a laboratory disinfection feature strategy memory library is obtained by proportional screening; The disinfection effect fitness function is used to perform disinfection effect optimization analysis on the laboratory disinfection feature strategy memory library, and the laboratory disinfection strategy parameter set is output.
6. The method according to claim 1, characterized in that The method comprises: Sampling and monitoring the target laboratory according to a preset time frequency to obtain a time series data stream of laboratory multi-source environmental monitoring; Conducting pollutant index evaluation on the laboratory multi-source environmental monitoring time series data stream in sequence to obtain laboratory time series pollutant index change information; Generate a pollutant distribution parameter change curve according to the laboratory time series pollutant index change information, and perform curvature analysis on the pollutant distribution parameter change curve to determine the pollutant distribution parameter increment rate information; The set of parameters of the regional disinfection-related factors is predicted and supplemented based on the pollutant distribution parameter value-added rate information.
7. The method according to claim 6, characterized in that The method comprises: The whole process of the experimenter's activities is monitored through monitoring equipment to obtain the experimenter's regional activity parameter information and experimental process operation information; Perform pollutant diffusion prediction based on the experimental personnel's regional activity parameter information and the experimental process operation information to obtain pollutant diffusion prediction parameter information; Determining the predicted cleanliness information of the laboratory space according to the pollutant diffusion prediction parameter information and the pollutant distribution parameter value-added rate information; The laboratory disinfection strategy parameter set is modified and optimized based on the predicted cleanliness information of the laboratory space.
8. The laboratory efficient disinfection system based on multi-source data analysis is characterized by: The system comprises: A laboratory space model building module is used to collect and obtain the spatial distribution data information of the target laboratory, and build a three-dimensional space model of the laboratory based on the spatial distribution data information; A space model segmentation module is used to segment the three-dimensional space model of the laboratory according to the laboratory operation application information to determine a set of equivalent space regions of the laboratory; An environmental sampling and detection module is used to perform environmental sampling and detection on each space area in the equivalent space area set of the laboratory in turn, and obtain a multi-source environmental data stream set of the equivalent space area, wherein the multi-source environmental data stream set of the equivalent space area includes air quality data, microbial distribution data, and environmental temperature and humidity data; A disinfection standard analysis module, used to perform disinfection standard analysis based on the laboratory equivalent space area set, and determine the cleanliness standard set of the equivalent space area; A disinfection-related factor extraction module is used to extract disinfection-related factors from the multi-source environmental data stream set of the equivalent space area to obtain a regional disinfection-related factor parameter set; The hierarchical disinfection control module is used to construct a laboratory disinfection strategy space, take the equivalent space area cleanliness standard set and the area disinfection associated factor parameter set as constraint parameters, map and match them with the laboratory disinfection strategy space, determine the laboratory disinfection strategy parameter set, and perform hierarchical disinfection control on the target laboratory based on the laboratory disinfection strategy parameter set.