Online Monitoring and Early Warning Method and System for Bioaerosols

Abstract

The present invention discloses an online monitoring and early warning method and system for bioaerosols, belonging to the field of bioaerosol monitoring. The method includes: dynamically monitoring bioaerosols at a first position in a target scenario to obtain first real-time monitoring data; analyzing the first real-time monitoring data to obtain a first bioaerosol concentration; transmitting the first real-time monitoring data and the first bioaerosol concentration to a monitoring and early warning center; analyzing the first real-time monitoring data by a monitoring calculation unit to obtain a first predicted bioaerosol concentration; dynamically displaying the first predicted bioaerosol concentration and the first bioaerosol concentration through an early warning display unit, and generating a first risk early warning according to the dynamic display information. This application solves the technical problems of single bioaerosol monitoring data, slow response, and inaccurate early warning in the prior art; and achieves the technical effects of comprehensively monitoring and timely responding to bioaerosols and improving the accuracy of early warning.

Description

Technical Field

[0001] The present invention relates to the field of bioaerosol monitoring, and particularly to an online monitoring and early warning method and system for bioaerosols. Background Art

[0002] As an important environmental pollutant, the monitoring and prevention of bioaerosols have attracted great attention. Existing bioaerosol monitoring mostly uses a single optical sensor for detection, and the monitoring data is incomplete, making it impossible to conduct multi-dimensional monitoring and analysis. At the same time, the monitoring data needs to be remotely transmitted through the network to the center for analysis and processing, resulting in a certain time delay and slow response speed. In addition, the early warning judgment mainly relies on the analysis results of the monitoring center, lacking verification of the original data from the monitoring terminal, and there is a certain degree of uncertainty. Generally speaking, there is still room for improvement in the comprehensiveness, response speed, and early warning accuracy of existing bioaerosol monitoring. Summary of the Invention

[0003] This application provides an online monitoring and early warning method and system for bioaerosols, aiming to solve the technical problems of single monitoring data, slow response, and inaccurate early warning in existing bioaerosol monitoring.

[0004] In view of the above problems, this application provides an online monitoring and early warning method and system for bioaerosols.

[0005] In the first aspect disclosed in this application, an online monitoring and early warning method for bioaerosols is provided. The method includes: dynamically monitoring bioaerosols at a first position in a target scenario through a first dual-channel monitoring device in a distributed dual-channel monitoring device to obtain first real-time monitoring data; analyzing the first real-time monitoring data through a first computing center in the first dual-channel monitoring device to obtain a first bioaerosol concentration, and the first bioaerosol concentration has an identifier of the first position information of the first position; transmitting the first real-time monitoring data and the first bioaerosol concentration to a monitoring and early warning center through an information transmission network; analyzing the first real-time monitoring data through a monitoring computing unit of the monitoring and early warning center to obtain a first bioaerosol predicted concentration; dynamically displaying the first bioaerosol predicted concentration and the first bioaerosol concentration through an early warning display unit of the monitoring and early warning center, and generating a first risk early warning based on the dynamic display information.

[0006] Another aspect disclosed in the present application provides an online monitoring and early warning system for bioaerosols, which includes: an aerosol dynamic monitoring module for dynamically monitoring bioaerosols at a first position in a target scenario through a first dual-channel monitoring device in a distributed dual-channel monitoring device to obtain first real-time monitoring data; a monitoring data analysis unit for analyzing the first real-time monitoring data through a first computing center in the first dual-channel monitoring device to obtain a first bioaerosol concentration, and the first bioaerosol concentration has an identifier of the first position information of the first position; an information transmission module for transmitting the first real-time monitoring data and the first bioaerosol concentration to a monitoring and early warning center through an information transmission network; an aerosol predicted concentration module for analyzing the first real-time monitoring data through a monitoring computing unit of the monitoring and early warning center to obtain a first bioaerosol predicted concentration; and a risk early warning generation module for dynamically displaying the first bioaerosol predicted concentration and the first bioaerosol concentration through an early warning display unit of the monitoring and early warning center, and generating a first risk early warning according to the dynamic display information.

[0007] One or more technical solutions provided in the present application have at least the following technical effects or advantages:

[0008] By adopting a distributed dual-channel monitoring device, the monitoring of multiple positions in the target scenario is realized, improving the comprehensiveness of monitoring; the dual-channel monitoring device includes an optical channel and an acoustic channel, realizing multi-dimensional monitoring of bioaerosols; a first computing center is set in the first dual-channel monitoring device to realize edge computing; the first computing center analyzes the monitoring data to obtain the bioaerosol concentration, realizing local data analysis and processing; the monitoring data and the bioaerosol concentration are transmitted to the monitoring and early warning center through an information network, realizing remote data transmission; the monitoring and early warning center conducts predictive analysis on the data to obtain the bioaerosol predicted concentration, realizing comprehensive analysis of the data at the center; the predicted concentration and the edge-computed concentration are dynamically displayed and compared to realize the verification of multi-source data; according to the display information, a risk early warning is generated, solving the technical problems of single bioaerosol monitoring data, slow response, and inaccurate early warning in the prior art; achieving the technical effects of comprehensive monitoring and timely response to bioaerosols and improving the accuracy of early warning.

[0009] The above description is only an overview of the technical solutions of the present application. In order to be able to understand the technical means of the present application more clearly, it can be implemented according to the content of the specification. And in order to make the above and other purposes, features, and advantages of the present application more obvious and understandable, the specific embodiments of the present application are specifically exemplified below. Description of the Drawings

[0010] Figure 1 It is a schematic flowchart of a method for online monitoring and early warning of bioaerosols provided by an embodiment of the present application;

[0011] Figure 2 This is a schematic flow diagram for obtaining the first real-time monitoring data in the online monitoring and early warning method of bioaerosols provided by the embodiments of the present application;

[0012] Figure 3 This is a schematic structural diagram of an online monitoring and early warning system for bioaerosols provided by the embodiments of the present application.

[0013] Explanation of reference numerals: aerosol dynamic monitoring module 11, monitoring data analysis unit 12, information transmission module 13, aerosol predicted concentration module 14, risk early warning generation module 15. Detailed implementation manners

[0014] The general idea of the technical solution provided by the present application is as follows:

[0015] The embodiments of the present application provide an online monitoring and early warning method and system for bioaerosols. First, a distributed dual-channel monitoring device is used to monitor the bioaerosol concentration at multiple locations in the target scenario. Through the combination of an optical channel and an acoustic channel, multi-dimensional data collection is achieved, improving the comprehensiveness of monitoring. Then, an edge computing function is set in the monitoring device to locally analyze the collected monitoring data to obtain the real-time concentration value of bioaerosols. Since edge computing avoids long-distance data transmission, the response time is significantly shortened. Next, both the original monitoring data and the concentration value obtained by edge computing are transmitted to the backend monitoring and early warning center through the information network. The center conducts multi-faceted comprehensive analysis and prediction on the massive monitoring data to obtain the predicted value of the bioaerosol concentration. Finally, through the dynamic comparison and display of the edge-computed concentration value and the predicted concentration value, multi-source data verification from the monitoring terminal and the center prediction is achieved, and then the bioaerosol pollution risk is comprehensively judged to achieve accurate and reliable risk early warning.

[0016] After introducing the basic principle of the present application, the following will specifically introduce various non-limiting implementation manners of the present application in conjunction with the accompanying drawings of the specification. Embodiment 1

[0017] As Figure 1 shown, the embodiments of the present application provide an online monitoring and early warning method for bioaerosols. This method is applied to an online monitoring and early warning system for bioaerosols, and this system is communicatively connected to a distributed dual-channel monitoring device, an information transmission network, and a monitoring and early warning center.

[0018] Specifically, the present application discloses an online monitoring and early warning method for bioaerosols. This method is applied to an online monitoring and early warning system for bioaerosols, which is communicatively connected to a distributed dual-channel monitoring device, an information transmission network, and a monitoring and early warning center. Among them, the distributed dual-channel monitoring device is a monitoring device network composed of multiple dual-channel monitoring devices. Each dual-channel monitoring device in this monitoring device network is evenly distributed at different positions in the target scenario (target monitoring area) to achieve omnidirectional monitoring of the target area. Each dual-channel monitoring device includes two heterogeneous sensing channels, namely an optical monitoring channel and an acoustic monitoring channel; the information transmission network uses a wireless network to be responsible for transmitting the monitoring data collected by the distributed dual-channel monitoring device to the monitoring and early warning center; the monitoring and early warning center centrally receives and analyzes the heterogeneous monitoring data from the distributed dual-channel monitoring network, predicts the bioaerosol concentration, and visualizes the monitoring and prediction information to generate an early warning.

[0019] The online monitoring and early warning method includes:

[0020] Dynamically monitor bioaerosols at a first position in the target scenario through the first dual-channel monitoring device in the distributed dual-channel monitoring device to obtain first real-time monitoring data;

[0021] Further, as Figure 2 shown, this step includes:

[0022] The first dual-channel monitoring device is arranged at the first position, and the first dual-channel monitoring device includes a first optical monitoring channel;

[0023] The first optical monitoring channel includes an optical transmitter, a flat glass optical waveguide, and an optical receiver;

[0024] The flat glass optical waveguide receives a first detection optical signal from the optical transmitter;

[0025] The flat glass optical waveguide performs a surface scattering effect on the first detection optical signal, and the optical receiver receives the first scattered optical signal scattered on the surface;

[0026] Obtain first optical comparison data, where the first optical comparison data is data obtained by comparing and analyzing the first detection optical signal and the first scattered optical signal;

[0027] Add the first optical comparison data to the first real-time monitoring data.

[0028] Further, this step further includes:

[0029] The first dual-channel monitoring device further includes a first acoustic monitoring channel,

[0030] The first sound monitoring channel includes an ultrasonic transmitter and an ultrasonic receiver;

[0031] The ultrasonic transmitter emits a first ultrasonic transmission signal to the ultrasonic receiver to obtain a first ultrasonic reception signal of the ultrasonic receiver;

[0032] First sound comparison data is obtained, and the first sound comparison data is data obtained by comparing and analyzing the first ultrasonic transmission signal and the first ultrasonic reception signal;

[0033] The first sound comparison data is added to the first real-time monitoring data.

[0034] Further, this step further includes:

[0035] Before the flat glass optical waveguide receives the first detection optical signal from the optical transmitter, the surface of the flat glass optical waveguide is sensitized by a preset gradient film to obtain a sensitized flat glass optical waveguide.

[0036] In the embodiment of the present application, the distributed dual-channel monitoring device includes a plurality of dual-channel monitoring devices, and each dual-channel monitoring device includes an optical monitoring channel and a sound monitoring channel. The first dual-channel monitoring device is any one of the dual-channel monitoring devices in the distributed dual-channel monitoring device. The first dual-channel monitoring device includes a first optical monitoring channel and a first sound monitoring channel. The first position is the position where the first dual-channel monitoring device is arranged in the target scenario. The area at the first position is dynamically monitored for bioaerosols through the two heterogeneous sensing channels of the first dual-channel monitoring device, and first real-time monitoring data including two types of sensing information is collected in real time.

[0037] Specifically, the first optical monitoring channel in the first dual-channel monitoring device includes an optical transmitter, a flat glass optical waveguide, and an optical receiver. Among them, the optical transmitter generates and emits a first optical signal for detection through lidar technology, and this first optical signal provides a light source for optical monitoring; the flat glass optical waveguide is used to transmit the first optical signal. In an environment containing bioaerosol particles, the first optical signal will scatter with the bioaerosol particles during transmission, generating a first scattered light signal; the optical receiver receives the first scattered light signal passing through the bioaerosol area. When the first optical monitoring channel is working, the optical transmitter generates and emits a first detection optical signal, and this first detection optical signal is directed towards the flat glass optical waveguide, and the flat glass optical waveguide receives the first detection optical signal from the optical transmitter. After the first detection optical signal enters the flat glass optical waveguide, bioaerosol particles condense on the surface of the flat glass optical waveguide. When the first detection optical signal passes by, it scatters with these particles, forming a first scattered light signal. After obtaining the first detection optical signal and the first scattered light signal, the first detection optical signal is used as a reference optical signal and compared with the first scattered light signal generated after passing through the bioaerosol area. By analyzing the parameter differences between the two optical signals, the scattering and attenuation effects of bioaerosol on the first detection optical signal are quantitatively evaluated. The first optical comparison data reflects the differential results between the first detection optical signal and the first scattered light signal, and this difference comes from the scattering and absorption effects of bioaerosol particles on the first detection optical signal. Based on this, the concentration of bioaerosol can be determined. After obtaining the first optical comparison data, this first optical comparison data is added to the first real-time monitoring data as the real-time optical monitoring data of the first position of the target scene by the first dual-channel monitoring device, reflecting the parameters of bioaerosol in terms of optical response.

[0038] The first acoustic monitoring channel in the first dual-channel monitoring device includes an ultrasonic transmitter and an ultrasonic receiver. Among them, the ultrasonic transmitter is used to generate and transmit ultrasonic signals as the detection source signal for acoustic monitoring; the ultrasonic receiver is used to receive the echo signals generated after passing through the bioaerosol-containing area. When monitoring in the first acoustic monitoring channel, the ultrasonic transmitter first emits a first ultrasonic emission signal, which propagates in the direction of the ultrasonic receiver. The first ultrasonic emission signal propagates through the air medium. When passing through the spatial area containing bioaerosol particles, it will cause signal reflection and scattering, and finally reach the ultrasonic receiver in a changed form. The ultrasonic receiver receives the transmitted signal to obtain the first ultrasonic reception signal. After obtaining the first ultrasonic emission signal and the first ultrasonic reception signal, the first ultrasonic emission signal is used as a reference signal and compared with the first ultrasonic reception signal after passing through the bioaerosol area. By analyzing the parameter changes of the two acoustic signals, the scattering and attenuation effects of bioaerosols on the first ultrasonic emission signal are quantitatively evaluated. The first acoustic comparison data reflects the differential results between the two signals, and this difference comes from the scattering and absorption effects of bioaerosol particles on the first ultrasonic emission signal. Based on this, the concentration parameters of bioaerosols can be determined. Subsequently, the first acoustic comparison data is added to the first real-time monitoring data as the real-time acoustic monitoring data of the first position of the target scene by the first dual-channel monitoring device, reflecting the parameters of bioaerosols in terms of acoustic response.

[0039] By adding the first optical comparison data and the first acoustic comparison data to the first real-time monitoring data, the first real-time monitoring data forms a data set that combines the acoustic monitoring results and the optical monitoring results, providing a more comprehensive and accurate input source data for subsequent analysis and processing.

[0040] In a preferred embodiment, before performing the optical monitoring of bioaerosols through the first optical monitoring channel, the surface of the flat glass optical waveguide is first processed to obtain a sensitized flat glass optical waveguide to improve its detection sensitivity to bioaerosols. Specifically, a preset gradient thin film is covered on the surface of the flat glass optical waveguide, and the surface properties of the flat glass optical waveguide are changed by using the continuous gradient change characteristics of the gradient thin film. After the gradient thin film sensitization treatment, the scattering effect of the surface of the flat glass optical waveguide on bioaerosol particles is enhanced, thereby generating a more significant scattered light signal, and at the same time reducing the negative impact of the accumulation of bioaerosol particles on the surface. By obtaining a sensitized flat glass optical waveguide with enhanced detection sensitivity to bioaerosols, the accuracy and sensitivity of subsequent bioaerosol concentration detection and monitoring are improved.

[0041] Analyze the first real-time monitoring data through the first computing center in the first dual-channel monitoring device to obtain the first bioaerosol concentration, and the first bioaerosol concentration is marked with the first location information of the first location;

[0042] Further, this step includes:

[0043] Analyze the first light contrast data through the first computing center to obtain the first light scattering intensity;

[0044] Call the preset light detection bioaerosol function, and combine it with the first light scattering intensity to obtain the first light detection bioaerosol concentration;

[0045] Analyze the first sound contrast data through the first computing center, and predict to obtain the first sound sensing bioaerosol concentration;

[0046] According to the preset weight distribution rule, obtain the first weight coefficient of the first light detection bioaerosol concentration and the second weight coefficient of the first sound sensing bioaerosol concentration respectively;

[0047] Combine the first weight coefficient and the second weight coefficient, and weight the first light detection bioaerosol concentration and the first sound sensing bioaerosol concentration to obtain the first bioaerosol concentration.

[0048] Further, this step also includes:

[0049] The expression of the preset light detection bioaerosol function is as follows:

[0050] ;

[0051] Wherein, represents the first light scattering intensity, represents the th dual-channel monitoring device arranged at the position in the distributed dual-channel monitoring device, represents the number of aerosol deposition particles on the optical waveguide surface of the sensitized flat glass optical waveguide, represents the aerosol deposition particle feedback adjustment coefficient, represents the aerosol concentration at the position, that is, the th light detection bioaerosol concentration,

[0052] In a preferred embodiment, a corresponding first computing center is provided in the first dual-channel monitoring device to process the first real-time monitoring data obtained by the first dual-channel monitoring device, and to implement the analysis of the optical monitoring result of the first optical contrast data and the acoustic monitoring result of the first acoustic contrast data included in the first real-time monitoring data. The first computing center is provided in the first dual-channel monitoring device to ensure that the data from the monitoring device can enter the first computing center in a timely and efficient manner for real-time processing.

[0053] After the first dual-channel monitoring device obtains the first real-time monitoring data, first, the first computing center extracts the characteristic parameters representing the light scattering intensity from the first optical contrast data based on signal processing technologies such as wavelet transform and spectrum analysis, and normalizes the extracted characteristic parameters to obtain the light scattering intensity quantization value in the range of 0-1 as the first light scattering intensity. Secondly, call the preset optical detection bioaerosol function model, and substitute the first light scattering intensity into the function model for calculation, then the first optical detection bioaerosol concentration can be obtained. The expression of the preset optical detection bioaerosol function is: ; where represents the first light scattering intensity, reflecting the degree of scattering effect of bioaerosol on the optical signal at the first position, represents the th dual-channel monitoring device arranged at the position in the distributed dual-channel monitoring device, represents the number of aerosol deposition particles on the optical waveguide surface of the sensitized flat glass optical waveguide, represents the aerosol deposition particle feedback adjustment coefficient, which can be corrected according to factors such as the pollution degree and humidity of the sensitized flat glass optical waveguide surface, represents the th position, that is, the optical detection bioaerosol concentration, represents the aerosol concentration feedback adjustment coefficient, which is corrected according to the ambient aerosol background concentration, etc. By substituting the first light scattering intensity into this function expression, the corresponding first optical monitoring aerosol concentration value can be calculated.

[0054] Then, a neural network algorithm is adopted to construct a non-linear mapping model between acoustic features and bio-aerosol concentration, which is used to perform intelligent calculation from the first acoustic contrast data to concentration prediction. The structure and parameters of this mapping model are optimized through training and learning with historical monitoring data. The first computing center inputs the first acoustic contrast data into this mapping model. Through the layer-by-layer calculation of the model, the feature extraction of the data and the learning of complex mapping relationships are realized, and the first acoustic sensing bio-aerosol concentration reflecting the acoustic monitoring results is output. Next, in order to reasonably fuse the first optical detection bio-aerosol concentration and the first acoustic detection bio-aerosol concentration, different weight coefficients are assigned to the two results according to the preset weight distribution rules in different situations, and the first weight coefficient corresponding to the first optical detection bio-aerosol concentration and the second weight coefficient corresponding to the first acoustic sensing bio-aerosol concentration are obtained. Among them, the preset weight distribution rule is that due to the bright ambient light but more noise during the day, the optical monitoring results are more reliable while the acoustic monitoring results are easily interfered. Therefore, for the monitoring data during the day, the weight coefficient of the first optical detection bio-aerosol concentration is set larger, and the weight coefficient of the first acoustic sensing bio-aerosol concentration is set smaller; while at night, the ambient light is weak and the acoustic wave propagation condition is good, making the acoustic monitoring results more reliable while the optical monitoring results are easily limited. Therefore, for the monitoring data at night, the weight coefficient of the first acoustic sensing bio-aerosol concentration is set larger, and the weight coefficient of the first optical detection bio-aerosol concentration is set smaller. After obtaining the first optical detection bio-aerosol concentration and the first acoustic sensing bio-aerosol concentration representing the results of the two monitoring methods, and their corresponding weight coefficients, the two will be weighted and fused to obtain the final first bio-aerosol concentration, which reflects the actual bio-aerosol concentration at the first location.

[0055] Transmit the first real-time monitoring data and the first bio-aerosol concentration to the monitoring and early warning center through the information transmission network;

[0056] To realize the data collection and transmission of the distributed dual-channel monitoring device, an information transmission network is set up to connect each dual-channel monitoring device with the monitoring and early warning center. The information transmission network adopts the networking technology of wireless network. By planning and arranging each dual-channel monitoring device and setting up wireless communication modules, such as WIFI modules, Bluetooth modules, etc., a wireless transmission network is constructed to realize the wireless data transmission between each dual-channel monitoring device and the monitoring and early warning center.

[0057] The first real-time monitoring data output by the first dual-channel monitoring device and the first bio-aerosol concentration analyzed by the first computing center are transmitted to the monitoring and early warning center through the established wireless network to realize the centralized processing and analysis of the data.

[0058] Analyze the first real-time monitoring data through the monitoring and calculation unit of the monitoring and early warning center to obtain the first bio-aerosol predicted concentration;

[0059] In the embodiment of the present application, first, a large amount of historical monitoring data is prepared as a training set. These data include optical and acoustic monitoring results in multiple time periods and multiple locations. At the same time, other environmental parameter datasets related to aerosol concentration are collected as additional inputs. According to the deep network structure, a model framework is designed, such as designing the number of nodes in the input layer and hidden layer, and selecting connection functions, etc. The network model parameters are iteratively updated using the training set data, and the network weights are gradually trained and optimized to improve the fitting effect of the model on the training data. Eventually, the mapping learning from the monitoring data to the concentration prediction can be completed. In the training process, algorithms such as gradient descent and backpropagation are used to update the network weights, and after verification, a monitoring calculation unit is obtained. After the monitoring and warning center receives the first real-time monitoring data and the first bioaerosol concentration, the monitoring calculation unit preprocesses the first real-time monitoring data, including denoising, normalization, etc., to obtain the normalized first real-time monitoring data. The normalized first real-time monitoring data is input into the monitoring calculation unit, and through the multi-layer neural network calculation of this unit, the high-dimensional abstraction and modeling of data features are realized. The model synthesizes various dimensional features, including time series data, the correlation between different locations, and the mapping relationship with other influencing factors. Finally, the output layer obtains a prediction sequence reflecting the change trend of the bioaerosol concentration at the first location within a certain future time period, that is, the first bioaerosol predicted concentration.

[0060] The warning display unit of the monitoring and warning center dynamically displays the first bioaerosol predicted concentration and the first bioaerosol concentration, and generates a first risk warning according to the dynamic display information.

[0061] Furthermore, the embodiment of the present application further includes:

[0062] The warning display unit visually displays the first bioaerosol concentration, and generates a visual bioaerosol concentration distribution map in combination with the identifier of the first location information;

[0063] Render the first bioaerosol predicted concentration onto the visual bioaerosol concentration distribution map in a preset form.

[0064] In a preferred implementation manner, the warning display unit is a display module in the monitoring and warning center, which receives the first bioaerosol predicted concentration output by the monitoring calculation unit, and the first real-time concentration data output by the edge calculation unit, that is, the first dual-channel monitoring device. This warning display unit integrates visualization software, which can image-process these concentration data to realize the dynamic visual display of the bioaerosol concentration distribution. At the same time, the warning display unit combines the warning threshold preset according to the monitoring requirements to identify the exceeded monitoring or prediction situations and generate a first risk warning.

[0065] First, the warning display unit receives the first bioaerosol concentration, calls the map coordinate information of the target scenario, and determines the spatial coordinates of the first position. Secondly, based on the first bioaerosol concentration and the spatial coordinates of the first position, a visual bioaerosol concentration distribution map is drawn on the map using color depth mapping. This visual bioaerosol concentration distribution map synthesizes the bioaerosol concentrations at multiple monitoring positions and clearly shows the bioaerosol concentration distribution of the entire target scenario. After the bioaerosol concentration visualization distribution map is drawn, the warning display unit renders the first bioaerosol predicted concentration predicted by the monitoring and calculation unit in a specific form. For example, in the form of prominent numerical markings or dot markings of a specific color, the predicted concentration value is displayed at the corresponding monitoring position. When the user views the visualization distribution map, they can intuitively compare the currently monitored concentration with the predicted future concentration change trend, which helps to judge the regional risk.

[0066] During the dynamic display process, after the monitoring and warning center receives the first real-time monitoring data and the first bioaerosol concentration, it immediately displays the first bioaerosol concentration result through the warning display unit to achieve real-time monitoring of the first position and reduce display latency. At the same time, the monitoring and calculation unit deeply analyzes the first bioaerosol concentration to generate the first bioaerosol predicted concentration and compares it with the first bioaerosol concentration for verification. By displaying the first bioaerosol concentration and the first bioaerosol predicted concentration in a dynamic visualization form, that is, the edge-computed concentration is updated and displayed in real time, and the predicted concentration is rendered and integrated in a specific form, the mutual verification of the results is achieved, which not only ensures the real-time monitoring responsiveness but also ensures the accuracy and reliability of the prediction, obtaining fine and dynamic aerosol concentration distribution information to support the generation of the first risk warning.

[0067] Meanwhile, multiple risk levels of bioaerosol concentration, such as blue, yellow, orange, red, etc., corresponding to different numerical thresholds, are preset in the warning display unit. When the first bioaerosol concentration obtained by edge computing during real-time display or the first bioaerosol predicted concentration predicted by the monitoring and calculation unit exceeds different thresholds, the corresponding risk warning is triggered. After receiving different-level warnings, the warning display unit generates the first risk warning and conducts visual and audible alarms in different colors, volumes, etc. to clearly show the risk level. At the same time, the first risk warning is pushed to the mobile terminals of the monitoring personnel for extended reminders.

[0068] In summary, the online monitoring and warning method for bioaerosols provided by the embodiments of the present application has the following technical effects:

[0069] The first dual-channel monitoring device in the distributed dual-channel monitoring device is used to dynamically monitor bioaerosols at the first position in the target scene, obtain the first real-time monitoring data, realize multi-point and multi-dimensional data collection, and improve the comprehensiveness of monitoring. The first computing center in the first dual-channel monitoring device analyzes the first real-time monitoring data to obtain the first bioaerosol concentration. The first bioaerosol concentration has the identification of the first position information of the first position, realizes local data processing at the edge, and shortens the response time. The first real-time monitoring data and the first bioaerosol concentration are transmitted to the monitoring and early warning center through the information transmission network to realize remote data centralized management. The monitoring computing unit of the monitoring and early warning center analyzes the first real-time monitoring data to obtain the first predicted bioaerosol concentration, and realizes comprehensive intelligent prediction analysis at the central end. The warning display unit of the monitoring and early warning center dynamically displays the first predicted bioaerosol concentration and the first bioaerosol concentration, and generates the first risk warning according to the dynamic display information, realizes the verification of multi-source data, improves the accuracy of early warning, and finally realizes the risk judgment and early warning output of bioaerosols. Embodiment 2

[0070] Based on the same inventive concept as the online monitoring and early warning method for bioaerosols in the foregoing embodiment, as Figure 3 shown, the embodiment of the present application provides an online monitoring and early warning system for bioaerosols. The system is communicatively connected to a distributed dual-channel monitoring device, an information transmission network, and a monitoring and early warning center. The system includes:

[0071] An aerosol dynamic monitoring module 11, configured to dynamically monitor bioaerosols at the first position in the target scene through the first dual-channel monitoring device in the distributed dual-channel monitoring device to obtain the first real-time monitoring data;

[0072] A monitoring data analysis unit 12, configured to analyze the first real-time monitoring data through the first computing center in the first dual-channel monitoring device to obtain the first bioaerosol concentration, and the first bioaerosol concentration has the identification of the first position information of the first position;

[0073] An information transmission module 13, configured to transmit the first real-time monitoring data and the first bioaerosol concentration to the monitoring and early warning center through the information transmission network;

[0074] An aerosol predicted concentration module 14, configured to analyze the first real-time monitoring data through the monitoring computing unit of the monitoring and early warning center to obtain the first predicted bioaerosol concentration;

[0075] The risk warning generation module 15 is used to dynamically display the predicted concentration of the first bio-aerosol and the concentration of the first bio-aerosol through the warning display unit of the monitoring and warning center, and generate a first risk warning according to the dynamic display information.

[0076] Furthermore, the aerosol dynamic monitoring module 11 includes the following execution steps:

[0077] The first dual-channel monitoring device is arranged at the first position, and the first dual-channel monitoring device includes a first optical monitoring channel;

[0078] The first optical monitoring channel includes an optical transmitter, a flat glass optical waveguide, and an optical receiver;

[0079] The flat glass optical waveguide receives a first detection optical signal from the optical transmitter;

[0080] The flat glass optical waveguide performs a surface scattering effect on the first detection optical signal, and the optical receiver receives the first scattered optical signal scattered on the surface;

[0081] First optical comparison data is obtained, and the first optical comparison data is data obtained by comparing and analyzing the first detection optical signal and the first scattered optical signal;

[0082] The first optical comparison data is added to the first real-time monitoring data.

[0083] Furthermore, the aerosol dynamic monitoring module 11 further includes the following execution steps:

[0084] Before the flat glass optical waveguide receives the first detection optical signal from the optical transmitter, the surface of the flat glass optical waveguide is sensitized through a preset gradient thin film to obtain a sensitized flat glass optical waveguide.

[0085] Furthermore, the aerosol dynamic monitoring module 11 further includes the following execution steps:

[0086] The first dual-channel monitoring device further includes a first acoustic monitoring channel. After the first optical comparison data is added to the first real-time monitoring data, it includes:

[0087] The first acoustic monitoring channel includes an ultrasonic transmitter and an ultrasonic receiver;

[0088] The ultrasonic transmitter emits a first ultrasonic emission signal to the ultrasonic receiver to obtain a first ultrasonic reception signal of the ultrasonic receiver;

[0089] Obtain the first acoustic comparison data, where the first acoustic comparison data is the data obtained by comparing and analyzing the first ultrasonic emission signal and the first ultrasonic reception signal;

[0090] Add the first acoustic comparison data to the first real-time monitoring data.

[0091] Further, the monitoring data analysis unit 12 includes the following execution steps:

[0092] Analyze the first optical comparison data through the first calculation center to obtain the first light scattering intensity;

[0093] Call the preset optical detection bio-aerosol function and combine it with the first light scattering intensity to obtain the first optical detection bio-aerosol concentration;

[0094] Analyze the first acoustic comparison data through the first calculation center and predict to obtain the first acoustic sensing bio-aerosol concentration;

[0095] Obtain the first weight coefficient of the first optical detection bio-aerosol concentration and the second weight coefficient of the first acoustic sensing bio-aerosol concentration respectively according to the preset weight distribution rule;

[0096] Combine the first weight coefficient and the second weight coefficient, and weight the first optical detection bio-aerosol concentration and the first acoustic sensing bio-aerosol concentration to obtain the first bio-aerosol concentration.

[0097] Further, the monitoring data analysis unit 12 further includes the following execution steps:

[0098] The expression of the preset optical detection bio-aerosol function is as follows:

[0099] ;

[0100] Wherein, represents the first light scattering intensity, represents the th dual-channel monitoring device disposed at the position in the distributed dual-channel monitoring device, represents the number of aerosol sedimentation particles on the optical waveguide surface of the sensitized flat glass optical waveguide, represents the aerosol sedimentation particle feedback adjustment coefficient, represents the aerosol concentration at the position, that is, the first optical detection bio-aerosol concentration,

[0101] Further, the risk warning generation module 15 includes the following execution steps:

[0102] The warning display unit visually displays the first bioaerosol concentration and generates a visual bioaerosol concentration distribution map by combining the identification of the first position information;

[0103] Render the first predicted bioaerosol concentration onto the visual bioaerosol concentration distribution map in a preset form.

[0104] Any step of the methods described above can be stored as computer instructions or programs in an unrestricted computer memory and can be called and recognized by an unrestricted computer processor to implement any of the methods in the embodiments of the present application, without further limitation here.

[0105] Furthermore, the first or second described above may not only represent an order relationship, but may also represent a specific concept, and / or refer to the selection of multiple elements individually or in whole. Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalent technologies, the present application is intended to include these modifications and variations.

Claims

1. An online monitoring and early warning method for bioaerosols, characterized in that: The method is applied to an online monitoring and early warning system for bioaerosols, wherein the system is connected to a distributed dual-channel monitoring device, an information transmission network, and a monitoring and early warning center for communication, and the method comprises: Performing bioaerosol dynamic monitoring on a first position in a target scene by using a first dual-channel monitoring device in the distributed dual-channel monitoring device to obtain first real-time monitoring data; Analyzing the first real-time monitoring data through a first computing center in the first dual-channel monitoring device to obtain a first bioaerosol concentration, wherein the first bioaerosol concentration has an identifier of the first position information of the first position; Transmitting the first real-time monitoring data and the first bioaerosol concentration to the monitoring and early warning center through the information transmission network; Analyzing the first real-time monitoring data by the monitoring calculation unit of the monitoring and early warning center to obtain a first bioaerosol predicted concentration; Dynamically displaying the predicted concentration of the first bioaerosol and the first bioaerosol concentration through the warning display unit of the monitoring and warning center, and generating a first risk warning according to the dynamic display information; The first real-time monitoring data is analyzed by the first computing center in the first dual-channel monitoring device to obtain the first bioaerosol concentration, including: Analyzing the first light contrast data by the first computing center to obtain a first light scattering intensity; Calling a preset light detection bioaerosol function, and obtaining a first light detection bioaerosol concentration in combination with the first light scattering intensity; Analyzing the first acoustic comparison data through the first computing center and predicting the first acoustic sensing bioaerosol concentration; According to a preset weight allocation rule, a first weight coefficient of the first light detection bioaerosol concentration and a second weight coefficient of the first acoustic sensing bioaerosol concentration are respectively obtained; Combining the first weight coefficient and the second weight coefficient, weighting the first light detection bioaerosol concentration and the first acoustic sensing bioaerosol concentration to obtain the first bioaerosol concentration; The expression of the preset light detection bioaerosol function is as follows: Det i =μ*(εSc i ); Among them, Sc i represents the first light scattering intensity, i represents the i-th dual-channel monitoring device arranged at the i-th position in the distributed dual-channel monitoring device, εSc i represents the number of aerosol precipitation particles on the optical waveguide surface of the sensitized flat glass optical waveguide, ε represents the feedback adjustment coefficient of aerosol precipitation particles, Det i represents the aerosol concentration at the i-th position, that is, the i-th light-detected bioaerosol concentration, and μ represents the aerosol concentration feedback adjustment coefficient.

2. The method according to claim 1, characterized in that: The first dual-channel monitoring device is arranged at the first position, and the first dual-channel monitoring device includes a first optical monitoring channel, and obtaining the first real-time monitoring data includes: The first optical monitoring channel includes an optical transmitter, a flat glass optical waveguide, and an optical receiver; receiving a first detection light signal from the light emitter by the flat glass optical waveguide; The flat glass optical waveguide performs surface scattering on the first detection light signal, and the optical receiver receives the first scattered light signal scattered by the surface; Obtaining first light comparison data, where the first light comparison data is data obtained by comparing and analyzing the first detection light signal and the first scattered light signal; The first light contrast data is added to the first real-time monitoring data.

3. The method according to claim 2, characterized in that: Before the flat glass optical waveguide receives the first detection light signal from the light transmitter, the flat glass optical waveguide is subjected to surface sensitization treatment by a preset gradient film to obtain a sensitized flat glass optical waveguide.

4. The method according to claim 3, characterized in that: The first dual-channel monitoring device further includes a first acoustic monitoring channel, and after adding the first optical comparison data to the first real-time monitoring data, includes: The first acoustic monitoring channel includes an ultrasonic transmitter and an ultrasonic receiver; The ultrasonic transmitter sends a first ultrasonic transmission signal to the ultrasonic receiver to obtain a first ultrasonic reception signal from the ultrasonic receiver; Obtaining first acoustic comparison data, where the first acoustic comparison data is data obtained by comparing and analyzing the first ultrasonic transmission signal and the first ultrasonic reception signal; The first acoustic comparison data is added to the first real-time monitoring data.

5. The method according to claim 1, characterized in that: The method comprises: The early warning display unit visually displays the first bioaerosol concentration, and generates a visual bioaerosol concentration distribution map in combination with the identifier of the first location information; The first bioaerosol predicted concentration is rendered in a preset form to the visualized bioaerosol concentration distribution map.

6. The online monitoring and early warning system of bioaerosols is characterized by: The method for online monitoring and early warning of bioaerosols according to any one of claims 1 to 5 is used for implementing the method, wherein the system is connected to a distributed dual-channel monitoring device, an information transmission network, and a monitoring and early warning center for communication, and the system comprises: An aerosol dynamic monitoring module, the aerosol dynamic monitoring module is used to perform bioaerosol dynamic monitoring on a first position in a target scene through a first dual-channel monitoring device in the distributed dual-channel monitoring device to obtain first real-time monitoring data; A monitoring data analysis unit, the monitoring data analysis unit is used to analyze the first real-time monitoring data through a first computing center in the first dual-channel monitoring device to obtain a first bioaerosol concentration, wherein the first bioaerosol concentration has an identifier of the first position information of the first position; An information transmission module, the information transmission module is used to transmit the first real-time monitoring data and the first bioaerosol concentration to the monitoring and early warning center through the information transmission network; An aerosol prediction concentration module, the aerosol prediction concentration module is used to analyze the first real-time monitoring data through the monitoring calculation unit of the monitoring and early warning center to obtain a first bioaerosol prediction concentration; A risk warning generation module, wherein the risk warning generation module is used to dynamically display the predicted concentration of the first bioaerosol and the first bioaerosol concentration through the warning display unit of the monitoring and warning center, and generate a first risk warning according to the dynamic display information.

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