WO2020248965A1

WO2020248965A1 - Internet-of-things-based method and system for measuring and analyzing bacteria content of indoor air in real time

Info

Publication number: WO2020248965A1
Application number: PCT/CN2020/095059
Authority: WO
Inventors: 曾俊; 吴叶芳
Original assignee: 江苏钛科圈物联网科技有限公司
Priority date: 2019-06-11
Filing date: 2020-06-09
Publication date: 2020-12-17
Also published as: CN110118711A; CN110118711B

Abstract

Disclosed is an Internet-of-Things-based method for measuring and analyzing bacteria content of indoor air in real time. The method comprises: generating a bioaerosol concentration measurement curve; generating a particulate matter concentration curve; collecting statistics of environmental parameters within a set time range; obtaining a real-time bioaerosol concentration in the current environment through calculation in conjunction with the bioaerosol concentration measurement curve and the particulate matter concentration curve; and obtaining, through calculation in conjunction with a room type, a real-time bacteria content of indoor air in the current environment. By means of the method, the real-time measurement of bacteria content in a current environment can be realized, the starting of a disinfection and sterilization device can be guided, and the making of a decision regarding emergency treatment for an indoor environment can be assisted; in addition, a change trend of indoor bacteria content is estimated in conjunction with an access control subsystem, a photographing subsystem and an environment measurement subsystem so as to realize early warning, so that an instruction is more accurate, thereby effectively reducing energy consumption, and realizing early warning for a high-risk environment in a timely manner, such that the occurrence of mass health incidents is reduced. Moreover, the process can be tracked, and a result thereof is traceable.

Description

Real-time detection and analysis method and system for indoor air bacteria content based on internet of things

Technical field

The present invention relates to the technical field of the Internet of Things, in particular to a method and system for real-time detection and analysis of indoor air bacteria content based on the Internet of Things.

Background technique

At present, the detection of air bacteria content indicators is mainly carried out through collection, cultivation, and counting, which cannot meet the requirements of real-time and continuity. At this stage, the sensor can detect the number of particles of different sizes in the air in real time and accurately. It is known that bacteria, viruses, molds, etc. in the air exist in the form of bioaerosols, and the particles detected by the sensor include bioaerosol particles. . At present, the detection of the amount of bioaerosol in the air uses fluorescence calibration of the sensor, but this kind of equipment is bulky and cannot be used in classrooms, hospitals and other scenarios.

In the invention patent "Bioaerosol real-time monitoring device" with application number CN201310009382.X, a real-time monitoring device for bioaerosols is mentioned. The aerosol particle cluster is formed by sucking indoor air into the buffer cavity to detect the buffer cavity. Calculate the concentration of bioaerosol in the collected indoor air by calculating the light intensity of the aerosol particle cluster in the sample. This method is obtained by dividing the fluorescence intensity of the detected aerosol particle cluster by the atmospheric volume The intensity of fluorescent light per unit volume of the atmosphere is used to obtain the bioaerosol concentration. Since the detection target is an aerosol cluster, the fluorescence signal is relatively strong, and this relatively sensitive detection result can be achieved by adopting a detection device with a relatively simple structure. It can be seen from the foregoing that the more aerosol particle clusters in the buffer cavity, the stronger the fluorescence signal, and the more accurate the detection result. For on-site and net-like spot monitoring equipment, due to the limitation of the structure, the detection equipment used is low in accuracy. In theory, it is necessary to collect a period of time to form a large number of aerosol particle clusters to obtain sufficient strength. Fluorescence signal, that is, in this case, real-time monitoring of bioaerosol cannot be truly achieved.

Summary of the invention

The purpose of the present invention is to provide a real-time detection and analysis method and system for the amount of bacteria in indoor air based on the Internet of Things. The particle sensor detects the particle concentration in the environment in real time to generate a particle concentration curve. The bioaerosol detection device is used to collect air periodically. Sol particle clusters, detect the fluorescence intensity of aerosol particle clusters, generate a bioaerosol concentration detection curve, count the space volume of the environment, the number of active people, the number of pathogen carriers, and basic temperature and humidity parameters, combined with bioaerosol concentration detection Curve and particle concentration curve, calculate the real-time bioaerosol concentration in the current environment, combined with the room type, determine the ratio of the number of bioaerosols formed by bacteria and germs to the total number of bioaerosols, and calculate the indoor air in the current environment Real-time bacterial content. In addition, the present invention is based on the Internet of Things technology, combined with the access control subsystem, the photographing subsystem, and the environment detection subsystem to predict the change trend of the indoor bacterial content and realize early warning.

In order to achieve the above objective, in conjunction with FIG. 1, the present invention proposes a real-time detection and analysis method of indoor air bacteria content based on the Internet of Things, which is characterized in that the method includes:

S1: Detect the collected bioaerosol concentration of indoor air according to a set period, and generate a bioaerosol concentration detection curve C(t).

S2: Collect the concentration of particulate matter in the indoor air in real time to generate a particulate matter concentration curve P(t).

S3: Select a set time range, the set time range includes at least two set periods, and calculate the indoor temperature T _t , indoor humidity RH _t , room area S _t and indoor ventilation per unit time within the set time range The quantity Q _t , the total number of indoor people N _t , and the number of pathogen carriers M _t .

S4: Combine the bioaerosol concentration detection curve C(t) and the particle concentration curve P(t) to generate the real-time bioaerosol concentration in the current environment F(t)=f(C(t), P(t), T _t , RH _t , S _t , Q _t , N _t , M _t ).

S5: According to the room type, determine the ratio of the amount of bioaerosol formed by bacteria and germs to the total amount of bioaerosol, and calculate the real-time bacterial content U(t) of the indoor air in the current environment.

Based on the foregoing method, combined with Figures 3 and 4, the present invention also mentions a real-time detection and analysis system for indoor air bacteria content based on the Internet of Things, characterized in that the system includes an access control subsystem, a shooting subsystem, and an environment Detection subsystem, control device.

The access control subsystem includes a human body infrared sensor, a face image acquisition device, and a counting device. The human body infrared sensor is used to identify the attributes of entering and exiting personnel. The attributes of the entering and exiting personnel include pathogen carriers and non-virus carriers. The image acquisition device is used to collect facial images of pathogen carriers, and the collected facial images are sent to the storage device, and the counting device is used to count the current total number of people in the room and the number of pathogen carriers.

The photographing subsystem includes a photographing device and an image analysis device. The photographing device is used to photograph video images in the room and send the photographed video images to the image analysis device. The image analysis device analyzes the video images taken by the photographing device. Identify whether there is a person who has been sick, and compare the face image of the person who has the sick behavior with the face image of the pathogen carrier in the storage device to determine whether a new pathogen carrier has appeared.

The environmental detection subsystem includes a track circuit, a rotating platform, a housing, a temperature and humidity sensor, a rain and snow sensor, a particle detection device, and a bioaerosol detection device.

The housing includes a detection end face facing a designated area, the track circuit is distributed on the wall of the room, the housing is installed on the track circuit through a rotating platform, and moves along the track circuit according to an external control command while rotating around The platform rotates so that the detection end face always faces the designated area.

The set period is the time for the shell to move one loop along the track loop.

The rain and snow sensor is arranged outdoors to detect the outdoor rain and snow level in real time, and send the detected rain and snow level to the control device.

The temperature and humidity sensor is installed in the housing, and its detection end is installed near the detection end surface of the housing. The temperature and humidity sensor is electrically connected to the control device for real-time detection of indoor temperature and humidity, and the detection result is fed back to the control device.

A hollow turntable with a circular cross-section is installed in the housing, and the hollow turntable rotates around its axis centerline. The particulate matter detection device and the bioaerosol detection device are all installed in the hollow turntable. The air inlets are all located on the detection end surface of the housing.

The particulate matter detection device is used to collect the concentration of particulate matter in indoor air in real time, and send the collection result to the control device, and the control device generates a particulate matter concentration curve P(t).

The biological aerosol detection device includes an air pump, a buffer cavity, and a fluorescence detection unit. The air pump sucks indoor air in real time into the buffer cavity to form aerosol particle clusters. The fluorescence detection unit detects the aerosol particle clusters in the buffer cavity according to a set period. Light intensity, send the detected light intensity to the control device.

The control device calculates the bioaerosol concentration in the indoor air collected during the aforementioned set period according to the received light intensity, and generates a bioaerosol concentration detection curve C(t).

The control device selects a set time range, the set time range includes at least two set periods, and calculates indoor temperature T _t , indoor humidity RH _t , room area S _t , and unit time within the set time range The indoor ventilation rate Q _t , the total number of people in the room N _t , the number of pathogen carriers M _t , combined with the bioaerosol concentration detection curve C(t) and the particulate matter concentration curve P(t), generate the real-time bioaerosol concentration F in the current environment (t)=f(C(t), P(t), T _t , RH _t , S _t , Q _t , N _t , M _t ).

The control device determines the ratio of the amount of bioaerosol formed by bacteria and germs to the total amount of bioaerosol in combination with the room type, and calculates the real-time bacterial content U(t) of the indoor air in the current environment.

The method and system for real-time detection and analysis of indoor air bacteria content based on the Internet of Things mentioned in the present invention are particularly suitable for fixed public places, such as hospitals, kindergartens, offices and other indoor areas with distinctive features, such as relatively fixed membership, Or the member structure is relatively fixed, and the room use function, the member's behavior mode is relatively fixed, etc. The changes in the bacterial content and particle concentration of this type of area mainly depend on the number of indoor personnel, the amount of behavior and the current attributes of indoor personnel. For example, the more people indoors, the more bacteria and particles they bring in, the more frequent the activities of indoor people, the more bacteria and particles produced during the activities, the more suitable the indoor environment temperature and humidity, because of the bacteria caused by indoor human activities The easier it is to produce and maintain the suspended state of particles and particles, and the bacteria can also multiply in a suitable environment, resulting in a rapid increase in bacterial content.

From the foregoing, it can be seen that the number of indoor personnel and their behavior will increase the concentration of bacteria and particulates at the same time. In addition to making bacteria and particulates easier to produce, a suitable environment also affects the reproduction of bacteria. The influencing factors of indoor bacteria content and particle concentration are almost the same. In addition, bacteria and germs in the air mostly exist in the form of bioaerosols. The proportion of bioaerosols produced by bacteria and germs in the total amount of bioaerosols in different types of rooms is different. You can obtain each room by analyzing empirical data. The specific gravity value.

Bacteria and pathogens are characterized by their ability to reproduce. The reproduction speed depends on environmental parameters, such as temperature, humidity, season, indoor unit ventilation, etc., especially bioaerosols adsorbed on fine particles, which will use adsorbents as culture media It reproduces and enters the human body through the respiratory tract, posing a threat to human health. Therefore, based on the more distinctive indoor environment, there is a correlation between the concentration changes of particulate matter and bioaerosol.

When indoor personnel include members who are sick (defined as pathogen carriers in the present invention), the pathogen carriers will bring more germs and bacteria than healthy members, especially patients with infectious diseases, but it is The effect of indoor particulate matter concentration is similar to that of healthy members.

In a sunny indoor environment, the environmental parameters change within a certain range, and the change curve of the environmental parameters is relatively gentle. Therefore, the following takes the sunny weather indoor environment as an example to analyze the effects of the aforementioned environmental parameters on the bacterial content and particle concentration. influences.

1. Indoor temperature and humidity

Within a certain range of change, the greater the indoor temperature and humidity, the more suspended particulates in the air, and the higher the particulate concentration and bacterial content. However, the greater the temperature and humidity, the more suitable the environment for bacterial growth. Therefore, under the same conditions, The influence of indoor temperature and humidity on the bacterial content is greater than the influence on the concentration of particulate matter.

2. Room area and indoor ventilation per unit time

Combine the following formula to obtain indoor ventilation per unit area per unit time:

Indoor ventilation volume per unit time = indoor ventilation volume per unit time / room area

In fine weather, the concentration of particulate matter and bacterial content in the outdoor air is lower than that in the room. Therefore, the greater the indoor ventilation per unit time, the smaller the concentration of particulate matter and bacterial content in the indoor air. Under the same conditions , The influence value of indoor ventilation per unit area per unit time on the bacterial content and the influence value on the concentration of particulate matter are relatively fixed.

3. Number of pathogen carriers

As one of the sources of pathogens, especially carriers of infectious diseases, in addition to the increase in the concentration of bacteria and particulates due to activities, compared with ordinary members, they will also produce additional pathogens. These pathogens will affect indoor members. The health threat is greater.

Based on the foregoing analysis, in step S4, the bioaerosol concentration detection curve C(t) and the particulate matter concentration curve P(t) are combined to generate the real-time bioaerosol concentration in the current environment F(t)=f(C(t) ), P(t), T _t , RH _t , S _t , Q _t , N _t , M _t ) process includes the following steps:

S41: Calculate the indoor ventilation per unit area per unit time according to the following formula:

Indoor ventilation per unit area per unit time

= Indoor ventilation quantity per unit time Q _t /room area S _t .

S42: Calculate the indoor temperature T _t in the indoor air, indoor humidity RH _t , and indoor ventilation per unit area per unit time

The weight of the influence of the total number of indoor people N _t and the number of pathogen carriers M _t on the bioaerosol concentration detection curve C(t) and the particle concentration curve P(t).

S43: Calculate the real-time bioaerosol concentration F(t) in the current environment based on the particle concentration curve P(t) in combination with the influence weight.

In some examples, when the outdoor air quality is excellent, the real-time bioaerosol concentration F(t) is:

Among them, K ₁ is the influencing factor of the indoor environment on bacterial reproduction, K ₂ is the influence of indoor temperature T _t , indoor humidity RH _t , room area S _t , indoor ventilation rate per unit time Q _t , and total number of people in the room N _t on the bioaerosol concentration Detection curve C(t) and particle concentration curve P(t) influence weight ratio, b is the adjustment parameter, RH ₁ is the humidity correction factor, and ΔC is the average bioaerosol concentration produced by each pathogen carrier per unit time.

Preferably, according to experiments, when other parameters are constant, the greater the humidity, the stronger the fertility of the bacteria, which is about an exponential upward trend. Similarly, when other parameters are constant, the higher the temperature, the stronger the fertility of bacteria, which is about a straight upward trend. The present invention uses thermodynamic temperature to represent the actual temperature to avoid negative values caused by low temperature conditions, and finally obtain the real-time bioaerosol concentration F(t) as:

Among them, RH ₁ is the humidity correction factor, and T ₁ is the temperature correction factor, which is affected by environmental factors such as the actual room type and weather.

The present invention collects indoor particle concentration in real time and periodically collects indoor bioaerosol concentration to generate a particle concentration curve and a bioaerosol concentration detection curve in the current environment, and then combine the collected environmental parameters to calculate the biological aerosol in the current environment. Aerosol-particulate matter concentration correlation, combined with the influence weight, based on the particulate matter concentration curve and the bioaerosol concentration detection curve, calculates the real-time bioaerosol concentration in the current environment; combined with the room type, judges the formation of bacteria and germs The ratio of the number of bioaerosols to the total number of bioaerosols, and calculate the real-time bacterial content.

With reference to Figure 2, based on the aforementioned method for real-time detection of indoor bacterial content, the present invention also mentions a method for real-time analysis of indoor air bacterial content based on the Internet of Things, specifically:

When a person enters, the access control subsystem detects the body temperature of the person who enters. If the body temperature of the person who enters is higher than the set body temperature threshold, it means that the person who entered is sick and judged as a pathogen carrier. When the person enters the room , Will undoubtedly cause a larger increase in the indoor bacterial content. At this time, it is judged whether the number of indoor pathogen carriers exceeds the first set threshold. If it exceeds, an alarm will be issued and the staff will be notified to deal with it, so as to avoid more risk of infection .

For different room types, the value of the first set threshold varies. For example, the members in the kindergarten are weak and easy to be infected. Therefore, once a pathogen carrier is found, it needs to be dealt with immediately. For example, in a hospital, due to its unique nature, The number of pathogen carriers is much larger than that in other areas, and it needs to be ventilated and disinfected at any time, but even in the same room, at different time periods, the number of pathogen carriers is different, and different ventilation needs to be adopted according to the number of different pathogen carriers , Sterilization measures to reduce energy consumption and medical pollution.

When there are a lot of people indoors, because the room already contains a lot of bacteria and germs, plus the bacteria and germs carried by the human body, as the amount of indoor people's activities increases, the increase in bacterial content and particulate matter caused and aroused The concentration will also continue to increase. Therefore, the present invention proposes that if the total number of indoor people/room volume is greater than the second set threshold, an alarm will be issued to notify the staff to deal with or increase the ventilation, so as to avoid the risk of disease caused by the increase in bacterial content and particulate matter . Similarly, for different room types, the second set threshold has different values.

When the number of indoor members and the composition structure remain unchanged, regardless of the influence of ventilation, the particle concentration and bacterial content are constantly increasing. If the bacterial content exceeds the third set threshold, an alarm is issued and the staff is notified to deal with it.

The present invention is based on a particle detection device capable of detecting the concentration of particles in real time, a bioaerosol detection device that periodically detects the concentration of bioaerosols, and combining real-time collected environmental parameters to create a bioaerosol-particle concentration correlation fitting model, thereby realizing the current Real-time detection of bioaerosol concentration in the environment, and then combined with the room type, calculate the real-time bacterial content in the current environment, guide the startup of disinfection and sterilization equipment, and assist in the decision-making of emergency treatment in the indoor environment. In addition, combined with the access control subsystem and shooting Subsystem, environmental detection subsystem, predict the change trend of indoor bacteria content, realize early warning, make instructions more accurate, effectively reduce energy consumption, timely warning of high-risk environments, reduce the occurrence of mass health incidents, and do The process can be traced and the results can be traced.

Compared with the existing technical solutions of the present invention, its remarkable beneficial effects are:

1) By generating the bioaerosol-particle concentration correlation fitting calculation formula in the current environment, a real-time detection model of indoor bacterial content suitable for the current environmental scene is established, and the model is combined with the real-time detected particulate matter in the environment Concentration, calculate the real-time aerosol concentration, and then combine the room type to calculate the real-time bacterial content.

2) Based on the Internet of Things technology, combined with the access control subsystem, the shooting subsystem, and the environmental detection subsystem, the trend of the indoor bacterial content is estimated to achieve early warning.

3) By collecting the aerosol particle clusters, detecting the fluorescence intensity of the aerosol particle clusters, and calculating the bioaerosol concentration, the requirement for lasers is low, and the bioaerosol detection device has a compact and simple structure, low cost, and is suitable for network deployment.

4) After using the track loop to collect and analyze the air everywhere in the room, the analysis results are averaged, and the error of the detection results is small.

5) The detection end face always faces the set detection area, so that the air sample pumped by the air pump is more representative, and at the same time, it is convenient for the user to observe the current working status of the system.

6) The particle detection device and the aerosol detection device are installed in a hollow turntable that can rotate. The air pumped by the two is almost the same, which improves the correlation between the bioaerosol concentration detection curve and the particle concentration curve. The calculated current environment The error of real-time bioaerosol concentration is small.

It should be understood that all combinations of the aforementioned concepts and the additional concepts described in more detail below can be regarded as part of the inventive subject matter of the present disclosure as long as such concepts are not mutually contradictory. In addition, all combinations of the claimed subject matter are regarded as part of the inventive subject matter of the present disclosure.

The foregoing and other aspects, embodiments and features of the teachings of the present invention can be more fully understood from the following description with reference to the accompanying drawings. Other additional aspects of the present invention, such as the features and/or beneficial effects of the exemplary embodiments, will be apparent in the following description, or learned from the practice of the specific embodiments taught by the present invention.

Description of the drawings

The drawings are not intended to be drawn to scale. In the drawings, each identical or nearly identical component shown in each figure may be represented by the same reference numeral. For clarity, not every component is labeled in every figure. Now, embodiments of various aspects of the present invention will be described by way of examples and with reference to the accompanying drawings, in which:

Fig. 1 is a flowchart of the method for real-time detection of indoor air bacteria content based on the Internet of Things of the present invention.

Fig. 2 is a flowchart of the method for real-time analysis of indoor air bacteria content based on the Internet of Things of the present invention.

Fig. 3 is a schematic diagram of modules of the real-time detection and analysis system of indoor air bacteria content based on the Internet of Things of the present invention.

Fig. 4 is a schematic structural diagram of the detection end face based on the Internet of Things of the present invention.

Detailed ways

In order to better understand the technical content of the present invention, specific embodiments are described below in conjunction with the accompanying drawings.

With reference to Figure 1, the present invention proposes a real-time detection and analysis method of indoor air bacteria content based on the Internet of Things, which is characterized in that the method includes:

The following analysis of each step in turn with specific examples.

The first step is to generate a bioaerosol concentration detection curve C(t)

Due to the particularity of bioaerosol detection, it is currently impossible to achieve an absolute real-time detection method, but it has been possible to achieve a periodic detection method, such as the following two methods.

The first way

Inhale indoor air in real time to enter the buffer cavity to form aerosol particle clusters, detect the light intensity of the aerosol particle clusters in the buffer cavity according to the set period, and calculate the bioaerosol concentration in the indoor air collected during the set period. Generate a bioaerosol concentration detection curve C(t).

The second way

The traditional colony count culture method is used to periodically detect the bioaerosol in the indoor air. This method is suitable for indoor situations where the environment is relatively stable, the change of bioaerosol concentration is relatively gentle, or there is a certain regularity.

Specifically, in step S1, the number of colonies in the indoor air is detected according to a set period, and after the number of colonies is corrected, the bioaerosol concentration detection curve C(t) is calculated;

The process of calculating the bioaerosol concentration detection curve C(t) after correcting the colony count includes the following steps:

S11: Use positive-hole method to correct the number of colonies:

Among them, Pr and r respectively represent the number of colonies after correction and the actual number of colonies, and N is the number of wells in each level of sampling;

S12: According to the gas flow σ and the collection time τ, the bioaerosol concentration detection curve C(t) is calculated according to the following formula, and the unit is (CFU·m ^-3 ):

Among them, I is the adjusted value of average bacterial content.

The second step is to generate a particle concentration curve P(t)

The particle concentration detection device similar to the particle concentration sensor can realize the real-time detection of indoor particle concentration.

Studies have shown that bacteria and germs are more easily adsorbed on fine particles, and the diameters of the fine particles that are easily adsorbed by different types of bacteria and germs are different. Some bacteria and germs that have a strong toxic effect on the human body are more likely to attach to smaller diameters. In addition, because the smaller the diameter of the fine particles, the easier it is to enter the human body, and the bacteria and germs adsorbed on it are more toxic to the human body. What users are most concerned about is the greater threat to human health. Germs and viruses. Therefore, the present invention proposes that when it is necessary to focus on monitoring the content of more toxic bacteria and viruses, the particle concentration can be corrected in combination with the particle size. For example, to divide the diameter of fine particles, introduce a weighting factor to correct the real-time indoor bacterial content, for example, the particle detection device detects indoor air particles, which are divided into the following categories according to the particle size: less than 0.3mm, 0.3mm -0.5mm, 0.5mm-1mm, 1mm-2.5mm, greater than 2.5mm, the corresponding particle concentration values of each particle size are P ₁ (t), P ₂ (t), P ₃ (t), P ₄ ( t), P ₅ (t). Preferably, the smaller the particle size, the greater the weight. Combined with the weight, the indoor particulate matter concentration P(t)=(P ₁ (t)·ω ₁ +P ₂ (t)·ω ₂ +P ₃ (t)·ω ₃ +P ₄ (t)·ω ₄ +P ₅ (t)·ω ₅ )/(ω ₁ +ω ₂ +ω ₃ +ω ₄ +ω ₅ ). It should be understood that the aforementioned particles are only to illustrate the principle of particle concentration correction, and in actual applications, corresponding designs can be made according to specific requirements and actual performance of the detection device.

Preferably, in order to reduce detection errors, the particulate matter detection device sends the collected particulate matter concentration to the control device, and the control device corrects the particulate matter concentration in the indoor air according to the following formula:

P(i) is the concentration of particulate matter collected at the i-th time, and the corrected concentration of particulate matter in indoor air P′(t) is the average value of the concentration of the latest M particulate matter collected. By taking the average value of the first M particle concentrations, the detected particle concentration can be corrected.

The third step is to obtain environmental impact parameters

The environmental impact parameters have an impact on the concentration of particulate matter and the amount of bacteria, including indoor temperature T _t , indoor humidity RH _t , room area S _t , indoor ventilation rate per unit time Q _t , total indoor number N _t , and number of pathogen carriers M _t etc.

In some cases, weather factors should also be considered, such as rain and snow, haze and so on.

In rain and snow, the humidity in the air will increase greatly, and it is easy to cause a sudden drop in temperature, leading to colds and other diseases. When the weather is hazy, the ventilation effect will be greatly reduced due to the poor outdoor air quality.

The fourth step is to calculate the real-time bioaerosol concentration F(t) in the current environment

In step S4, the bioaerosol concentration detection curve C(t) and the particulate matter concentration curve P(t) are combined to generate the real-time bioaerosol concentration F(t)=f(C(t), P( t), T _t , RH _t , S _t , Q _t , N _t , M _t ) process includes the following steps:

Indoor ventilation per unit area per unit time

= Indoor ventilation quantity per unit time Q _t /room area S _t .

The fifth step is to calculate the real-time bacterial content U(t) of the indoor air in the current environment

The bioaerosol contains not only germs and bacteria, but also other biomolecules, such as pollen, etc. Therefore, the present invention proposes to determine the ratio of the amount of bioaerosol formed by bacteria and germs to the total amount of bioaerosol based on the room type, and calculate Get the real-time bacterial content U(t) of the indoor air in the current environment.

The ratio of the number of bioaerosols formed by bacteria and germs to the total number of bioaerosols is an empirical value, which can be obtained by creating an empirical model through machine learning algorithms, or by analyzing historical data.

With reference to Fig. 2, based on the aforementioned method for real-time detection of indoor bacterial content, the present invention also mentions a method for real-time analysis of indoor air bacterial content based on the Internet of Things, including two situations where people enter and leave.

In the first case, someone enters

The method also includes:

S110: In response to a person entering the room, determine whether the person is a pathogen carrier, if so, go to step S120, otherwise, go to step S130.

S120: Add 1 to the number of pathogen carriers M _t , and determine whether the number of indoor pathogen carriers M _t exceeds the first set threshold. If yes, generate an alarm signal and go to step S170; otherwise, go to step S130.

S130: Add 1 to the total number of people in the room N _t , and determine whether the total number of people in the room N _t /room volume S _t exceeds the second set threshold. If yes, generate an alarm signal and go to step S170; otherwise, go to step S140;

S140: Detect the particulate matter concentration P(t) in the indoor air and environmental parameters in real time, and calculate the real-time bioaerosol concentration F(t) in the indoor air.

S150: Combining the bioaerosol concentration F(t) in the indoor air and the room type, calculate the real-time indoor bacterial content U(t).

S160: Determine whether the indoor real-time bacterial content U(t) exceeds the third set threshold, and if so, generate an alarm signal.

S170: End the analysis of the bacterial content in the case of personnel entry.

specific:

In the second situation, someone leaves

The method also includes:

S210: In response to a person leaving the room, determine whether the person is a pathogen carrier, if yes, go to step S220, the number of pathogen carriers M _{t is} reduced by 1, and go to step S220; otherwise, go directly to step S230;

S220: The total number of people in the room N _{t is} reduced by 1, the particle concentration P(t) in the indoor air and environmental parameters are detected in real time, and the real-time bioaerosol concentration F(t) in the indoor air is calculated;

S230: Calculate the real-time bacterial content U(t) in the room based on the bioaerosol concentration F(t) in the indoor air and the room type;

S240: Determine whether the indoor real-time bacterial content U(t) exceeds the third set threshold, and if so, generate an alarm signal.

S250: End the analysis of bacterial content in the case of personnel leaving.

When a person leaves, first determine whether the person is a pathogen carrier. Compared with ordinary members, the departure of the pathogen carrier will reduce the increase of indoor pathogens more, so different treatment is required.

If the leaver is a pathogen carrier, the number of pathogen carriers M _{t is} reduced by 1, and the total number of indoor people N _{t is} reduced by 1. The real-time bioaerosol concentration is calculated according to the number of new carriers M _t and the new total number of indoor people N _t , Otherwise, only the total number of people in the room N _{t is} reduced by 1, and the real-time bioaerosol concentration is calculated according to the new total number of people in the room N _t , and then the real-time bacteria content in the room is calculated.

Regarding the tracking of pathogen carriers, the present invention proposes two treatment measures.

The first treatment is for members who have been infected before entering the room

The human body infrared sensor is used to detect the body temperature of the entering person. If the detected body temperature exceeds the set body temperature threshold, the entering person is determined to be a pathogen carrier, and the image acquisition system is used to collect the face image of the person, and the collected face image is stored Enter the pathogen carrier database.

When a person leaves the room, the face image of the person who has left is collected, and the collected face image is compared with the face image in the virus carrier database to determine whether the person who has left is a virus carrier.

The second treatment measure is for members who have contracted diseases after entering the room

Collect video images in the room in real time, and track and analyze the behavior of people in the video images within the second set time range. If the sickness behavior of any person in the image within the second set time range exceeds the set threshold, Determine that the person is a pathogen carrier, compare the person’s face image with the pathogen carrier database, and

In response to the person's face image not being stored in the germ carrier database, the number of germ carriers M _{t is} increased by 1, and the person's face image is stored in the germ carrier database.

The sick behavior includes coughing, sneezing, runny nose, nasal congestion and so on.

It should be understood that the real-time analysis method of indoor air bacterial content based on the Internet of Things mentioned in the present invention is also applicable to other real-time or periodic detection methods of bacterial content related to the number of indoor people and the number of pathogen carriers, and is not limited to The detection method mentioned in the present invention.

The access control subsystem includes a human body infrared sensor, a face image acquisition device, and a counting device. The human body infrared sensor is used to identify the attributes of entering and exiting personnel. The attributes of the entering and exiting personnel include pathogen carriers and non-virus carriers. The image acquisition device is used to collect facial images of pathogen carriers, and the collected facial images are sent to the storage device, and the counting device is used to count the current total number of people in the room and the number of pathogen carriers. The specific identification method is as described above.

The photographing subsystem includes a photographing device and an image analysis device. The photographing device is used to photograph video images in the room and send the photographed video images to the image analysis device. The image analysis device analyzes the video images taken by the photographing device. Identify whether there is a person who has been sick, and compare the face image of the person who has the sick behavior with the face image of the pathogen carrier in the storage device to determine whether a new pathogen carrier has appeared. The specific judgment method is as described above.

The environmental detection subsystem includes a track circuit, a rotating platform, a housing 11, a temperature and humidity sensor 15, a rain and snow sensor, a particulate matter detection device 13, and a bioaerosol detection device 14.

The housing 11 includes a detection end surface facing a designated area. The track circuit is distributed on the wall of the room. The housing 11 is installed on the track circuit through a rotating platform and moves along the track circuit according to external control instructions. Rotate around the rotating platform so that the detection end face always faces the designated area.

Preferably, the track loop surrounds the indoor wall from top to bottom, so that the housing 11 can collect air from multiple locations in the room.

More preferably, the time for the housing 11 to move one loop along the track loop is defined as a set period to fully collect the air in multiple places in the room. After the track loop is used to collect and analyze the air everywhere in the room, Taking the average value of the analysis results, the error of the detection results is small, and the collected samples are universal.

By rotating the platform, the detection end face is always facing the set detection area, such as the center of the room, etc., so that the air sample pumped by the air pump is more representative, and at the same time, it is convenient for users to observe the current working status of the system. For example, an indicator light 16 is set on the detection end face. To indicate the working status of each detection component of the system and so on.

The rain and snow sensor is set outdoors to detect outdoor rain and snow levels in real time, and send the detected rain and snow levels to the control device, and the control device adjusts the real-time bioaerosol concentration calculation formula according to the received rain and snow levels. Adjust parameter b.

The temperature and humidity sensor 15 is installed in the housing 11, and its detection end is installed adjacent to the detection end face of the housing 11. The temperature and humidity sensor 15 is electrically connected to the control device for real-time detection of indoor temperature and humidity, and feedback of the detection results to Control device.

A hollow turntable 12 with a circular cross-section is installed in the housing 11. The hollow turntable 12 rotates around its axis centerline. The particle detection device 13 and the bioaerosol detection device 14 are both installed in the hollow turntable 12. The particle detection device 13. The air inlets of the bioaerosol detection device 14 are all located on the detection end surface of the housing 11.

The particulate matter detection device 13 is used to collect the concentration of particulate matter in the indoor air in real time, and send the collection result to the control device, and the control device generates a particulate matter concentration curve P(t).

The biological aerosol detection device 14 includes an air pump, a buffer cavity, and a fluorescence detection unit. The air pump sucks indoor air in real time into the buffer cavity to form aerosol particle clusters. The fluorescence detection unit detects the aerosol particle clusters in the buffer cavity according to a set period. Send the detected light intensity to the control device.

The particle detection device 13 and the bioaerosol detection device 14 are installed in the hollow turntable 12 that can rotate. The air pumped by the two is almost the same, which improves the correlation between the bioaerosol concentration curve and the particle concentration curve. The calculated current environment The error of the real-time bioaerosol concentration is small.

The control device selects a set time range, the set time range includes at least two set periods, and calculates indoor temperature T _t , indoor humidity RH _t , room area S _t , and unit time within the set time range Indoor ventilation Q _t , total number of people in the room N _t , number of pathogen carriers M _t , combined with the bioaerosol concentration detection curve C(t) and particulate matter concentration curve P(t), calculate the real-time bioaerosol concentration in the current environment F(t)=f(C(t), P(t), T _t , RH _t , S _t , Q _t , N _t , M _t ).

In a further embodiment, the system further includes a communication module, and the control device is connected with the communication module to establish a communication link with the fresh air system.

The control device responds to the establishment of any one of the following conditions:

1) The number of pathogen carriers in the room is greater than the first set threshold, 2) Whether the total number of people in the room/room volume exceeds the second set threshold, 3) Whether the real-time indoor bacterial content exceeds the third set threshold, an alarm signal is generated , Through the communication module to send ventilation control instructions to the fresh air system to increase the ventilation volume to the set ventilation threshold.

There are many ways to determine the ventilation threshold, which are determined according to actual needs.

For example, it can be set according to the level, for example, if any one of the aforementioned conditions is satisfied, the ventilation volume can be increased by one level. For another example, it is determined according to the level of the alarm signal, for example, the number of pathogen carriers entering at the same time is too large, and the ventilation rate is adjusted according to the increased number of pathogen carriers. Even the aforementioned two methods are combined to form an intelligent ventilation adjustment method, etc. The purpose is to reduce the indoor particulate matter concentration and bacterial content by increasing the ventilation.

For some special occasions, sterilization equipment and/or sterilization equipment are also matched. The aforementioned control method is also applicable to sterilization equipment and/or sterilization equipment. For example, in response to any of the foregoing conditions being established, the sterilization equipment and/or sterilization equipment, or Increase the operating power of the sterilization equipment and/or disinfection equipment, etc., to achieve the purpose of intelligent control based on the Internet of Things, and improve the sterilization effect as much as possible on the basis of saving energy. The method of increasing the operating power can refer to the aforementioned ventilation volume The adjustment method will not be repeated here.

In this disclosure, various aspects of the present invention are described with reference to the accompanying drawings, in which many illustrated embodiments are shown. The embodiments of the present disclosure are not necessarily defined to include all aspects of the present invention. It should be understood that the various concepts and embodiments introduced above, as well as those described in more detail below, can be implemented in any of many ways, because the concepts and embodiments disclosed in the present invention are not Limited to any implementation. In addition, some aspects disclosed in the present invention can be used alone or in any appropriate combination with other aspects disclosed in the present invention.

Although the present invention has been disclosed as above in preferred embodiments, it is not intended to limit the present invention. Those with ordinary knowledge in the technical field of the present invention can make various changes and modifications without departing from the spirit and scope of the present invention. Therefore, the protection scope of the present invention shall be subject to what is defined in the claims.

Claims

A real-time detection and analysis method of indoor air bacteria content based on the Internet of Things, characterized in that the method includes:

S1: Detect the collected bioaerosol concentration of indoor air according to the set period, and generate a bioaerosol concentration detection curve C(t);

S2: Collect the concentration of particulate matter in the indoor air in real time to generate a particulate matter concentration curve P(t);

S3: Select a set time range, the set time range includes at least two set periods, and calculate the indoor temperature T t , indoor humidity QH t , room area S t , and indoor ventilation per unit time within the set time range Quantity Q t , the total number of indoor people N t , and the number of pathogen carriers M t ;

S4: Combine the bioaerosol concentration detection curve C(t) and the particulate matter concentration curve P(t) to calculate the real-time bioaerosol concentration F(t)=f(C(t), P(t) in the current environment, T t , RH t , S t , Q t , N t , M t );

S5: According to the room type, determine the ratio of the amount of bioaerosol formed by bacteria and germs to the total amount of bioaerosol, and calculate the real-time bacterial content U(t) of the indoor air in the current environment.
The method for real-time detection and analysis of indoor air bacterial content based on the Internet of Things according to claim 1, wherein in step S4, the combined bioaerosol concentration detection curve C(t) and particulate matter concentration curve P(t) ), the process of generating the real-time bioaerosol concentration F(t) = f(C(t), P(t), T t , RH t , S t , Q t , N t , M t ) in the current environment includes The following steps:

S41: Calculate the indoor ventilation per unit area per unit time according to the following formula:

Indoor ventilation per unit area per unit time

S42: Calculate the indoor temperature T t in the indoor air, indoor humidity RH t , and indoor ventilation per unit area per unit time
The weight of the influence of the total number of indoor people N t and the number of pathogen carriers M t on the bioaerosol concentration detection curve C(t) and particulate matter concentration curve P(t);

S43: Calculate the real-time bioaerosol concentration F(t) in the current environment based on the particle concentration curve P(t) in combination with the influence weight.
The method for real-time detection and analysis of indoor air bacteria content based on the Internet of Things according to claim 1, wherein the method further comprises:

When the outdoor air quality is excellent, the real-time bioaerosol concentration F(t) is:

Among them, K 1 is the influencing factor of the indoor environment on bacterial reproduction, K 2 is the influence of indoor temperature T t , indoor humidity RH t , room area S t , indoor ventilation rate per unit time Q t , and total number of people in the room N t on the bioaerosol concentration Detection curve C(t) and particle concentration curve P(t) influence weight ratio, b is the adjustment parameter, RH 1 is the humidity correction factor, and ΔC is the average bioaerosol concentration produced by each pathogen carrier per unit time.
The method for real-time detection and analysis of indoor air bacteria content based on the Internet of Things according to claim 1, wherein the method further comprises:

S110: In response to a person entering the room, determine whether the person is a pathogen carrier, if yes, go to step S120, otherwise, go to step S130;

S120: add 1 to the number of pathogen carriers M t , determine whether the number of indoor pathogen carriers M t exceeds the first set threshold, if yes, generate an alarm signal and go to step S170; otherwise, go to step S130;

S130: Add 1 to the total number of people in the room N t , determine whether the total number of people in the room N t /room volume S t exceeds the second set threshold, if yes, generate an alarm signal and go to step S170, otherwise, go to step S140;

S140: real-time detection of the concentration of particulate matter P(t) in the indoor air and environmental parameters, and calculation of the real-time bioaerosol concentration F(t) in the indoor air;

S150: Calculate the real-time bacterial content U(t) in the room based on the bioaerosol concentration F(t) in the indoor air and the room type;

S160: Determine whether the indoor real-time bacterial content U(t) exceeds the third set threshold, and if so, generate an alarm signal;

S170: End the analysis of the bacterial content in the case of personnel entry.
The method for real-time detection and analysis of indoor air bacteria content based on the Internet of Things according to claim 1, wherein the method further comprises:

S210: In response to a person leaving the room, determine whether the person is a pathogen carrier, if yes, go to step S220, the number of pathogen carriers M t is reduced by 1, and go to step S220; otherwise, go directly to step S230;

S220: The total number of people in the room N t is reduced by 1, the particle concentration P(t) in the indoor air and environmental parameters are detected in real time, and the real-time bioaerosol concentration F(t) in the indoor air is calculated;

S230: Calculate the real-time bacterial content U(t) in the room based on the bioaerosol concentration F(t) in the indoor air and the room type;

S240: Determine whether the indoor real-time bacterial content U(t) exceeds the third set threshold, and if so, generate an alarm signal;

S250: End the analysis of bacterial content in the case of personnel leaving.
The method for real-time detection and analysis of indoor air bacteria content based on the Internet of Things according to claim 1, wherein the method further comprises:

The human body infrared sensor is used to detect the body temperature of the entering person. If the detected body temperature exceeds the set body temperature threshold, the entering person is determined to be a pathogen carrier, and the image acquisition system is used to collect the face image of the person, and the collected face image is stored Enter the pathogen carrier database.
The method for real-time detection and analysis of indoor air bacteria content based on the Internet of Things according to claim 6, wherein the method further comprises:

In response to a person leaving the room, the face image of the person leaving the room is collected, and the collected face image is compared with the face image in the pathogen carrier database to determine whether the person leaving is a pathogen carrier.
The method for real-time detection and analysis of indoor air bacteria content based on the Internet of Things according to claim 6, wherein the method further comprises:

Collect video images in the room in real time, and track and analyze the behavior of people in the video images within the second set time range. If the sickness behavior of any person in the image within the second set time range exceeds the set threshold, Determine that the person is a pathogen carrier, compare the person’s face image with the pathogen carrier database, and

In response to the person's face image not being stored in the germ carrier database, the number of germ carriers Mt is increased by 1, and the person's face image is stored in the germ carrier database.
A real-time detection and analysis system for indoor air bacteria content based on the Internet of Things, characterized in that the system includes an access control subsystem, a photographing subsystem, an environment detection subsystem, and a control device;

The access control subsystem includes a human body infrared sensor, a face image acquisition device, and a counting device. The human body infrared sensor is used to identify the attributes of entering and exiting personnel. The attributes of the entering and exiting personnel include pathogen carriers and non-virus carriers. The image acquisition device is used to collect the facial images of the germ carriers, and the collected facial images are sent to the storage device, and the counting device is used to count the total number of people in the room and the number of germ carriers;

The photographing subsystem includes a photographing device and an image analysis device. The photographing device is used to photograph video images in the room and send the photographed video images to the image analysis device. The image analysis device analyzes the video images taken by the photographing device. Recognize whether there is a person who has been sick, and compare the face image of the person who has the sick behavior with the face image of the pathogen carrier in the storage device to determine whether a new pathogen carrier has appeared;

The environmental detection subsystem includes a track loop, a rotating platform, a housing, a temperature and humidity sensor, a rain and snow sensor, a particle detection device, and a bioaerosol detection device;

The housing includes a detection end face facing a designated area, the track circuit is distributed on the wall of the room, the housing is installed on the track circuit through a rotating platform, and moves along the track circuit according to an external control command while rotating around The platform rotates so that the detection end face always faces the designated area;

The time for the housing to move one loop along the track loop is defined as a set period;

The rain and snow sensor is arranged outdoors to detect the outdoor rain and snow level in real time, and send the detected rain and snow level to the control device;

The temperature and humidity sensor is installed in the housing, and its detection end is installed near the detection end face of the housing. The temperature and humidity sensor is electrically connected to the control device for real-time detection of indoor temperature and humidity, and the detection result is fed back to the control device;

A hollow turntable with a circular cross-section is installed in the housing, and the hollow turntable rotates around its axis centerline. The particulate matter detection device and the bioaerosol detection device are all installed in the hollow turntable. The air inlets are all located on the detection end surface of the shell;

The particulate matter detection device is used to collect the concentration of particulate matter in the indoor air in real time, and send the collection result to the control device, and the control device generates a particulate matter concentration curve P(t);

The biological aerosol detection device includes an air pump, a buffer cavity, and a fluorescence detection unit. The air pump sucks indoor air in real time into the buffer cavity to form aerosol particle clusters. The fluorescence detection unit detects the aerosol particle clusters in the buffer cavity according to a set period. Light intensity, send the detected light intensity to the control device;

The control device calculates the bioaerosol concentration in the indoor air collected during the aforementioned set period according to the received light intensity, and generates a bioaerosol concentration detection curve C(t);

The control device selects a set time range, the set time range includes at least two set periods, and calculates indoor temperature T t , indoor humidity RH t , room area S t , and unit time within the set time range Indoor ventilation Q t , total number of people in the room N t , number of pathogen carriers M t , combined with the bioaerosol concentration detection curve C(t) and particulate matter concentration curve P(t), calculate the real-time bioaerosol concentration in the current environment F(t)=f(C(t), P(t), T t , RH t , S t , Q t , N t , M t );

The control device determines the ratio of the amount of bioaerosol formed by bacteria and germs to the total amount of bioaerosol in combination with the room type, and calculates the real-time bacterial content U(t) of the indoor air in the current environment.
The real-time detection and analysis system of indoor air bacteria content based on the Internet of Things according to claim 9, wherein the system further comprises a communication module, and the control device is connected with the communication module to establish a communication link with the fresh air system ；

The control device responds to the establishment of any one of the following conditions:

1) The number of pathogen carriers in the room is greater than the first set threshold, 2) Whether the total number of people in the room/room volume exceeds the second set threshold, 3) Whether the real-time indoor bacterial content exceeds the third set threshold, an alarm signal is generated , Through the communication module to send ventilation control instructions to the fresh air system to increase the ventilation volume to the set ventilation threshold.