KR20240077724A - Apparatus for detecting aerosol - Google Patents

Abstract

The present invention is a lightweight, small-sized device with a simple structure, which not only detects and identifies bio particles such as fine dust suspended in the air, allergens, and microorganisms with a single detection element. , It is about aerosol detection technology that can estimate the type of bioparticles, measure the size and quantity of fine dust or bioparticles, and estimate the shape. The light irradiated to the aerosol is scattered as light of the same wavelength on the surface of the fine dust, so the presence of fine dust can be recognized through this scattered light, and bio particles such as microorganisms and allergens are determined by the composition of their constituent proteins. Accordingly, the irradiated light is split into several wavelengths, so bioparticles that are distinct from fine dust can be recognized by analyzing this split light.

Description

Aerosol detection device {Apparatus for detecting aerosol}

The present invention relates to a technology for detecting components contained in aerosol, and specifically, to identify fine dust and bio particles contained in aerosol, estimate the type of bio particles, and detect fine dust and bio particles. It is about technology that can measure the size and quantity and estimate the shape.

Aerosols present in industries, homes, roads, etc. contain fine dust and microorganisms. As a prior technology for detecting fine dust and microorganisms in aerosols, there is domestic patent publication 10-2016-0029183 (device for detecting fine dust and microorganisms). This is a technology that detects fine dust and microorganisms by irradiating light of a specific wavelength to aerosols and detecting scattered light reflected and scattered from fine dust particles and fluorescent signals emitted from microorganisms.

Figure 1 is a cross-sectional view for explaining the prior art. A measurement sample (aerosol) flows into the sample chamber 11. The LED 21 of the light source unit 2 irradiates light to the aerosol through the first optical system 3. The scattered light reflected and scattered by colliding with the fine dust in the aerosol and the fluorescence generated by the microorganisms in the aerosol are split at 45° by the spectral element 51 of the second optical system 5 and transmitted to the first detector 6 and the second detector, respectively. It is detected by the detection unit 7. The first detection unit 6 and the second detection unit 7 respectively detect scattered light and fluorescence and transmit them to the signal processing unit, and the signal processing unit processes these detection signals separately to calculate the presence and amount of fine dust and microorganisms. do.

This prior art has two optical systems and two detection units, and as shown in FIG. 1, the structure is complex, and accordingly, it is heavy and expensive, so it is not suitable for industrial use and is difficult to use for personal or home use, especially portable use.

In addition, in the above prior art as well as other prior art, fine dust and microorganisms can be distinguished, but it is not possible to determine the type of microorganism and distinguish, for example, whether it is a normal bacterium or a harmful bacterium. In particular, as people mainly live in indoor environments in a situation where infectious diseases such as COVID-19 are prevalent, there is a need to identify allergens such as mites, bear mites, dog and cat dander, and pollen, but these cannot be identified using conventional technology. .

Accordingly, the present invention is a lightweight, small-sized device with a simple structure, which detects and identifies bio particles such as fine dust suspended in the air, allergens, and microorganisms with a single detection element. In addition, we propose an aerosol detection technology that can estimate the type of bioparticles, measure the size and quantity of fine dust and bioparticles, and estimate the shape.

According to the present invention to solve the above problem, a light source is concentrated and irradiated to the aerosol inlet passage. When the light is irradiated to fine dust and bioparticles, some of it is reflected and scattered on the surface of each particle and some emits fluorescence. Since the irradiated light is reflected and scattered as light of the same wavelength on the surface of fine dust, the presence of fine dust can be recognized through this reflected and scattered light, and information on the size and quantity of the fine dust can be obtained. And bio particles such as microorganisms and allergens split the irradiated light into various wavelengths depending on the composition of their protein components. By analyzing this spectralized light, bioparticles that are distinct from fine dust can be recognized. At this time, the spectral spectrum appears differently depending on the type of bioparticle, and if this is passed through a diffraction grid or grating and analyzed in detail, the type of each bioparticle can be clearly distinguished.

In order to estimate the type of bioparticles using the fluorescence (spectroscopic) spectrum emitted from bioparticles, it is necessary to further subdivide the spectral information. For this purpose, the intensity of fluorescence wavelengths emitted differently depending on the protein and shape of the bioparticles is acquired for each wavelength using a transmission-type or reflection-type diffraction grid or grating, and the intensity of the fluorescence wavelength is converted into a database through machine learning to further improve analysis precision. It can be improved.

Since only one optical element and one detection element are required to irradiate and detect light in the aerosol, the composition is simpler than that of prior art, so it can be commercialized for personal and home use and can be used easily in real time.

Additionally, by using machine learning technology for detection and analysis, precise analysis of the type, size, quantity, and shape of bioparticles is possible.

A more detailed structure and operation of the present invention will become clearer through specific embodiments described later together with the drawings.

According to the present invention, a technology that can detect fine dust and floating bioparticles (including allergens Polen, Mold, Mite, and Pet Dander), recognize the type of bioparticles in real time, and estimate their size and quantity. It can be used in fields such as identification of various chemical species, environmental monitoring, identification of allergens, and clinical diagnosis.

1 is a cross-sectional view of a detection device according to the prior art
Figure 2 is a configuration diagram of an aerosol detection device according to the present invention
Figure 3 is a configuration diagram of an aerosol detection device according to a preferred embodiment of the present invention.
Figure 4 is an example of a transmission type diffraction grating.
Figure 5 is an example of a reflective diffraction grating.
Figure 6 is a configuration diagram of one embodiment of the analysis unit 700.
Figures 7a and 7b are examples of spectral spectra for each bioparticle.
8 is a configuration diagram of another embodiment of the analysis unit 700.
Figure 9 is a configuration diagram of a computer system that can be used to implement the present invention
Figures 10 and 11 are examples of the exterior of an aerosol detector commercialized with the aerosol detection device of the present invention, Figure 10 is an external perspective view, and Figure 11 is an internal plan view.
Figure 12 is a diagram explaining the principle of measuring the size of fine dust or bioparticles from a detection signal
Figure 13 is a diagram explaining the principle of measuring the quantity of fine dust or bioparticles from a detection signal

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. The terms used in the following description are intended to describe preferred embodiments of the present invention and are not intended to limit the present invention. In this specification, the singular also includes the plural unless specifically stated. Additionally, the term 'comprise, comprising, etc.' used in the specification refers to the presence or absence of one or more other components, steps, operations, and/or elements other than the mentioned elements, steps, operations, and/or elements. It is used in the sense that it does not exclude addition.

Figure 2 is a configuration diagram of an aerosol detection device according to the present invention.

The aerosol detection device includes an aerosol chamber 100 into which the aerosol to be measured is introduced; A light source 200 that emits light to irradiate the aerosol in the aerosol chamber 100; A light concentrator 300 that focuses light to be radiated onto the aerosol in the aerosol chamber 100; An emitter 400 that converts light scattered or split from aerosol fine dust or bioparticles into parallel light; a spectral display unit 500 that receives the parallel light formed in the emitter 400 and subdivides the spectral information to reveal a spectral spectrum; a detection unit 600 that receives the spectral spectrum displayed by the spectrum salience unit 500 and outputs it as a spectrum detection signal, which is an electrical signal; An analysis unit 700 that analyzes the spectrum detection signal received from the detection unit 600 to identify fine dust and bioparticles, estimate the type of bioparticles, and estimate the size and quantity of fine dust and bioparticles; An output unit 800 that outputs the results analyzed by the analysis unit 700; It includes a control unit 900 that controls the components of the configured aerosol detection device.

Hereinafter, each component will be described in detail. The following description primarily refers to Figure 3, which shows a preferred embodiment of the present invention.

The aerosol chamber 100 may include an inlet 120 and a passage 130 through which the aerosol to be measured 110 flows, and an outlet 140 through which the aerosol 110 flows out. Since light is continuously irradiated while the aerosol passes through the inlet, passage, and outlet, aerosol detection can be performed in real time.

The chamber 100 can be structurally designed so that the inflow and outflow of the aerosol 110 is achieved by natural atmospheric flow. In another embodiment, the inflow and outflow of the aerosol 110 may be induced using a blower or fan 150. At this time, the blower or fan 150 can be controlled by the controller 900 to turn on/off and adjust the flow rate of the aerosol 110 passing through the aerosol chamber 100. In FIG. 3, the location of the fan 150 is shown as being at the outlet 140, but the location is arbitrary and may be located at the inlet 120 or the passage 130.

The wall of the aerosol chamber 100 may be made of a transparent material so that the light emitted from the light source 200 irradiates the aerosol. Alternatively, the light collection unit 300 may be installed directly in the aerosol chamber 100 and manufactured to internally radiate light to the aerosol. And although the term chamber is used here, its shape can actually be implemented in various ways. For example, it can be manufactured in a chamber shape, tube shape, etc. It can also be designed as a separate space, or it can be designed to form a space together with other components, for example, optical-related elements (see FIG. 11).

The light source 200 emits light (emission light 210) to be irradiated to the aerosol 110 in the aerosol chamber 100. As the light source 200, optical devices such as laser diodes and LEDs can be used, and optical devices with an emission wavelength in the infrared (UV) band can be used. The light source 200 may also be controlled by the control unit 900 in terms of on/off, light quantity, and emission wavelength.

The light concentrator 300 forms a light focus 310 at a predetermined point in the aerosol chamber 100 in order to focus light on the aerosol 110 in the aerosol chamber 100, and the irradiation light 220 is directed at this position. Be focused. To this end, the light concentrator 300 can be implemented as one or several combinations of lens assemblies 320. The control unit 900 can be designed to control the position, angle, etc. of the light concentrator 300 to automatically converge light to an accurate location or manually converge light to a location desired by the user. For example, the control unit 900 may control the light concentrator 300 electrically or mechanically using a motor, actuator, or other displacement element.

In this way, when the irradiation light 220 is irradiated to the aerosol 110, the light is scattered or split from fine dust and bio particles in the aerosol. In other words, light is reflected and scattered on the fine dust surface, generating reflected and scattered light 230 of the same wavelength as the irradiated light, and the light irradiated to allergens, microorganisms, and other bio-particles is split into various wavelengths and contains spectral information. Spectral or fluorescence 240 occurs (of course, reflection and scattering also occur in bio particles). The spectral information included in the spectrometer 240 has various wavelength distributions depending on the type of bioparticle. The emitter 400 serves to transform the light 230 reflected or scattered from fine dust and bio-particles and the split light 240 into parallel light 250. In order to create parallel light 250, the emitter 400 can be implemented as a paraboloid 410. However, it is also possible to implement the emitter 400 as a lens rather than a paraboloid.

Here, the function of the emitting unit 400 may also be controlled by the control unit 900. For example, the control unit 900 can be designed to automatically or manually control the parabola, lens, or other mechanisms of the emitter 400 to create accurate parallel light 250.

The spectral display unit 500 receives the parallel light 250 emitted from the emitter 400, subdivides the spectral information contained in the parallel light 250, and displays it as a spectral spectrum. For this purpose, the spectral salient portion 500 can be implemented as a diffraction grating or diffraction grid. Looking at FIG. 3, a spectral spectrum 520 can be seen in which the wavelength information (λ1, λ2, λ3, ...) included in the parallel light 250 is subdivided by the diffraction grating 510. Different spectral information appears depending on the type of bioparticle, and this is subdivided through a diffraction grid or grating, expressed as a spectrum, and then sent to the detection unit 600.

Although FIG. 3 shows that a transmission type diffraction grating 510 is used as the diffraction grating, it is also possible to use a reflection type diffraction grating. FIG. 4 illustrates the transmission type diffraction grating 510 and the spectral spectrum 520 displayed thereby, and FIG. 5 illustrates the reflective diffraction grating 515 and the spectral spectrum 520 displayed thereby. Also here, the spectrum salience unit 500 may be controlled by the control unit 900. The diffraction function and position of the diffraction grating can be adjusted through electrical control by the control unit 900.

The detection unit 600 detects the spectral spectrum 520 displayed by the spectrum salience unit 500 and converts it into a detection signal 610, which is an electrical signal. This detection signal 610 may include the unique wavelength distribution characteristics (spectral spectrum) for the bioparticles if the aerosol component is bioparticles, but if the aerosol component is fine dust, the irradiated light ( 220) will contain the same wavelength information.

The device used as the detection unit 600 is generally a photodiode, but it is preferable to use a color photodiode to accurately estimate the type of bioparticle, and to detect finer spectral (fluorescence) information, a PMT (PMT) is used. It is more desirable to use a photo multiplying tube (SiPM) or a silicon photomultiplier (SiPM). The detection unit 600 may also be controlled for on/off, sensitivity adjustment, position adjustment, etc. by the control unit 900.

The analysis unit 700 analyzes the detection signal 610 received from the detection unit 600 to identify fine dust and bioparticles, estimate the type of bioparticles, and measure the size and quantity of fine dust and bioparticles and form them. Estimate .

Figure 6 is a detailed configuration diagram of the analysis unit 700.

A fine dust/bio-particle identification unit 710 that distinguishes whether the component contained in the aerosol is fine dust or bio-particles from the detection signal 610 received from the detection unit 600; a spectrum analysis unit 720 that analyzes the spectral spectrum of the bioparticles contained in the detection signal 610 when the aerosol component is identified as a bioparticle; It includes a bioparticle type estimation unit 730 that estimates the type of bioparticle corresponding to the analyzed spectrum.

If the component of the aerosol is bioparticles, the received detection signal 610 will include spectroscopic (fluorescence) information about the bioparticles. However, if the component of the aerosol is fine dust, the irradiated light irradiated to the aerosol (FIG. 3 It will contain the same wavelength information as the wavelength of 220). Therefore, the fine dust/bio-particle identification unit 710 can analyze the detection signal 610 to identify whether the component contained in the aerosol is fine dust or bio-particles. Furthermore, the fine dust/bio particle identification unit 710 can identify the ratio of fine dust and bio particles contained in the aerosol. For example, identification results such as “70% fine dust, 30% bioparticles” could be output.

To improve the precision of identification, machine learning techniques such as deep learning can be used. For example, by learning the wavelength characteristic data of various fine dust and bioparticles to build a learning model and database, and analyzing the detection signal 610 input in real time with a neural network, the corresponding detection signal 610 is generated from the learning model. It is possible to infer whether it is about fine dust or bioparticles.

If the fine dust/bio particle identification unit 710 identifies the component of the aerosol as fine dust, the fine dust identification result 715 is output from the analysis unit 700. On the other hand, if it is identified as a bio particle, it is output as a bio particle. The particle spectrum analysis unit 720 analyzes the bioparticle spectrum included in the detection signal 610. The bioparticle spectrum is, for example, as shown in Figures 7a,b. Figure 7a shows the spectral spectrum for E. coli, and Figure 7b shows the spectral spectrum for mold.

The bioparticle type estimation unit 730 estimates the type of bioparticle corresponding to the bioparticle spectrum and outputs a type estimation result 735. Since the distribution of peak wavelength(s) in the spectral spectrum as illustrated in FIGS. 7A and 7B is a unique characteristic of each bioparticle, the bioparticle type estimation unit 730 estimates the type of the corresponding bioparticle from the aspect of these wavelength distributions. It can be done. Machine learning techniques such as deep learning can be used to improve the precision of analysis and estimation. For example, a learning model and database are built by learning feature data extracted from the wavelength spectrum of various bioparticles, and the bioparticle spectral spectrum included in the detection signal 610 input in real time is analyzed using a neural network to determine the corresponding spectrum. It is possible to infer what type of bioparticle it is about.

Figure 8 is a configuration diagram of another embodiment of the analysis unit 700.

In addition to the fine dust/bio particle identification unit 710, bio particle spectrum analysis unit 720, and bio particle type estimation unit 730 shown in FIG. 6, the size of fine dust or bio particles can be determined from the detection signal 610. A size measuring unit 740 may be included to measure the size. To measure the size of fine dust or bioparticles, the flow rate control function of the aerosol 110 by the control unit 900 and the blower or fan 150 mentioned above and the detection signal 610 received from the detection unit 600 can be used. . The control unit 900 knows the speed of the aerosol 110 passing through the aerosol chamber 100, that is, the flow velocity (V). This is because the control unit 900 operates the blower or fan 150 to flow the aerosol 110. Since the flow velocity V of the aerosol 110 is known and the time (T) during which the aerosol 110 flows is known, the size (L) of the aerosol 110 can be obtained by calculating L = VT. Figure 12 shows the detection signal detected by the detection unit 600 in the time-intensity dimension. Referring to FIG. 12, the intensity of the detection signal when there is no fine dust or bioparticles in the aerosol 110 is that 100% of the light emitted from the light source 200 is detected by the detection unit 600 and the fine dust or bioparticles are detected. It can be seen that when light is scattered or dispersed, it is detected at a predetermined y%. In this detection signal, the flow time T of the aerosol 110 is the difference between the time t1 when the detection intensity drops from 100% to y% and the time t2 when it rises again to 100%. Therefore, the size L of fine dust or bioparticles can be obtained by calculating L=VT.

In addition, a quantity measuring unit 750 that measures the quantity of fine dust or bioparticles from the detection signal 610 may be additionally included. Quantity measurement of fine dust or bioparticles can also be performed using detection signals appearing in the time-intensity dimension as shown in FIG. 12, as in the case of size measurement. If a large number of fine dust or bioparticles contained in the aerosol 110 pass through the aerosol chamber 100, a pulse-shaped signal as shown in FIG. 13 will be detected. This is because 100% signal intensity and y% signal intensity are detected for particles contained in aerosol, respectively. By counting the number of each pulse piece P1, P2, ..., PN in this pulse-type detection signal, the quantity of fine dust or bioparticles can be obtained. (In FIG. 13, the different widths (duration) of each pulse piece mean that the size of each particle is different or the density of the particles is different.)

Additionally, a shape estimation unit 760 that estimates the shape of the bioparticle from the detection signal 610 may be additionally included. Since the shape of bioparticles (spherical, long, ring, irregular, etc.) is correlated with the type of bioparticle, it can be basically estimated by analyzing the bioparticle spectroscopic spectrum. Furthermore, since differences in shape within the same type may be associated with fine wavelength distribution of the spectral spectrum, machine learning techniques are used to train a learning model with a relatively large number of training data, and then the detection signal is input to the neural network in real time. The shape of the bioparticle can be inferred from (610).

Returning to FIG. 2, the output unit 800 outputs the identified, measured, and estimated results 715, 735, and 745 from the analysis unit 700. The output unit 800 is implemented using a display including a predetermined UI, or sends the results to the relevant device wired or wirelessly (Bluetooth, WiFi, LTE, etc.) for display on another external device (PC, mobile device, etc.). It can be implemented to transmit. The operation of the output unit 800 can be controlled by the control unit 900 similarly to other components.

The control, analysis, and operation of the aerosol detection device of the present invention, especially the processes executed in the analysis unit 700 and the control unit 900, can be designed as a computer system using a microcomputer or microprocessor. That is, it can be configured to use general-purpose computer system hardware and perform the above-described functions with an appropriate software program.

Figure 9 is a block diagram of a computer system that can be utilized to implement the aerosol detection device and method of the present invention. The computer system shown in FIG. 9 includes a processor, memory, input interface device, output interface device, and and a storage device. A computer system may also include a communication device coupled to a network. A processor may be a central processing unit (CPU) or a semiconductor device that executes instructions stored in memory or a storage device. A communication device can transmit or receive wired or wireless signals. Memory and storage devices may include various forms of volatile or non-volatile storage media. And the memory may include read only memory (ROM) and random access memory (RAM). Memory may be located inside or outside the processor and may be connected to the processor through various known means.

Accordingly, the present invention may be implemented as a computer-implemented method or as a non-transitory computer-readable medium storing computer-executable instructions. In one embodiment, when executed by a processor, computer readable instructions can perform a method according to at least one aspect described herein.

Additionally, the operating software of the present invention may be implemented in the form of program instructions that can be executed through various computer means and recorded on a computer-readable medium. This computer-readable medium may include program instructions, data files, data structures, etc., singly or in combination. The program instructions recorded on the computer-readable medium may be specially designed and configured for embodiments of the present invention, or may be known and usable by those skilled in the computer software field. A computer-readable recording medium may include a hardware device configured to store and perform program instructions. For example, computer-readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tapes, optical media such as CD-ROMs and DVDs, and floptical disks. It may be the same magneto-optical media, ROM, RAM, flash memory, etc. Program instructions may include not only machine language code such as that created by a compiler, but also high-level language code that can be executed by a computer through an interpreter, etc.

Figures 10 and 11 are exemplary exterior views of an aerosol detector commercialized with the aerosol detection device of the present invention described above, where Figure 10 is an external perspective view and Figure 11 is an internal plan view.

As mentioned above, the present invention can simultaneously identify fine dust and bioparticles with a single detection unit 600, so the accompanying light source 200 and optical-related elements (light concentrator 300, emitter 400, ), only one spectrum salience unit 500) is required, and it is possible to mount the analysis unit 700, output unit 800, and control unit 900 on one PCB or manufacture it with an ASIC, resulting in a compact appearance (approximately, 100 × 80 × 30 mm), making it possible to commercialize it. Specifically explained, it is as follows.

Referring to FIG. 11, there is an optical module 1100 in the inner space of the exterior casing 1000. Inside this optical module 1100, a passage 130 of the aerosol chamber 100 is formed, and an aerosol inlet 120 and an outlet 140 come out of the optical module 1100 and are formed on the side of the optical casing 1000. do. A fan 150 was installed at the outlet 140 to allow the aerosol to be measured to pass in the direction of the arrow. A light source 200 and a detection unit 600 are located around the aerosol chamber 100, and they are located in the right place in the optical module 1100 along with the light collection unit 300, the emission unit 400, and the spectrum salient unit 500. It is installed. In addition, the optical module 1100 includes a lens assembly 320 and a diffraction grating 510 as shown in FIG. 3, and can be modularized into a small size because a parabola 410 is used to shorten the optical path. , maintenance becomes easier. As such, in Figure 11, the aerosol chamber 100 and other optical-related elements are designed to be integrated into one optical module 1100, but the aerosol chamber 100 is separated into a separate module and designed to be independent of other optical-related elements. You may.

Inside the casing 1000, an electronic module 1200 in which an analysis unit 700, an output unit 800, and a control unit 900 are mounted is located on the side of the optical module 1100. This electronic module 1200 can be constructed by mounting the above electronic elements on a PCB (a heat sink or cooling fan that dissipates heat generated during operation can be installed on the PCB). To simplify the electronic module 1200, all or part of the electronic elements can be integrated and manufactured as a custom IC (ASIC).

In addition, a display/manipulation unit 1300 for status display and user manipulation may be installed in the casing 1000, and an output terminal 1400 for transmitting an output signal from the output unit 800 to an external device is provided. Can be installed. Additionally, a cable 1500 for control and data reception and transmission is connected between the electronic module 1200, the fan 150, and the optical module 1100. In Figure 10, the power supply device that supplies power to each component is omitted. Power may be supplied from an independent power supply installed inside the casing 1000 or from an external adapter.

As described above, according to the present invention, not only is the structure itself simple, but it is also easy to modularize by integrating various components, so it is possible to commercialize it as a small, lightweight, low-power consumption product, and can be implemented for personal, portable, and home use.

Above, an embodiment that specifically implements the idea of the present invention has been described. However, the technical scope of the present invention is not limited to the embodiments and drawings described above, but is determined by a reasonable interpretation of the claims.

Claims (15)

An aerosol chamber into which the aerosol to be measured is introduced;
A light source that emits light to irradiate aerosols in the aerosol chamber;
A detection unit that receives light scattered or split from aerosol fine dust or bioparticles and outputs a detection signal; and
An aerosol detection device comprising an analysis unit configured to identify fine dust and bioparticles and estimate the type of bioparticles by analyzing the detection signal received from the detection unit. According to paragraph 1,
a light condenser that focuses the light emitted from the light source to illuminate the aerosol; and
An aerosol detection device further comprising an emitter that converts the light scattered or split from the fine dust or bioparticles of the aerosol into parallel light. The method of claim 2, wherein the emitting unit
An aerosol detection device including a paraboloid that reflects light scattered and split from fine dust and bioparticles and emits it as parallel light. The aerosol detection device according to claim 1, further comprising a spectral display unit that subdivides the spectral information of the light spectralized from the bioparticles contained in the aerosol to display the spectral spectrum. The aerosol detection device according to claim 4, wherein the spectral salience part includes a diffraction grating or a diffraction grid. The method of claim 1, wherein the analysis unit
An aerosol detection device further configured to measure the size and quantity of fine dust or bioparticles by analyzing the detection signal received from the detection unit. The method of claim 6, wherein the analysis unit
An aerosol detection device configured to use the speed of the aerosol passing through the aerosol chamber and the time the aerosol flows to measure the size of the fine dust or bioparticles. The method of claim 6, wherein the analysis unit
An aerosol detection device configured to use a time-intensity detection signal detected by the detection unit when an aerosol passes through the aerosol chamber to measure the quantity of fine dust and bioparticles. The method of claim 1, wherein the analysis unit
An aerosol detection device further configured to estimate the shape of bioparticles by analyzing the detection signal received from the detection unit. The method of claim 9, wherein the analysis unit
An aerosol detection device configured to infer the shape of the bioparticles using a neural network that has learned the spectral spectrum of the bioparticles in order to estimate the shape of the bioparticles. The method of claim 1, wherein the analysis unit
a fine dust/bio-particle identification unit that distinguishes whether the component contained in the aerosol is fine dust or bio-particles from the detection signal received from the detection unit;
a spectrum analysis unit that analyzes the spectral spectrum of the bioparticles contained in the detection signal when the aerosol component is identified as bioparticles; and
An aerosol detection device including a bioparticle type estimation unit that estimates the type of bioparticles using the analyzed spectrum. The aerosol detection device according to claim 1, further comprising a neural network that learns wavelength characteristic data of fine dust and bioparticles and then infers whether the input detection signal is for fine dust or bioparticles. The aerosol detection device according to claim 1, further comprising a neural network that learns wavelength characteristic data of fine dust and bioparticles and then analyzes the input detection signal to infer the type of bioparticle. The aerosol detection device according to claim 1, wherein the aerosol chamber, the light source, and the detection unit are integrated into one module. The aerosol detection device according to claim 1, further comprising at least one of a display/manipulation unit for displaying and manipulating the status of the aerosol detection device and an output terminal for transmitting the output from the analysis unit to the outside.

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