Patent Publication Number: US-11391659-B2

Title: Optical detecting system

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
     The present application is a continuation of U.S. patent application Ser. No. 16/492,577, filed Sep. 9, 2019, which claims priority to U.S. National Stage of International Patent Application No. PCT/KR2019/005944 filed May 17, 2019, which claims the benefit of priority of Korean Patent Application No. 10-2019-0057747 filed May 17, 2019, Korean Patent Application No. 10-2019-0057746 filed May 17, 2019, Korean Patent Application No. 10-2018-0077193 filed on Jul. 3, 2018, and Korean Patent Application No. 10-2018-0057326 filed on May 18, 2018, the respective disclosures of which are each incorporated herein by reference in their entireties. 
    
    
     TECHNICAL FIELD 
     The present disclosure relates to an optical detection system for detecting microbes or impurities. 
     BACKGROUND ART 
     Human beings coexist with other lifeforms. Invisible lifeforms, as well as visible lifeforms, coexist with human beings, and directly/indirectly affect human lives. Among them, microbes or fine lifeforms affecting health states of human beings are not visible to human eyes, but exist around human beings and trigger various illnesses. 
     In order to measure invisible microbes, a microbe culture method, a mass spectrometry method, a nuclear magnetic resonance method, etc. is used according to the related art. When the microbe culture method, the mass spectrometry method, and the nuclear magnetic resonance method are used, it takes a long time to culture bacteria and precise and complicated equipment that is very expensive is necessary. 
     Alternately, a method of measuring microbes by using an optical method may be used. For example, a Raman spectrometry or a multispectral imaging method may be used as the optical method, but a complicated optical system is necessary, professional knowledge about the complicated optical system and laboratory level equipment are also necessary, and measurement takes a long time. Thus, it may be difficult for the general public to access the system. 
     DESCRIPTION OF EMBODIMENTS 
     Technical Problem 
     Provided is an optical detection system capable of detecting microbes or impurities in real time by using a chaotic wave sensor. 
     Solution to Problem 
     According to an aspect of the present disclosure, an impurity detection system includes: a pipe unit comprising a body portion formed with an inner space penetrating through a first cross section and a second cross section such that a fluid introduced through the first cross section is discharged through the second cross section and a multiple scattering amplification region configured to amplify the number of times a first wave incident between the first cross section and the second cross section in a fluid located in the inner space is multiply scattered; a wave source configured to irradiate the first wave toward the fluid of the pipe unit; a detector arranged outside the pipe unit and configured to detect a laser speckle generated by multiple scattering of the irradiated first wave in the fluid for each preset first time and a controller configured to obtain a temporal correlation of the detected laser speckle using the detected laser speckle and estimate the presence of impurities in the fluid in real time based on the obtained temporal correlation, wherein one or more emission holes configured to guide a second wave emitted by being multiply scattered in the fluid to the detector are formed in the body portion of the pipe unit. 
     Advantageous Effects of Disclosure 
     The optical detection system according to embodiments of the present disclosure may use a variation in a temporal correlation of a laser speckle, thereby estimating existence of impurities or concentration of impurities in a sample rapidly at low cost. 
    
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         FIG. 1  is a diagram illustrating principles of a chaotic wave sensor according to an embodiment of the present disclosure. 
         FIG. 2  is a conceptual diagram schematically illustrating an impurity detection system according to an embodiment of the present disclosure. 
         FIG. 3  is a cross-sectional view taken along a line II-II of  FIG. 2 . 
         FIG. 4  is a conceptual diagram schematically showing an impurity detection system according to another embodiment of the present disclosure. 
         FIG. 5  is an absorbance diagram for each wavelength band when a fluid is water. 
         FIGS. 6A and 6B  are conceptual diagrams schematically showing an impurity detection system according to another embodiment of the present disclosure. 
         FIG. 7  is a conceptual diagram schematically showing a microbial population counting system according to an embodiment of the present disclosure. 
         FIG. 8  is a cross-sectional view taken along a line III-III of  FIG. 7 . 
         FIG. 9  is a flowchart sequentially showing a method of counting a microbial population according to an embodiment of the present disclosure. 
         FIGS. 10 and 11  are diagrams for explaining a method of counting a microbial population. 
         FIG. 12  is a conceptual diagram schematically showing a microbial population counting system according to another embodiment of the present disclosure. 
         FIG. 13  is a conceptual diagram schematically showing a sample placement unit according to another embodiment of the present disclosure. 
         FIG. 14  is a diagram schematically showing an airborne bacteria measuring device according to an embodiment of the present disclosure. 
         FIG. 15  is a conceptual diagram for explaining the sampling principle of the airborne bacteria measuring device of  FIG. 14 . 
         FIG. 16  is a block diagram of the airborne bacteria measuring device of  FIG. 14 . 
         FIGS. 17A to 17D  are diagrams for explaining a process performed by the airborne bacteria measuring device of  FIG. 14  of sampling bacteria and then processing a collection liquid. 
         FIG. 18  is a diagram showing an example of a network environment according to an embodiment of the present disclosure. 
         FIG. 19  is a block diagram schematically showing a server according to an embodiment of the present disclosure. 
         FIG. 20  is a diagram for describing a method, performed by a learner, of analyzing a temporal correlation of speckles according to an embodiment of the present disclosure. 
         FIG. 21  is a diagram showing a standard deviation distribution of the light intensity of wave speckles measured over time. 
         FIG. 22  is a diagram showing a convolutional neural network (CNN) according to an embodiment of the present disclosure. 
         FIGS. 23 and 24  are diagrams for describing a convolution operation of FIG. 
         FIG. 25  is a graph comparing prediction microbe information (prediction) obtained by measuring airborne bacteria through machine learning according to an embodiment of the present disclosure and actual microbe information (ground truth). 
         FIG. 26  is a diagram schematically showing an optical detection system according to an embodiment of the present disclosure. 
         FIG. 27  is a diagram for explaining a process, performed by a first speckle generation unit of generating a first speckle. 
         FIG. 28  is a diagram for explaining a process, performed by a second speckle generation unit of generating a second speckle. 
         FIG. 29  is a diagram for explaining a method, performed by a controller of the present disclosure, of controlling an operation of a second image sensor due to a first speckle. 
         FIG. 30  is a diagram schematically showing an optical detection system of another embodiment. 
         FIG. 31  is a diagram schematically showing an optical detection system according to another embodiment of the present disclosure. 
         FIGS. 32A and 32B  are diagrams for explaining a method of determining the presence of live bacteria in a measurement sample using an optical detection system according to embodiments of the present disclosure. 
     
    
    
     BEST MODE 
     According to an aspect of the present disclosure, a pipe unit includes: a body portion comprising a first cross section, a second cross section facing the first cross section, and an inner surface penetrating the first cross section and the second cross section to form an inner space, wherein the inner surface of the body portion comprises a multiple scattering amplification region in which a pattern for amplifying the number of times a first wave incident between the first cross section and the second cross section in a fluid located in the inner space is multiply scattered is formed, and wherein the pattern is formed by arranging a plurality of grooves having a preset depth d from the inner surface at a preset interval Λ. 
     The depth d and the interval Λ of the pattern may be determined based on the wavelength λ of the first wave. 
     The depth d of the pattern may be determined to satisfy an equation below, wherein n is a refractive index of the fluid. 
     
       
         
           
             
               λ 
               
                 2 
                 * 
                 n 
               
             
             ≤ 
             d 
           
         
       
     
     The interval Λ of the pattern may be determined to satisfy an equation below, wherein θ denotes a scattering angle of the first wave scattered by the pattern. 
     
       
         
           
             
               1 
               Λ 
             
             = 
             
               
                 sin 
                 ⁢ 
                 
                     
                 
                 ⁢ 
                 θ 
               
               λ 
             
           
         
       
     
     The body portion may include one or more emission holes configured to guide a second wave emitted by being multiple scattered in the fluid to a detector for detecting. 
     When two or more emission holes are formed, the two or more emission holes may be disposed at different positions of the body portion. 
     According to another aspect of the present disclosure, an impurity detection system includes: a pipe unit comprising a body portion formed with an inner space penetrating through a first cross section and a second cross section such that a fluid introduced through the first cross section is discharged through the second cross section and a multiple scattering amplification region configured to amplify the number of times a first wave incident between the first cross section and the second cross section in a fluid located in the inner space is multiply scattered; a wave source configured to irradiate the first wave toward the fluid of the pipe unit; a detector disposed outside the pipe unit and configured to detect a laser speckle generated by multiple scattering the irradiated first wave in the fluid for each preset first time and a controller configured to obtain a temporal correlation of the detected laser speckle using the detected laser speckle and estimate the presence of impurities in the fluid in real time based on the obtained temporal correlation, wherein one or more emission holes configured to guide a second wave emitted by being multiple scattered in the fluid to the detector are formed in the body portion of the pipe unit. 
     The body portion may include an inner surface surrounding the inner space, the multiple scattering amplification region may be provided in the inner surface of the body portion and formed with a pattern for amplifying the number of times the first wave is multiply scattered, and the pattern may be formed by arranging a plurality of grooves having a preset depth d from the inner surface at a preset interval Λ. 
     The depth d and the interval Λ of the pattern may be determined based on the wavelength λ of the first wave. 
     The depth d of the pattern may be determined to satisfy an equation below, 
     
       
         
           
             
               λ 
               
                 2 
                 * 
                 n 
               
             
             ≤ 
             d 
           
         
       
     
     wherein n is a refractive index of the fluid. 
     The interval Λ of the pattern may be determined to satisfy an equation below, 
     
       
         
           
             
               1 
               Λ 
             
             = 
             
               
                 sin 
                 ⁢ 
                 
                     
                 
                 ⁢ 
                 θ 
               
               λ 
             
           
         
       
     
     wherein θ denotes a scattering angle of the first wave scattered by the pattern. 
     The second wave emitted from the one or more emission holes may have a power range of 1 mW/cm 2  or more in order for the detector to detect the laser speckle at a preset measurement speed or more. 
     The measurement speed of the detector may be set such that a time for the fluid to pass through the one or more emission holes is greater than a time between first times. 
     When two or more emission holes are formed, the two or more emission holes may be disposed at different positions along a circumferential direction of the body portion, and the detector may be provided to correspond to the number of the two or more emission holes. 
     The first wave may have a wavelength range of 200 nm to 1.8 μm. 
     According to an aspect of the present disclosure, a microbial population counting method includes 
     providing a sample placement unit including a plurality of split cells each including a culture material, distributing samples to be measured to the plurality of split cells, irradiating waves sequentially to the plurality of split cells, sequentially detecting individual wave information emitted from samples includes in each split cell in association with the sequentially irradiated waves, determining the presence of microbe in each split cell using the individual wave information, and calculating a microbial population in the sample using the number of split cells in which the microbe is present. 
     The individual wave information may be information obtained by detecting a laser speckle generated by multiple scattered from the sample accommodated in each of the plurality of split cells for each preset time. 
     The determining of the presence of the microbe may include obtaining a temporal correlation of the detected laser speckle using the detected laser speckle and determining the presence of the microbe in the corresponding split cell based on the obtained temporal correlation. 
     The individual wave information may include first image information of a laser speckle detected at a first time, second image information of a laser speckle detected at a second time, and third image information of a laser speckle detected at a third time among the laser speckle emitted from the corresponding split cell, wherein the first to third times are different times, and the determining of the presence of the microbe may include determining the presence of the microbe by using a difference between the first image information to the third image information. 
     The plurality of split cells may be arranged in the form of a matrix, and the number thereof may be greater than a predicted microbial population included in the sample. 
     According to another aspect of the present disclosure, a microbial population counting system includes a sample placement unit including a plurality of split cells each including a culture material, configured to distribute and accommodate samples to be measured to the plurality of split cells, a wave source configured to irradiate waves sequentially to the plurality of split cells, a detector configured to sequentially detect individual wave information emitted from samples includes in each split cell in association with the sequentially irradiated waves, and a controller configured to determine the presence of microbe in each split cell using the individual wave information and calculate a microbial population in the sample using the number of split cells in which the microbe is present. 
     The individual wave information may be information obtained by detecting a laser speckle generated by multiple scattered from the sample accommodated in each of the plurality of split cells for each preset time. 
     The controller may obtain a temporal correlation of the detected laser speckle using the detected laser speckle and determine the presence of the microbe in the corresponding split cell based on the obtained temporal correlation. 
     The individual wave information may include first image information of a laser speckle detected at a first time, second image information of a laser speckle detected at a second time, and third image information of a laser speckle detected at a third time among the laser speckle emitted from the corresponding split cell, wherein the first to third times are different times, and the controller may determine the presence of the microbe by using a difference between the first image information to the third image information. 
     The plurality of split cells may be arranged in the form of a matrix, and the number thereof may be greater than a predicted microbial population included in the sample. 
     According to another aspect of the present disclosure, an airborne bacteria measuring device includes a collection unit including a storage tank configured to accommodate a collection liquid therein, an inhalation flow path configured to inhale external air to guide an external air to the collection liquid in one side of the storage tank, and an exhaust flow path configured to discharge the air of the storage tank to the outside in the other side of the storage tank, a wave source configured to irradiate a wave toward the collection liquid of the collection unit, an image sensor configured to time serially measure a wave speckle generated by multiple scattering the wave in the collection liquid, and a controller configured to detect the presence of microbe in the collection liquid according to a change in the measured wave speckle over time. 
     The controller may obtain a temporal correlation of the wave speckle and detect the presence of the microbe in the collection liquid based on the obtained temporal correlation. 
     The collection unit may further include a collection liquid discharge pipe configured to discharge the completely detected collection liquid and a collection liquid flow pipe configured to flow a new collection liquid into the storage tank. 
     The airborne bacteria measuring device may further include a first valve installed in the collection liquid flow pipe and selectively opening and closing the collection liquid flow pipe and a second valve installed in the collection liquid discharge pipe and selectively opening and closing the collection liquid discharge pipe, and the controller may control an operation of the first valve or the second valve by a preset program. 
     The airborne bacteria measuring device may further include a sterilization unit configured to sterilize the completely detected collection liquid in the storage tank, and the controller may control an operation of the second valve to discharge the collection liquid after a sterilization process of the collection liquid is completed. 
     The airborne bacteria measuring device may further include a filter unit installed in the inhalation flow path and configured to filter a substance having a predetermined size or more included in the external air introduced into the inhalation flow path. 
     The collection unit may further include a multiple scattering amplifier configured to reflect at least a part of the wave emitted from the collection liquid to the collection liquid to amplify the number of times of multiple scattering in the collection liquid. 
     The controller may identify a type or concentration of microbe present in the collection liquid based on a change in the wave speckle over time. 
     The controller may learn a microbial classification criteria based on the change of the wave speckle over time measured in time series order, and identify the type or concentration of microbe present in the collection liquid using the microbial classification criteria. 
     According to another aspect of the present disclosure, an optical detection system includes a wave source, an optical unit configured to transferring a wave generated in the wave source to a first path or a second path, a first speckle generation unit disposed on the first path and including a static scattering medium to scatter the first wave incident along the first path and generate a first speckle, a first image sensor configured to detect the first speckle in time series order, a sample accommodation unit disposed on the second path and including a sample to be measured, a second image sensor configured to detect an optical signal generated in the sample in time series order, and a controller configured to obtain a temporal correlation of the first speckle using the detected first speckle and control an operation of the second image sensor based on the obtained temporal correlation of the first speckle. 
     The sample accommodation unit may include a second speckle generation unit configured to scatter a second wave incident along the second path and generate a second speckle. 
     The controller may obtain a temporal correlation of the second speckle detected using the detected second speckle, and estimate the presence or concentration of microbe in the sample based on the obtained temporal correlation of the second speckle. 
     The controller may determine a change in the property of the first wave based on the temporal correlation of the first speckle, and control an operation of the second image sensor according to the change in the property of the first wave. 
     The controller may calculate a temporal correlation coefficient of the first speckle and operate the second image sensor only when the temporal correlation coefficient of the first speckle corresponds to a preset range. 
     The controller may calculate the temporal correlation coefficient of the first speckle and use the temporal correlation coefficient of the first speckle to calibrate a detection signal of the second image sensor. 
     The first speckle generation unit and the second speckle generation unit may be integrally formed. 
     The second speckle generation unit may further include a multiple scattering amplifier including a multiple scattering material to amplify the number of times of multiple scattering of the second wave in the sample. 
     According to another aspect of the present disclosure, an optical detection system includes a wave source, an optical unit configured to transferring a wave generated in the wave source to a first path or a second path, a first speckle generation unit disposed on the first path and including a static scattering medium to scatter the first wave incident along the first path and generate a first speckle, a second generation unit disposed on the second path and including a sample to be measured to scatter a second wave incident along the second path and generate a second speckle, a second shutter disposed between the first optical unit and the second speckle generation unit, an image sensor configured to detect the first speckle or the second speckle in time series order, and a controller configured to obtain a temporal correlation of the first speckle using the detected first speckle by the image sensor and control an operation of the second shutter based on the obtained temporal correlation of the first speckle. 
     The controller may obtain a temporal correlation of the second speckle detected using the detected second speckle, and estimate the presence or concentration of microbe in the sample based on the obtained temporal correlation of the second speckle. 
     The controller may determine a change in the property of the first wave based on the temporal correlation of the first speckle, and control an operation of the second shutter according to the change in the property of the first wave. 
     The controller may calculate a temporal correlation coefficient of the first speckle and open the second shutter to detect the second speckle only when the temporal correlation coefficient of the first speckle corresponds to a preset range. 
     The optical detection system may further include a first shutter disposed between the first optical unit and the first speckle generation unit, and the controller may control the first shutter to be closed while the second shutter is opened. 
     The second speckle generation unit may further include a multiple scattering amplifier including a multiple scattering material to amplify the number of times of multiple scattering of the second wave in the sample. 
     According to another aspect of the present disclosure, an optical detection system includes a wave source, an optical unit configured to transferring a wave generated in the wave source to a first path or a second path, a first speckle generation unit disposed on the first path and including a control group sample to scatter the first wave incident along the first path and generate a first speckle, a first image sensor configured to detect the first speckle in time series order, a second generation unit disposed on the second path and including a measurement group sample and a medium to scatter a second wave incident along the second path and generate a second speckle, a second image sensor configured to detect the second speckle in time series order, and a controller configured to estimate a first concentration of the control group sample and a second concentration of the measurement group sample using the detected first speckle and the detected second speckle, and determine the presence of live bacteria in the measurement group sample using the first concentration and the second concentration. 
     The controller may obtain a temporal correlation of the first speckle detected using the detected first speckle, and then estimate the first concentration of the control group sample using the temporal correlation of the first speckle, obtain a temporal correlation of the second speckle detected using the detected second speckle, and then estimate the second concentration of the measurement group sample using the temporal correlation of the second speckle. 
     The measurement group sample may be a sample diluted m times the control group sample, and the controller may obtain a growth time at which the second concentration is equal to the first concentration and then derive a ratio of live bacteria and dead bacteria in the measurement group sample using the growth time. 
     The second speckle generation unit may further include a multiple scattering amplifier including a multiple scattering material to amplify the number of times of multiple scattering of the second wave in the sample. 
     Other aspects, features and advantages of the present disclosure will become better understood through the accompanying drawings, the claims and the detailed description. 
     MODE OF DISCLOSURE 
     The exemplary embodiments will be described below in more detail with reference to the accompanying drawings. Those components that are the same or are in correspondence are rendered the same reference numeral regardless of the figure number, and redundant explanations are omitted. 
     As the present disclosure allows for various changes and numerous embodiments, particular embodiments will be illustrated in the drawings and described in detail in the written description. The attached drawings for illustrating one or more embodiments are referred to in order to gain a sufficient understanding, the merits thereof, and the objectives accomplished by the implementation. However, the embodiments may have different forms and should not be construed as being limited to the descriptions set forth herein. 
     While such terms as “first,” “second,” etc., may be used to describe various components, such components must not be limited to the above terms. The above terms are used only to distinguish one component from another. 
     An expression used in the singular encompasses the expression of the plural, unless it has a clearly different meaning in the context. 
     In the present specification, it is to be understood that the terms such as “including,” “having,” and “comprising” are intended to indicate the existence of the features or components disclosed in the specification, and are not intended to preclude the possibility that one or more other features or components may exist or may be added. 
     It will be understood that when a unit, region, or component is referred to as being “formed on” another layer, region, or component, it can be directly or indirectly formed on the other layer, region, or component. That is, for example, intervening units, regions, or components may be present. 
     It will be understood that when an element is referred to as being “connected” or “coupled” to another element, it does necessarily not mean direct and/or fixed connection or coupling of to the two elements or intervening elements may be present, unless it has a clearly different meaning in the context. 
     It will be further understood that the terms “comprises,” “comprising,” “includes” and/or “including,” when used herein, specify the presence of stated features or components, but do not preclude the presence or addition of one or more other features or components. 
     Sizes of components in the drawings may be exaggerated for convenience of explanation. In other words, since sizes and thicknesses of components in the drawings are arbitrarily illustrated for convenience of explanation, the following embodiments are not limited thereto. 
     Hereinafter, principles of a chaotic wave sensor according to an embodiment of the present disclosure will be described with reference to  FIG. 1 . 
       FIG. 1  is a diagram illustrating principles of a chaotic wave sensor according to an embodiment of the present disclosure. 
     When light is irradiated to a material having a uniform internal refractive index, e.g., glass, the light is refracted in a constant direction. However, when coherent light such as a laser is irradiated to a material having a non-uniform internal refractive index, multiple scattering that is very complicated occurs in the material. 
     Referring to  FIG. 1 , in light or waves (hereinafter, referred to as waves for convenience&#39;s sake) irradiated from a wave source  120 , some of the waves scatter through complicated paths due to the multiple scattering pass through a test target surface. Waves passing through multiple points in the test target surface generate constructive interference or destructive interference, and the constructive/destructive interference of the waves generates grain patterns (speckles). 
     In the present specification, the waves scattered in the complicated paths are referred to as “chaotic wave”, and the chaotic wave may be detected through laser speckles. 
     The left side of  FIG. 1  shows a state in which a laser is irradiated to a stabilized medium. When interference light (e.g., laser) is irradiated to the stabilized medium, in which internal component material does not move, a stabilized speckle pattern without a variation may be observed. 
     However, as shown at the right side of  FIG. 1 , when the medium has a non-stabilized internal component that is moving, such as bacteria, the speckle pattern varies. 
     That is, fine activity of life, e.g., movement of microbes, may finely change an optical path according to time. Since the speckle pattern is generated due to interference of the waves, a fine change in the optical path may cause variation in the speckle pattern. Accordingly, when a temporal variation in the speckle pattern is measured, the activities of microbes may be rapidly measured. As described above, when the variation in the speckle pattern according to time is measured, existence of the microbes and concentration of the microbes may be identified, and further, kinds of the microbes may be identified. 
     In the present specification, a structure for measuring the variation in the speckle pattern is defined as a chaotic wave sensor. 
     In the present specification, embodiments of an optical detection system having various applications such as technology of detecting impurities in a fluid, technology of counting microbial population, airborne bacteria measuring technology and wave correction technology while having a basic idea of detecting microbe or impurities present in a static medium by using the chaotic wave sensor as described above will be described. At this time, the optical detection system may be called a different name for each embodiment, and may be designated with a different name or numeral for the convenience of description even if it includes components that perform the same function. Here, the medium may be applied to any material or state having a static property. 
       FIG. 2  is a conceptual diagram schematically illustrating an impurity detection system  10  according to an embodiment of the present disclosure, and  FIG. 3  is a cross-sectional view taken along line II-II of  FIG. 2 .  FIG. 4  is a conceptual diagram schematically showing an impurity detection system  10 ′ according to another embodiment of the present disclosure. 
     Referring to  FIGS. 2 and 3 , an impurity detection system  10  in a fluid according to an embodiment of the present disclosure may include a pipe unit  1110 , a wave source  1200 , a detector  1300 , and a controller  1400 . 
     The pipe unit  1110  may include a first cross section A 11  and a second cross section A 21 , and may include a body portion  1100  including an inner surface  1101  penetrating the first cross section A 11  and the second cross section A 21  to form an inner space. In this case, the first cross section A 11  and the second cross section A 21  may be disposed to face each other. The body portion  1100  may be formed, for example, in a cylindrical shape, but the present disclosure is not limited thereto. 
     A fluid may be introduced through the second cross section A 21  of the pipe unit  1110  and may be discharged through the first cross section A 11  via the inner space. In the present specification, the fluid may be a liquid or a gas, and may have a preset flow rate. The pipe unit  1110  may be disposed at any part of a production line of liquid such as bottled water or beverage, and the fluid may be introduced through the second cross section A 21  to penetrate the inner space of the pipe unit  1110  and then may be discharged through the first cross section A 11 . For example, the flow rate of the fluid may range from 4 m/s to 5 m/s, which is a flow rate of an actual factory environment. However, the present disclosure is not limited thereto, and the flow rate of the fluid may have a flow rate of 1 m/s or less like a water pipe. 
     As another example, the flow rate of the fluid may be set based on the measurement conditions in the detector  1300 . In other words, even if the flow rate of the actual factory environment is 4 m/s to 5 m/s, the impurity detection system  10  may reduce the flow rate of the fluid to a preset rate such that the flow rate of the fluid immediately before the pipe unit  1110  is a rate measurable by the detector  1300 . 
     As used herein, an impurity may be a material of a small size, such as a microbe, that exceeds the visual limit of the human eye. In an embodiment, when the impurity is a microbe, the fluid may be a material to which the microbe may proliferate, for example, water that does not include a scattering material therein. However, the present disclosure is not limited thereto, and in another embodiment, the fluid may be a material such as milk including the scattering material therein. In another embodiment, the fluid may also be air. 
     Although not shown, the fluid may be introduced into the pipe unit  1110  through a fluid supply unit. The fluid supply unit may include a fluid storage tank and a supply means such as a hydraulic pump or a compressor for providing a flow force to the fluid include in the fluid storage tank. The fluid may pass through the pipe unit  1110  in one direction through the supply means. 
     In an embodiment, the pipe unit  1110  may introduce the fluid through the entire area of the second cross section A 21 , and discharge the fluid through the entire area of the first cross section A 11 . In other words, the fluid may move in a state in which the inside of the pipe unit  1110  is filled up. When the fluid moves in a state where the cross-sectional area of the pipe unit  1110  is not 100% filled, a wavefront may be generated in the fluid due to the flow of the fluid. Such a wavefront may act as a scatterer, and may act as a noise to detect impurities through the detector  1300 . Accordingly, in order to minimize such noise, the pipe unit  1110  may discharge the fluid through the entire areas of the first cross section A 11  and the second cross section A 21 . 
     Meanwhile, the body portion  1100  of the pipe unit  1110  may include a multiple scattering amplification region MSA 1  formed on an inner surface  1101 . A pattern for amplifying the number of times of multiple scattering of a first wave L 11  incident between the first cross section A 11  and the second cross section A 21  in the fluid located in the inner space of the pipe unit  1110  may be formed in the multiple scattering amplification region MSA 1 . 
     The multiple scattering amplification region MSA 1  may scatter at least a part of the first wave L 11  that is incident into the inner space of the pipe unit  1110  and passes through the fluid and is emitted toward the inner surface  1101  into the fluid again. The first wave L 11  scattered as described above may be emitted to the other side of the inner surface  1101  through the fluid and scattered, and through this process, the number of times of multiple scattering in the fluid may increase. In this case, the multiple scattering amplifier region MSA 1  may amplify the number of multiple scattering due to patterns formed based on a wavelength λ of the incident first wave L 11 . 
     The pattern may include a plurality of grooves g formed in a concave shape from the inner surface  1101  toward an outer surface of the pipe unit  1110 . The pattern may be formed by arranging the plurality of grooves g having a preset depth d from the inner surface  1101  at a preset interval Λ. Here, the depth d and the interval Λ of the pattern may be determined based on the wavelength λ of the first wave. 
     Specifically, the depth d of the pattern may be determined to satisfy Equation 1 below, 
     
       
         
           
             
               
                 
                   
                     λ 
                     
                       2 
                       * 
                       n 
                     
                   
                   ≤ 
                   d 
                 
               
               
                 
                   [ 
                   
                     Equation 
                     ⁢ 
                     
                         
                     
                     ⁢ 
                     1 
                   
                   ] 
                 
               
             
           
         
       
     
     wherein n may be a refractive index of the fluid passing through the inner space of the pipe unit  1110 . When the depth d of the pattern is smaller than 
               λ     2   *   n       ,         
the first wave L 11  incident on the inner surface  1101  has a high reflectance, making it difficult to increase the intended number of times of multiple scattering. The pipe unit  1110  may increase a scattering rate in the inner space by forming the pattern to satisfy Equation 1 above. In addition, the depths d of the pattern including the plurality of grooves g may not need to be the same, and even if they are formed irregularly, if the depth d of each of the grooves g satisfies the above Expression 1, a sufficient scattering rate may be secured. In this case, the depth d of the pattern may not exceed the cross-sectional thickness of the pipe unit  1110 .
 
     In addition, the interval Λ of the pattern may be determined to satisfy Equation 2 below, 
     
       
         
           
             
               
                 
                   
                     1 
                     Λ 
                   
                   = 
                   
                     
                       sin 
                       ⁢ 
                       
                           
                       
                       ⁢ 
                       θ 
                     
                     λ 
                   
                 
               
               
                 
                   [ 
                   
                     Equation 
                     ⁢ 
                     
                         
                     
                     ⁢ 
                     2 
                   
                   ] 
                 
               
             
           
         
       
     
     wherein θ may denote a scattering angle of the first wave L 11  scattered by the pattern. In addition, the interval Λ of the grooves g may be an interval between peaks of unevennesses formed by the grooves g. The scattering angle θ may be determined according to an area of the multiple scattering amplification region MSA 1  and/or power of the first wave L 11 . When the scattering angle θ is large, the first wave L 11  may be scattered over a larger area than that when the scattering angle θ is small, whereas the power of the first wave L 11  after scattered may be reduced rather than when the scattering angle θ is small. Using this relationship, the scattering angle θ may be determined according to the measurement conditions, for example, a diameter R 1  of the pipe unit  1110  or the power of the first wave L 11  emitted from the wave source  1200 . 
     Meanwhile, the pattern may include the plurality of grooves g arranged in a predetermined direction. In an embodiment, as shown in the drawing, the pattern may be formed by arranging the grooves g extending in a direction perpendicular to a longitudinal direction of the pipe unit  1110  at the interval Λ. In another embodiment, although not shown, the pattern may be formed by arranging the grooves g extending in the longitudinal direction of the pipe unit  1110  at the interval Λ. In another embodiment, the pattern may include first grooves extending and arranged along the longitudinal direction of the pipe unit  1110  and second grooves formed to overlapping the first grooves and extending and arranged in the direction perpendicular to the longitudinal direction of the pipe unit  1110 . 
     In this case, the multiple scattering amplification region MSA 1  may be configured in a pattern formed in a lattice form. When the plurality of grooves g extending along the circumferential direction are arranged along the longitudinal direction of the pipe unit  1110 , the incident first wave L 11  is different depending on an incident angle, but the incident first wave L 11  is mostly scattered in the longitudinal direction of the pipe unit  1110 . In addition, when the plurality of grooves g extending in the longitudinal direction are arranged along the circumferential direction of the pipe unit  1110 , the incident first wave L 11  is mostly scattered in the circumferential direction of the pipe unit  1110 . In other words, in the case where the first wave L 11  is scattered to amplify the number of times of multiple scattering to the cross-section of the pipe unit  1110 , the grooves g may be formed to be arranged along the circumferential direction, and in the case where the number of multiple scattering is amplified in the longitudinal direction of the pipe unit  1110 , the grooves g may be formed to be arranged along the longitudinal direction. In addition, because the number of times of multiple scattering is amplified in various directions by forming the pattern in grooves crossing in different directions, the cross-section and the longitudinal direction of the pipe unit  1110  may be closely filled with the first wave L 11 . Through this, the impurity detection system  10  may increase a probability of detecting impurities in the fluid. 
     Meanwhile, in another embodiment, the multiple scattering amplification region MSA 1  may include a multiple scattering material. For example, the multiple scattering material may include particles having a diameter of a micrometer having a large refractive index or less, for example, titanium oxide (TiO 2 ) nanoparticles. In this case, the multiple scattering amplification region MSA 1  may be formed by coating the multiple scattering material on an outer surface of a main body of the pipe unit  1110 . However, the present disclosure is not limited thereto, and in another embodiment, the multiple scattering amplification region MSA 1  may be formed by including the multiple scattering material in the main body of the pipe unit  1110 . Alternatively, in the case of an opaque pipe such as a metal pipe, the multiple scattering amplification region MSA 1  may be formed by coating a multiple scattering material on an inner surface of the main body of the pipe unit  1110 . 
     In another embodiment, the multiple scattering amplification region MSA 1  may include a multiple scattering amplifier (not shown) disposed adjacent to the main body of the pipe unit  1110  to reflect at least a part of wave emitted from the fluid to the outside of the pipe unit  1110  to the inside of the pipe unit  1110 . In this case, the multiple scattering amplifier (not shown) may cause the wave emitted from the pipe unit  1110  to reciprocate a space between the pipe unit  1110  and the multiple scattering amplifier (not shown) at least one or more times. Meanwhile, the multiple scattering amplification region MSA 1  may be disposed in at least a partial region between the first cross section A 11  and the second cross section A 21  of the pipe unit  1110 , for example, in the entire region. 
     Meanwhile, at least a part of the multiple scattering amplification region MSA 1  may be a reflection region  1105  reflecting the entirety of the first wave L 11  emitted from the fluid into the fluid. The reflection region  1105  may increase the impurity detection rate of the detector  1300  by minimizing the emission of the first wave L 11  from the fluid to the outside of the pipe unit  1110 . The reflection region  1105  may be disposed to face an incident region where the first wave L 11  is incident from the wave source  1200 . The reflection region  1105  may reflect the entirety of the first wave L 11  irradiated from the wave source  1200  into the fluid, thereby increasing an amount of waves capable of being multiple scattered in the fluid, and accordingly amplifying the impurity detection rate in the detector  1300 . In another embodiment, the entire region of the multiple scattering amplification region MSA 1  except for an emission hole  1103  may be a reflection region. 
     Meanwhile, the pipe unit  1110  may include one or more emission holes  1103  guiding a second wave emitted by being multiple scattered in the fluid to the detector  1300  for detecting. The detector  1300 , which will be described later, may be disposed adjacent to the emission hole  1103  to detect the second wave L 21  emitted from the emission hole  1103 . The emission hole  1103  may be configured as a hole penetrating the body portion  1100  as shown. 
     At this time, as shown, the pipe unit  1110  may further include a cover portion  1109  disposed at one side of the emission hole  1103 . The cover portion  1109  may include a transparent or translucent material such that the second wave L 21  may pass therethrough. For example, the cover portion  1109  may include a glass or plastic material, and may be formed in a plate shape having flexibility, but may also be manufactured in a film. In another embodiment, the cover portion  1109  may be formed to fill the inside of the emission hole  1103  rather than one side of the emission hole  1103 . 
     Meanwhile, although in the drawing exaggerated for convenience of explanation, the emission hole  1103  may have a minimum diameter R 2  by which the second wave L 21  may be emitted while ensuring the scattering rate in the inner space of the pipe unit  1110  to the maximum. 
     Meanwhile, referring to  FIG. 4 , two or more emission holes  1103  may be formed in the body portion  1100  of the pipe unit  1110 . When two or more emission holes  1103  are formed, the two or more emission holes  1103  may be disposed at different positions along the circumferential direction of the body portion  1100 . Through this structure, the plurality of second waves L 21  may be guided to a plurality of detectors  31 ,  33 , and  35  that will be described later. 
     Hereinafter, the impurity detection system  10  including the pipe unit  1110  described above will be described in more detail. 
     Because a fluid such as water does not include a homogeneous substance that causes scattering therein as described above, a laser speckle may not be generated when a microbe M, which is an impurity, is not present. However, the system  10  for detecting the microbe M in a fluid according to an embodiment of the present disclosure may multiple scatter the first wave through the multiple scattering amplification region MSA 1  of the pipe unit  1110  described above to generate a static laser speckle pattern. The system  10  for detecting the microbe M in the fluid L may change a path of the first wave by a movement of the microbe M when the microbe M is present in the fluid L that moves in the pipe unit  1110 . A subtle change in a first wave path may cause a change in the speckle pattern. Accordingly, by measuring a temporal change of the speckle pattern, the presence of the microbe M in the fluid L may be rapidly detected. 
     Referring to  FIGS. 2 and 3  again, the wave source  1200  may irradiate the first wave L 11  toward the fluid of the pipe unit  1110 . The wave source  1200  may apply all types of source device capable of generating a wave, and may be, for example, a laser capable of irradiating light of a specific wavelength band. Although the present disclosure is not limited to a type of a wave source, a case where the wave source is the laser will be described for convenience of description. 
     For example, laser with a good coherence may be used as the wave source  1200  to form speckle in the fluid. In this case, the shorter the spectral bandwidth of the wave source that determines the coherence of the laser wave source, the greater the measurement accuracy. That is, the longer the coherence length, the greater the measurement accuracy. Accordingly, a laser light whose spectral bandwidth of the wave source is less than a predetermined reference bandwidth may be used as the wave source  1200 , and the measurement accuracy may increase as the spectral bandwidth of the wave source is shorter than the reference bandwidth. For example, the spectral bandwidth of the wave source may be set such that the condition of Equation 3 below is maintained.
 
spectralbandwidth&lt;5 nm  [Equation 3]
 
     According to Equation 3, in order to measure the pattern change of the laser speckle, the spectral bandwidth of the wave source  1200  may be maintained less than 5 nm when light is irradiated into the fluid every reference time. 
     In an embodiment, the wave source  1200  may be disposed outside the pipe unit  1110  to irradiate the first wave L 11  toward the pipe unit  1110  as shown. In this case, an incidence hole (not shown) penetrating the body portion  1100  may be formed in the pipe unit  1110  to transmit the first wave L 11  radiated from the wave source  1200  to the fluid. The incidence hole (not shown) may be formed to have the same diameter as the emission hole  1103  described above, and the cover portion  1109  may be disposed like the emission hole  1103 . In another embodiment, the wave source  1200  may be disposed in the inner surface of the pipe unit  1110  or may be embedded in the body portion  1100  of the pipe unit  1110  to irradiate the first wave L 11  toward the fluid. In the drawing, the wave source  1200  is illustrated as one, but a plurality of wave sources  1200  may be provided as necessary. 
     Meanwhile, the wave source  1200  may output the first wave L 11  having a predetermined first power and the wavelength A. 
       FIG. 5  is an absorbance diagram for each wavelength band when a fluid is water. 
     Referring to  FIG. 5 , the first wave L 11  may have the wavelength λ in the range of a first wavelength λ 1  to a second wavelength λ 2 . The fluid may absorb waves. Absorbance generally means that the energy of photons, such as electrons in an atom, is absorbed by a material, and the energy of such waves may be converted into the internal energy of the fluid, such as thermal energy. As the absorption occurs more, the fluid internal temperature increases, and the power of the first wave L 11  decreases as much as the fluid internal temperature increases. If a degree of the power reduction of the first wave L 11  is large while passing through the fluid, detection by the detector  1300  may be difficult. 
     Because the absorption in the fluid is different for each wavelength band as shown in  FIG. 5 , the first wave L 11  may be set to have a wavelength range that may minimize absorption in the fluid. For example, when the fluid is water, the fluid may have an absorption coefficient for each wavelength band as shown in  FIG. 5 . The impurity detection system  10  according to an embodiment of the present disclosure may use the first wave L 11  having a wavelength range in which the absorption coefficient of the fluid is equal to or less than a predetermined value in order to minimize absorption of waves in the fluid. For example, the first wave L 11  may have a wavelength range of 200 nm to 1.8 mm such that an absorption coefficient of water has a value less than 1×10 3  to 1×10 4 . 
     Referring to  FIGS. 2 and 3  again, the detector  1300  may detect a laser speckle generated by multiple scattering the irradiated first wave L 11  in the fluid for each preset time. Here, time means any moment in a continuous flow of time, and times may be set in advance at the same time interval, but are not limited thereto, and may be set in advance at any time interval. 
     The detector  1300  may include a sensing means corresponding to a type of the wave source  1200 . For example, when a light source of a visible light wavelength band is used, a CCD camera which is an image capturing device may be used. The detector  1300  may detect a laser speckle at least at a first time, detect a laser speckle at a second time, and provide the detected laser speckles to the controller  1400 . Meanwhile, the first point and the second time are merely one example selected for convenience of description, and the detector  1300  may detect laser speckles at a plurality of times more than the first point and the second time. 
     Specifically, when the first wave L 11  is irradiated to the fluid, the incident first wave L 11  may form a laser speckle by multiple scattering. Because the laser speckle is generated by the interference of light, if there is no microbe in the fluid, a multiple scattering amplification region may always show a constant interference pattern over time. In comparison, when the microbe M is present in the fluid, the laser speckle may change over time by a movement of the microbe M. The detector  1300  may detect the laser speckle that changes over time for each preset time and provide the laser speckle to the controller  1400 . The detector  1300  may detect the laser speckle at a speed sufficient to detect the movement of the microbe M, and for example, may detect the laser speckle at the speed of 25 to 30 frames per second. 
     The detector  1300  may be disposed adjacent to the emission hole  1103  of the pipe unit  1110 , and detect the second wave L 21  emitted through the emission hole  1103  after the first wave L 11  irradiated from the wave source  1200  is multiply scattered. In this case, the second wave L 21  may have a power range of 1 mW/cm 2  or more such that the detector  1300  may detect the laser speckle at a measurement speed greater than or equal to a preset measurement speed. When the second power of the second wave L 21  is smaller than 1 mW/cm 2 , the detector  1300  which measures rapidly may not sufficiently detect the second wave L 21 . In addition, the detector  1300  should be capable of high speed measurement in order to detect the microbe M which is an impurity from the flowing fluid. Here, high speed measurement means detecting a laser speckle faster than a flow rate of the fluid. For example, the measurement speed of the detector  1300  may be set such that a time T 1  at which the fluid passes the emission hole  1103  is greater than a time T 2  between the first times for detecting the laser speckle. 
     
       
         
           
             
               
                 T 
                 ⁢ 
                 
                     
                 
                 ⁢ 
                 1 
               
               
                 T 
                 ⁢ 
                 
                     
                 
                 ⁢ 
                 2 
               
             
             &gt; 
             1 
           
         
       
     
     Meanwhile, the first wave L 11  irradiated from the wave source  1200  has the first power, and the second wave L 21  that is multiply scattered and emitted from the pipe unit  1110  has the second power. Ideally, the first power of the first wave L 11  and the second power of the second wave L 21  are equal to each other, and the wave source  1200  may irradiate waves with power of 1 mW/cm 2  or more but the first power of the first wave L 11  is significantly reduced in a multiple scattering process. Therefore, the second power of the second wave L 21  may be smaller than the first power of the first wave L 11 . The second power of the second wave L 21  may be different according to the diameter R 1  of the pipe unit  1110 , the first power magnitude of the first wave L 11 , a degree of absorption of the fluid with respect to a wavelength of the first wave L 11  and a diameter R 2  of the emission hole  1103 . For example, the second power of the second wave L 21  may be proportional to the first power of the first wave L 11 , inversely proportional to the diameter R 1  of the pipe unit  1110 , and proportional to the diameter R 2  of the emission hole  1103 . 
     Meanwhile, when an image sensor is used as the detector  1300 , the image sensor may be disposed such that a size d of one pixel of the image sensor is smaller than or equal to a grain size of a speckle pattern. For example, the image sensor may be disposed in an optical system included in the detector  300  to satisfy the condition of Equation 4 below.
 
 d ≥speckle grain size  [Equation 4]
 
     As shown in Equation 4, the size d of one pixel of the image sensor should be less than or equal to the grain size of the speckle pattern. However, if the size of the pixel becomes too small, undersampling may occur and there may be difficulties in utilizing pixel resolution. Accordingly, the image sensor may be disposed such that a maximum of five pixels or less are positioned at a speckle grain size to achieve an effective signal to noise ratio (SNR). 
     The controller  1400  may obtain a temporal correlation of the detected laser speckles using the detected laser speckles. The controller  1400  may estimate the presence of impurities in the fluid in real time based on the obtained temporal correlation. Real time in the present specification means estimating the presence of the microbe M within 3 seconds, preferably, it is possible to estimate the presence of the microbe M within 1 second. 
     In an embodiment, the controller  1400  may use a difference between first image information of the laser speckle detected at the first time and second image information of a second laser speckle detected at the second time to estimate the presence of the microbe M. Here, the first image information and the second image information may be at least one of pattern information of the laser speckle and intensity information of waves. Meanwhile, an embodiment of the present disclosure does not use only the difference between the first image information at the first time and the second image information at the second time but may extend this to use image information of a plurality of laser speckles at a plurality of times. The controller  1400  may calculate a temporal correlation coefficient between images using image information of laser speckles generated for a plurality of preset times, and estimate the presence of the microbe M in the fluid based on the temporal correlation coefficient. The detected temporal correlation of the laser speckle images may be calculated using Equation 5 below. 
     
       
         
           
             
               
                 
                   
                     
                       C 
                       _ 
                     
                     ⁡ 
                     
                       ( 
                       
                         x 
                         , 
                         
                           y 
                           ; 
                           τ 
                         
                       
                       ) 
                     
                   
                   = 
                   
                     
                       1 
                       
                         T 
                         - 
                         τ 
                       
                     
                     ⁢ 
                     
                       
                         ∑ 
                         
                           t 
                           = 
                           1 
                         
                         
                           T 
                           - 
                           τ 
                         
                       
                       ⁢ 
                       
                         
                           
                             I 
                             _ 
                           
                           ⁡ 
                           
                             ( 
                             
                               x 
                               , 
                               
                                 y 
                                 ; 
                                 t 
                               
                             
                             ) 
                           
                         
                         ⁢ 
                         
                           
                             I 
                             _ 
                           
                           ⁡ 
                           
                             ( 
                             
                               x 
                               , 
                               
                                 y 
                                 ; 
                                 
                                   t 
                                   + 
                                   τ 
                                 
                               
                             
                             ) 
                           
                         
                         ⁢ 
                         δ 
                         ⁢ 
                         
                             
                         
                         ⁢ 
                         t 
                       
                     
                   
                 
               
               
                 
                   
                     [ 
                     
                       Equation 
                       ⁢ 
                       
                           
                       
                       ⁢ 
                       5 
                     
                     ] 
                   
                   ⁢ 
                   
                       
                   
                 
               
             
           
         
       
     
     In Equation 5,  C  denotes the temporal correlation coefficient, Ī denotes normalized light intensity, (x, y) denotes a pixel coordinate of a camera, t denotes a measured time, T denotes a total measurement time, and denotes a time lag. 
     The temporal correlation coefficient may be calculated according to Equation 5, and in an embodiment, the presence of the microbe may be estimated through an analysis in which the temporal correlation coefficient falls below a preset reference value. Specifically, it may be estimated that the microbe is present from that the temporal correlation coefficient falls below the reference value exceeding a preset error range. 
     Referring to  FIG. 3  again, in another embodiment, the impurity detection system  10 ′ may include a plurality of detectors  1310 ,  1330 , and  1350 . As described above, a plurality of emission holes  1103  may be formed in the body portion  1100  of the pipe unit  1110 , and the detectors  1300  may be positioned at positions corresponding to the respective emission holes  1103 . 
     The first wave L 11  irradiated to the pipe unit  1110  may be multiply scattered in the fluid and then emitted through the emission hole  1103 , and the second power of the emitted second wave L 21  may be different according to the position of the emission hole  1103 . The first wave L 11  irradiated to the pipe unit  1110  is scattered according to the interval Λ and the depth d of the pattern in the multiple scattering amplification region MSA 1 . The pattern has irregularity due to tolerances or intentional patterning in a manufacturing process. Accordingly, the first wave L 11  is not scattered regularly in the fluid of the multiple scattering amplification region MSA 1  but is scattered irregularly, and the second power of the second wave L 21  may be different according to the emission position. The impurity detection system  10 ′ according to another embodiment of the present disclosure detects the laser speckle of the second wave L 21  emitted by using the plurality of detectors  1310 ,  1330 , and  1350  disposed at different positions, and thus a stable impurity detection is possible. 
     Specifically, the plurality of detectors  1310 ,  1330 , and  1350  may detect the second wave L 21  having different second powers. For example, the first detector  1310  may detect the second wave L 21  having a 2-1th power, the second detector  1330  may detect the second wave L 21  having a 2-2th power, and the third detector  1350  may detect the second wave L 21  having a 2-3th power. The 2-1th power, the 2-2th power, and the 2-3th power may have different values. Ideally, because the irradiated first wave L 11  is multiply scattered in the pipe unit  1110  in various directions and fills up the cross-section of the pipe unit  1110 , the microbe M of a fine size may be effectively detected regardless of which direction the laser speckle is detected. 
     However, in an actual detection environment, the power of the emitted second wave L 21  may be different according to the position due to factors such as a pattern degree of the pipe unit  1110  or a flow rate of the fluid. If only the first detector  1310  is provided, the second wave L 21  of the 2-1th power is detected. In this case, a position corresponding to the first detector  1310  may be a shade region of the second wave L 21 , which may reduce detection power. The impurity detection system  10 ′ may include a plurality of emission holes  1103 , and the plurality of detectors  1310 ,  1330 , and  1350  disposed in various directions, and thus complementary detection may be possible. The controller  1400  may detect impurities using values detected by the first to third detectors  1310 ,  1330 , and  1350 . For example, the controller  1400  may average information of laser speckles detected by the first to third detectors  1310 ,  1330 , and  1350  and utilize the information to detect impurities. 
     In this case, when there are two or more emission holes  1103 , the emission holes  1103  may be disposed at different positions of the body portion  1100 , and the detectors  1310 ,  1330 , and  1350  may be provided to correspond to the number of emission holes  1103 . The impurity detection system  10 ′ may allow the detectors  1310 ,  1330 , and  1350  to be disposed at different positions on the same circumference, and thus when the impurity microbe M pass through the same cross section of the pipe unit  1110 , the impurity microbe M may be detected at the same time. In addition, when a plurality of emission holes  1103  are provided, one of the emission holes  1103  may be disposed on the same circumference as an incidence position at which the first wave L 11  is incident from the wave source  1200 . The emission holes  1103  except for the one emission hole  1103  may be disposed on a circumference different from the wave source  1200 . For example, as shown, the plurality of emission holes  1103  may be disposed on different circumferences so as not to overlap with respect to the longitudinal direction of the pipe unit  1110 . 
     Meanwhile, the impurity detection system  10  may be capable of detecting impurities when the impurities in the fluid are present in a certain concentration range. The impurity detection system  10  may also perform a function of measuring an optical density (OD) of the fluid by estimating the concentration of impurities in the fluid. It is difficult for a general OD measuring device in measuring impurity concentration of 10 5  cfu/ml or less. However, the impurity detection system  10  according to an embodiment of the present disclosure may also be capable of measuring the impurity concentration of 10 5  cfu/ml or less through a method of determining the impurity concentration as follows. Here, impurities are not limited to microbes. The impurity detection system  10  may be capable of detecting impurities even at 1×10 0  cfu/ml by the number of times of multiple scattering of the amplified first wave L 11 . In addition, the impurity detection system  10  may be capable of detecting impurities even when the impurities of the range of 9×10 9  cfu/ml are present. When the range is converted into an OD range, the impurity detection system  10  may be capable of detecting impurities in the fluid with an OD in the range of 0 to 30. 
     Hereinafter, for convenience of description, a method, performed by the controller  1400 , of determining the concentration of microbes by using a laser speckle will be described mainly on the case where impurities are microbes. 
     The controller  1400  may calculate a standard deviation of light intensity of the laser speckle on a laser speckle image measured at each reference time. As microbes included in the fluid continuously move, constructive interference and destructive interference may change in response to the movement. In this case, as the constructive interference and the destructive interference change, a degree of light intensity may change greatly. Then, the controller  1400  may detect the microbes by calculating the standard deviation indicating the degree of change in the light intensity, and measure the distribution of the microbes. 
     For example, the controller  1400  may synthesize the laser speckle image measured at a predetermined time and calculate the standard deviation of the light intensity of the laser speckle over time from the synthesized image. The standard deviation of light intensity of the laser speckle over time may be calculated based on Equation 6 below. 
     
       
         
           
             
               
                 
                   
                     S 
                     ⁡ 
                     
                       ( 
                       
                         x 
                         , 
                         y 
                       
                       ) 
                     
                   
                   = 
                   
                     
                       
                         1 
                         T 
                       
                       ⁢ 
                       
                         
                           ∑ 
                           
                             t 
                             = 
                             1 
                           
                           T 
                         
                         ⁢ 
                         
                           
                             ( 
                             
                               
                                 
                                   I 
                                   t 
                                 
                                 ⁡ 
                                 
                                   ( 
                                   
                                     x 
                                     , 
                                     y 
                                   
                                   ) 
                                 
                               
                               - 
                               
                                 I 
                                 _ 
                               
                             
                             ) 
                           
                           2 
                         
                       
                     
                   
                 
               
               
                 
                   [ 
                   
                     Equation 
                     ⁢ 
                     
                         
                     
                     ⁢ 
                     6 
                   
                   ] 
                 
               
             
           
         
       
     
     In Equation 6, S may denote the standard deviation, (x, y) may denote camera pixel coordinates, T may denote the total measurement time, t may denote the measurement time, It may denote light intensity measured at the time t, and Ī may denote a mean light intensity over time. 
     Constructive and destructive interference patterns vary according to the movement of the microbes, and a standard deviation value calculated based on Equation 6 may become large, and thus the concentration of the microbes may be measured. However, the present disclosure is not limited to the method of measuring the concentration of the microbes by Equation 6 above, and may measure the concentration of the microbes by using any method using a difference of the detected laser speckle. 
     The controller  1400  may estimate a distribution, i.e., concentration, of the microbes included in the fluid based on a linear relationship between the magnitude of a standard deviation value of a light intensity of a second laser speckle and the microorganism concentration. 
     Meanwhile,  FIGS. 6A and 6B  are conceptual diagrams schematically showing an impurity detection system according to another embodiment of the present disclosure. 
     Referring to  FIGS. 6A and 6B , the impurity detection system may further include an optical unit  1550  restoring and modulating a first wave signal scattered in a fluid into a second wave signal before a first wave of the wave source  1200  is scattered by the fluid. In this case, the optical unit  1550  may include a spatial light modulator (SLM)  1551  and the detector  1300 . When a scattered wave is incident from a measurement target, the optical unit  1550  may control a wavefront of the scattered wave, restore the wave to a wave (light) before being scattered, and provide the wave to the detector  1300 . 
     The wave (light) may be incident on the SLM  1551  from a sample. The SLM  1551  may control a wavefront of the wave scattered from the sample to provide the wave to a lens  1552 . The lens  1552  may concentrate the controlled light and provide the light to the detector  1300  again. The detector  1300  may detect the wave concentrated by the lens and restore and output the wave output from an initial wave source to be scattered. 
     Here, when a microbe is not present in a stable medium, that is, the fluid, the optical unit  1550  may restore the first wave signal scattered from the fluid to the wave before scattered. However, when the microbe M is present in the fluid, because the first wave signal changes due to a movement of the microbe, a phase control wavefront may not be detected, and thus the first wave signal may not be modulated into the second wave signal having a phase conjugation wavefront. The impurity detection system including the optical unit  1550  described above may estimate the presence of impurities more finely by using a difference of the second wave signal. 
       FIG. 7  is a conceptual diagram schematically showing a microbial population counting system  20  according to an embodiment of the present disclosure.  FIG. 8  is a cross-sectional view taken along line III-III of  FIG. 7 . 
     Referring to  FIGS. 7 to 8 , the microbial population counting system  20  according to an embodiment of the present disclosure may include a sample placement unit  2100 , a wave source  2200 , a detector  2300 , and a controller  2400 . 
     As used herein, the term “microbe” refers to a prokaryotic or eukaryotic microbe with the ability to produce useful target substances such as L-amino acids. For example, a microbe with an increased intracellular ATP concentration may be a microbe belonging to  Escherichia  sp.,  Erwinia  sp.,  Serratia  sp.,  Providencia  sp.,  Corynebacterium  sp.,  Pseudomonas  sp.,  Leptospira, Salmonella  sp.,  Brevibacteria  sp.,  Hypomononas . sp.,  Chromobacterium  sp.,  Norcardia , fungi, or yeast. Specifically, the microbe may be the  Escherichia  sp. microbe. 
     Alternatively, the microbe may include bacteria selected from the group consisting of  Staphylococcus , staph Coagulase negative, Staph.  Aureus, Streptococcus  spp.,  Streptococcus viridans  group,  Enterococcus  spp.,  Corynebacterium  spp.,  Aerococcus  spp.,  Micrococcus  spp.,  Peptostreptococcus  spp.,  Lactococcus  spp.,  Leuconostoc  spp.),  Tothia  spp.  Gemella  spp.,  Alcaligenes  spp.,  Alternaria  spp.,  Flavobacterium  spp.,  Bacillus  spp.,  Achromobacter  spp.,  Acinetobacter  spp.,  Actinobacillus  spp.,  Alcaligenes  spp.,  Campylobacter  spp.,  Edwardsiella  spp.,  Ehrlichia  spp.,  Enterobacter  spp.,  Ewingella  spp.,  Flavobacteria, Hafnia  spp.,  klebsiella, Klebsiella  spp.,  Kluyvera  spp.,  Legionella  spp., Morxella spp.,  Morganella  spp.,  Neisseria  spp.,  Pasteurella  spp.,  Prevotella  spp.,  Proteus  spp.,  Providencia  spp.,  Pseudomonas  spp.,  Rahnella  spp.,  Salmonella  spp.,  serratia, Serratia  spp.,  Shigella  spp.,  Sphingobacterium  spp.,  Vibrio  spp.,  yersinia, Yersinia  spp.,  Neisseria  spp.,  Kingella  spp.,  Cardiobacterium , NTB:non-Tuberculosis mycobacteria),  Mycobacterium tuberculosis , and  Mycobacterium avium . More specifically, the microbe may be  E. coli . However, the technical idea of the present disclosure is not limited thereto, and may further include other microbes. 
     The sample placement unit  2100  may include a plurality of split cells  2110  distributing and accommodating samples to be measured. In this case, each of the plurality of split cells  2110  may include a culture material  2120  for microbe culture. The culture material  2120  may include a material corresponding to a type of microbe to be counted to effectively culture the microbe. 
     A medium including the culture material  2120  used for culture should suitably meet the requirements of a specific microbe. Various microbe culture media are described, for example, in “Manual of Methods for General Bacteriology” by the American Society for Bacteriology, Washington D.C., USA, 1981.) These media include various carbon sources, nitrogen sources and trace element components. Carbon sources may include carbohydrates such as glucose, lactose, sucrose, fructose, maltose, starch and fiber; fats such as soybean oil, sunflower oil, castor oil and coconut oil; fatty acids such as palmitic acid, stearic acid and linoleic acid; alcohols such as glycerol and ethanol and organic acids such as acetic acid, and these carbon sources may be used alone or in combination, but are not limited thereto. Nitrogen sources may include organic nitrogen sources and urea, such as peptone, yeast extract, gravy, malt extract, corn steep liquor (CSL), and bean flour, and inorganic nitrogen sources such as ammonium sulfate, ammonium chloride, ammonium phosphate, ammonium carbonate, and ammonium nitrate, and these nitrogen sources may be used alone or in combination, but are not limited thereto. The medium may further include potassium dihydrogen phosphate, dipotassium hydrogen phosphate, and corresponding sodium-containing salts as phosphoric acid sources, but is not limited thereto. The medium may also include metals such as magnesium sulfate or iron sulfate, and amino acids, vitamins and suitable precursors may be added. 
     In addition, in order to maintain aerobic conditions of a culture solution, oxygen or a gas including oxygen (e.g., air) may be injected into the culture solution. A temperature of the culture may generally be 20-45° C., specifically 25-40° C. 
     Here, a sample S 2  may be prepared by diluting according to the dilution ratio for counting the number of colonies. In general, the number of bacteria that may be deployed on a plate and measured separately is about 1000 as the number of colonies of  E. coli  in the case of the plate having a diameter of 10 cm. As will be described later, in the present disclosure, because after microbes are deployed on the plate, each of the microbes included in the plurality of divided cells  2110  may be detected without forming a colony, the number of countable bacteria may be different according to the dilution ratio of the sample S 2  and/or the number of split cells  2110 , and more bacteria may be counted than the bacteria described above. 
     Specifically, the plurality of split cells  2110  may be provided in the form of a matrix of (n, m), and the number thereof may be greater than a predicted microbial population included in the sample S 2 . As will be described later, the samples S 2  may equally accommodated in the plurality of split cells  2110 , and may be prepared generally by diluting according to a dilution ratio for counting the number of colonies. For example, when the plurality of split cells  2110  is provided in a matrix of (100, 100), the sample S 2  may be diluted such that the microbial population does not exceed 10 4 . Alternatively, when the plurality of divided cells  2110  is provided in a matrix of (100, 100), the sample S 2  may be diluted such that the microbial population does not exceed 10 6 . 
     Meanwhile, the sample placement unit  2100  may include a multiple scattering amplification region for amplifying the number of times a wave incident on the split cell  2110  is multiply scattered in the sample S 2 . For example, the sample placement unit  2100  may be formed by including a multiple scattering material in at least a lower region. For example, the multiple scattering material may include titanium oxide (TiO 2 ), and may reflect at least a part of the wave passing through the sample S 2  and incident on the sample placement unit  2100 . The multiple scattering amplification region may cause waves that are multiply scattered from the sample S 2  to reciprocate a space between the sample S 2  and the multiple scattering amplification region at least one time. 
     In another embodiment, the microbial population counting system  20  may be configured such that a multiple scattering material T 2  the time T 2  is included in the culture material  2120 . In  FIG. 2 , the culture material  2120  and the sample S 2  are separated from each other, but may be mixed with the culture material  2120  when the sample S 2  is accommodated in the split cell  2110 . At this time, the multiple scattering material T 2  may be arranged to surround the microbe M to scatter the incident wave and increase the number of times of multiple scattering. 
     Meanwhile, in another embodiment, the microbial population counting system  20  may further include a separate multiple scattering amplifier (not shown). The multiple scattering amplifier (not shown) may be provided on a wave movement path between the wave source  2200  and the sample placement unit  2100  and/or between the sample placement unit  2100  and the detector  2300  to amplify the number of times of multiple scattering of waves. When the multiple scattering amplifier (not shown) is disposed between the wave source  2200  and the sample placement unit  2100 , the multiple scattering amplifier may be formed in a detachable structure to distribute the sample S 2  to the sample placement unit  2100 . For example, the multiple scattering amplifier (not shown) may be configured in a structure such as a lid. In addition, the multiple scattering amplifier (not shown) may be provided to correspond to each of the split cells  2110 , or may be formed in a structure covering the entirety of the plurality of split cells  2110 . 
     Meanwhile, the sample placement unit  2100  may include a blocking region  2110 A on a side surface of each split cell  2110  to block the wave incident to each split cell  2110  not to introduce into another split cell  2110 . The microbial population counting system  20  according to an embodiment of the present disclosure sequentially irradiates waves to the plurality of split cells  2110  and detects laser speckles emitted correspondingly. As will be described later, such a process should accurately detect whether the microbe is present in each of the plurality of split cells  2110 , and the accuracy thereof may be reduced due to a laser speckle emitted from the split cell  2110  other than the corresponding split cell  2110  during a rapid detection process. In order to prevent this, the sample placement unit  2100  may include the blocking region  2110 A on the side surface of each split cell  2110 , such that a wave incident on the corresponding split cell  2110  may be introduced into the other split cell  2110  so as not to cause interference. In an embodiment, the blocking region  2110 A may include a metal material having a reflective characteristic. 
     Meanwhile, in  FIG. 8 , only the blocking region  2110 A is disposed on the side surface of the split cell  2110 , but the technical idea of the present disclosure is not limited thereto. In another embodiment, the blocking region  2110 A may also be disposed on a lower surface of the split cell  2110 . In this case, unlike that shown in  FIG. 8 , the detector  2300  may be disposed on an upper portion of the sample placement unit  2100  to detect an emitted laser speckle. Alternatively, the detector  2300  may be disposed to face the wave source  2200  with respect to the sample placement unit  2100  as shown in  FIG. 7  but may detect a laser speckle emitted through a predetermined through region of the lower surface of the sample placement unit  2100  in which a blocking region is not formed. 
     Although not shown, the sample placement unit  2100  may further include a reference cell (not shown) formed in the same shape as the plurality of split cells  2110  and positioned on an irradiation path of wave. At this time, the reference cell (not shown) may have the same size as the plurality of split cells  2110  to include a culture material of the same type and capacity. However, unlike the split cells  2110 , the sample S 2  is not accommodated in the reference cell (not shown). 
     The culture material may have some degree of fluidity, which may act as noise to detect a laser speckle according to a subtle movement of a microbe. In this case, because the reference cell (not shown) provided in the sample placement unit  2100  together with the plurality of split cells  2110  does not accommodate the sample S 2  but includes the culture material, when a subtle vibration occurs in the sample placement unit  2100  and thus the culture material of the plurality of split cells  2110  has fluidity, the culture material of the reference cell (not shown) also has the same fluidity. The microbial population counting system  20  may equally irradiate waves to the reference cell (not shown) and set a laser speckle detected therefrom as a reference value, thereby removing noise to correctly identify the presence of the microbe in the other split cells  2110 . 
     Referring to  FIGS. 7 and 8  again, the wave source  2200  may sequentially irradiate waves to the plurality of split cells  2110  of the sample placement unit  2100 . The wave source  2200  may apply all kinds of source device capable of generating waves, and may be, for example, a laser capable of irradiating light of a specific wavelength band. Meanwhile, the wave source  2200  may be connected to a driving device such as a motor or an actuator to sequentially irradiate waves toward the respective split cells  2110  according to a preset time interval. Although the present disclosure is not limited to a type of a wave source, a case where the wave source is the laser will be described for convenience of description. 
     For example, laser with a good coherence may be used as the wave source  2200  to form speckle in the sample S 2  accommodated in the plurality of split cells  2110 . In this case, the shorter the spectral bandwidth of the wave source that determines the coherence of the laser wave source, the greater the measurement accuracy. That is, the longer the coherence length, the greater the measurement accuracy. Accordingly, a laser light whose spectral bandwidth of the wave source is less than a predetermined reference bandwidth may be used as the wave source  1200 , and the measurement accuracy may increase as the spectral bandwidth of the wave source is shorter than the reference bandwidth. 
     Meanwhile, the detector  2300  may sequentially detect individual wave information emitted from the sample S 2  accommodated in each split cell  2110  in association with sequentially irradiated waves. At this time, the individual wave information may be information obtained by detecting a laser speckle generated by multiple scattered from the sample S 2  accommodated in each of the plurality of split cells  2110  for each preset time. Specifically, the individual wave information includes first image information of a laser speckle detected at a first time, second image information of a laser speckle detected at a second time, and third image information of a laser speckle detected at a third time among the laser speckles emitted from the corresponding split cell  2110 , wherein the first to third times may be different times. The detector  2300  may provide the controller  2400  with information about the laser speckles detected at the first to third times with respect to the one split cell  2110 . In this case, the first to third times are the minimum number of detections for the controller  2400  to analyze temporal correlation of the laser speckles, and the detector  2300  may detect the laser speckles at a plurality of times more than the times. 
     Here, time means any moment in a continuous flow of time, and times may be set in advance at the same time interval, but are not limited thereto, and may be set in advance at any time interval. The detector  2300  may include a sensing means corresponding to a type of the wave source  2200 . For example, when a light source of a visible light wavelength band is used, a CCD camera which is an image capturing device may be used. 
     Specifically, when a wave is irradiated to the sample S 2  accommodated in the one split cell  2110 , the incident wave may form a laser speckle by multiple scattering. 
     Because the laser speckle is generated by the interference of light, if there is no microbe in the sample S 2 , a multiple scattering amplification region may always show a constant interference pattern over time. In comparison, when the microbe M is present in the sample S 2 , the laser speckle may change over time by a movement of the microbe M. The detector  2300  may detect the laser speckle that changes over time for each preset time and provide the laser speckle to the controller  2400 . The detector  2300  may detect the laser speckle at a speed sufficient to detect the movement of the microbe M, and for example, may detect the laser speckle at the speed of 25 to 30 frames per second. 
     The controller  2400  may determine the presence of the microbe M in each split cell  2110  using the detected individual wave information, and calculate the microbial population in the sample S 2  by using the number of split cells  2110  in which the microbe M is present. Specifically, the controller  2400  may obtain a temporal correlation of the detected laser speckles using the detected laser speckles and determine the presence of the microbe M in the corresponding split cell  2110  based on the obtained temporal correlation. The controller  2400  may estimate the presence of the microbe in each split cells  2110  in real time based on the obtained temporal correlation. Real time in the present specification means estimating the presence of the microbe M within 3 seconds, preferably, it is possible to estimate the presence of the microbe M within 1 second. 
     In an embodiment, the controller  2400  may estimate the presence of the microbe using the laser speckles emitted from the sample S 2  at different times due to the wave irradiated to the one divided cell  2110 . For example, in  FIG. 7 , when a first wave S 12  is irradiated to a (1,1) split cell, the controller  2400  may estimate the presence of the microbe M in the (1,1) split cell by obtaining a temporal relation between first laser speckles P 12  that are multiply scattered by the first wave S 12  and emitted. At this time, the controller  2400  may estimate the presence of the microbe M by using a difference between using first image information of the first laser speckle P 12  detected at the first time, second image information of a first laser speckle P 22  detected at the second time, and third image information of a first laser speckle P 32  detected at the third time. 
     Here, the first image information to the third image information may be at least one of pattern information of the laser speckle and intensity information of waves. Meanwhile, an embodiment of the present disclosure may use the difference between the at least three image information of the laser speckles detected at different times, but may extend this to use image information of a plurality of laser speckles at a plurality of times. The controller  2400  may calculate a temporal correlation coefficient between images using the image information of the laser speckles generated for a plurality of preset times, and estimate the presence of the microbe M in the corresponding split cell  2110  based on the temporal correlation coefficient. 
     Hereinafter, a method of counting the microbial population using the microbial population counting system  20  described above will be described in detail. 
       FIG. 9  is a flowchart sequentially showing a method of counting a microbial population according to an embodiment of the present disclosure, and  FIGS. 10 and 11  are diagrams for explaining the method of counting the microbial population. 
     Referring to  FIGS. 9 to 11 , the method of counting the microbial population according to an embodiment of the present disclosure may, first, prepare the sample placement unit  2100  (S 100 ). The sample placement unit  2100  may include the plurality of split cells  2110  each including a culture material. 
     Thereafter, the sample S 2  to be measured is diluted at a predetermined dilution ratio and distributed to the plurality of split cells  2110  (S 200 ). At this time, sizes of the plurality of split cells  2110  are equally configured, and the sample S 2  may be uniformly distributed Because the sample S 2  is diluted such that an expected microbe M population is smaller than the number of the plurality of split cells  2110 , when the sample S 2  is uniformly distributed, as shown in  FIG. 4 , the microbe M may be or may not be present in each split cell  2110 . 
     Thereafter, waves may be sequentially irradiated to the plurality of split cells  2110  by the wave source  2200 , and individual wave information emitted from the sample S 2  accommodated in each split cell  2110  may be sequentially detected in association with sequentially irradiated waves (S 300 ). For example, when the plurality of split cells  2110  are arranged in the form of an (n, m) matrix as shown, the waves may be irradiated in a sequentially scanning manner along each column. At this time, the detector  2300  detects individual wave information emitted from each split cell  2110  in association with the irradiated waves. As described above, the individual wave information may be a plurality of pieces of image information of laser speckles detected at different times in the corresponding split cell  2110 . 
     The controller  2400  may determine the presence of the microbe M in each split cell  2110  using the detected individual wave information (S 400 ). 
     For example, as shown in  FIG. 4 , when the microbe M is present in the (1,1) split cell and the microbe M is not present in a (2,1) split cell, the controller  2400  may define the (1,1) split cell as 1 and the (2,1) split cell as 0. Such determination of the presence of the microbe M may be performed from the (1,1) split cell to the (n, m) split cell according to an irradiation path of sequential waves. 
     When the determination of the presence of the microbe with respect to all the split cells  2110  is completed, the controller  2400  may calculate the microbial population in the entire samples S 2  using the number of split cells in which the microbe M is present. In other words, by calculating the number of split cells defined as 1 in the entire split cells  2110 , the microbial population included in the entire samples S 2  may be calculated. 
       FIG. 12  is a conceptual diagram schematically showing a microbial population counting system  20 - 1  according to another embodiment of the present disclosure. 
     Referring to  FIG. 12 , the microbial population counting system  20 - 1  according to another embodiment of the present disclosure may further include a wave path changer  2210  in order to sequentially irradiate waves irradiated from the wave source  2200  into the plurality of split cells  2110 . In other words, the waves are not irradiated directly to the plurality of split cells  2110  from the wave source  2200 , but the waves may be irradiated to the plurality of split cells  2110  using the wave path changer  2210 . In another embodiment of the present disclosure, except for a method of irradiating waves, the other components are the same as those in an embodiment, and thus redundant descriptions will be omitted for the convenience of description. 
     The waves may be incident on the wave path changer  2210  from the wave source  2200 . The wave path changer  2210  may be a micro mirror. The wave path changer  2210  may include a reflective surface to reflect the incident waves toward the plurality of split cells  2110 . The reflective surface is shown as a flat surface without refractive power, but the present disclosure is not limited thereto. The wave path changer  2210  may be finely driven by a drive controller (not shown). 
     In another embodiment, the wave path changer  2210  may be finely driven by the controller  2400 , and accordingly, may sequentially irradiate the waves to the plurality of split cells  2110 . At this time, the controller  2400  may also control the detector  2300  to detect the laser speckle emitted from the corresponding split cell  2110  in association with a wave order irradiated by the wave path changer  2210 . 
     The micro mirror constituting the wave path changer  2210  may employ various configurations in which mechanical displacement of the reflective surface may occur according to electrical control. For example, a generally known micro electromechanical system (MEMS) mirror, a digital micromirror device (DMD) element or the like may be employed. The wave path changer  2210  is illustrated as one micro mirror, but this is exemplary and may be a configuration in which a plurality of micro mirrors are two-dimensionally arrayed. 
     Meanwhile, the wave path changer  2210  may further include a mirror  2215  disposed on the wave path to adjust angles of the waves irradiated to the plurality of split cells  2110  to be uniform. In other words, when the wave path changer  2210  irradiates the waves to the plurality of split cells  2110  using the micro mirror, the incident angles of the waves may be different according to positions of the split cells  2110 . Accordingly, because a degree of multi-scattering in the sample S 2  may be different according to positions of the plurality of split cells  2110 , accurate comparison and evaluation may be difficult, and thus, the mirror  2215  may be further disposed such to adjust the angles of the waves irradiated to the split cells  2110  to be uniform. In the drawing, only the one mirror  2215  disposed on the (1,1) split cell is illustrated, but is schematically illustrated for convenience of description, and a mirror is disposed in an upper end of each of the split cells  2110  such that the angles of the waves irradiated to the split cells  2110  may be adjusted. 
       FIG. 13  is a conceptual diagram schematically showing a sample placement unit  2100 - 1  according to another embodiment of the present disclosure. 
     Referring to  FIG. 13 , unlike the sample placement unit  2100  of an embodiment which is formed in the form of a petri dish such as an agar plate, the sample placement unit  2100 - 1  according to another embodiment may be in the form of a multi-well based microfluidics chip connected to a microfluid channel  2135 . 
     Specifically, the sample placement unit  2100 - 1  may include the plurality of split cells  2110  having a multi-well shape and an injector  2130  through which the samples S 2  may be injected, and the plurality of split cells  2110  and the injector  2130  may connected to the microfluidics channel  2135 . When the sample S 2  is injected into the injector  2130 , the sample placement unit  2100 - 1  may uniformly distribute the sample S 2  to each split cell  2110  through the microfluidics channel  2135 . 
     The sample placement unit  2100 - 1  according to another embodiment may include a culture material for culturing a microbe in each of the plurality of split cells  2110  in the same manner as in an embodiment. In addition, an upper surface of the sample placement unit  2100 - 1  may include a transparent material for optical imaging. However, the present disclosure is not limited thereto, and as described above, a multiple scattering amplifier may be disposed on the upper surface for multiple scattering amplification. 
     Meanwhile, the sample placement unit  2100 - 1  has a blocking region on at least a side surface of each split cell  2110  to block a wave incident to each split cell  2110  from entering another split cell  2110 . Through the blocking region, the sample placement unit  2100 - 1  may minimize wave interference between the split cells  2110  to improve the accuracy of the population count. In addition, the sample placement unit  2100 - 1  may be provided as a disposable kit. 
       FIG. 14  is a diagram schematically showing an airborne bacteria measuring device  30  according to an embodiment of the present disclosure, and  FIG. 15  is a conceptual diagram for explaining the sampling principle of the airborne bacteria measuring device  30  of  FIG. 14 .  FIG. 16  is a block diagram of the airborne bacteria measuring device  30  of  FIG. 14 , and  FIGS. 17A to 17D  are diagrams for explaining a process performed by the airborne bacteria measuring device  30  of  FIG. 14  of sampling bacteria and then processing collection liquid. 
     The air sampler of the related art inhales air including airborne bacteria for airborne bacteria sampling and then grows the air by spreading the air in a medium to be a measurable amount. At this time, a culture time is long, which made it difficult to detect airborne bacteria quickly. 
     The present disclosure is to solve the above problem, and the airborne bacteria measuring device  30  according to an embodiment of the present disclosure allows air in which microbes such as bacteria and germs are floating to contact with the collection liquid, collecting the airborne bacteria in the collection liquid, and then detects the airborne bacteria using a wave speckle, and thus the airborne bacteria is detected within a short time. 
     First, referring to  FIGS. 14 and 15 , the airborne bacteria measuring device  30  according to an embodiment of the present disclosure may include a collection unit  3200 , a wave source  3100 , an image sensor  3300 , and a controller  3400 . 
     The collection unit  3200  performs a function of accommodating the collection liquid to collect the bacteria from the inhaled air. Specifically, the collection unit  3200  may include a storage tank  3201  for accommodating the collection liquid W therein, an inhalation flow path  3211  for inhaling external air to guide the external air to the collection liquid W in one side of the storage tank  3201 , and an exhaust flow path  3212  for discharging the air of the storage tank  3201  to the outside in the other side of the storage tank  3201 . 
     Here, the collection liquid W may be any kind of sample capable of collecting the bacteria through contact with the airborne bacteria. In other words, the collection liquid W may be a liquid or a sample in the form of a gel. However, in the present disclosure, in order to accurately detect the presence or concentration of the airborne bacteria, the collection liquid W may be prepared without including impurities such as microbes before contacting the air, or may be previously stored by in advance measuring concentration of microbes including impurities in the collection liquid W before contacting the air through a chaotic wave sensor that will be described later. 
     In an embodiment, the collection liquid W may include a liquid, and may include a culture material for culturing microbes. The collection liquid W may include various microbe culture materials and is described, for example, in “Manual of Methods for General Bacteriology” by the American Society for Bacteriology, Washington D.C., USA, 1981.) These media include various carbon sources, nitrogen sources and trace element components. Carbon sources may include carbohydrates such as glucose, lactose, sucrose, fructose, maltose, starch and fiber; fats such as soybean oil, sunflower oil, castor oil and coconut oil; fatty acids such as palmitic acid, stearic acid and linoleic acid; alcohols such as glycerol and ethanol and organic acids such as acetic acid, and these carbon sources may be used alone or in combination, but are not limited thereto. Nitrogen sources may include organic nitrogen sources and urea, such as peptone, yeast extract, gravy, malt extract, corn steep liquor (CSL), and bean flour, and inorganic nitrogen sources such as ammonium sulfate, ammonium chloride, ammonium phosphate, ammonium carbonate, and ammonium nitrate, and these nitrogen sources may be used alone or in combination, but are not limited thereto. The medium may further include potassium dihydrogen phosphate, dipotassium hydrogen phosphate, and corresponding sodium-containing salts as phosphoric acid sources, but is not limited thereto. The medium may also include metals such as magnesium sulfate or iron sulfate, and amino acids, vitamins and suitable precursors may be added. 
     In addition, in order to maintain aerobic conditions of the collection liquid W, oxygen or a gas including oxygen (e.g., air) may be injected into the collection liquid W. A temperature of the collection liquid W may generally be 20-45° C., specifically 25-40° C. 
     At least a part of the storage tank  3201  may include a material through which a wave may pass. For example, at least a region of the storage tank  3201  on which the wave is incident or from which the wave is emitted may include a material such as glass. In another embodiment, when the storage tank  3201  includes a material through which the wave may not pass, for example, a metal material, a through hole corresponding to the region on which the wave is incident or from which the wave is emitted may be formed. At this time, the storage tank  3201  may further include a cover portion (not shown) disposed at one side of the through hole. The cover portion (not shown) may include a transparent or translucent material such that the second wave L 21  may pass therethrough. For example, the cover portion (not shown) may include a glass or plastic material, and may be formed in a plate shape having flexibility, but may also be manufactured in a film. In another embodiment, the cover portion (not shown) may be formed to fill the inside of the through hole rather than disposed in one side of the through hole. 
     Meanwhile, the collection unit  3200  may further include a multiple scattering amplifier MS for reflecting at least a part of the waves emitted from the collection liquid W to the collection liquid W to amplify the number of times of multiple scattering in the collection liquid W. For example, the multiple scattering amplifier MS may scatter at least a part of the waves incident to the storage tank  3201  and scattered due to bacteria in the collection liquid W, and then emitted from the storage tank  3201  into the collection liquid W again. The scattered waves may be scattered and emitted again due to the bacteria in the collection liquid W again, and the number of times of multiple scattering in the collection liquid W may increase through this process. 
     In an embodiment, the multiple scattering amplifier MS may be disposed between the storage tank  3201  and the wave source  3100 , and disposed between the storage tank  3201  and the image sensor  3300  to reflect at least a part of waves multiple scattered and emitted from the collection liquid W. In other words, the multiple scattering amplifier MS may allow the waves multiple scattered and emitted from the collection liquid W to reciprocate a space between the collection liquid W and the multiple scattering amplifier MS at least once time. The multiple scattering amplifier MS may include a multiple scattering material, for example, the multiple scattering material may include titanium oxide (TiO 2 ). 
     In another embodiment, the collection unit  3200  may form a multiple scattering amplification region including the multiple scattering material in at least a part of the storage tank  3201 . For example, the multiple scattering amplification region may be formed by coating, with the multiple scattering material, a region corresponding to at least a space in which the collection liquid W is accommodated in the storage tank  3201 . However, the technical idea of the present disclosure is not limited thereto, and the multiple scattering amplification region may be disposed in the entire region of the storage tank  3201  except for the wave incidence part and emission part. 
     Meanwhile, the inhalation flow path  3211  may be disposed on one side of the storage tank  3201  and perform a function of inhaling external air to guide the external air to the collection liquid W, and the exhaust flow path  3212  mat be disposed on the other side of the storage tank  3201  and perform a function of discharging the air of the storage tank  3201  to the outside. As shown in the drawing, the inhalation flow path  3211  may be formed in which one end is immersed in the collection liquid W and the air is capable of directly contacting with the collection liquid W. However, the present disclosure is not limited thereto, and the inhalation flow path  3211  may be formed in any form capable of guiding the external air to the collection liquid W. 
     Meanwhile, a filter unit  3240  may be installed in the inhalation flow path  3211 . The filter unit  3240  may perform a function of filtering a substance having a predetermined size or more included in the external air introduced into the inhalation flow path  3211 . 
     The exhaust flow path  3212  may be disposed at one end of an accommodation space of the storage tank  3201  except for the collection liquid W so as to discharge the air of the storage tank  3201  to the outside. The external air is guided to the collection liquid W through the inhalation flow path  3211 , and then the remaining air excluding the collected bacteria is discharged from the collection liquid W, and the exhaust flow path  3212  performs the function of discharging the air to the outside. Although not shown, the collection unit  3200  may connect the exhaust flow path  3212  with a means such as a pneumatic pump or a compressor to discharge the air in the storage tank  3201  to the outside. In addition, by generating a pressure difference of the storage tank  3201  through the above-described process, the collection unit  3200  may inhale the air into the storage tank  3201 . 
     The collection unit  3200  may include a collection liquid flow pipe  3221  for flowing the collection liquid W stored in the outside into the storage tank  3201 , and a collection liquid discharge pipe  3222  for discharging the completely detected collection liquid W from the storage tank  3201 . The collection liquid flow pipe  3221  and the collection liquid discharge pipe  3222  may be installed at a lower portion of the storage tank  3201  as illustrated in the drawing to facilitate the introduction and discharge of the collection liquid W. 
     Meanwhile, the wave source  3100  may irradiate a wave toward the collection liquid W of the collection unit  3200 . The wave source  3100  may apply all types of source device capable of generating a wave, and may be, for example, a laser capable of irradiating light of a specific wavelength band. Although the present disclosure is not limited to a type of a wave source, a case where the wave source is the laser will be described for convenience of description. 
     For example, laser with a good coherence may be used as the wave source  3100  to form speckle in the fluid. 
     The image sensor  3300  may time serially measure wave speckles generated by multiple scattered in the collection liquid W. In other words, the image sensor  3300  may be disposed on an emission path of the wave, and may time serially capture the waves emitted from the collection liquid W and obtain a plurality of images. The image sensor  3300  may include sensing means corresponding to the type of the wave source  3100 . For example, when a light source of a visible light wavelength band is used, a CCD camera which is an image capturing device may be used. 
     Here, each of the plurality of images may include information of speckles multiple scattered and generated by the bacteria due to the waves incident on the collection liquid W. In other words, the image sensor  3300  may detect the wave speckles generated by the irradiated waves multiple scattered in the collection liquid W, at a preset time. Here, time means any moment in a continuous flow of time, and times may be set in advance at the same time interval, but are not limited thereto, and may be set in advance at any time interval. 
     The image sensor  3300  may detect a first image including first speckle information at least at a first time and capture a second image including second speckle information at a second time to control the first and second images to the controller  3400 . Meanwhile, the first point and the second point are merely one example selected for convenience of description, and the image sensor  3300  may capture a plurality of images at a plurality of points more than the first point and the second point. The image sensor  3300  may include a polarizer  3305  in a path from which waves are emitted, thereby maximizing interference efficiency for speckle formation and removing unnecessary external reflected light, etc. 
     The controller  3400  may detect the presence of the bacteria, that is, microbes, in the collection liquid W based on a change in the measured wave speckles over time. In an embodiment, the controller  3400  may obtain a temporal correlation of the wave speckles and detect the presence of microbes in the collection liquid W based on the obtained temporal correlation. 
     Specifically, the controller  3400  may use a difference between first image information of a first wave speckle detected at the first time and second image information of a second wave speckle detected at the second time to detect the presence of the microbe M. Here, the first image information and the second image information may be at least one of pattern information of the wave speckle and intensity information of waves. 
     Meanwhile, an embodiment of the present disclosure does not use only the difference between the first image information at the first time and the second image information at the second time but may extend this to use image information of a plurality of wave speckles at a plurality of times. The controller  3400  may calculate a temporal correlation coefficient between images using image information of wave speckles generated for a plurality of preset times, and estimate the presence of the microbe M in the collection liquid W and furthermore the presence of the airborne bacteria based on the temporal correlation coefficient. 
     Referring to  FIGS. 16 and 17 , the airborne bacteria measuring device  30  according to an embodiment of the present disclosure may further include a sterilization unit  3500 . 
     The sterilization unit  3500  may sterilize the collection liquid W in the storage tank  3201 . The sterilization unit  3500  may be any means capable of removing microbes in the collection liquid W. For example, the sterilization unit  3500  may include at least one of an ultraviolet (UV) lamp or a laser having a predetermined or higher output. Alternatively, the sterilization unit  3500  may sterilize using electrolysis. Meanwhile, in another embodiment, the sterilization unit  3500  does not sterilize the collection liquid W in the storage tank  3201 , but is disposed on the discharge path of the collection liquid discharge pipe  3222  to sterilize the discharged collection liquid W. 
     Meanwhile, the airborne bacteria measuring device  30  may further include a first valve  3231  installed in the collection liquid flow pipe  3221  and selectively opening and closing the collection liquid flow pipe  3221  and a second valve  3232  installed in the collection liquid discharge pipe  3222  and selectively opening and closing the collection liquid discharge pipe  3222 . In this case, the controller  3400  may control an operation of the first valve  3231  or the second valve  3232  by a preset program. 
     Specifically, referring to  FIG. 17A , the airborne bacteria measuring device  30  may collect airborne bacteria M in the collection liquid W using the collection unit  3200 . As described above, the airborne bacteria measuring device  30  may introduce the managed collection liquid W into the storage tank  3201  immediately before detection such that the collection liquid W does not include a microbe before inhaling the microbe M or previously measure the collection liquid W accommodated in the storage tank  3201  to store concentration of impurities including the microbes. When the collection liquid W stored outside is introduced into the storage tank  3201 , the controller  3400  may control the first valve  3231  to be opened, after accommodating a predetermined amount of the collection liquid W, control the first valve  3231  to be closed. Thereafter, the airborne bacteria measuring device  30  may collect the bacteria M included in the external air by contacting the inhaled external air with the collection liquid W. 
     Referring to  FIG. 17B , the airborne bacteria measuring device  30  may detect the presence or concentration of the microbe M in real time by irradiating waves in the collection liquid W, but in another embodiment, may culture the microbe M in the collection liquid W for a certain period of time and then detect the microbe M. When culturing the microbe M in the collection liquid W for a certain period of time and then measuring the microbe M, the airborne bacteria measuring device  30  may estimate an actual concentration of the airborne bacteria from the concentration of the microbe M detected in consideration of the above period of time. 
     Referring to  FIG. 17B , the completely detected collection liquid W as described above may be sterilized by the sterilization unit  3500 . Through this, the airborne bacteria measuring device  30  may not only minimize the generation of contaminants by sterilizing and then discharging the collection liquid W but also more ultimately increasing the accuracy of a repetitive detection process by removing microbes in the storage tank  3201 . 
     Referring to  FIG. 17D , when the sterilization process is completed, the controller  3400  may control the second valve  3322  to be opened to discharge the collection liquid W in the storage tank  3201  to the outside. By repeating the above process, the airborne bacteria measuring device  30  may repeatedly measure the airborne bacteria, such data may be provided to an external server to be utilized as big data. 
     Hereinafter, a network environment including the airborne bacteria measuring device  30  having the above-described configuration will be described with reference to the drawings. In this regard, a method of identifying concentration or type of airborne bacteria as well as detecting the airborne bacteria through machine learning will be described. 
       FIG. 18  is a diagram showing an example of a network environment  1  according to an embodiment of the present disclosure. 
     The network environment  1  of  FIG. 18  shows the example including one or more airborne bacteria measuring devices  30 , a user terminal  2 , a server  3 , and a network  4 .  FIG. 18  is an example for describing the present disclosure, and the number of terminals of a user and the number of servers is not limited to that in  FIG. 18 . 
     The one or more airborne bacteria measuring devices  30  may be provided and disposed in different regions to detect airborne bacteria in each region through the above-described detection process. The airborne bacteria measuring device  30  may be provided to the server  3  or the user terminal  2  using the network  4  which is the communication network. Using data provided in this way, the server  3  may generate airborne bacteria information according to a region, and more specifically, anti-bacterial information related to the bacteria, with a map and provide the same to the user terminal  2 . 
     The user terminal  2  may be a fixed terminal  22  implemented as a computer device or a mobile terminal  21 . The user terminal  2  may be a terminal of an administrator controlling the server  3 . Examples of the user terminal  2  include a smart phone, a mobile phone, a navigation device, a computer, a notebook computer, a digital broadcasting terminal, a personal digital assistant (PDA), a portable multimedia player (PMP), a tablet PC, and the like. For example, the user terminal  121  may communicate with another user terminal  22  and/or the server  3  through the communication network  4  using a wireless or wired communication method. 
     The communication method is not limited and may include not only a communication method using a communication network (e.g., a mobile communication network, a wired internet, a wireless internet, and a broadcasting network) that the network  4  may include, but also a short range wireless communication between devices. For example, the network  4  may include any one or more of networks among a personal area network (PAN), a local area network (LAN), a campus area network (CAN), a metropolitan area network (MAN), a wide area network (WAN), a broadband network (BBN), and the Internet. The network  4  may also include any one or more of network topologies, including bus networks, star networks, ring networks, mesh networks, star-bus networks, tree or hierarchical networks but is not limited thereto. 
     The server  3  may communicate with the user terminal  2  or the airborne bacteria measuring device  30  through the network  4  to be implemented as a computer device or a plurality of computer devices providing command, code, file, content, service, etc. 
     The airborne bacteria measuring device  30  according to an embodiment of the present disclosure may perform a function of collecting the airborne bacteria through an independent configuration, measuring wave speckles emitted from a collection liquid, learning a microbial classification criteria using the wave speckles by the controller  3400 , and detecting bacteria in the collection liquid using the learned microbial classification criteria. 
     However, the technical idea of the present disclosure is not limited thereto, the airborne bacteria measuring device  30  may transmit detection data to the external server  3 , and the external server  3  may use the transmitted data to machine learn the microbial classification criteria and provide a learned algorithm to the airborne bacteria measuring device  30 . The airborne bacteria measuring device  30  may detect the presence of airborne bacteria or identify the concentration or the type of the airborne bacteria using the provided algorithm and data about newly measured wave speckles. Hereinafter, for convenience of explanation, the case where the server  3  machine learns the microbial classification criteria will be mainly described. 
       FIG. 19  is a block diagram schematically showing the server  3  according to an embodiment of the present disclosure. 
     The server  3  may correspond to at least one processor or may include at least one processor. Accordingly, the server  3  may be driven by included in a hardware device such as a microprocessor or a general purpose computer system. Here, the ‘processor’ may refer to, for example, a data processing unit embedded in hardware and including a circuit physically structured to perform a function represented in codes or commands included in a program. An example of the data processing unit embedded in the hardware may include a processing device such as a microprocessor, a central processing unit (CPU), a processor core, a multiprocessor, application-specific integrated circuit (ASIC), field programmable gate array (FPGA), and the like, but the scope of the present disclosure is not limited thereto. 
     The server  3  shown in  FIG. 19  shows only the components related to the present embodiment in order to prevent the features of the present embodiment from being blurred. Accordingly, it will be understood by those skilled in the art that other general purpose components may be further included in addition to the components illustrated in  FIG. 19 . 
     Referring to  FIG. 19 , the server  3  according to an embodiment of the present disclosure may include an input/output interface  31 , a receiver  32 , a processor  33 , and a memory  34 . 
     The memory  34  is a computer readable recording medium, and may include a permanent mass storage device such as random access memory (RAM), read only memory (ROM), and a disk drive. 
     The input/output interface  31  may be means for interfacing with input/output devices. For example, the input device may include a device such as a keyboard or mouse, and the output device may include a device such as a display for displaying a communication session of an application. As another example, the input/output interface  31  may be means for interfacing with a device such as a touch screen in which functions for input and output are integrated into one. 
     The receiver  32  may receive a plurality of images from the airborne bacteria measuring device  30 . At this time, the plurality of images may be images obtained by the image sensor  3300  of the airborne bacteria measuring device  30  by capturing waves emitted from the collection liquid W in the time series order. That is, the receiver  32  may function as a communication module using wired or wireless communication, and may receive the plurality of images. At this time, the receiver  32  may provide a function for the user terminal  121  and the server  3  to communicate with each other over the network  4 , and may provide a function for communicating with another user terminal (e.g., the user terminal  222 ) or another server. 
     The processor  33  may be configured to process commands of a computer program by performing basic arithmetic, logic, and input/output operations. The command may be provided to the processor  33  by the memory  34  or the receiver  32 . For example, the processor  33  may be configured to execute a command received according to a program code stored in a recording device such as the memory  34 . The processor  33  may include a learner  331 , a detector  332 , and a determiner  333 . 
     The detector  322  may extract a feature of change over time from a plurality of learning images received by the receiver  32 . Here, the plurality of learning images are images continuously captured at a time interval, and include time information between the plurality of learning images captured in the time series order. The detector  322  may extract the feature of change over time from the plurality of learning images. 
     The learner  331  may learn the microbial classification criteria for identifying the type or the concentration of microbes present in the collection liquid W based on the extracted feature. The learner  331  learns the microbial classification criteria based on deep learning, and deep learning is defined as a set of machine learning algorithms that attempt high level abstractions (a job of summarizing core content or function in a large amount of data or complex data) through a combination of several non-linear transformation methods. The learner  331  may use any one of models of deep learning, for example, deep neural networks (DNNs), convolutional neural networks (CNNs), recurrent neural networks (RNNs), and deep belief networks (DBNs). 
     In an embodiment, the learner  331  may machine learn a classification criterion based on temporal correlation of the received plurality of learning images. 
     As described above, the plurality of learning images may include information of wave speckles multiple scattered and generated from the microbe M in the collection liquid W. As described above with reference to  FIG. 3 , when bacteria are present in the collection liquid W, a speckle may change over time due to the life activity of microbes. In addition, because a change of the speckle over time is different according to the type or the concentration of the microbe, the learner  331  may learn the microbial classification criteria for classifying the type or concentration of the microbe using the change of the speckle over time. 
       FIG. 20  is a diagram for describing a method, performed by the learner  331 , of analyzing a temporal correlation of speckles according to an embodiment of the present disclosure. 
     Referring to  FIG. 20 , the learner  331  may calculate temporal correlation coefficients between images as shown in Equation 3 by using image information of speckles generated at a plurality of preset times, and may learn a microbial classification criteria based on the temporal correlation coefficients. As shown in  FIG. 20 , as the concentration of microbe increases, a time that the temporal correlation coefficients fall below a reference value decreases. Using this, the concentration of the microbe may be analyzed through inclination values of a graph representing the temporal correlation coefficients. The learner  331  may learn the microbial classification criteria for identifying the concentration of the microbe by analyzing the inclination values of the temporal correlation coefficients. 
       FIG. 21  is a diagram showing a standard deviation distribution of the light intensity of wave speckles measured over time. 
     Referring to  FIG. 21 , the learner  331  may calculate a standard deviation of the light intensity of speckle patterns using a plurality of learning images measured for each reference time. As germs and microbes present in a sample continuously move, constructive interference and destructive interference may change in response to the movement. At this time, as the constructive interference and the destructive interference change, a degree of light intensity may change. The learner  331  may calculate the standard deviation indicating the degree of change of the light intensity, analyze locations of the germs and the microbes in the sample, and learn the distribution of the germs and the microbes. 
     For example, the learner  331  may calculate the standard deviation of the light intensity of the speckle pattern detected in each of the plurality of learning images over time. The standard deviation of the light intensity of the speckle over time may be calculated based on Equation 6 described above. 
     Because constructive and destructive interference change according to movements of germs and microbes, and a value of the standard deviation calculated based on Equation 6 is different, concentrations of germs and microbes may be measured based on this. The learner  331  may learn the classification criteria based on the linear relationship between the magnitude of the standard deviation value of the light intensity of the speckle pattern and the concentrations of germs and microbes. 
     Hereinafter, the case where the learner  331  learns the classification criteria using a CNN will be mainly described. 
     Here, the CNN is a type of multilayer perceptrons designed to use minimal prepocessing. The CNN may include a convolutional layer that performs convolution on input data, and may further include a subsampling layer that performs subsampling on an image to extract a feature map from the corresponding data. Here, the subsampling layer is a layer that increases the contrast between neighboring data and reduces an amount of data to be processed and may use max pooling, average pooling, etc. 
       FIG. 22  is a diagram showing a CNN  2510  according to an embodiment of the present disclosure, and  FIGS. 23 and 24  are diagrams for describing a convolution operation of  FIG. 22 . 
     Referring to  FIGS. 22 to 24 , the CNN  2510  according to an embodiment of the present disclosure used by the learner  331  may include a plurality of convolutional layers A 1 . The learner  331  may generate an output by performing the convolution operation between kernels and inputs of the convolution layers. 
     The input of the convolutional layer is data employed as an input of the corresponding convolutional layer and includes at least one input feature map corresponding to initial input data or an output generated by a previous layer. For example, an input of the convolutional layer  1  A 113  shown in  FIG. 8  may be a plurality of images  2501  which are initial inputs of the CNN  2510 , and an input of a convolutional layer  2  A 123  may be an output  2511  of the convolutional layer  1  A 113 . 
     The input  2501  of the CNN  2510  is the plurality of C images  2501  received by the receiver  32 , and a temporal correlation may be established between images that are input feature maps. Each image, that is, each input feature map may have a plurality of pixels including previously set width W and height H. Because there are C input feature maps, the size of the input  2501  may be expressed as W×H×C. The learner  331  may perform the convolution operation corresponding to the input  2501  by using one kernel corresponding to a convolution layer A 1 . 
     At least one kernel of a convolutional layer A 13  is data employed for the convolution operation corresponding to the corresponding convolutional layer A 1 , and may be defined based on, for example, an input and an output of the corresponding convolutional layer. At least one kernel may be designed for each convolutional layer A 13  constituting the CNN  2510 . At least one kernel corresponding to each convolutional layer may be referred to as a kernel set G 600 . 
     Here, the kernel set G 600  may include kernels corresponding to output channels D. For example, in order to obtain a desired output of the convolutional layer A 13 , the kernel set G 600  of the corresponding convolutional layer may be defined such that an input and a convolution operation of the corresponding convolutional layer are performed. The output of the convolutional layer A 13  is data based on a result of the convolution operation between the input of the corresponding convolutional layer and the kernel set, and may include at least one output feature map and be employed as an input of a next layer. 
     The learner  331  may generate an output  2511  by performing the convolution operation between the kernel set G 600  corresponding to the convolution layer A 13  and the input  2501 . The output  2511  of the convolutional layer A 13  may include output feature maps  25111  corresponding to the D output channels, and the size of each output feature map  25111  may be W×H. Here, the width, height, and number (depth) of the output  2511  are W, H, and D, respectively, and the size of the output  2511  may be expressed as W×H×D. 
     For example, the kernel set G 600  corresponding to the convolutional layer A 1  may include convolutional kernels corresponding to the D output channels. The learner  331  may generate the output feature maps  25111  corresponding to the D output channels based on operation results between the input  2501  and the kernels corresponding to the D output channels. 
     The learner  331  may include the plurality of convolution layers A 13 , and in an embodiment, may include the 4 to 7 convolution layers A 13 . For example, as shown in the figure, the learner  331  may include 5 convolution layers A 113 , A 123 , A 133 , A 143 , and A 153 . Through the plurality of convolution layers A 113 , A 123 , A 133 , A 143 , and A 153 , the learner  331  may increase a learning capacity that may imply a complex non-linear relationship. However, the present disclosure is not limited thereto, and the more convolutional layers A 13  may be used to learn. 
     Meanwhile, each of the convolution layers A 13  may include an activation function. The activation function may be applied with respect to layers of each layer to perform a function that allows respective inputs to have a complex non-linear relationship. The activation function may use a sigmoid function, a tan h function, a rectified linear unit (ReLU), a leaky ReLU, etc., which may convert an input into a normalized output. 
     The learner  331  according to an embodiment of the present disclosure may completely initialize the kernels by using values of −1 to 1 during first learning using the CNN  2510 . In the case of using the activation function that outputs all of data having a negative value as 0, output values including valid information may not be transferred to a next convolution layer, which may reduce learning efficiency. Therefore, in an embodiment of the present disclosure, the learner  331  may add a leaky ReLU layer after the convolutional layer A 13  and output a positive value as it is, but may output input data of a negative value to have a constant inclination. Through this, the learner  331  may prevent the convergence speed degradation and local minimization problems while learning. 
     The input  2501  may be a set of input feature maps to which padding is applied, wherein padding refers to a technique of filling a partial region of an input with a specific value. Specifically, applying padding to the input with the pad size of 1 means an operation of filling an edge of the input feature map with the specific value and zero padding refers to setting the specific value to 0. For example, when zero padding with the pad size of 1 is applied to the size input of X×Y×Z, the input to which padding is applied is data in which the edge is 0 and the size is ((X+1)×(Y+1)×Z and may include (X+1)×(Y+1)×Z input elements. 
     Meanwhile, the learner  331  learns using temporal correlations of a plurality of images in performing the convolution operation with the plurality of images including speckle information as input. At this time, each image may include a plurality of speckles that are grain shape patterns. At this time, the learner  331  may learn the classification criteria based on a temporal correlation of each speckle. In other words, the learner  331  learns the classification criteria using three-dimensional information including information of time other than two-dimensional information of an image. 
     The learner  331  should concentrate on information about one speckle, and in order to accurately obtain three-dimensional information about one speckle, should learn the classification criteria by identifying the one speckle and surrounding speckles. Therefore, the learner  331  may perform the convolution operation using a convolution kernel having a size smaller than that of one speckle. That is, when the size of one speckle corresponds to m pixels, the learner  331  performs the convolution operation using a convolution kernel of a size of n×n smaller than m. In an embodiment, as described above, because the image sensor  3300  is arranged such that at most 5 pixels are located in a speckle grain size, m may be 5, where n may have a value of 1. That is, the learner  331  may perform the convolution operation using a 1×1 convolution kernel. However, the technical idea of the present disclosure is to perform the convolution operation using a kernel having a size smaller than that of a speckle, but the present disclosure is not limited thereto. 
     The kernel set G 600  may include convolution kernels corresponding to the D output channels, and each convolution kernel may include kernel feature maps corresponding to a plurality of image number. Because the size of each kernel feature map is n×n, the kernel set G 600  includes n×n×C×D kernel elements. Here, the size of the convolution kernel is n×n×C, where C may be the number of a plurality of images, that is, the number of image frames. The number of convolution kernels may be equal to the number C of the plurality of images. In this case, the number of convolution kernels may be used for Fourier transformation of the same condition or analysis using Fourier transformation using an output result of each layer. 
     As shown in  FIG. 21 , the learner  331  may perform an operation between a convolution kernel corresponding to a first output channel of the kernel set G 600  and the input  2501  to generate the output feature map  25111  corresponding to the first output channel. In this way, the learner  331  may generate the output feature maps  25111  corresponding to the D output channels by performing operations between the D kernels of the kernel set G 600  and the input  2501  and generate an output  252511  including the generated output feature maps  25111 . 
     For example, the learner  331  may perform an operation between a convolution kernel  600  corresponding to a D-th output channel having the size of n×n×C and the input  501  having the size of W×H×C to generate the output feature map  25111  of the size of W×H, and the generated output feature map  25111  corresponds to the D-th output channel. Specifically, the convolution kernel  600  corresponding to the D-th output channel includes C kernel feature maps, and the size of each kernel feature map is n×n. The learner  331  may slide each kernel feature map having the size of n×n on each input feature map having the size of W×H included in the input  501  by a specific stride to generate the output feature map  25111  that is the operation result between the convolution kernel  2600  correspond to the D-th output channel and the input  2501 . 
     Here, the stride means an interval for sliding the kernel feature map during the convolution operation. As described above, in order to concentrate on the information about one speckle, because the learner  331  needs to learn the classification criteria by identifying the one speckle and the surrounding speckles, the slid s that is the sliding interval may have a value corresponding to the size of the convolution kernel such that each convolution kernel and its corresponding region do not overlap. In other words, when using the convolution kernel of the size n×n, the stride s may have a value of n. For example, in the case of the 1×1 convolution kernel, the stride s may be 1. Through this, the learner  331  may learn the classification criteria based on only the time information of one speckle by non-overlapping one speckle and other surrounding speckles. 
     In an embodiment, the learner  331  may perform the convolution operation to have the same output channel number D as the plurality of image number C in learning the classification criteria using the CNN  2510 . In other words, the kernel set G 600  may include D convolution kernels including C kernel feature maps, where C and D may be the same. 
     Meanwhile, the learner  331  may reduce the size of the output  2515  using a pooling operation after the convolution operation using the convolution layers A 1 . For example, the learner  331  may reduce the size of the output  2515  using subsampling A 2 . For example, the subsampling may be global average pooling which is an operation of setting an average value within a range of a predetermined size as a representative of the range. However, the present disclosure is not limited thereto, and may use max pooling, min pooling, etc. 
     Thereafter, the learner  331  may obtain a final output  2541  by applying a predetermined operation and a weight to the feature maps  2521  extracted through a filter of the subsampling A 23 , using a fully connected layer. For example, the learner  331  may further apply A 33  a leaky reLU to the fully connected layer after performing the subsampling A 23 , and then obtain the final output by applying A 43  a softmax layer to the fully connected layer. Here, the final output  2541  may be microbial classification criteria for identifying a type or a concentration of microbe by the temporal correlation of the speckle. 
     Thereafter, the server  3  may receive an image related to a wave speckle obtained by irradiating a wave to the new collection liquid W from the airborne bacteria measuring device  30 , and the determiner  333  may identify a type or a concentration of bacteria included in the new collection liquid W based on the obtained microbial classification criteria. However, the determiner  333  does not necessarily need to be included in the server  3 , and when the microbial classification criteria learned from the server  3  is provided to the controller  3400  of the airborne bacteria measuring device  30 , the controller  340  may identify the type or the concentration of bacteria included in the new collection liquid W based on the microbial classification criteria, like a function of the determiner  333 . 
       FIG. 25  is a graph comparing predicted microbe information (prediction) obtained by measuring airborne bacteria through machine learning according to an embodiment of the present disclosure and actual microbe information (ground truth). 
     Referring to  FIG. 25 , it may be seen that a matching rate between the predicted microbe information obtained through an airborne bacteria measuring technology according to an embodiment of the present disclosure and the actual microbe information is very high. It may be confirmed through a result of  FIG. 25  that the airborne bacteria measuring device  30  may use microbial classification criteria to identify a type ( B. subtilis, E. coli, P. aeruginosa, S. aureus ) of microbe included in the collection liquid W, etc., as well as identify each concentration. 
     As described above, the airborne bacteria measuring device according to the embodiments of the present disclosure may collect airborne bacteria in a collection liquid, and then detect the presence of microbe in the collection liquid using a wave speckle, thereby detecting the airborne bacteria quickly and accurately without a separate chemical method. In addition, the airborne bacteria measuring device may obtain the classification criteria for classifying types or concentrations of microbes using a change in a temporal correlation of a speckle through machine learning, thereby quickly and accurately identifying a type or a concentration of the airborne bacteria. Through this, it is possible to identify the presence of pathogens in the air within a region, and effectively determine regional prevention information through a network environment. 
       FIG. 26  is a diagram schematically showing an optical detection system  40  according to an embodiment of the present disclosure,  FIG. 27  is a diagram for explaining a process, performed by a first speckle generation unit  4310  of generating a first speckle LS 14 , and  FIG. 28  is a diagram for explaining a process, performed by a second speckle generation unit  4410  of generating a second speckle LS 24 . 
     Referring to  FIG. 26 , the optical detection system  40  according to an embodiment of the present disclosure may include a wave source  4100 , an optical unit  4200 , a first speckle generator  4300 , a sample measurer  4400 , and a controller  4500 . 
     The wave source  4100  may generate a wave L 4 . The wave source  4100  may apply all types of source device capable of generating a wave L, and may be, for example, a laser capable of irradiating light of a specific wavelength band. Although the present disclosure is not limited to a type of a wave source, a case where the wave source is the laser will be described for convenience of description. 
     For example, laser with a good coherence may be used as the wave source  4100  to form speckle in a sample to be measured. In this case, the shorter the spectral bandwidth of the wave source that determines the coherence of the laser wave source, the greater the measurement accuracy. That is, the longer the coherence length, the greater the measurement accuracy. Accordingly, a laser light whose spectral bandwidth of the wave source is less than a predetermined reference bandwidth may be used as the wave source  1200 , and the measurement accuracy may increase as the spectral bandwidth of the wave source is shorter than the reference bandwidth. 
     However, in an actual measurement environment, various environmental variables such as temperature exist, and properties of the wave L 4  generated from the wave source  4100  may change due to minute vibrations or external factors. As an example, a wavelength of the wave L 4  may change by an ambient temperature. The change in the wave L 4  may cause a change in the measurement data output from the sample. In particular, as in the present disclosure, when a change of speckle over time is detected and is used to detect a minute life activity of microbe, it must be sensitive to even a small change in the wave L 4 . 
     The technical idea of the present disclosure is to accurately detect the property change in the wave L 4  due to external environmental factors, to measure only when it is stable using detection results, or to correct measurement data, thereby improving the accuracy of microbe detection. 
     To this end, embodiments of the present disclosure may provide the one wave L 4  generated from the wave source  4100  by changing a path of the wave L 4  to a first path or a second path by using the optical unit  4200  or by splitting the wave L 4  into a first wave L 14  and a second wave L 24 . 
     At this time, the optical detection system  40  merely splits the first wave L 14  and the second wave L 24  by the optical unit  4200  or changes paths but provides the same environmental condition, and thus the properties of the first wave L 14  and the second wave L 24  are the same. The first wave L 14  may be used as an incident wave for generating a reference signal, and the second wave L 24  may be used as an incident wave for generating a measurement signal. 
     The optical unit  4200  may include one or more optical elements to perform a function of transferring the wave L 4  generated by the wave source  4100  to the first path or the second path. In an embodiment, the optical unit  4200  may include an optical path changing means for providing the wave L 4  to the first path and then changing the wave L 4  to the second path. In this case, as the optical path changing means, a generally known micro electromechanical system (MEMS) mirror, a digital micromirror device (DMD) element, or the like may be employed. In another embodiment, the optical unit  4200  may include an optical element that performs a function of splitting into the first wave L 14  and the second wave L 24 . As shown in the drawing, the optical unit  4200  may include a beam splitter that splits the incident wave L 4  into the first wave L 14  and the second wave L 24  to the first path and the second path which are different paths. However, the present disclosure is not limited thereto. 
     In another embodiment, the optical unit  4200  may further include a multiple beam reflector. The multiple beam reflector may split the wave incident from the wave source  4100  to provide the wave to a plurality of wave paths. The multiple beam reflector may reflect waves at front and rear surfaces to provide the parallel and split first wave L 14  and second wave L 24 . At this time, the beam splitter may be disposed on the plurality of wave paths provided from the multiple beam reflector and provide the first wave L 14  and the second wave L 24  to the first speckle generation unit  4310  and the sample measurer  4400 , more specifically, the second speckle generation unit  4410 , respectively. 
     In addition, the optical unit  4200  may further include a mirror for changing the wave path provided from the wave source  4100 . 
     Hereinafter, for convenience of description, the case where the optical unit  4200  splits and provides the wave L 4  into the first wave L 14  and the second wave L 24  will be mainly described. 
     Referring to  FIGS. 26 and 27 , the first speckle generator  4300  may detect the first speckle LS 14  which is a reference signal generated using the first wave L 14 . The first speckle generator  4300  may include a first speckle generation unit  4310  and a first image sensor  4330 . 
     The first speckle generation unit  4310  may be disposed on a path of the first wave L 14 . The first speckle generation unit  4310  may include a static scattering medium  311  to scatter the first wave L 14  when the first wave L 14  is incident and generate the first speckle LS 14 . As shown in  FIG. 27 , the scattering medium  311  included in the first speckle generation unit  4310  may include scattering materials disposed in a spatially uniform position. The scattering materials may be arranged without limitations on the intervals spaced apart from each other or positions, but maintain a static state without moving in an arrangement state. At this time, there is no limitation on a type of the scattering material  311 , for example, titanium oxide (TiO 2 ) may be used as the scattering material. 
     When the first wave L 14  is incident on the first speckle generation unit  4310 , the first wave L 14  may be multiply scattered by the scattering medium  311  maintaining the static state, and some of the waves scattered in a complicated path through multiple scattering may be emitted from the first speckle generation unit  4310 . Waves emitted by passing through various points of the first speckle generation unit  4310  cause constructive interference or destructive interference with each other, and the constructive/destructive interferences of the waves generate a pattern (a speckle) in grain shape. 
     At this time, when the first wave L 14  has a uniform characteristic without a change in the property over time, the first speckle LS 14  generated by the first speckle generation unit  4310  may also form a uniform pattern or pattern by the static scattering medium  311  over time. However, when the property of the wave L 4  generated from the wave source  4100 , that is, the first wave L 14 , changes due to the surrounding environment, the pattern or pattern of the first speckle LS 14  changes. 
     The first image sensor  4330  may be disposed on a path from which the first speckle LS 14  is emitted to detect the first speckle LS 14  in time series order. The first image sensor  4330  may include sensing means corresponding to the type of the wave source  4100 . For example, when a light source of a visible light wavelength band is used, a CCD camera which is an image capturing device may be used. When the first image sensor  4330  is the CCD camera, the first image sensor  4330  may time serially capture the first speckle LS 14  and obtain a plurality of images. 
     Here, each of the plurality of images includes information of first speckles multiple scattered and generated by the scattering medium  311  due to the first wave L 14  incident on the first speckle generation unit  4310 . In other words, the first image sensor  4330  may detect the first speckles generated by the irradiated first wave L 14  multiple scattered in the scattering medium  311  at a preset time. Here, time means any moment in a continuous flow of time, and times may be set in advance at the same time interval, but are not limited thereto, and may be set in advance at any time interval. 
     The first image sensor  4330  may detect a first image at least at a first time and capture a second image at a second time to control the first and second images to the controller  4500 . Meanwhile, the first point and the second point are merely one example selected for convenience of description, and the first image sensor  4330  may capture a plurality of images at a plurality of points more than the first point and the second point. 
     Meanwhile, referring back to  FIGS. 26 and 28 , the sample measurer  4400  may detect a measurement signal generated using the second wave L 24 . Here, the measurement signal may be applicable to any kind of measurement signal that may be generated using the second wave L 24 . In an embodiment, the measurement signal may be a signal having the same intensity of an emitted wave. In another embodiment, the measurement signal may be a signal including speckle information. In other words, the sample measurer  4400  may detect the second speckle LS 24  which is a measurement signal generated using the second wave L 24 . Hereinafter, for convenience of description, a case where the sample measurer  4400  is a second speckle generation unit for detecting the second speckle LS 24  will be mainly described. Same reference numerals are provided to the sample measurer and the second speckle generation unit. 
     The second speckle generation unit  4400  may include the second speckle generation unit  4410  and a second image sensor  4430 . The second speckle generation unit  4410  may be disposed on a path of the second wave L 24 . The second speckle generation unit  4410  may include a sample to be measured to scatter the incident second wave L 24  and generate the second speckle LS 24 . The sample may be any sample for detecting microbes or impurities. For example, the sample may be a sample such as saliva, blood, or tissue collected from an individual to be measured, or may be a sample such as feces, urine, or dead skin discharged to the outside of the individual. Alternatively, the sample may include an organic sample collected from an individual such as food. Meanwhile, the sample may mean the individual to be measured itself. In other words, when the food is an individual and the presence of microbes are measured without damaging the food, the food itself may be a sample. For example, an individual such as meat packaged for sale may be a sample. 
     The second speckle generation unit  4410  may accommodate only the sample described above, or may accommodate the sample by including a material for culturing microbes such as an agar plate. Alternatively, the second speckle generation unit  4410  may accommodate a collection means of a sample together. For example, the collecting means may be prepared using a means by which microbes may move such as a tape, a membrane, or the like. 
     In another embodiment, the second speckle generation unit  4410  may accommodate a sample such as a fluid. At this time, the second speckle generation unit  4410  may be a container for accommodating the fluid, or may be a pipe unit through which the fluid may flow. 
     Meanwhile, the second speckle generation unit  4410  may include a multiple scattering amplification region for amplifying the number of times an incident second wave is multiply scattered in the sample. For example, the multiple scattering amplification region may be formed by including a multiple scattering material in a partial region on which the second wave is incident and a partial region from which the second wave is emitted. For example, the multiple scattering material may include titanium oxide (TiO 2 ), and may be formed by coating a partial region of the second speckle generation unit  4410  on the partial region on or from which the second wave is incident or emitted. The multiple scattering amplification region may reflect at least a part of the second wave emitted by passing through the sample. 
     In another embodiment, the second speckle generation unit  4410  may further include a separate multiple scattering amplifier  401  other than the multiple scattering amplification region which is coated on a surface of the second speckle generation unit  4410  and integrated. The multiple scattering amplifier  401  may be provided on a movement path of the second wave L 24  between the wave source  4100  and the second speckle generation unit  4410  and/or between the second speckle generation unit  4410  and the second image sensor  4430  to amplify the number of times of multiple scattering. The multiple scattering amplifier  401  reflects at least a part of the second wave L 24  emitted from the sample to be incident on the sample again, such that the second wave L 24  may reciprocate a space between the sample and the multiple scattering amplifier  401  at least one time, thereby effectively amplifying the number of times of multiple scattering of the second wave L 24  in the sample. 
     In addition, as another embodiment, the multi-scattering amplification region or the multi-scattering amplifier to perform the above function is not provided only in the second speckle generating unit  4410 , but also provided in the first speckle generating unit  4310  as well. Of course, the same scattering conditions can be given to the first speckle generation and the second speckle generation. 
     Meanwhile, the first image sensor  4430  may be disposed on a path from which the second speckle LS 24  is emitted to detect the second speckle LS 24  in time series order. The second image sensor  4430  may include sensing means corresponding to a type of the wave source  4100 , and should detect speckle using the same second wave L 24  as the first wave L 14 , and thus the second image sensor  4430  may be the same type of sensing means as the first image sensor  4330 . The second image sensor  4430  may be a CCD camera, and may obtain a plurality of images by capturing the second speckle LS 24  in time series order. At this time, a principle for the second image sensor  4430  of obtaining the plurality of images is the same as that of the first image sensor  4330 , and thus redundant descriptions thereof will be omitted for convenience of description. 
     The second image sensor  4430  detects the second speckle LS 24  caused by the second wave L 24 , and the first image sensor  4330  detects the first speckle LS 14  caused by the first wave L 14 . Here, the first wave L 14  and the second wave L 24  are split from the wave L 4  irradiated from the one wave source  4100  and may have the same wave properties when the surrounding environment is the same. Therefore, when a wavelength of the first wave L 14  changes, because a wavelength of the second wave L 24  also changes, the present disclosure may determine a change in the properties of the first wave L 14  and proceed with measurement by utilizing the second wave only in a stable state. In particular, a bacteria detection sensor using the speckle may detect the second speckle LS 24  only in a state where the first wave L 14  is stable, and thus accurate measurement may be possible. 
       FIG. 29  is a diagram for explaining a method, performed by the controller  4500  of the present disclosure, of controlling an operation of the second image sensor  4430  due to the first speckle LS 14 . 
     Referring to  FIG. 29 , the controller  4500  may obtain a temporal correlation of the first speckle LS 14  using the detected first speckle LS 14 , and control the operation of the second image sensor  4430  based on the obtained temporal correlation of the first speckle LS 14 . More specifically, the controller  4500  may determine a change in the property of the first wave L 14  based on the temporal correlation of the first speckle LS 14 , and control the operation of the second image sensor  4430  according to the change in the property of the first wave L 14 . 
     The controller  4500  may obtain the temporal correlation of the first speckle LS 14  by using a plurality of images obtained from the first image sensor  4330 . At this time, a first image obtained at a first time and a second image obtained at a second time may include at least one of speckle pattern information and intensity information of waves. Meanwhile, an embodiment of the present disclosure does not use only the difference between the first image information at the first time and the second image information at the second time but may extend this to use image information of a plurality of laser speckles at a plurality of times. 
     The controller  4500  may calculate a temporal correlation coefficient of the first speckle LS 14  using the plurality of images generated for a plurality of preset times. When the first wave L 14  is stable without a change, because the first speckle LS 14  generated by the static scattering medium  311  included in the first speckle generation unit  4310  has a uniform pattern, the temporal correlation coefficient of the first speckle LS 14  may have a uniform first value. However, when the first wave L 14  is unstable due to a change in the surrounding environment, because the first speckle LS 14  also changes, the temporal correlation coefficient changes to a second value different from the first value. The controller  4500  may determine a change in the property of the first wave L 14  by using the change in the temporal correlation coefficient. 
     In an embodiment, the detected temporal correlation of the first wave L 14  may be calculated using Equation 5 described above. 
     The temporal correlation coefficient may be calculated according to Equation 5, and in an embodiment, the temporal correlation coefficient of the first speckle LS 14  may be expressed in a graph over time as shown in  FIG. 29 . As described above, when the first wave L 14  is stable, for example, as shown in the graph up to a first time t 1 , the temporal correlation coefficient maintains a preset range P 1  to P 2 . Unlike this, when the first wave L 14  is unstable, for example, as shown in the graph of the first time t 1  to a fourth time t 4 , the temporal correlation coefficient may be beyond the preset range. 
     The controller  4500  may operate the second image sensor  4430  to detect the second speckle LS 24  only when the temporal correlation coefficient corresponds to the preset range. In other words, as shown in  FIG. 29 , the controller  4500  may control the second image sensor  4430  not to operate during the first time t 1  to the fourth time t 4  at which the temporal correlation coefficient of the first speckle LS 14  is beyond the preset range P 1  to P 2 . Meanwhile, when the first wave L 14  is in an unstable state, the temporal correlation coefficient may be included in the preset range such as a second time t 2  to a third time t 3  of  FIG. 29 . 
     Even though the temporal correlation coefficient is temporarily included in the preset range, because the first wave L 14  is actually unstable, in this case, the controller  4500  may calculate the temporal correlation coefficient to a ratio at which the temporal correlation coefficient is beyond the preset range within a predetermined time such that the second image sensor  4430  does not operate and determine the change in the property of the first wave L 14 . 
     In another embodiment, the controller  4500  may calculate the temporal correlation coefficient of the first speckle LS 14  and use the temporal correlation coefficient of the first speckle LS 14  to calibrate a detection signal of the second image sensor  4430 . For example, the controller  4500  may calculate the temporal correlation coefficient of the first speckle LS 14  and calibrate the detection signal through an equation formula such as subtraction or division, etc. of the temporal correlation coefficient from the detection signal provided from the second image sensor  4430 . The controller  4500  may detect microbes more accurately by using the calibrated detection signal, that is, the calibrated second speckle LS 24 . 
     The controller  4500  may obtain a temporal correlation of the second speckle LS 24  detected using the second speckle LS 24  detected by the second image sensor  4430 , and estimate the presence or concentration of microbe in a sample based on the obtained temporal correlation of the second speckle. 
     Principle of estimating the presence or the concentration of the microbe based on the temporal correlation of the second speckle LS 24  may be also the same as the principle of determining the change in the property of the first wave L 14  by using the temporal correlation of the first speckle LS 14 . 
     Specifically, a temporal correlation coefficient of the second speckle LS 24  may be calculated according to Equation 3, and in an embodiment, the presence or the concentration of microbe may be estimated through an analysis in which the temporal correlation coefficient falls below a preset reference value. Specifically, it may be estimated that microbe is present from that the temporal correlation coefficient falls below the reference value exceeding a preset error range. Also, as the concentration of microbe increases, a time that the temporal correlation coefficients fall below a reference value decreases. Using this, the concentration of microbe may be estimated through inclination values of a graph representing the temporal correlation coefficient. The reference value may be different according to a type of microbe. 
       FIG. 30  is a diagram schematically showing an optical detection system  40 - 2  of another embodiment. 
     Referring to  FIG. 30 , the optical detection system  40 - 2  may include the wave source  4100 , the first optical unit  4200 , the first speckle generation unit  4310 , the second speckle generation unit  4410 , the first image sensor  4330 , the second image sensor  4430 , and the controller  4500 . 
     In another embodiment, the first speckle generation unit  4310  of the optical detection system  40 - 2  may be integrally formed with the second speckle generation unit  4410 . Specifically, the second speckle generation unit  4410  may be an accommodation container for accommodating a sample to be measured, and the first speckle generation unit  4310  may be provided in one side of the accommodation container. For example, the first speckle generation unit  4310  may be formed in a container of a predetermined shape including a static scattering medium, and may be mounted on one side of the second speckle generation unit  4310 . However, the present disclosure is not limited thereto, and in another embodiment, the first speckle generation unit  4410  may be formed by coating the scattering medium fixed to one side of the second speckle generation unit  4310 . 
     In the optical detection system  40 - 2 , because the first speckle generation unit  4310  and the second speckle generation unit  4410  are integrally formed, the first speckle L 514  measured through the first speckle generation unit  4310  may include information about mechanical vibration of the integrally formed second speckle generation unit  4410 . Therefore, the optical detection system  40 - 2  may remove noise due to the mechanical vibration of the second speckle generation unit  4410  through a reference signal by the first speckle LS 14 . 
       FIG. 31  is a diagram schematically showing an optical detection system  40 - 3  according to another embodiment of the present disclosure. 
     Referring to  FIG. 31 , the optical detection system  40 - 3  according to another embodiment of the present disclosure may include the wave source  4100 , the first optical unit  4200 , the first speckle generation unit  4310 , the second speckle generation unit  4410 , the image sensor  430 , and the controller  4500 . In addition, the optical detection system  40 - 3  according to another embodiment of the present disclosure may include a first shutter  4350  and a second shutter  4450 . Except that the optical detection system  40 - 3  according to another embodiment of the present disclosure controls detection of the second speckle LS 24  using the second shutter  4450 , the remaining components of the optical detection system  40 - 3  according to another embodiment of the present disclosure are the same as those of the optical detection system  40  according to an embodiment, and thus the same reference numerals are used for convenience of description, and redundant descriptions will be omitted. 
     The wave source  4100  may generate the wave L 4 . The wave source  4100  may apply all kinds of source device capable of generating the wave L, and may be, for example, a laser capable of irradiating light of a specific wavelength band. 
     The first optical unit  4200  may include one or more optical elements to perform a function of splitting the wave L 4  generated by the wave source  4100  into the first wave L 14  and the second wave L 24 . In an embodiment, as shown in the drawing, the optical unit  4200  may include a beam splitter that splits the incident wave L 4  into the first wave L 14  and the second wave L 24  to the first path and the second path which are different paths. 
     A path of the first wave L 14  provided from the first optical unit  4200  may be changed to the first speckle generation unit  4310  through a first mirror  4320 . In addition, a path of the second wave L 24  provided from the first optical unit  4200  may be changed to the second speckle generation unit  4410  through a second mirror  4420 . However, the present disclosure is not limited thereto and may use any means capable of changing a light path. 
     The first speckle generation unit  4310  may be disposed on the path of the first wave L 14 . The first speckle generation unit  4310  may include a static scattering medium  311  to scatter the first wave L 14  when the first wave L 14  is incident and generate the first speckle LS 14 . 
     The second speckle generation unit  4410  may be disposed on the path of the second wave L 24 . The second speckle generation unit  4410  may include a sample to be measured to scatter the incident second wave L 24  and generate the second speckle LS 24 . 
     The image sensor  430  may detect the first speckle LS 14  generated from the first speckle generation unit  4310  or the second speckle LS 24  generated from the second speckle generation unit  4410  in time series order. The image sensor  430  may be provided in an independently driven component like the optical detection system  40  according to an embodiment, but the first speckle LS 14  or the second speckle LS 24  may be detected by using one. To this end, the optical detection system  40 - 2  according to another embodiment, as shown in  FIG. 31 , may further include a second optical unit  4210  that changes paths of the first speckle LS 14  and the second speckle LS 24  and provide the first speckle LS 14  and the second speckle LS 24  to the image sensor  430 . 
     Meanwhile, the second shutter  4450  may be disposed between the first optical unit  4200  and the second speckle generation unit  4410  and may operate under the control of the controller  4500 . 
     The controller  4500  may obtain a temporal correlation of the first speckle LS 14  by using the first speckle LS 14  detected by the image sensor  430  and control an operation of the second shutter  4450  based on the obtained temporal correlation of the first speckle LS 14 . Specifically, the controller  4500  may calculate a temporal correlation coefficient of the first speckle LS 14  and open the second shutter  4450  such that the second speckle LS 24  is detected only when the temporal correlation coefficient corresponds to a preset range. That is, the controller  4500  may detect the second speckle LS 24  by opening the second shutter  4450  only when it is determined that the first wave L 14  is stable. 
     In this case, the optical detection system  40 - 2  may further include the first shutter  4350  disposed between the first optical unit  4200  and the first speckle generation unit  4310 . Because the optical detection system  40 - 2  according to another embodiment detects the first speckle LS 14  or the second speckle LS 24  using the one image sensor  430 , the controller  4500  may close the first shutter  4350  such that the first speckle L 514  is not detected while the image sensor  430  detects the second speckle LS 24 . 
     The controller  4500  may calculate the temporal correlation coefficient of the first speckle LS 14 , use the same to open the second shutter  4450 , detect the second speckle LS 24  for a predetermined time, and then periodically monitor a change in the first wave L 14  by closing the second shutter  4450  again and opening the first shutter  4350 . 
       FIGS. 32A and 32B  are diagrams for explaining a method of determining the presence of live bacteria in a measurement sample using an optical detection system according to embodiments of the present disclosure. 
     In the optical detection system according to an embodiment of the present disclosure, a control group sample may be placed in a first speckle generation unit  4310 ′ and a measurement group sample may be placed in a second speckle generation unit  4410 ′ to derive the presence of live bacteria in a sample or a ratio of live and dead bacteria by using detected speckle information. 
     Specifically, the first speckle generation unit  4310 ′ may include the control group sample. Here, the control group sample may be a sample prepared by injecting a sample to be measured into phosphate buffered saline (PBS). The control group sample may include microbes having a first concentration, and is injected into the PBS, and thus both live and dead bacteria in microbes do not grow over time. 
     The second speckle generation unit  4410 ′ may include the measurement group sample and a medium. Here, the medium may include a culture material for culturing microbes, and the culture material may include a material corresponding to a type of microbe to be identified and capable of effectively culturing the microbe. 
     The medium including the culture material used for culturing should suitably meet the requirements of a specific microbe. Various microbe culture media are described, for example, in “Manual of Methods for General Bacteriology” by the American Society for Bacteriology, Washington D.C., USA, 1981.) These media include various carbon sources, nitrogen sources and trace element components. Carbon sources may include carbohydrates such as glucose, lactose, sucrose, fructose, maltose, starch and fiber; fats such as soybean oil, sunflower oil, castor oil and coconut oil; fatty acids such as palmitic acid, stearic acid and linoleic acid; alcohols such as glycerol and ethanol and organic acids such as acetic acid, and these carbon sources may be used alone or in combination, but are not limited thereto. Nitrogen sources may include organic nitrogen sources and urea, such as peptone, yeast extract, gravy, malt extract, corn steep liquor (CSL), and bean flour, and inorganic nitrogen sources such as ammonium sulfate, ammonium chloride, ammonium phosphate, ammonium carbonate, and ammonium nitrate, and these nitrogen sources may be used alone or in combination, but are not limited thereto. The medium may further include potassium dihydrogen phosphate, dipotassium hydrogen phosphate, and corresponding sodium-containing salts as phosphoric acid sources, but is not limited thereto. The medium may also include metals such as magnesium sulfate or iron sulfate, and amino acids, vitamins and suitable precursors may be added. 
     In an embodiment, the measurement group sample may be the same sample as the control group sample, and may be a sample having the same concentration as the control group sample. At this time, because the measurement group sample is injected to the medium including the culture material, population of live bacteria may increase due to the culture material over time. In other words, as time passes, because the control group sample is injected into the PBS, the population of live and dead bacteria remains constant, whereas the measurement group sample is injected into the medium and the population of live bacteria increases, and thus the concentration of the measurement group sample is higher than the concentration of the control group sample. 
     The controller  4500  may use the first speckle LS 14  and the second speckle LS 24  detected from the first speckle generation unit  4310 ′ and the second speckle generation unit  4410 ′ to estimate a first concentration of the control group sample and a second concentration of the measurement group sample, and determine the presence of live bacteria in the measurement group sample using the first concentration and the second concentration. Specifically, the controller  4500  may obtain a temporal correlation of the first speckle LS 14  using the detected first speckle L 514 , and then estimate the first correlation of the control group sample by using the temporal correlation of the first speckle. In addition, the controller  4500  may obtain a temporal correlation of the second speckle LS 24  using the detected second speckle LS 24 , and then estimate the second correlation of the measurement group sample by using the temporal correlation of the second speckle. The controller  4500  may compare the estimated first concentration and second concentration to determine the presence of live bacteria in the measurement group sample. 
     On the other hand, in another embodiment, the measurement group sample may be a sample diluted m times the control group sample. In other words, the measurement group sample may have a concentration of 1/m of the control group sample when the measurement group sample is initially injected. As shown in FIG.  32 A, the control group sample is included in the PBS, even if a certain time passes, the population of live bacteria b and dead bacteria a of the control group sample does not change. However, as shown in  FIG. 32B , in the measurement group sample included in the medium, if a certain time passes, the population of the dead bacteria a of the measurement group sample does not change, but the population of the live bacteria b increases. 
     The controller  4500  may estimate the first concentration of the control group sample using the continuously detected first speckle L 514 , and estimates the second concentration of the measurement group sample using the detected second speckle LS 24 , and obtain a growth time t at which the second concentration is equal to the first concentration. The controller  4500  may derive the ratio of the live bacteria b and the dead bacteria a in the measurement group sample using the growth time t. 
     In other words, when the live bacteria b and the dead bacteria a are present in the control group sample at the first concentration as shown in  FIG. 32A , the live bacteria b and the dead bacteria a are present at a concentration of 1/m in the measurement group sample obtained by diluting this by m times, and then may be expressed as shown in Equation 7 below after the growth time t. 
     
       
         
           
             
               
                 
                   
                     a 
                     - 
                     
                       
                         ( 
                         
                           1 
                           - 
                           
                             α 
                             ⁢ 
                             
                                 
                             
                             ⁢ 
                             t 
                           
                         
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                       ⁢ 
                       b 
                     
                   
                   m 
                 
               
               
                 
                   [ 
                   
                     Equation 
                     ⁢ 
                     
                         
                     
                     ⁢ 
                     7 
                   
                   ] 
                 
               
             
           
         
       
     
     Here, α denotes a growth rate of the corresponding microbe and may be a previously known value. 
     The controller  4500  may obtain the growth time t at which the first concentration of the control group sample and the second concentration of the measurement group sample are equal to each other. Thus, a ratio b/a of the live bacteria b and the dead bacteria a may be derived through a process of Equation 8 below. 
     
       
         
           
             
               
                 
                   
                     
                       a 
                       - 
                       b 
                     
                     = 
                     
                       
                         a 
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                             ( 
                             
                               a 
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                                 α 
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                                 ⁢ 
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                           ⁢ 
                           b 
                         
                       
                       m 
                     
                   
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                   ⁢ 
                   
                     
                       b 
                       a 
                     
                     = 
                     
                       
                         m 
                         - 
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                         ( 
                         
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                   [ 
                   
                     Equation 
                     ⁢ 
                     
                         
                     
                     ⁢ 
                     8 
                   
                   ] 
                 
               
             
           
         
       
     
     As described above, the optical measuring device according to the embodiments of the present disclosure may split a wave generated from a wave source, irradiate a split first wave to a static scattering medium to generate a first speckle that is a reference signal, and then calculate a temporal correlation of the first speckle, thereby accurately determining a change in properties of the first wave. By using this, the optical measuring device may check and calibrate noise caused by the surrounding environment, thereby more accurately detecting microbe in a sample to be measured. In addition, the optical measuring device has the advantage of deriving the presence of live bacteria or a ratio of live bacteria and dead bacteria in a sample by comparing the concentration of a control group sample and a measurement group sample. 
     The embodiments have been described above. It will be understood by those of ordinary skill in the art that various changes in form and details may be made therein without departing from the spirit and scope of the present disclosure as defined by the appended claims. Therefore, it should be understood that the embodiments are to be considered in an illustrative rather than a restrictive sense. The scope of the present disclosure is set forth in the appended claims rather than the foregoing description and should be interpreted as including all differences within the equivalent range thereto. 
     INDUSTRIAL APPLICABILITY 
     According to an embodiment of the present disclosure, an optical detection system using a chaotic wave sensor is provided. In addition, embodiments of the present disclosure may be applied to an industrially used impurity or microbe detection device.