WO2020026328A1 - Information processing device, control method, and program - Google Patents

Abstract

This information processing device (2000) acquires feature values for a subject gas that associate a set of characteristic constants and a set of contribution values. The information processing device (2000) specifies smell information indicating feature values similar to the feature values of the subject gas and specifies, as a smell label for the subject gas, a smell label indicated by the specified smell information. The smell information associates smell labels with the feature values of gasses producing the smells corresponding to the smell labels. The gas feature values for a given gas indicate the amount by which each of a plurality of feature constants contributes to time-series data of detection values obtained from a sensor that has sensed that gas. The sensor detection values vary according to the adhesion and detachment of molecules included in the gas. The feature constants are time constants or speed constants relating to the amount of variation over time in the amount of molecules adhered to the sensor.

Description

Information processing apparatus, control method, and program

The present invention relates to the analysis of gas characteristics.

技術 Technology has been developed to obtain information about gas by measuring gas with a sensor. Patent Literature 1 discloses a technique for determining the type of a sample gas using a signal (time-series data of a detection value) obtained by measuring the sample gas with a nanomechanical sensor. Specifically, the diffusion time constant of the sample gas with respect to the receptor of the sensor is determined by the combination of the type of the receptor and the type of the sample gas, and therefore, based on the diffusion time constant obtained from the signal and the type of the receptor. It is disclosed that the type of the sample gas can be determined.

JP 2017-156254 A

Patent Document 1 assumes that the sample gas contains only one type of molecule, and does not assume that a sample gas in which a plurality of types of molecules are mixed is handled. The present invention has been made in view of the above problems, and has as its object to provide a technique for specifying the type or component of a gas in which a plurality of types of molecules are mixed.

A first information processing apparatus according to the present invention includes: 1) a feature amount acquiring unit for acquiring a feature amount of a target gas; and 2) a odor information in which a label of an odor is associated with a feature amount of a gas generating the odor. And a label specifying unit that specifies odor information similar to the characteristic amount of the target gas and specifies the odor label indicated by the specified odor information as the odor label of the target gas.
The characteristic amount of the gas indicates the magnitude of each of the plurality of characteristic constants with respect to the time-series data of the detection value obtained from the sensor that sensed the gas. The detection value of the sensor changes according to the attachment and detachment of molecules contained in the gas. The characteristic constant is a time constant or a rate constant relating to the magnitude of a temporal change in the amount of molecules attached to the sensor.

A second information processing apparatus according to the present invention includes: 1) a feature amount acquisition unit for acquiring a feature amount of a target gas; and 2) a unit in which an identifier of a unit component is associated with a feature amount of a gas including only the unit component. A component specifying unit that specifies one or more unit components contained in the target gas using the component information and the characteristic amount of the target gas.
The characteristic amount of the gas indicates the magnitude of each of the plurality of characteristic constants with respect to the time-series data of the detection value obtained from the sensor that sensed the gas. The detection value of the sensor changes according to the attachment and detachment of molecules contained in the gas. The characteristic constant is a time constant or a rate constant relating to the magnitude of a temporal change in the amount of molecules attached to the sensor.

The first control method of the present invention is executed by a computer. The control method includes: 1) a characteristic amount obtaining step of obtaining a characteristic amount of the target gas; and 2) a characteristic of the target gas from the odor information in which the label of the odor is associated with the characteristic amount of the gas generating the odor. A label specifying step of specifying odor information similar to the amount and specifying a odor label indicated by the specified odor information as a odor label of the target gas.
The characteristic amount of the gas indicates the magnitude of each of the plurality of characteristic constants with respect to the time-series data of the detection value obtained from the sensor that sensed the gas. The detection value of the sensor changes according to the attachment and detachment of molecules contained in the gas. The characteristic constant is a time constant or a rate constant relating to the magnitude of a temporal change in the amount of molecules attached to the sensor.

The second control method of the present invention is executed by a computer. The control method includes: 1) a feature amount obtaining step of obtaining a feature amount of a target gas; 2) unit component information in which an identifier of a unit component is associated with a feature amount of a gas including only the unit component; A component specifying step of specifying one or more unit components contained in the target gas using the characteristic amount of the target gas.
The characteristic amount of the gas indicates the magnitude of each of the plurality of characteristic constants with respect to the time-series data of the detection value obtained from the sensor that sensed the gas. The detection value of the sensor changes according to the attachment and detachment of molecules contained in the gas. The characteristic constant is a time constant or a rate constant relating to the magnitude of a temporal change in the amount of molecules attached to the sensor.

プ ロ グ ラ ム The program of the present invention causes a computer to execute each step of the control method of the present invention.

According to the present invention, there is provided a technique for specifying the type or component of a gas in which a plurality of types of molecules are mixed.

The above and other objects, features and advantages will become more apparent from the preferred embodiments described below and the accompanying drawings.
FIG. 2 is a diagram illustrating an outline of the information processing apparatus according to the first embodiment. FIG. 3 is a diagram illustrating a sensor for obtaining a characteristic amount of gas handled by the information processing apparatus. FIG. 2 is a diagram illustrating a functional configuration of the information processing apparatus according to the first embodiment. FIG. 2 is a diagram illustrating a computer for realizing an information processing device. 6 is a flowchart illustrating a flow of a process executed by the information processing apparatus according to the first embodiment. It is a figure which illustrates odor information in a table format. It is a figure which represents conversion of a feature-value notionally. It is a figure which displays the characteristic amount of the target gas and the characteristic amount which odor information shows by a graph. FIG. 9 is a diagram illustrating an outline of an information processing apparatus according to a second embodiment. FIG. 9 is a diagram illustrating a functional configuration of an information processing apparatus according to a second embodiment. 13 is a flowchart illustrating a flow of a process executed by the information processing apparatus according to the second embodiment. It is a figure which illustrates unit component information about a single kind of molecule in a table form. It is a figure showing the component of target gas with a graph.

Hereinafter, embodiments of the present invention will be described with reference to the drawings. In all the drawings, the same components are denoted by the same reference numerals, and description thereof will not be repeated. In addition, unless otherwise specified, in each block diagram, each block represents a configuration of a functional unit, not a configuration of a hardware unit.

[Embodiment 1]
<Summary of the Invention and Theoretical Background>
FIG. 1 is a diagram illustrating an outline of an information processing apparatus 2000 according to the first embodiment. The information processing apparatus 2000 according to the first embodiment specifies a label (hereinafter, an odor label) indicating the odor of the target gas based on the feature amount of the target gas. For example, the odor label indicates the name of the substance that generates the odor. Specifically, when the substance that generates the target gas is apple (that is, when the target gas is a gas indicating the smell of apple), the smell label “apple” is specified. The substance generating the smell is not limited to foods such as apples, but may be any substance such as a machine, a building material, a medicine, mold, burnt food, or garbage.

In addition, for example, the smell label may represent an abstract concept such as a place or a situation where the smell is smelled. For example, odor labels such as "Cafe Smell", "Pool Smell", "Blue Smell Smell", "Smell like Closet", "Sweet Smell", "Smell Smell", or "Smell on a Rainy Day" Conceivable.

た め In order to realize the identification of such an odor label, information that associates the odor label with the characteristic amount of the gas corresponding to the odor label is prepared in advance. This information is called odor information.

The information processing apparatus 2000 specifies a feature amount similar to the feature amount of the target gas from the feature amounts indicated in the odor information, and sets the odor label associated with the specified feature amount to the odor label of the target gas. To be specified.

(4) The information processing device 2000 handles a feature newly found by the present inventor as a gas feature. Hereinafter, the characteristic amount of the gas handled by the information processing apparatus 2000 will be described.

FIG. 2 is a diagram exemplifying the sensor 10 for obtaining the characteristic amount of gas handled by the information processing apparatus 2000. The sensor 10 has a receptor to which a molecule is attached, and a detection value changes according to attachment and detachment of the molecule at the receptor. The time series data of the detection values output from the sensor 10 is referred to as time series data 14. Here, the time-series data 14 is also denoted as {Y}, and the detected value at the time {t} is denoted as {y (t)}, as necessary. Y is a vector in which y (t) is enumerated.

For example, the sensor 10 is a membrane-type surface stress (MSS) sensor. The MSS sensor has, as a receptor, a functional film to which a molecule adheres, and the stress generated in a support member of the functional film changes due to the attachment and detachment of the molecule to and from the functional film. The MSS sensor outputs a detection value based on the change in the stress. In addition, the sensor 10 is not limited to the MSS 、 sensor, and the physical quantity related to the viscoelasticity and dynamic characteristics (mass, moment of inertia, etc.) of the members of the sensor 10 that occur in response to the attachment and detachment of the molecule to and from the receptor. Any sensor that outputs a detection value based on the change may be used, and various types of sensors such as a cantilever type, a film type, an optical type, a piezo, and a vibration response can be employed.

Here, for explanation, the sensing by the sensor 10 is modeled as follows.
(1) The sensor 10 is exposed to a gas containing K kinds of molecules.
(2) The concentration of each molecule k contained in the gas is constant ρk.
(3) The sensor 10 can adsorb a total of N molecules.
(4) The number of molecules k attached to the sensor 10 at time t is nk (t).

The time change of the number nk (t) of the molecules k attached to the sensor 10 can be formulated as follows.

The first and second terms on the right-hand side of the equation (1) are the increasing amount of the molecule {k} per unit time (the number of molecules {k} newly attached to the sensor 10) and the decreasing amount (the molecule {k} detached from the sensor 10). Number). Αk and βk are a rate constant representing the rate at which the molecule {k} adheres to the sensor 10 and a rate constant representing the rate at which the molecule {k} separates from the sensor 10, respectively.

Here, since the concentration ρk is constant, the number nk (t) of the numerator k at time t can be formulated from the above equation (1) as follows.

Assuming that no molecules are attached to the sensor 10 at time t0 (initial state), nk (t) is expressed as follows.

検 出 The detection value of the sensor 10 is determined by the stress applied to the sensor 10 by the molecules contained in the gas. Then, it is considered that the stress acting on the sensor 10 by a plurality of molecules can be represented by a linear sum of the stress acting on each molecule. However, it is considered that the stress generated by the molecule differs depending on the type of the molecule. That is, it can be said that the contribution of the molecule to the detection value of the sensor 10 differs depending on the type of the molecule.

Then, the detection value y (t) of the sensor 10 can be formulated as follows.

Here, both γk and ξk represent the contribution of the numerator k to the detection value of the sensor 10. The purge gas is a gas used when removing the gas to be measured from the sensor 10.

Here, if the time-series data 14 obtained from the sensor 10 that sensed the gas can be decomposed as in the above equation (4), the types of molecules contained in the gas and the ratio of each type of molecule contained in the gas Can be grasped. That is, by the decomposition shown in Expression (4), data representing the characteristics of the gas (that is, the characteristic amount of the gas) is obtained.

More specifically, the information processing apparatus 2000 handles a feature amount obtained by decomposing the time-series data 14 as shown in the following equation (5).

{Where, θi} is a constant called a feature constant. {I} is a contribution value representing the contribution of the characteristic constant θi} to the detection value of the sensor 10.

As the characteristic constant θ, the above-mentioned velocity constant β or a time constant τ which is the reciprocal of the velocity constant can be adopted. For each case where β and τ are used as θ, equation (5) can be expressed as follows.

The feature quantity of gas corresponds to the set of feature constants Θ = {θ1, 2θ2, ..., mθm} obtained in this way and the set of contribution values Ξ = {{1, ξ2, ..., ξm} This is the attached information. The association between the set of feature constants 寄 与 and the set of contribution values Ξ is represented, for example, by m feature matrix {F} having two rows and two columns (m is the number of each of the feature constant and the contribution value). For example, this matrix {F} has a vector Θ = (θ1,..., Θm) representing a set of feature constants in the first column, and a vector Ξ = (ξ1, ..., ξm) representing a set of contribution values. ) In the second column. That is, F = ({T, {T)}.

In the case where the set of characteristic constants is common to each gas, the vector representing the set of characteristic constants may be omitted in the characteristic amount of the gas. In this case, the characteristic amount of the gas is represented by a set of contribution values.

(4) The information processing device 2000 acquires a feature amount (a set of feature constants may be omitted) that associates a set of feature constants with a set of contribution values for the target gas. The feature quantity indicated by the odor information is obtained by associating a set of feature constants with a set of contribution values for time-series data obtained by sensing the gas specified by the odor label indicated by the odor information with the sensor 10. Information. The information processing apparatus 2000 compares such characteristic amounts with each other to specify odor information indicating a characteristic amount similar to the characteristic amount of the target gas. Then, the information processing device 2000 specifies the odor label indicated by the specified odor information as the odor label of the target gas.

<Effects>
The information processing apparatus 2000 according to the present embodiment specifies the odor label of the target gas using the feature amount in which the feature constant vector and the contribution vector obtained for the time-series data of the detected gas value are associated with each other. As described above, since this characteristic amount changes depending on the molecules contained in the gas and the mixing ratio thereof, the gas can be distinguished with high accuracy. Therefore, by using such a characteristic amount, according to the information processing apparatus 2000 of the present embodiment, the odor label of the target gas can be accurately specified.

The above description with reference to FIG. 1 is an example for facilitating understanding of the information processing device 2000, and does not limit the functions of the information processing device 2000. Hereinafter, the information processing apparatus 2000 of the present embodiment will be described in more detail.

<Example of functional configuration>
FIG. 3 is a diagram illustrating a functional configuration of the information processing apparatus 2000 according to the first embodiment. The information processing apparatus 2000 according to the first embodiment includes a feature amount acquiring unit 2020 and a label specifying unit 2040. The feature amount acquisition unit 2020 acquires the feature amount of the target gas. The label specifying unit 2040 extracts, from the plurality of pieces of odor information, odor information indicating a characteristic amount similar to the characteristic amount of the target gas. Further, the label specifying unit 2040 specifies the odor label indicated in the extracted odor information as the odor label of the target gas.

<Hardware configuration of information processing device 2000>
Each functional component of the information processing apparatus 2000 may be implemented by hardware (eg, a hard-wired electronic circuit or the like) that implements each functional component, or a combination of hardware and software (eg: Electronic circuit and a program for controlling the same). Hereinafter, a case where each functional component of the information processing apparatus 2000 is realized by a combination of hardware and software will be further described.

FIG. 4 is a diagram illustrating a computer 1000 for realizing the information processing device 2000. The computer 1000 is an arbitrary computer. For example, the computer 1000 is a stationary computer such as a personal computer (PC) or a server machine. In addition, for example, the computer 1000 is a portable computer such as a smartphone or a tablet terminal. The computer 1000 may be a dedicated computer designed to realize the information processing device 2000, or may be a general-purpose computer.

The computer 1000 has a bus 1020, a processor 1040, a memory 1060, a storage device 1080, an input / output interface 1100, and a network interface 1120. The bus 1020 is a data transmission path through which the processor 1040, the memory 1060, the storage device 1080, the input / output interface 1100, and the network interface 1120 mutually transmit and receive data. However, a method for connecting the processors 1040 and the like to each other is not limited to a bus connection.

The processor 1040 is various processors such as a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), and an FPGA (Field-Programmable Gate Array). The memory 1060 is a main storage device realized using a RAM (Random Access Memory) or the like. The storage device 1080 is an auxiliary storage device realized using a hard disk, an SSD (Solid State Drive), a memory card, or a ROM (Read Only Memory).

The input / output interface 1100 is an interface for connecting the computer 1000 and an input / output device. For example, an input device such as a keyboard and an output device such as a display device are connected to the input / output interface 1100.

The network interface 1120 is an interface for connecting the computer 1000 to a communication network. The communication network is, for example, a LAN (Local Area Network) or a WAN (Wide Area Network). The method by which the network interface 1120 connects to the communication network may be a wireless connection or a wired connection.

The storage device 1080 stores a program module that implements each functional component of the information processing apparatus 2000. The processor 1040 realizes a function corresponding to each program module by reading out each of these program modules into the memory 1060 and executing them.

<Process flow>
FIG. 5 is a flowchart illustrating a flow of a process executed by the information processing apparatus 2000 according to the first embodiment. The characteristic amount acquisition unit 2020 acquires the characteristic amount of the target gas (S102). The label specifying unit 2040 extracts odor information indicating a characteristic amount similar to the characteristic amount of the target gas from the plurality of odor information (S104). The label specifying unit 2040 specifies the odor label indicated by the extracted odor information as the odor label of the target gas (S106).

<Acquisition of characteristic amount of target gas: S102>
The feature amount acquisition unit 2020 acquires the feature amount of the target gas. For example, the characteristic amount acquiring unit 2020 acquires the characteristic amount of the target gas by accessing a storage device in which the characteristic amount of the target gas is stored. This storage device may be provided inside the information processing device 2000 or may be provided outside the information processing device 2000. In addition, for example, the information processing apparatus 2000 may acquire the characteristic amount of the target gas by receiving the characteristic amount of the target gas transmitted from another device. The “other device” is, for example, a device that calculates the feature amount of the target gas using the time-series data 14 obtained from the sensor 10 for the target gas.

<About odor information>
FIG. 6 is a diagram illustrating the odor information in a table format. The table in FIG. 6 is called a table 200. The table 200 has two columns of an odor label 202 and a feature 204. In each record of the table 200, the odor label indicated by the odor label 202 is associated with the characteristic amount (in this example, the characteristic matrix F) indicated by the characteristic amount 204. Note that it is assumed that the odor information is stored in advance in a storage device provided inside or outside the information processing device 2000.

<Extraction of odor information: S104>
The label specifying unit 2040 extracts odor information indicating a characteristic amount similar to the characteristic amount of the target gas from the plurality of odor information (S104). For example, the label specifying unit 2040 extracts odor information indicating a feature amount most similar to the feature amount of the target gas. In this case, the odor label of the target gas is uniquely specified.

The odor information extracted by the label specifying unit 2040 may be plural. For example, the label specifying unit 2040 extracts one or more pieces of odor information indicating a characteristic amount whose similarity to the characteristic amount of the target gas is equal to or greater than a threshold. In this case, one or more odor labels having a high probability of being a label indicating the odor of the target gas are specified. That is, one or more candidates for the odor label of the target gas are specified.

Note that the label specifying unit 2040 outputs that there is no odor label candidate of the target gas when there is no odor information indicating the characteristic amount whose similarity with the characteristic amount of the target gas is equal to or more than the threshold value in the table 200. You may. In this case, the target gas can be interpreted as a new smell not registered in the table 200.

<< Method of Determining Similarity of Feature Amount >>
The label specifying unit 2040 calculates the similarity of the target gas by comparing the characteristic amount of the target gas with the characteristic amount indicated by the odor information. Hereinafter, a method of calculating the similarity will be exemplified.

<<<< When the set of feature constants is common >>>>
A set of characteristic constants is assumed to be common between the characteristic amount of the target gas and the characteristic amount indicated by the odor information. In this case, each feature can be represented by 表 す = (Ξ1, Ξ2,..., Ξm), which is a vector representation of a set of contribution values. Therefore, the label specifying unit 2040 calculates the distance between the vectors for the characteristic amount of the target gas and the characteristic amount of the odor information, and uses the calculated distance as an index of the similarity between the characteristic amounts. Specifically, the shorter the distance between the feature values, the more similar those feature values are handled.

For example, suppose that odor information indicating a feature amount most similar to the feature amount of the target gas is extracted. In this case, the label specifying unit 2040 extracts the odor information indicating the feature amount having the shortest distance from the feature amount of the target gas.

In addition, for example, it is assumed that one or more pieces of odor information indicating a characteristic amount whose similarity with the characteristic amount of the target gas is equal to or larger than a threshold value are extracted. In this case, a threshold value is set for the distance from the feature amount of the target gas. The label specifying unit 2040 extracts each odor information indicating a feature amount whose distance from the feature amount of the target gas is equal to or less than a threshold value.

<<<< When the set of feature constants is not common >>>>
It is assumed that a set of characteristic constants is not common between the characteristic amount of the target gas and the characteristic amount indicated by the odor information. In this case, for example, the label specifying unit 2040 converts one or both of the characteristic amount of the target gas and the characteristic amount of the odor information such that a set of these characteristic constants is common. Such conversion enables similarity determination using the distance between the feature amounts described above. Therefore, the label specifying unit 2040 performs similarity determination using the distance between the feature amounts using the converted feature amount, thereby extracting odor information indicating a feature amount similar to the feature amount of the target gas.

(4) A method of converting feature values will be described. FIG. 7 is a diagram conceptually showing the conversion of the feature amount. In FIG. 7, the feature quantity before conversion is a set of contribution values Ξa = {{a1, ξa2, ξa3, ξa4, ξa5}} with respect to a set of feature constants Θa = {θa1, θa2, θa3, θa4, θa5}}. It is a correspondence. The label identifying unit 2040 associates this feature amount with a set of contribution values {b = {{b1, {b2, .., {b9}} for a set of feature constants {b = {θb1, {θb2, ..., {θb9}}. It is converted to the attached feature value. At this time, {ai} associated with the feature constant θai in the feature quantity before conversion is associated with θbj that satisfies {θbj ≦ θai <θ_ (bj + 1)} in the feature quantity after conversion. For example, in FIG. 7, to satisfy θb2 ≦ θa1 <θb3b, the contribution value {a1} associated with θa1a in the feature amount before conversion is associated with {θb2} in the feature amount after conversion. That is, {b2 = {a1}.

It is assumed that there are a plurality of θais that satisfy θbj ≦ θai <θ_ (bj + 1). In this case, the sum of the contribution values {ai} associated with the plurality of θai is associated with the converted feature constant θbj. For example, in FIG. 7, both θa3 ° and θa4 ° satisfy θb7 ≦ θi <θb8 °. Therefore, in the feature amount after the conversion, the value of the contribution value {b7} corresponding to θb7} is set to ({a3 + ξa4) ”.

As described above, the conversion of the characteristic amount may be performed for one of the characteristic amount of the target gas and the characteristic amount of the odor information, or may be performed for both of them. In the former case, the label specifying unit 2040 may convert the characteristic amount of the target gas to match the set of characteristic constants of the characteristic amount of the odor information, or may convert the characteristic amount of the target gas into a set of characteristic constants of the target gas. The feature amount of the odor information may be converted so as to match. However, when the set of characteristic constants is not common to a plurality of pieces of odor information, it is preferable to convert the characteristic amount of the odor information to match the set of characteristic constants of the characteristic amount of the target gas. This is because the similarity determination is performed after setting the set of feature constants common to all feature amounts.

{When converting both the characteristic amount of the target gas and the characteristic amount of the odor information, a common set {c} of characteristic constants is prepared in advance. Then, the label specifying unit 2040 converts both the characteristic amount of the target gas and the characteristic amount of the odor information so that the set of characteristic constants becomes {c}.

The method of similarity determination when the set of feature constants is not common is not limited to the method of performing similarity determination after converting feature values as described above. For example, when the contribution values の of the two feature values to be compared are all positive, the label specifying unit 2040 treats the two feature values to be compared as a probability distribution, and determines the similarity of these feature values as KL (Kullback- Leibler) Calculate divergence. KL divergence is an index value indicating the degree of similarity between probability distributions, and becomes smaller as the difference between two probability distributions to be compared is smaller. Therefore, the label specifying unit 2040 treats the smaller the {KL} divergence calculated between the characteristic amount of the target gas and the characteristic amount indicated by the odor information, the more similar these are.

As a method of treating the above-described feature amount as a probability distribution, for example, a kernel method can be used. Specifically, the label specifying unit 2040 calculates KL divergence by treating the feature value F as a probability distribution represented by the following equation.

Here, g is a kernel function, and C is a normalization constant of the probability distribution.

The label specifying unit 2040 may use, for example, Wasserstein metric as the similarity between the two feature amounts to be compared. The Wasserstein metric is a metric that represents the minimum cost of moving one distribution to the other, and the smaller the difference between the two distributions to be compared, the smaller the value. Therefore, the label identifying unit 2040 treats the smaller the Wasserstein metric calculated between the characteristic amount of the target gas and the characteristic amount indicated by the odor information, as the similarity thereof. Note that the Wasserstein metric is applicable even when the contribution value を includes a negative value.

<Output of specific result>
The information processing device 2000 outputs information indicating the odor label of the target gas (hereinafter, output information). For example, the output information is text data representing an odor label of the target gas. In addition, for example, the output information may include odor information indicating the specified odor label. In this case, for example, the output information may indicate the characteristic amount of the target gas and the characteristic amount indicated by the odor information by graphical information such as a graph or a table.

FIG. 8 is a view showing the characteristic amount of the target gas and the characteristic amount indicated by the odor information in a graph. In FIG. 8, the solid line indicates the characteristic amount of the target gas. On the other hand, the dotted line indicates the feature amount indicated by the odor information having the label “smell A”. By looking at this graph, the user of the information processing apparatus 2000 visually grasps the odor label of the target gas and visually determines how similar the characteristic amount of the target gas is to the characteristic amount indicated by the odor information. It can be easily confirmed.

Note that, as described above, when a plurality of odor labels are specified, it is preferable that the information processing apparatus 2000 output these odor labels in order. For example, the information processing apparatus 2000 outputs the odor label in the order of the degree of similarity to the feature amount of the target gas (in order of decreasing distance).

具体 There are various specific methods for outputting the output information. For example, the information processing device 2000 stores the output information in an arbitrary storage device. In addition, for example, the information processing apparatus 2000 causes the display device to display the output information. Alternatively, for example, the information processing device 2000 may transmit the output information to a device other than the information processing device 2000.

[Embodiment 2]
FIG. 9 is a diagram illustrating an outline of an information processing apparatus 2000 according to the second embodiment. The information processing apparatus 2000 according to the second embodiment specifies the component of the target gas based on the feature amount of the target gas. Here, the specification of the component of the target gas includes at least specifying one or more unit components contained in the target gas. Further, the specification of the component of the target gas may include specifying the concentration of each unit component contained in the target gas and specifying the mixing ratio (relative concentration) of each unit component.

The unit component is, for example, a single type of molecule. In this case, the information processing apparatus 2000 estimates one or more types of molecules contained in the target gas and estimates the concentration ratio of a plurality of molecules based on the feature amount of the target gas. Unit components other than a single type of molecule will be described later.

In addition, for example, the unit component is a combination of molecules that generate a specific odor. The specific odor is the odor specified by the odor label described in the first embodiment. For example, as a unit component that produces an apple odor, a combination of molecules that produce an apple odor (that is, a combination of molecules contained in gas produced from an apple) can be defined.

情報 In order to realize the estimation of the component of the target gas, information indicating the feature amount of each unit component is prepared in advance. This information is called unit component information. The unit component information is information in which an identifier of the unit component is associated with a feature amount of the unit component. The feature amount of a unit component is a feature amount calculated for time-series data obtained by sensing a gas containing only the unit component with the sensor 10.

Here, it is assumed that a set of characteristic constants is common to the characteristic amount of the target gas and the characteristic amount of each unit component. In this case, if the characteristic amount of the target gas and the characteristic amount of each unit component are represented by a vector expression, it is considered that the characteristic amount of the target gas can be represented by a linear sum of the characteristic amounts of the unit components included in the target gas. . For example, when the target gas includes the unit components 1 to k, it is considered that the characteristic amount of the target gas can be expressed as follows.

Here, Ξi is the feature vector of the unit component i, and ai is the concentration of the unit component i in the target gas. When the target gas is composed of only one type of unit component, k = 1 and therefore, Ξg = Ξ1.

Thus, the information processing apparatus 2000 uses the unit component information to decompose the feature vector Ξg of the target gas into a linear sum of the feature vectors Ξi of one or more unit components. By doing so, the information processing apparatus 2000 specifies one or more unit components contained in the target gas. Here, various existing methods can be used as a method of decomposing a certain vector into a linear sum of known vectors (here, each feature amount vector indicated in unit component information). . For example, a least-squares method with a non-negative constraint represented by the following objective function can be used.

When specifying the concentration of the unit component, a vector {A = (a1, {a2, ..., ak)} obtained by the decomposition into the linear sum described above can be obtained as information representing the concentration of each unit component. . The mixing ratio of the unit components can be represented by the ratio of these concentrations. Here, the concentration of the unit component is a value represented by (concentration of gas in air) × (concentration ratio of unit component in gas). That is, it means the relative concentration of the unit component with respect to the concentration of the gas in the air. In addition, the concentration of the unit component as used herein can be regarded as a ratio of the partial pressure of the unit component to the air pressure.

Here, when it is not necessary to specify the concentration of the unit component and it is sufficient to specify the mixture ratio, each feature amount vector may be normalized in advance. In this case, the characteristic amount Ξg of the target gas is decomposed as follows.

If the set of feature constants is not the same between the feature amount of the target gas and the feature amount of the unit component, the set of feature constants is made to match by the above-described method, and then the feature amount of the target gas is changed to the unit component. Decompose into linear sum of features.

<Effects>
The information processing apparatus 2000 according to the present embodiment specifies one or more unit components included in the target gas using a feature amount determined based on the contribution of each feature constant to the time-series data of the detected gas value. As described above, since this characteristic amount is a characteristic amount that changes depending on the molecules contained in the gas and the mixing ratio thereof, the characteristic amount is compared with the characteristic amount of each unit component to obtain the unit component contained in the target gas. And its mixing ratio can be specified with high accuracy.

<Example of functional configuration>
FIG. 10 is a diagram illustrating a functional configuration of the information processing apparatus 2000 according to the second embodiment. The information processing apparatus 2000 according to the second embodiment includes a feature amount acquisition unit 2020 and a component identification unit 2060. The feature amount acquisition unit 2020 is as described in the first embodiment. The component specifying unit 2060 specifies one or more unit components included in the target gas by using the unit component information and the characteristic amount of the target gas.

<Example of hardware configuration>
The hardware configuration of a computer that implements the information processing apparatus 2000 according to the second embodiment is represented by, for example, FIG. 4 as in the first embodiment. However, the storage device 1080 of the computer 1000 that implements the information processing apparatus 2000 of the present embodiment stores a program module that implements the functions of the information processing apparatus 2000 of the present embodiment.

<Process flow>
FIG. 11 is a flowchart illustrating a flow of a process executed by the information processing apparatus 2000 according to the second embodiment. The feature amount acquisition unit 2020 acquires the feature amount vector Ξg of the target gas (S402). The component specifying unit 2060 specifies one or more unit components contained in the target gas using the acquired feature amount vector Ξg and the unit component information (S404).

<About unit component information>
As described above, the unit component information is information in which the identifier of the unit component is associated with the feature amount of the unit component. Assume that the unit component is a single type of molecule. In this case, the unit component information associates an identifier of a molecule with a feature amount of the molecule. The identifier of a molecule is the name or chemical formula of the molecule. The feature amount of a molecule is a feature amount (for example, feature matrix F) obtained by decomposing time-series data obtained by sensing a gas containing only the molecule with the sensor 10. It is assumed that the unit component information is stored in a storage device provided inside or outside the information processing device 2000 in advance.

FIG. 12 is a diagram exemplifying unit component information on a single type of molecule in a table format. The table in FIG. 12 is called a table 300. The table 300 has two columns of a molecule identifier 302 and a feature amount 304. In each record of the table 300, the feature amount indicated by the feature amount 304 is associated with the molecule identifier (unit component identifier) indicated by the molecule identifier 302.

と す る Assume that the unit component is a combination of molecules that generate a specific odor. “Specific odor” corresponds to the odor represented by the odor label described in the first embodiment. The combination of molecules that generate a specific odor corresponds to the combination of molecules contained in the gas specified by the odor label. In the “combination of molecules” here, not only which molecules are contained, but also the mixing ratio of those molecules is specified.

If the unit component is a combination of molecules that generate a specific odor, the identifier of the unit component indicated by the unit component information is an odor label. The characteristic amount of the unit component is a characteristic amount of the gas specified by the odor label. That is, the unit component information corresponds to the odor information in the first embodiment (see FIG. 6).

<Output of specific result>
The information processing device 2000 outputs information indicating a component of the target gas (hereinafter, second output information). For example, the second output information is text data indicating the identifier of each unit component contained in the target gas and their concentration and mixing ratio. In addition, for example, the second output information may be graphical information in which the identifiers of the unit components contained in the target gas and their concentrations and mixing ratios are expressed in a table or a graph.

FIG. 13 is a graph showing the components of the target gas in a graph. In this graph, the horizontal axis indicates the name of each molecule contained in the target gas, and the vertical axis indicates the concentration of each molecule. Specifically, it indicates that the target gas contains molecules B, C, E, and G, and the concentrations thereof. In this graph, the unit components are sorted in descending order of density. By outputting the components of the target gas as graphical information in this manner, the user of the information processing apparatus 2000 can easily and intuitively understand the components of the target gas.

Although the embodiments of the present invention have been described above with reference to the drawings, these are merely examples of the present invention, and a configuration obtained by combining the above embodiments or various configurations other than the above can be adopted.

Some or all of the above embodiments may be described as in the following supplementary notes, but are not limited thereto.
1. A feature amount obtaining unit that obtains a feature amount of the target gas;
From the odor information in which the odor label and the characteristic amount of the gas generating the odor are associated, the odor information similar to the characteristic amount of the target gas is specified, and the odor label indicated in the specified odor information is specified. A label specifying unit for specifying as a label of the odor of the target gas,
The feature value of the gas represents the magnitude of each of a plurality of feature constants with respect to the time-series data of the detection value obtained from the sensor that sensed the gas,
The detection value of the sensor changes according to the attachment and detachment of molecules contained in the gas,
The information processing apparatus, wherein the feature constant is a time constant or a rate constant relating to a magnitude of a temporal change in an amount of a molecule attached to the sensor.
2. The label identification unit calculates the similarity between the distribution of the contribution value represented by the characteristic amount of the target gas and the distribution of the contribution value represented by the characteristic amount indicated by each of the odor information, and uses the calculated similarity. , Specifying odor information similar to the characteristic amount of the target gas; An information processing apparatus according to claim 1.
3. The gas feature amount is a feature vector in which contribution values indicating the magnitude of contribution of each feature constant are listed,
The label specifying unit calculates the distance between the feature vector of the target gas and the feature vector indicated by each of the odor information, and displays the label indicated by the odor information having the calculated distance that is the minimum, the label of the target gas. 1. Identify as odor label An information processing apparatus according to claim 1.
4. The gas feature quantity is information that associates a set of feature constants with a set of contribution values of each feature constant,
The label identification unit,
Both or one of the feature quantity of the target gas and the feature quantity indicated by the odor information is set so that the set of feature constants indicated by the feature quantity of the target gas and the set of feature constants indicated by the odor information become the same. Converted,
After the conversion, a distance between a feature vector indicating a set of contribution values indicated by the feature amount of the target gas and a feature vector indicating a set of contribution values indicated by each of the odor information is calculated, and the calculated distance is calculated. 1. The label indicated by the minimum odor information is specified as the odor label of the target gas. An information processing apparatus according to claim 1.
5. The gas feature quantity is information that associates a set of feature constants with a set of contribution values of each feature constant,
The label identification unit,
A Kullback-Leibler (KL) divergence or Wasserstein metric is calculated between the distribution of the contribution value represented by the characteristic amount of the target gas and the distribution of the contribution value represented by the characteristic amount indicated by each of the odor information. 1. Specify the label indicated by the odor information having the minimum KL divergence or Wasserstein weighing as the odor label of the target gas. An information processing apparatus according to claim 1.

6. A feature amount obtaining unit that obtains a feature amount of the target gas;
Identifying one or more unit components contained in the target gas using unit component information in which an identifier of a unit component is associated with a feature amount of a gas including only the unit component and the feature amount of the target gas And a component specifying part,
The feature value of the gas represents the magnitude of each of a plurality of feature constants with respect to the time-series data of the detection value obtained from the sensor that sensed the gas,
The detection value of the sensor changes according to the attachment and detachment of molecules contained in the gas,
The information processing apparatus, wherein the feature constant is a time constant or a rate constant relating to a magnitude of a temporal change in an amount of a molecule attached to the sensor.
7. The component specifying unit decomposes the characteristic amount of the target gas into one or more characteristic amounts indicated in the unit component information, and converts a unit component corresponding to each of the characteristic amounts obtained by the decomposition into the target component. 5. specified as the unit component contained in the gas; An information processing apparatus according to claim 1.
8. The characteristic amount of the gas indicates a characteristic vector in which contribution values indicating the magnitude of contribution of each characteristic constant are listed,
The component identification unit decomposes the feature vector of the target gas into a linear sum of the feature vectors indicated by each of the one or more unit component information, and generates a unit component corresponding to the feature vector forming the linear sum, 6. Identify as the unit component contained in the target gas; An information processing apparatus according to claim 1.
9. The gas feature quantity is information that associates a set of feature constants with a set of contribution values of each feature constant,
The component identification unit,
Both the characteristic amount of the target gas and the characteristic amount indicated by the unit component information or the characteristic amount indicated by the unit component information so that the set of characteristic constants indicated by the characteristic amount of the target gas and the set of characteristic constants indicated by the unit component information become the same. Convert one,
After the conversion, a feature vector representing a set of contribution values indicated by the feature values of the target gas is decomposed into a linear sum of feature vectors representing a set of contribution values indicated by the feature values of each of one or more unit components, 6. Specify a unit component corresponding to the feature vector forming the linear sum as the unit component included in the target gas; An information processing apparatus according to claim 1.
10. 8. The component specifying unit specifies a mixture ratio of each of the unit components in the target gas based on a coefficient of a feature vector of each of the unit components in the linear sum. An information processing apparatus according to claim 1.
11. 5. The unit component is a single type of molecule or a combination of molecules constituting a gas that generates a specific odor. To 10. An information processing device according to any one of the above.

12. A control method executed by a computer,
A feature value obtaining step of obtaining a feature value of the target gas;
From the odor information in which the odor label and the characteristic amount of the gas generating the odor are associated, the odor information similar to the characteristic amount of the target gas is specified, and the odor label indicated in the specified odor information is specified. A label specifying step of specifying as a label of the odor of the target gas,
The feature value of the gas represents the magnitude of each of a plurality of feature constants with respect to the time-series data of the detection value obtained from the sensor that sensed the gas,
The detection value of the sensor changes according to the attachment and detachment of molecules contained in the gas,
The control method, wherein the characteristic constant is a time constant or a rate constant relating to a magnitude of a temporal change in an amount of a molecule attached to the sensor.
13. In the label specifying step, calculate the similarity between the distribution of the contribution value represented by the characteristic amount of the target gas and the distribution of the contribution value represented by the characteristic amount indicated by each of the odor information, and use the calculated similarity. 11. specifying odor information similar to the characteristic amount of the target gas; The control method described in 1.
14． The gas feature amount is a feature vector in which contribution values indicating the magnitude of contribution of each feature constant are listed,
In the label specifying step, the distance between the feature vector of the target gas and the feature vector indicated by each of the odor information is calculated, and the label indicated by the odor information with the calculated distance being the minimum is set to the label of the target gas. 12. Identify as odor label; The control method described in 1.
15. The gas feature quantity is information that associates a set of feature constants with a set of contribution values of each feature constant,
In the label specifying step,
Both or one of the feature quantity of the target gas and the feature quantity indicated by the odor information is set so that the set of feature constants indicated by the feature quantity of the target gas and the set of feature constants indicated by the odor information become the same. Converted,
After the conversion, a distance between a feature vector indicating a set of contribution values indicated by the feature amount of the target gas and a feature vector indicating a set of contribution values indicated by each of the odor information is calculated, and the calculated distance is calculated. 12. Identify the label indicated by the minimum odor information as the odor label of the target gas; The control method described in 1.
16. The gas feature quantity is information that associates a set of feature constants with a set of contribution values of each feature constant,
In the label specifying step,
A Kullback-Leibler (KL) divergence or Wasserstein metric is calculated between the distribution of the contribution value represented by the characteristic amount of the target gas and the distribution of the contribution value represented by the characteristic amount indicated by each of the odor information. 12. Identify the label indicated by the odor information having the minimum KL divergence or Wasserstein weighing as the odor label of the target gas; The control method described in 1.

17． A control method executed by a computer,
A feature value obtaining step of obtaining a feature value of the target gas;
Identifying one or more unit components contained in the target gas using unit component information in which an identifier of a unit component is associated with a feature amount of a gas including only the unit component and the feature amount of the target gas Component identification step,
The feature value of the gas represents the magnitude of each of a plurality of feature constants with respect to the time-series data of the detection value obtained from the sensor that sensed the gas,
The detection value of the sensor changes according to the attachment and detachment of molecules contained in the gas,
The control method, wherein the characteristic constant is a time constant or a rate constant relating to a magnitude of a temporal change in an amount of a molecule attached to the sensor.
18. In the component specifying step, the characteristic amount of the target gas is decomposed into one or more characteristic amounts indicated in the unit component information, and a unit component corresponding to each of the characteristic amounts obtained by the decomposition is converted into the target component. 17. Specified as the unit component contained in the gas; The control method described in 1.
19. The characteristic amount of the gas indicates a characteristic vector in which contribution values indicating the magnitude of contribution of each characteristic constant are listed,
In the component identification step, the feature vector of the target gas is decomposed into a linear sum of feature vectors indicated by each of the one or more unit component information, and a unit component corresponding to the feature vector forming the linear sum is defined as 17. specified as the unit component contained in the target gas; The control method described in 1.
20. The gas feature quantity is information that associates a set of feature constants with a set of contribution values of each feature constant,
In the component identification step,
Both the characteristic amount of the target gas and the characteristic amount indicated by the unit component information or the characteristic amount indicated by the unit component information so that the set of characteristic constants indicated by the characteristic amount of the target gas and the set of characteristic constants indicated by the unit component information become the same. Convert one,
After the conversion, a feature vector representing a set of contribution values indicated by the feature values of the target gas is decomposed into a linear sum of feature vectors representing a set of contribution values indicated by the feature values of each of one or more unit components, 17. specifying a unit component corresponding to the feature vector forming the linear sum as the unit component included in the target gas; The control method described in 1.
21. 19. In the component specifying step, a mixing ratio of each unit component in the target gas is specified based on a coefficient of a feature vector of each unit component in the linear sum. The control method described in 1.
22. 16. The unit component is a single type of molecule or a combination of molecules constituting a gas that generates a specific odor. To 21. The control method according to any one of the above.

23. {12. To 22. A program for executing each step of the control method according to any one of the above.

Claims (23)

1. A feature amount obtaining unit that obtains a feature amount of the target gas;
   From the odor information in which the odor label and the characteristic amount of the gas generating the odor are associated, the odor information similar to the characteristic amount of the target gas is specified, and the odor label indicated in the specified odor information is specified. A label specifying unit for specifying as a label of the odor of the target gas,
   The feature value of the gas represents the magnitude of each of a plurality of feature constants with respect to the time-series data of the detection value obtained from the sensor that sensed the gas,
   The detection value of the sensor changes according to the attachment and detachment of molecules contained in the gas,
   The information processing apparatus, wherein the feature constant is a time constant or a rate constant relating to a magnitude of a temporal change in an amount of a molecule attached to the sensor.
2. The label identification unit calculates the similarity between the distribution of the contribution value represented by the characteristic amount of the target gas and the distribution of the contribution value represented by the characteristic amount indicated by each of the odor information, and uses the calculated similarity. The information processing apparatus according to claim 1, wherein odor information similar to a characteristic amount of the target gas is specified.
3. The gas feature amount is a feature vector in which contribution values indicating the magnitude of contribution of each feature constant are listed,
   The label specifying unit calculates the distance between the feature vector of the target gas and the feature vector indicated by each of the odor information, and displays the label indicated by the odor information having the calculated distance that is the minimum, the label of the target gas. The information processing device according to claim 2, wherein the information processing device specifies the odor label.
4. The gas feature quantity is information that associates a set of feature constants with a set of contribution values of each feature constant,
   The label identification unit,
   Both or one of the feature quantity of the target gas and the feature quantity indicated by the odor information is set so that the set of feature constants indicated by the feature quantity of the target gas and the set of feature constants indicated by the odor information become the same. Converted,
   After the conversion, a distance between a feature vector indicating a set of contribution values indicated by the feature amount of the target gas and a feature vector indicating a set of contribution values indicated by each of the odor information is calculated, and the calculated distance is calculated. The information processing apparatus according to claim 2, wherein a label indicated by the minimum odor information is specified as the odor label of the target gas.
5. The gas feature quantity is information that associates a set of feature constants with a set of contribution values of each feature constant,
   The label identification unit,
   A Kullback-Leibler (KL) divergence or Wasserstein metric is calculated between the distribution of the contribution value represented by the characteristic amount of the target gas and the distribution of the contribution value represented by the characteristic amount indicated by each of the odor information. The information processing apparatus according to claim 2, wherein a label indicated by the odor information having the minimum KL divergence or Wasserstein weighing is specified as the odor label of the target gas.
6. A feature amount obtaining unit that obtains a feature amount of the target gas;
   Identifying one or more unit components contained in the target gas using unit component information in which an identifier of a unit component is associated with a feature amount of a gas including only the unit component and the feature amount of the target gas And a component specifying part,
   The feature value of the gas represents the magnitude of each of a plurality of feature constants with respect to the time-series data of the detection value obtained from the sensor that sensed the gas,
   The detection value of the sensor changes according to the attachment and detachment of molecules contained in the gas,
   The information processing apparatus, wherein the feature constant is a time constant or a rate constant relating to a magnitude of a temporal change in an amount of a molecule attached to the sensor.
7. The component specifying unit decomposes the characteristic amount of the target gas into one or more characteristic amounts indicated in the unit component information, and converts a unit component corresponding to each of the characteristic amounts obtained by the decomposition into the target component. The information processing apparatus according to claim 6, wherein the information processing apparatus specifies the unit component contained in the gas.
8. The characteristic amount of the gas indicates a characteristic vector in which contribution values indicating the magnitude of contribution of each characteristic constant are listed,
   The component identification unit decomposes the feature vector of the target gas into a linear sum of the feature vectors indicated by each of the one or more unit component information, and generates a unit component corresponding to the feature vector forming the linear sum, The information processing apparatus according to claim 7, wherein the information processing apparatus specifies the unit component contained in the target gas.
9. The gas feature quantity is information that associates a set of feature constants with a set of contribution values of each feature constant,
   The component identification unit,
   Both the characteristic amount of the target gas and the characteristic amount indicated by the unit component information or the characteristic amount indicated by the unit component information so that the set of characteristic constants indicated by the characteristic amount of the target gas and the set of characteristic constants indicated by the unit component information become the same. Convert one,
   After the conversion, a feature vector representing a set of contribution values indicated by the feature values of the target gas is decomposed into a linear sum of feature vectors representing a set of contribution values indicated by the feature values of each of one or more unit components, The information processing apparatus according to claim 7, wherein a unit component corresponding to a feature vector forming the linear sum is specified as the unit component included in the target gas.
10. 10. The information processing apparatus according to claim 9, wherein the component specifying unit specifies a mixture ratio of each unit component in the target gas based on a coefficient of a feature vector of each unit component in the linear sum.
11. The information processing apparatus according to any one of claims 6 to 10, wherein the unit component is a single type of molecule or a combination of molecules constituting a gas generating a specific odor.
12. A control method executed by a computer,
    A feature value obtaining step of obtaining a feature value of the target gas;
    From the odor information in which the odor label and the characteristic amount of the gas generating the odor are associated, the odor information similar to the characteristic amount of the target gas is specified, and the odor label indicated in the specified odor information is specified. A label specifying step of specifying as a label of the odor of the target gas,
    The feature value of the gas represents the magnitude of each of a plurality of feature constants with respect to the time-series data of the detection value obtained from the sensor that sensed the gas,
    The detection value of the sensor changes according to the attachment and detachment of molecules contained in the gas,
    The control method, wherein the characteristic constant is a time constant or a rate constant relating to a magnitude of a temporal change in an amount of a molecule attached to the sensor.
13. In the label specifying step, calculate the similarity between the distribution of the contribution value represented by the characteristic amount of the target gas and the distribution of the contribution value represented by the characteristic amount indicated by each of the odor information, and use the calculated similarity. 13. The control method according to claim 12, wherein odor information similar to the characteristic amount of the target gas is specified.
14. The gas feature amount is a feature vector in which contribution values indicating the magnitude of contribution of each feature constant are listed,
    In the label specifying step, the distance between the feature vector of the target gas and the feature vector indicated by each of the odor information is calculated, and the label indicated by the odor information with the calculated distance being the minimum is set to the label of the target gas. 14. The control method according to claim 13, wherein the control method is specified as an odor label.
15. The gas feature quantity is information that associates a set of feature constants with a set of contribution values of each feature constant,
    In the label specifying step,
    Both or one of the feature quantity of the target gas and the feature quantity indicated by the odor information is set so that the set of feature constants indicated by the feature quantity of the target gas and the set of feature constants indicated by the odor information become the same. Converted,
    After the conversion, a distance between a feature vector indicating a set of contribution values indicated by the feature amount of the target gas and a feature vector indicating a set of contribution values indicated by each of the odor information is calculated, and the calculated distance is calculated. 14. The control method according to claim 13, wherein a label indicated by the minimum odor information is specified as the odor label of the target gas.
16. The gas feature quantity is information that associates a set of feature constants with a set of contribution values of each feature constant,
    In the label specifying step,
    A Kullback-Leibler (KL) divergence or Wasserstein metric is calculated between the distribution of the contribution value represented by the characteristic amount of the target gas and the distribution of the contribution value represented by the characteristic amount indicated by each of the odor information. The control method according to claim 13, wherein a label indicated by the odor information having the minimum KL divergence or Wasserstein weighing is specified as the odor label of the target gas.
17. A control method executed by a computer,
    A feature value obtaining step of obtaining a feature value of the target gas;
    Identifying one or more unit components contained in the target gas using unit component information in which an identifier of a unit component is associated with a feature amount of a gas including only the unit component and the feature amount of the target gas Component identification step,
    The feature value of the gas represents the magnitude of each of a plurality of feature constants with respect to the time-series data of the detection value obtained from the sensor that sensed the gas,
    The detection value of the sensor changes according to the attachment and detachment of molecules contained in the gas,
    The control method, wherein the characteristic constant is a time constant or a rate constant relating to a magnitude of a temporal change in an amount of a molecule attached to the sensor.
18. In the component specifying step, the characteristic amount of the target gas is decomposed into one or more characteristic amounts indicated in the unit component information, and a unit component corresponding to each of the characteristic amounts obtained by the decomposition is converted into the target component. The control method according to claim 17, wherein the control unit specifies the unit component contained in the gas.
19. The characteristic amount of the gas indicates a characteristic vector in which contribution values indicating the magnitude of contribution of each characteristic constant are listed,
    In the component identification step, the feature vector of the target gas is decomposed into a linear sum of feature vectors indicated by each of the one or more unit component information, and a unit component corresponding to the feature vector forming the linear sum is defined as The control method according to claim 18, wherein the control unit specifies the unit component contained in the target gas.
20. The gas feature quantity is information that associates a set of feature constants with a set of contribution values of each feature constant,
    In the component identification step,
    Both the characteristic amount of the target gas and the characteristic amount indicated by the unit component information or the characteristic amount indicated by the unit component information so that the set of characteristic constants indicated by the characteristic amount of the target gas and the set of characteristic constants indicated by the unit component information become the same. Convert one,
    After the conversion, a feature vector representing a set of contribution values indicated by the feature values of the target gas is decomposed into a linear sum of feature vectors representing a set of contribution values indicated by the feature values of each of one or more unit components, 19. The control method according to claim 18, wherein a unit component corresponding to the feature vector forming the linear sum is specified as the unit component included in the target gas.
21. 21. The control method according to claim 20, wherein in the component specifying step, a mixture ratio of each of the unit components in the target gas is specified based on a coefficient of a feature vector of each of the unit components in the linear sum.
22. The control method according to any one of claims 17 to 21, wherein the unit component is a single kind of molecule or a combination of molecules constituting a gas generating a specific odor.
23. A program for executing each step of the control method according to any one of claims 12 to 22.

Images