Estimation device, estimation system, estimation method, and program

Abstract

To grasp characteristics of an object with high accuracy based on a detection result of at least one substance generated from the object.SOLUTION: An estimation device may include: an acquisition unit that acquires a signal output from a sensor, which has a sensitive part that physically changes in response to at least one substance generated from an object and outputs a signal corresponding to the physical change, during a detection period from a time when the sensor switches from a first state of not being exposed to the at least one substance to a second state of being exposed to the at least one substance up to a time when the sensor switches again from the second state to the first state; and an estimation unit that estimates characteristics of the object based on the signal and relation information indicating a relation between a feature amount of a waveform of the signal and the characteristics of the object.SELECTED DRAWING: Figure 6

Description

[Technical field]

[0001] The present invention relates to an estimation device, an estimation system, an estimation method, and a program. [Background technology]

[0002] Patent Documents 1 to 3 describe outputting a quality value or fermentation status information of a solid fermented product based on a detected odor value of the solid fermented product. [Prior art document] [Patent documents] [Patent Document 1] JP 2022-157743 A [Patent Document 2] JP 2022-157744 A [Patent Document 3] JP 2022-157745 A Summary of the Invention [Problem to be solved by the invention]

[0003] It is desirable to grasp the characteristics of an object with higher accuracy based on the detection result of at least one substance emitted from the object. [Means for solving the problem]

[0004] An estimation device according to one aspect of the present invention may include an acquisition unit that acquires a signal output from a sensor having a sensitive part that physically changes in response to at least one substance generated from an object and outputs a signal corresponding to the physical change during a detection period from when a first state in which the sensor is not exposed to the at least one substance is switched to a second state in which the sensor is exposed to the at least one substance and until when the sensor switches again from the second state to the first state. The estimation device may include an estimation unit that estimates a characteristic of the object based on the signal and relationship information indicating a relationship between a feature amount of a waveform of the signal and a characteristic of the object.

[0005] In the estimation device, the sensor may have a plurality of sensing parts having different characteristics of physical changes corresponding to the at least one substance generated from the object. The acquisition part may acquire a plurality of signals output from the plurality of sensing parts during the detection period. The estimation part may estimate the characteristics of the object based on the relationship information indicating a relationship between a combination of waveform features of at least two signals among the plurality of signals and the characteristics of the object, and the plurality of signals.

[0006] In any one of the estimation devices, the sensitive part may include a sensitive film that is deformed by the at least one substance being adsorbed thereto and diffusing therein.

[0007] In any one of the estimation devices, the sensitive film may include an organic-inorganic hybrid material.

[0008] In any of the estimation devices, the feature amount of the waveform of the signal may include at least one of the amplitudes of a plurality of divided waveforms obtained by dividing the waveform of the signal at predetermined intervals, the sum of the amplitudes of the plurality of divided waveforms, the rate of change of each of the amplitudes of the plurality of divided waveforms, the sum of the rate of change of each of the amplitudes of the plurality of divided waveforms, and the average value of the rate of change of each of the amplitudes of the plurality of divided waveforms.

[0009] In any of the estimation devices, the combination of feature quantities of the waveforms of the at least two signals may include at least one of a ratio between the amplitudes of a plurality of divided waveforms of each of the at least two signals obtained by dividing the waveforms of the at least two signals at predetermined intervals, a ratio between total values ​​of the amplitudes of the plurality of divided waveforms of each of the at least two signals, a ratio between rates of change of the amplitudes of the plurality of divided waveforms of each of the at least two signals, and a ratio between average values ​​of the amplitudes of the plurality of divided waveforms of each of the at least two signals.

[0010] In any of the above estimation devices, the object may be a raw material of a food, and the property of the object may be at least one of a type of food and a state of the raw material of the food.

[0011] In any of the estimation devices, the estimation unit may estimate the time when the food can be shipped based on shipping time relationship information indicating the relationship between the condition of the food's raw materials and the period until the food can be shipped, and the estimated condition of the food's raw materials.

[0012] In any of the above estimation devices, the food may be miso, and the property of the object may be at least one of a type of miso and a fermentation state of the miso.

[0013] In any of the estimation devices, the estimation unit may estimate the time when the miso can be shipped based on shipping time relationship information indicating the relationship between the fermentation state of the miso and the period until the miso can be shipped, and based on the estimated fermentation state of the miso.

[0014] In any of the estimation devices, the acquisition unit may further acquire environmental information from a sensor that detects an environmental state around the object. The estimation unit may estimate a characteristic of the object further based on the environmental information.

[0015] An estimation system according to one embodiment of the present invention may include any of the estimation devices, the sensor, and a switching mechanism that is connected to the internal space of a storage section that stores the object and switches between the first state in which the sensor is not exposed to the at least one substance and the second state in which the sensor is exposed to the at least one substance.

[0016] In the estimation system, the switching mechanism may include a first pipe communicating with an internal space of the storage unit, a second pipe communicating with an external space of the storage unit, and a third pipe switchably communicating with one of the first pipe and the second pipe. The sensor may be disposed in the third pipe. When the third pipe communicates with the second pipe, the sensor may be in the first state, and when the third pipe communicates with the first pipe, the sensor may be in the second state.

[0017] An estimation method according to one aspect of the present invention may include a step of an acquisition unit acquiring a signal output from a sensor having a sensitive unit that physically changes in response to at least one substance generated from an object and outputs a signal corresponding to the physical change during a detection period from when the sensor switches from a first state in which the sensor is not exposed to the at least one substance to a second state in which the sensor is exposed to the at least one substance until when the sensor switches again from the second state to the first state. The estimation method may include a step of an estimation unit estimating a characteristic of the object based on the signal and relationship information indicating a relationship between a feature amount of a waveform of the signal and a characteristic of the object.

[0018] A program according to an aspect of the present invention may cause a computer to function as an acquisition unit that acquires a signal output from a sensor having a sensitive part that physically changes in response to at least one substance generated from an object and outputs a signal corresponding to the physical change during a detection period from when a sensor switches from a first state in which the sensor is not exposed to the at least one substance to a second state in which the sensor is exposed to the at least one substance to when the sensor switches again from the second state to the first state. The program may cause the computer to function as an estimation unit that estimates a characteristic of the object based on the signal and relationship information indicating a relationship between a feature amount of a waveform of the signal and a characteristic of the object.

[0019] The above summary of the invention does not list all of the features of the present invention. Also, subcombinations of these features may also be inventions. [Brief description of the drawings]

[0020] [Figure 1] FIG. 1 is a diagram illustrating an example of functional blocks of an overall configuration of an estimation system according to an embodiment. [Diagram 2] FIG. 2 is a diagram illustrating an example of a functional block of the estimation device. [Diagram 3] FIG. 2 is a diagram showing an example of a waveform of a signal output from channel 1 of the sensor. [Figure 4]FIG. 13 is a diagram showing an example of the waveform of a signal output from channel 2 of the sensor. [Diagram 5] FIG. 13 is a diagram showing an example of the waveform of a signal output from channel 3 of the sensor. [Figure 6] 1 is a flowchart showing an example of a procedure for estimating the fermentation and maturation state of miso. [Figure 7A] 10 is a flowchart showing an example of a procedure for deriving a feature amount of each signal. [Figure 7B] 10 is a flowchart showing an example of a procedure for deriving a feature amount of each signal. [Figure 8] FIG. 2 illustrates an example of a hardware configuration. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0021] The present invention will be described below through embodiments of the invention, but the following embodiments do not limit the scope of the invention according to the claims. Furthermore, not all of the combinations of features described in the embodiments are necessarily essential to the solution of the invention.

[0022] 1 is a diagram showing an example of functional blocks of the overall configuration of an estimation system 10 according to this embodiment. The estimation system 10 estimates characteristics of an object based on a detection result of at least one substance generated from the object.

[0023] The estimation system 10 includes a tank 20, a switching mechanism 30, a sensor 50, and an estimation device 100. The tank 20 accommodates an object. The tank 20 may accommodate food ingredients as the object. The tank 20 may be a tank that stores food ingredients. In this embodiment, the tank 20 stores ingredients of miso as the object. If the miso is rice miso, the tank 20 stores rice, koji, and soybeans as ingredients. If the miso is barley miso, the tank 20 stores barley, koji, and soybeans as ingredients. If the miso is soybean miso, the tank 20 stores soybeans and koji as ingredients. The tank 20 may be a preparation tank in which fermentation and maturation of miso are performed.

[0024] A switching mechanism 30 is connected to the tank 20. The switching mechanism 30 has a pipe 31 communicating with the internal space of the tank 20, a pipe 32 communicating with the external space of the tank 20, and a pipe 33 connected to the pipes 31 and 32 via a switching valve 34 and communicating with either the pipes 31 or 32. Gas present in the internal space of the tank 20 passes through the pipe 31. Gas present in the external space of the tank 20 passes through the pipe 32. The gas present in the internal space of the tank 20 includes at least one substance generated from the target object. The gas present in the internal space of the tank 20 includes gas generated by fermenting miso. The gas present in the external space of the tank 20 is air.

[0025] The gas generated by fermenting miso is, for example, at least one of aliphatic alcohols, aromatic compounds, and fatty acid ethyl esters. The aliphatic alcohols include, for example, at least one of 1-butanol, 2-methyl-1-propanol, 2-methyl-1-butanol, and 3-methyl-1-butanol. The aromatic compounds include, for example, at least one of 2-phenyl-1-ethanol, 2-6-dimethoxyphenol, ethyl benzoate, 2-phenylethyl acetate, and 2-phenyl-2-butenal. The fatty acid ethyl esters include, for example, at least one of hexadecanoate, octadecanoate, (Z)-9-octadecanoate, (Z,Z)-9,12-octadecadienoate, and (Z,Z,Z)-9,12,15-octadecatrienoate.

[0026] The gas generated by the fermentation of miso includes, for example, at least one of carbon dioxide, ethanol, methionol, 5-methyl-2-furfural, HEMF (4-hydroxy-2,5-ethyl-5,2-methyl-3(2H)-furanone), HDMF (4-hydroxy-2,5-dimethyl-3(2H)-furanone), 4-ethylguaiacol, and 4-ethylphenol.

[0027] The type of gas generated varies depending on the type of miso, and the amount or type of gas generated varies depending on the fermentation and maturation state of the miso. Therefore, by identifying at least one of the types and amounts of gas generated, it is possible to estimate the type of miso and its fermentation and maturation state.

[0028] The sensor 50 is provided inside the pipe 33 and detects gas passing through the pipe 33. The sensor 50 may be a so-called olfactory sensor. The configuration of the switching mechanism 30 shown above is merely an example. The switching mechanism 30 may be any mechanism that can switch between a non-detection state (first state) in which the sensor 50 is not exposed to at least one substance generated from the object, and a detection state (second state) in which the sensor 50 is exposed to at least one substance generated from the object. The switching mechanism 30 may have an injection unit that purges gas around the sensor 50 by injecting air into the inside of the pipe 33.

[0029] The sensor 50 may be a surface stress sensor that functions as an olfactory sensor. The surface stress sensor has a sensitive part that physically changes in response to at least one substance generated from the target object and outputs a signal corresponding to the physical change. The sensitive part includes a sensitive film that is deformed by adsorbing at least one substance and diffusing into the inside. The sensitive film may include an organic-inorganic hybrid material.

[0030] From the viewpoint of sensitivity and stability in a humid environment, the organic-inorganic hybrid is RSiO 3 / 2 where "R" represents an organic functional group.

[0031] In this embodiment, it is preferable that the organic functional group contains one or more aromatic rings (aromatic ring structures). When an aromatic ring is contained, moisture resistance tends to be further improved. The aromatic ring is not particularly limited because it can be appropriately selected in consideration of the use of the sensor, and examples thereof include aromatic hydrocarbon groups such as phenyl group, naphthyl group, p-tolyl group, and biphenyl group, substituted aromatic hydrocarbon groups such as 4-chlorophenyl group, 4-methoxyphenyl group, 4-aminophenyl group, and pentafluorophenyl group, heterocyclic hydrocarbon groups such as 3-furyl group, 3-thienyl group, 2-pyridyl group, 3-pyridyl group, and 4-pyridyl group, and metallocenes such as ferrocenyl group. The organic functional group in this embodiment may contain one type of the above-mentioned aromatic ring alone, or may contain two or more types in combination.

[0032] An environmental sensor 40 may be provided in the tank 20. The environmental sensor 40 detects an environmental condition in the tank 20. The environmental sensor 40 may detect temperature and humidity as the environmental conditions in the tank 20, and provide environmental information including the temperature information and humidity information to the estimation device 100.

[0033] When the target product is miso, it is necessary to check the fermentation and maturation states of the miso stored in the tank 20 in the manufacturing process to determine whether the miso is ready for shipment. The fermentation and maturation states of the miso are managed, for example, by a person in charge taking out a portion of the miso in the tank 20 and checking the color, flavor, and the like. The quality of the miso may be checked by subjecting the taken out miso to physicochemical analysis. However, there is a possibility that the checks will vary depending on the level of skill of the person in charge. Also, there are cases where checking by physicochemical analysis takes time. The fermentation and maturation states of the miso differ in each of the multiple tanks 20, making it difficult to control the quality and inventory of the miso.

[0034] Therefore, it is desirable to suppress variation in confirmation of characteristics such as the fermentation state of the object such as miso contained in the tank 20.

[0035] Therefore, in this embodiment, an estimation system 10 capable of estimating the properties of an object such as miso contained in a tank 20 is provided.

[0036] 2 shows an example of functional blocks of the estimation device 100. The estimation device 100 includes a control unit 110 and a storage unit 120. The control unit 110 may be configured with a central processing unit (CPU).

[0037] The estimation device 100 may be configured with a computer. The computer may be a personal computer, a tablet computer, a smartphone, a workstation, a server computer, a general-purpose computer, or a computer system in which a plurality of computers are connected. Such a computer system is also a computer in a broad sense. The computer may be a dedicated computer designed for the estimation process of the estimation device 100, or may be dedicated hardware realized by a dedicated circuit. The computer may be implemented by a virtual computer environment. When a computer is used, the estimation device 100 is realized by executing a program by the computer.

[0038] The control unit 110 includes an acquisition unit 112 and an estimation unit 114. The acquisition unit 112 acquires a signal output from the sensor 50 during a detection period from when the sensor 50 switches from a non-detection state in which it is not exposed to at least one substance generated from the target object to a detection state in which it is exposed to at least one substance, until when it switches from the detection state to the non-detection state again.

[0039] The sensor 50 may have a plurality of sensitive parts having different characteristics of a physical change in response to at least one substance generated from the object. The plurality of sensitive parts may have a plurality of sensitive films having different characteristics. The sensor 50 may have a plurality of channels for outputting signals from the plurality of sensitive parts, respectively.

[0040] As described above, for example, when the object is miso, the type and amount of gas generated differs depending on the type of miso or the fermentation or maturation state of the miso. Therefore, the signals output from the multiple channels of the sensor 50 also differ. That is, the feature amount of the waveform of each signal differs depending on the type of miso or the fermentation or maturation state of the miso. Therefore, if relationship information is generated in which the feature amount of the waveform of the signal is associated in advance with the type of miso and the fermentation or maturation state of the miso, the type of miso and the fermentation or maturation state of the miso can be estimated from the feature amount of the waveform of the signal.

[0041] Therefore, the estimation unit 114 estimates the characteristics of the object based on the relationship information indicating the relationship between the feature amount of the signal waveform and the characteristics of the object, and the signal from the sensor 50. The estimation unit 114 may estimate the characteristics of the object based on the relationship information indicating the relationship between at least two feature amounts of the signal waveform and the characteristics of the object, and the signal from the sensor 50. The feature amount of the signal waveform may include at least one of the amplitudes of multiple divided waveforms obtained by dividing the signal waveform at a predetermined interval, the sum of the amplitudes of the multiple divided waveforms, the rate of change of each of the amplitudes of the multiple divided waveforms, the sum of the rate of change of each of the amplitudes of the multiple divided waveforms, and the average value of the rate of change of each of the amplitudes of the multiple divided waveforms. The amplitude of the divided waveform corresponds to the signal intensity at a time corresponding to the divided waveform of the signal.

[0042] The characteristic of the object may be at least one of the type of the object and the state of the object. The state of the object is a state in which the type or amount of a substance generated from the object changes due to a change in the state of the object. If the object is a food, the state of the object may be the quality state, spoilage state, maturation state, fermentation state, or ripening state of the food.

[0043] 3 shows an example of the waveform of a signal output from one channel (channel 1) of the sensor 50. The estimation unit 114 may derive the amplitudes s1 to s5 of the multiple divided waveforms by dividing the waveform of the signal S1 at a predetermined interval t. The estimation unit 114 may derive the sum (s1+s2+s3+s4+s5=s_total) of the amplitudes s1 to s5 of the multiple divided waveforms. The estimation unit 114 may derive the change rates (s2-s1) / t=Δs1, (s3-s2) / t=Δs2, (s4-s3) / t=Δs3, and (s5-s4)t=Δs4 of the amplitudes s1 to s5 of the multiple divided waveforms. The estimation unit 114 may derive the sum (Δs1+Δs2+Δs3+Δs4) of the amplitudes of the multiple divided waveforms. The estimation section 114 may derive the average value ((Δs1+Δs2+Δs3+Δs4) / 4) of the rate of change of each amplitude of the multiple divided waveforms.

[0044] The acquiring unit 112 may acquire a plurality of signals output from the plurality of sensing units during a detection period. The estimating unit 114 may estimate the property of the object based on the plurality of signals and relationship information indicating the relationship between the property of the object and a combination of waveform feature amounts of at least two of the plurality of signals.

[0045] The combination of features of the waveforms of the at least two signals may include at least one of a ratio between the amplitudes of each of a plurality of divided waveforms of the at least two signals obtained by dividing the waveforms of the at least two signals at a predetermined interval t, a ratio between the sums of the amplitudes of each of the plurality of divided waveforms of the at least two signals, a ratio between the rates of change of the amplitudes of each of the plurality of divided waveforms of the at least two signals, a ratio between the sums of the rates of change of the amplitudes of each of the plurality of divided waveforms of the at least two signals, and a ratio between the average values ​​of the amplitudes of each of the plurality of divided waveforms of the at least two signals.

[0046] Fig. 4 shows an example of the waveform of the signal S2 output from another channel (channel 2) of the sensor 50. The estimation unit 114 may derive, for example, the ratio (s1 / m1, s2 / m2, s3 / m3, s4 / m4, s5 / m5) between the amplitudes s1 to s5 of the divided waveforms of the signal S1 of the channel 1 in Fig. 3 and the amplitudes m1 to m5 of the divided waveforms of the signal S2 of the channel 2 in Fig. 4. The estimation unit 114 may derive the ratio (s_total / m_total) between the sum of the amplitudes s1 to s5 of the divided waveforms of the signal S1 (s1+s2+s3+s4+s5=s_total) and the sum of the amplitudes m1 to m5 of the divided waveforms of the signal 2 (m1+m2+m3+m4+m5=m_total). The estimation unit 114 may derive the ratios (Δs1 / Δm1, Δs2 / Δm2, Δs3 / Δm3, Δs4 / Δm4) of the rates of change (Δs1, Δs2, Δs3, Δs4) of the amplitudes s1 to s5 of the divided waveforms of the signal S1 to the rates of change (Δm1, Δm2, Δm3, Δm4) of the amplitudes m1 to m5 of the divided waveforms of the signal S2. The estimation unit 114 may derive the ratio (s_total / m_total) of the average value (s_total / 4) of the amplitudes s1 to s5 of the divided waveforms of the signal S1 to the average value (m_total / 4) of the amplitudes m1 to m5 of the divided waveforms of the signal S2.

[0047] FIG. 5 shows an example of the waveform of a signal S3 output from yet another channel (channel 3) of the sensor 50. In FIG.

[0048] When signal S3 is output from another channel (channel 3) from sensor 50, estimation unit 114 may derive the ratios of amplitudes, ratios of sums of amplitudes, ratios of rates of change of amplitudes, ratios of sums of rates of change of amplitudes, and ratios of average amplitudes for combinations of the waveform features of signals S1 and S2, as well as combinations of the waveform features of signals S1 and S3, and combinations of the waveform features of signals S2 and S3.

[0049] The estimation unit 114 may estimate the characteristics of the object based on a combination of multiple feature amounts of the waveform of one signal, relationship information indicating the relationship with the characteristics of the object, and the signal. Alternatively, the estimation unit 114 may estimate the characteristics of the object based on a combination of multiple feature amounts of the waveforms of at least two signals, relationship information indicating the relationship with the characteristics of the object, and at least two signals.

[0050] In this way, the estimation unit 114 derives multiple parameters indicating the waveform characteristics of one or more signals, and estimates the characteristics of the object based on a combination of the respective parameters. This makes it possible to estimate the characteristics of the object more accurately than estimating the characteristics of the object based on one parameter for one signal.

[0051] The estimation unit 114 may estimate the characteristics of the object using a learning model generated by supervised learning as relationship information indicating the relationship between the waveform features of a signal and the characteristics of the object, or relationship information indicating the relationship between a combination of the waveform features of at least two of the multiple signals and the characteristics of the object.

[0052] The estimation unit 114 may perform machine learning according to a supervised learning algorithm using the feature amount of the waveform of a signal, at least two feature amounts of the waveform of a signal, or a combination of the feature amounts of the waveforms of two signals as explanatory variables and the property of the object as a target variable, to generate a trained learning model that estimates the property of the object from the feature amount of the waveform of a signal or a combination of the feature amounts of the waveforms of two signals, and store the trained learning model in the storage unit 120. The algorithm may be any type of algorithm, such as a neural network, a support vector machine, a multiple regression analysis, or a decision tree.

[0053] The estimation unit 114 may determine whether the estimated state of the raw materials of the food satisfies the predetermined shipping condition of the food, and may notify an external party that the food can be shipped if the estimated state of the raw materials of the food satisfies the predetermined shipping condition of the food. The estimation unit 114 may estimate the time when the food can be shipped based on the shipping time relationship information indicating the relationship between the state of the raw materials of the food and the period until the food can be shipped, and the estimated state of the raw materials of the food.

[0054] 6 is a flow chart showing an example of a procedure for estimating the fermentation and maturation state of miso. The acquisition unit 112 controls the switching valve 34 of the switching mechanism 30 to switch the sensor 50 from a non-detection state in which the sensor 50 is exposed to the outside air outside the tank 20 to a detection state in which the sensor 50 is exposed to the inside air inside the tank 20 (S100).

[0055] The estimation device 100 starts detecting the inside air of the tank 20 by the sensor 50 (S102). The acquisition unit 112 controls the switching valve 34 of the switching mechanism 30 to switch the sensor 50 from a detection state in which the sensor 50 is exposed to the inside air inside the tank 20 to a non-detection state in which the sensor 50 is exposed to the outside air outside the tank 20 (S104). Next, the acquisition unit 112 acquires each signal detected during the detection period in the detection state from each channel of the sensor 50 (S106).

[0056] The estimation unit 114 derives the waveform feature amount of each signal (S108). The estimation unit 114 estimates the fermentation and maturation state of the miso based on the waveform feature amount of each signal and the relationship information (S1010). The estimation device 100 determines whether the estimated fermentation and maturation state of the miso satisfies predetermined shipping conditions (S112).

[0057] When the estimated fermentation and maturation state of the miso satisfies the predetermined shipping conditions, the estimation device 100 notifies the outside that the miso in the tank 20 is ready for shipping (S114). The estimation device 100 may notify the terminal that manages the tank 20 that the miso in the tank 20 is ready for shipping.

[0058] The estimation unit 114 may estimate the time when the miso in the tank 20 can be shipped, based on the estimated fermentation state of the miso. The estimation unit 114 may estimate the time when the miso in the tank 20 can be shipped, based on shipping time relationship information indicating the relationship between the fermentation state (or maturation state) of the miso and the period until the miso can be shipped, and the estimated fermentation state (or maturation state) of the miso. The estimation device 100 may notify the terminal that manages the tank 20 of the time when the miso in the tank 20 can be shipped. Being notified of the time when the miso can be shipped makes it easier to manage the inventory of the miso.

[0059] 7A and 7B are flowcharts showing an example of a procedure for deriving the feature amount of each signal. The relational information used by the estimation unit 114 to estimate the property of the object may differ depending on the type of the object. Therefore, the estimation unit 114 specifies the type of feature amount of each waveform of each signal that is indicated by the relational information used to estimate the property of the object in association with the property of the object.

[0060] The estimation unit 114 acquires each signal of each channel for the gas in the tank 20 via the acquisition unit 112 (S200). The estimation unit 114 determines whether or not to derive each amplitude of each signal based on the type of the specified feature amount of each signal (S202).

[0061] If each amplitude is to be derived, the estimation unit 114 generates a feature amount set yc1 by deriving each amplitude of each signal for each interval t (S204).

[0062] Next, the estimation unit 114 determines whether to derive the sum of the amplitudes of each signal based on the type of the feature of each signal identified (S206). If the sum of the amplitudes is to be derived, the estimation unit 114 generates a feature set yc2 by deriving the sum of the amplitudes of each signal for each interval t (S208).

[0063] Next, the estimation unit 114 determines whether to derive the inter-channel ratio of each amplitude of each signal based on the type of the feature of each identified signal (S210). If the inter-channel ratio of each amplitude is to be derived, the estimation unit 114 generates a feature set yc3 by deriving the inter-channel ratio of each amplitude of each signal for each interval t (S212).

[0064] Next, based on the type of the feature of each signal identified, it is determined whether to derive the inter-channel ratio of the sum of the amplitudes of each signal (S214). If the inter-channel ratio of the sum of the amplitudes of each signal is to be derived, the estimation unit 114 generates a feature set yc4 by deriving the inter-channel ratio of the sum of the amplitudes of each signal for each interval t (S216).

[0065] Next, the estimation unit 114 determines whether to derive the rate of change of each amplitude of each signal based on the type of the feature of each identified signal (S218). If the rate of change of each amplitude of each signal is to be derived, the estimation unit 114 generates the feature yc5 by deriving the rate of change of each amplitude of each signal for each interval t (S220).

[0066] Next, the estimation unit 114 determines whether to derive the sum of the change rates of the amplitudes of each signal based on the type of the feature of each signal identified (S222). If the sum of the change rates of the amplitudes of each signal is to be derived, the estimation unit 114 generates a feature group yc6 by deriving the sum of the change rates of the amplitudes for each interval t (S224).

[0067] Next, the estimation unit 114 determines whether to derive an average value of the rate of change of each amplitude of each signal based on the type of the feature of each signal identified (S226). If the average value of the rate of change of each amplitude of each signal is to be derived, the estimation unit 114 generates a feature set yc7 by deriving the average value of the rate of change for each interval t (S228).

[0068] Next, the estimation unit 114 determines whether to derive the average temperature value and the standard deviation based on the type of the feature of each identified signal (S230). If the average temperature value and the standard deviation are to be derived, the estimation unit 114 acquires temperature information indicating the temperature inside the tank 20, and derives the temperature, the average temperature value, and the standard deviation of the temperature for each interval t to generate feature value groups yt1, yt2, and yt3 (S232).

[0069] Next, the estimation unit 114 determines whether to derive the average humidity value and the standard deviation based on the type of the feature amount of each identified signal (S234). If the average humidity value and the standard deviation are to be derived, the estimation unit 114 acquires humidity information indicating the humidity inside the tank 20, and derives the humidity, the average humidity value, and the standard deviation of the humidity value for each interval t to generate feature amount groups yh1, yh2, and yh3 (S236).

[0070] Through the above process, the estimation unit 114 derives a group of feature amounts used for estimating the target object. Note that the types and derivation order of the group of feature amounts shown in Figs. 7A and 7B are merely examples.

[0071] According to the estimation device 100 of this embodiment, it is possible to accurately estimate characteristics such as the type and state of an object based on relationship information indicating the relationship between the characteristics of an object and a feature of the waveform of a signal, at least two feature values ​​of the waveform of a signal, or a combination of feature values ​​of the waveforms of two signals, and the characteristics of the object, and based on a feature value of the waveform of at least one signal output from a sensor.

[0072] 8 shows an example of a computer 1200 in which aspects of the present invention may be embodied in whole or in part. A program installed on the computer 1200 may cause the computer 1200 to perform operations associated with an apparatus according to an embodiment of the present invention or one or more "parts" of the apparatus. Alternatively, the program may cause the computer 1200 to execute the operations or one or more "parts". The program may cause the computer 1200 to execute a process or steps of the process according to an embodiment of the present invention. Such a program may be executed by the CPU 1212 to cause the computer 1200 to execute specific operations associated with some or all of the blocks of the flowcharts and block diagrams described herein.

[0073] The computer 1200 according to this embodiment includes a CPU 1212 and a RAM 1214, which are connected to each other by a host controller 1210. The computer 1200 also includes a communication interface 1222 and an input / output unit, which are connected to the host controller 1210 via an input / output controller 1220. The computer 1200 also includes a ROM 1230. The CPU 1212 operates according to programs stored in the ROM 1230 and the RAM 1214, thereby controlling each unit.

[0074] The communication interface 1222 communicates with other electronic devices via a network. The hard disk drive may store programs and data used by the CPU 1212 in the computer 1200. The ROM 1230 stores a boot program executed by the computer 1200 when activated and / or a program that depends on the hardware of the computer 1200. The programs are provided via a computer-readable recording medium such as a CD-ROM, a USB memory, or an IC card, or a network. The programs are installed in the RAM 1214, which is also an example of a computer-readable recording medium, or the ROM 1230, and executed by the CPU 1212. The information processing described in these programs is read by the computer 1200, and brings about cooperation between the programs and the various types of hardware resources. An apparatus or method may be configured by implementing an operation or processing of information according to the use of the computer 1200.

[0075] For example, when communication is performed between the computer 1200 and an external device, the CPU 1212 may execute a communication program loaded in the RAM 1214 and instruct the communication interface 1222 to perform communication processing based on the processing described in the communication program. Under the control of the CPU 1212, the communication interface 1222 reads transmission data stored in a transmission buffer area provided in the RAM 1214 or a recording medium such as a USB memory, transmits the read transmission data to a network, or writes reception data received from the network to a reception buffer area or the like provided on the recording medium.

[0076] Furthermore, the CPU 1212 may cause all or a necessary portion of a file or database stored in an external recording medium such as a USB memory to be read into the RAM 1214, and may perform various types of processing on the data on the RAM 1214. The CPU 1212 may then write back the processed data to the external recording medium.

[0077] Various types of information, such as various types of programs, data, tables, and databases, may be stored in the recording medium and undergo information processing. The CPU 1212 may perform various types of processing on the data read from the RAM 1214, including various types of operations, information processing, conditional judgment, conditional branching, unconditional branching, information search / replacement, etc., as described throughout this disclosure and specified by the instruction sequence of the program, and write back the results to the RAM 1214. The CPU 1212 may also search for information in a file, database, etc. in the recording medium. For example, when a plurality of entries each having an attribute value of a first attribute associated with an attribute value of a second attribute are stored in the recording medium, the CPU 1212 may search for an entry that matches a condition, in which the attribute value of the first attribute is specified, from among the plurality of entries, read the attribute value of the second attribute stored in the entry, and thereby obtain the attribute value of the second attribute associated with the first attribute that satisfies a predetermined condition.

[0078] The above-described programs or software modules may be stored in a computer-readable storage medium on the computer 1200 or in the vicinity of the computer 1200. Also, a recording medium such as a hard disk or a RAM provided in a server system connected to a dedicated communication network or the Internet can be used as a computer-readable storage medium, thereby providing the programs to the computer 1200 via the network.

[0079] A computer-readable medium may include any tangible device capable of storing instructions that are executed by a suitable device. As a result, a computer-readable medium having instructions stored thereon comprises an article of manufacture that includes instructions that can be executed to create means for performing the operations specified in the flowchart or block diagram. Examples of computer-readable media may include electronic storage media, magnetic storage media, optical storage media, electromagnetic storage media, semiconductor storage media, and the like. More specific examples of computer-readable media may include floppy disks, diskettes, hard disks, random access memories (RAMs), read-only memories (ROMs), erasable programmable read-only memories (EPROMs or flash memories), electrically erasable programmable read-only memories (EEPROMs), static random access memories (SRAMs), compact disk read-only memories (CD-ROMs), digital versatile disks (DVDs), Blu-ray (RTM) disks, memory sticks, integrated circuit cards, and the like.

[0080] The computer readable instructions may include either source code or object code written in any combination of one or more programming languages. The source code or object code includes conventional procedural programming languages. The conventional procedural programming languages ​​may be assembler instructions, instruction set architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state setting data, or object oriented programming languages ​​such as Smalltalk®, JAVA®, C++, etc., and the “C” programming language or similar programming languages. The computer readable instructions may be provided to a processor or programmable circuitry of a programmable data processing apparatus locally or over a wide area network (WAN) such as a local area network (LAN), the Internet, etc. The processor or programmable circuitry may execute the computer readable instructions to create means for performing the operations specified in the flowcharts or block diagrams.

[0081] Here, the computer may be a computer such as a PC (personal computer), a tablet computer, a smartphone, a workstation, a server computer, or a general-purpose computer, or may be a computer system in which multiple computers are connected. Such a computer system in which multiple computers are connected is also called a distributed computing system, and is a computer in the broad sense. In a distributed computing system, each of the multiple computers executes a part of a program, and the multiple computers collectively execute a program by transferring data during program execution between the computers as necessary.

[0082] Examples of processors include computer processors, central processing units (CPUs), processing units, microprocessors, digital signal processors, controllers, microcontrollers, etc. A computer may have one processor or multiple processors. In a multiprocessor system with multiple processors, each processor executes a part of a program, and the multiple processors collectively execute a program by passing data during program execution between the processors as necessary. For example, in executing multitasks, each of the multiple processors may execute a part of each task in small chunks by switching tasks for each time slice. In this case, which part of a program each processor executes changes dynamically. Also, which part of a program each of the multiple processors executes may be statically determined by programming that takes the multiprocessor into consideration.

[0083] Although the present invention has been described above using the embodiments, the technical scope of the present invention is not limited to the scope described in the above embodiments. It is clear to those skilled in the art that various modifications and improvements can be made to the above embodiments. It is clear from the description of the claims that such modifications and improvements can also be included in the technical scope of the present invention.

[0084] It should be noted that the order of execution of each process, such as operations, procedures, steps, and stages, in the devices, systems, programs, and methods shown in the claims, specifications, and drawings is not specifically stated as "before," "prior to," etc., and may be realized in any order unless the output of a previous process is used in a later process. Even if the operational flow in the claims, specifications, and drawings is explained using "first," "next," etc. for convenience, it does not mean that it is essential to perform the process in this order. [Explanation of symbols]

[0085] 10 Estimation System 20. Tank 30 Switching Mechanism 31, 32, 33 Piping 34 Switching valve 40 Environmental Sensors 50 Sensors 100 Estimator 110 Control section 112 Acquisition Department 114 Estimation Department 120 Storage section 1200 Computer 1210 Host Controller 1212 CPU 1214 RAM 1220 Input / Output Controller 1222 Communication Interface 1230 ROM

Claims

1. an acquisition unit that acquires a signal output from a sensor having a sensitive unit that physically changes in response to at least one substance generated from an object and outputs a signal corresponding to the physical change during a detection period from when the sensor switches from a first state in which the sensor is not exposed to the at least one substance to a second state in which the sensor is exposed to the at least one substance until when the sensor switches from the second state to the first state again; an estimation unit that estimates the characteristics of the object based on relationship information indicating a relationship between a feature amount of a waveform of a signal and a characteristic of the object, and the signal; An estimation device comprising:

2. The sensor has a plurality of sensitive parts each having a different characteristic of a physical change in response to the at least one substance generated from the object, The acquisition unit acquires a plurality of signals output from the plurality of sensory units during the detection period, 2. The estimation device according to claim 1, wherein the estimation unit estimates the characteristic of the object based on the relationship information indicating a relationship between a combination of waveform feature quantities of at least two of the plurality of signals and the characteristic of the object, and based on the plurality of signals.

3. The estimation device according to claim 1 , wherein the sensitive part includes a sensitive film that is deformed by the at least one substance being adsorbed thereto and diffusing therein.

4. The estimation device according to claim 3 , wherein the sensitive film includes an organic-inorganic hybrid material.

5. 2. The estimation device according to claim 1, wherein the feature amount of the signal waveform includes at least one of the amplitudes of a plurality of divided waveforms obtained by dividing the waveform of the signal at predetermined intervals, a sum of the amplitudes of the plurality of divided waveforms, a rate of change of each of the amplitudes of the plurality of divided waveforms, a sum of the rate of change of each of the amplitudes of the plurality of divided waveforms, and an average value of the rate of change of each of the amplitudes of the plurality of divided waveforms.

6. 3. The estimation device according to claim 2, wherein the combination of feature quantities of the waveforms of the at least two signals includes at least one of a ratio between respective amplitudes of a plurality of divided waveforms of the at least two signals obtained by dividing the waveforms of the at least two signals at predetermined intervals, a ratio between respective sums of respective amplitudes of the plurality of divided waveforms of the at least two signals, a ratio between respective rates of change of respective amplitudes of the plurality of divided waveforms of the at least two signals, a ratio between respective sums of rates of change of respective amplitudes of the plurality of divided waveforms of the at least two signals, and a ratio between respective average values ​​of respective amplitudes of the plurality of divided waveforms of the at least two signals.

7. The object is a food ingredient, The estimation device according to claim 1 , wherein the property of the object is at least one of a type of food and a state of ingredients of the food.

8. The estimation device according to claim 7 , wherein the estimation unit estimates the time when the food can be shipped based on shipping time relationship information indicating the relationship between the state of the food's raw materials and the period until the food can be shipped, and the estimated state of the food's raw materials.

9. The food product is miso, The estimation device according to claim 7 , wherein the property of the object is at least one of a type of miso and a fermentation state of the miso.

10. 10. The estimation device according to claim 9, wherein the estimation unit estimates the time when the miso can be shipped based on shipping time relationship information indicating a relationship between a fermentation state of the miso and a period until the miso can be shipped, and based on the estimated fermentation state of the miso.

11. The acquisition unit further acquires environmental information from a sensor that detects an environmental state around the object; The estimation device according to claim 1 , wherein the estimation unit estimates the characteristic of the object further based on the environmental information.

12. An estimation device according to any one of claims 1 to 11; The sensor; a switching mechanism that communicates with an internal space of a storage unit that stores the object and switches between the first state in which the sensor is not exposed to the at least one substance and the second state in which the sensor is exposed to the at least one substance; An estimation system comprising:

13. The switching mechanism includes: A first pipe communicating with an internal space of the storage portion; A second pipe communicating with a space outside the storage unit; a third pipe that is switchably connected to one of the first pipe and the second pipe; and Including, The sensor is disposed in the third pipe, 13. The estimation system of claim 12, wherein the sensor is in the first state when the third pipe communicates with the second pipe, and the sensor is in the second state when the third pipe communicates with the first pipe.

14. a step in which an acquisition unit acquires a signal output from a sensor having a sensitive part which physically changes in response to at least one substance generated from an object and outputs a signal corresponding to the physical change during a detection period from when the sensor switches from a first state in which the sensor is not exposed to the at least one substance to a second state in which the sensor is exposed to the at least one substance until the sensor switches from the second state to the first state again; an estimation unit estimating a characteristic of the object based on the signal and relationship information indicating a relationship between a feature amount of a waveform of the signal and the characteristic of the object; The estimation method comprises:

15. an acquisition unit that acquires a signal output from a sensor having a sensitive unit that physically changes in response to at least one substance generated from an object and outputs a signal corresponding to the physical change during a detection period from when the sensor switches from a first state in which the sensor is not exposed to the at least one substance to a second state in which the sensor is exposed to the at least one substance until when the sensor switches from the second state to the first state again; an estimation unit that estimates the characteristics of the object based on relationship information indicating a relationship between a feature amount of a waveform of a signal and a characteristic of the object, and the signal; A program that allows a computer to function.

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