Food and drink state management system, food and drink state management method and program

Abstract

To provide a food and drink state management system, etc. capable of facilitating management of a storage state of food and drink and achievement of a high maturation degree.SOLUTION: A food and drink state management system for managing a storage state of food and drink, includes: a gas signal acquisition part including a plurality of gas sensor channels, where at least one of the plurality of gas sensor channels has sensitivity to concentrations of two or more types of gases out of a plurality of target gases; a measurement signal group including measurement signals output from the gas sensor channels in response to gases generated from the food and drink; a sensitivity information group including sensitivity information of the gas sensor channels for each of the plurality of target gases; and a prediction part for outputting a predicted gas concentration representing concentration of at least one gas out of the plurality of target gases using intensity of each measurement signal included in the measurement signal group, an intensity ratio between respective measurement signals, and the sensitivity information group, where at least one of the plurality of target gases relates to freshness or a maturity degree of the food and drink.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a food and drink status management system, a food and drink status management method, and a program for managing the storage status of food and drink. [Background technology]

[0002] It has been known that the management of the storage environment is important for controlling the freshness and maturity of food, sake, etc. In recent years, status management systems for food and beverages have been developed that utilize IoT (Internet of Things) technology to monitor food and beverages in real time during storage.

[0003] Patent Document 1 proposes a freshness management system for managing the freshness of ingredients stored inside a food storehouse. In this system, an imaging module is used to capture images of the inside of the food storehouse, and the freshness of each ingredient in the storehouse is estimated by analyzing the type of ingredient, moisture distribution, oil distribution, fat distribution, sugar / acidity distribution, and protein distribution. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent Publication No. 2022-98763 Summary of the Invention [Problem to be solved by the invention]

[0005] However, the method of Patent Document 1 uses image data, so it is not possible to obtain information on places that cannot be photographed. Even if multiple image data are obtained from various angles for one food ingredient, there will always be shadowed areas, and in cases where multiple ingredients are placed close together, only the ingredients close to the imaging module can be photographed, making it difficult to capture the internal state of the food storage in a macroscopic manner. In addition, imaging requires light, and if one were to use the method of Patent Document 1 to monitor freshness in real time, it would require constant exposure to light, which would be problematic in terms of power consumption.

[0006] In order to solve the above-mentioned problems, the present invention aims to provide a food and beverage status management system, a food and beverage status management method, and a program that can visualize the freshness and maturity of food and beverages from multiple gases including aroma components emitted from food and beverages such as food and sake, and make it easy to manage the storage conditions of food and beverages and to control the maturity level. [Means for solving the problem]

[0007] <1> A food and beverage status management system for managing the storage status of food and beverage, a gas signal acquiring unit having a plurality of gas sensor channels, at least one of the plurality of gas sensor channels having sensitivity to concentrations of two or more types of gas among a plurality of target gases; a measurement signal group including measurement signals output from the gas sensor channels in response to gas generated from the food and drink; a sensitivity information group including sensitivity information of the gas sensor channel for each of the plurality of target gases; a prediction unit that outputs a predicted gas concentration indicating a concentration of at least one of the plurality of target gases using the intensity of each measurement signal included in the group of measurement signals and the intensity ratio between each measurement signal and the group of sensitivity information; having A food and beverage status management system, wherein at least one of the plurality of target gases is a gas associated with the freshness or maturity of the food and beverage. <2> the prediction unit outputs information indicating the freshness or maturity of the food or beverage based on the predicted gas concentration. The above <1> The food and beverage status management system according to claim 1. <3> At least one of the plurality of gas sensor channels is sensitive to concentrations of all of the target gases. The above <1> or <2> The food and beverage status management system according to claim 1. <4> All of the plurality of gas sensor channels are sensitive to concentrations of two or more types of gases among the target gases. The above <1> ~ <3> A food and beverage status management system according to any one of the preceding claims. <5> At least one of the plurality of target gases is responsive to two or more of the plurality of gas sensor channels. The above <1> ~ <4> A food and beverage status management system according to any one of the preceding claims. <6> At least one of the plurality of target gases is responsive to all of the plurality of gas sensor channels. The above <1> ~ <5> A food and beverage status management system according to any one of the preceding claims. <7> all of the plurality of target gases are responsive to two or more of the plurality of gas sensor channels; The above <1> ~ <6> A food and beverage status management system according to any one of the preceding claims. <8> an environmental temperature acquisition unit that acquires a temperature of an external environment in which the gas signal acquisition unit exists or a temperature of an internal environment of the gas signal acquisition unit; The prediction unit corrects the group of measurement signals using a temperature of the external environment or a temperature of the internal environment. The above <1> ~ <7> A food and beverage status management system according to any one of the preceding claims. <9> a food and drink temperature acquisition unit that acquires food and drink temperature information that can be converted into a temperature of the food and drink; the prediction unit predicts a concentration of a substance having the same component as the target gas in the food or beverage based on the predicted gas concentration of a target gas which is at least one of the plurality of target gases and the food or beverage temperature information; The above <1> ~ <8> A food and beverage status management system according to any one of the preceding claims. <10> The prediction unit uses at least one of the plurality of measurement signals as a reference signal, and corrects at least one of the other measurement signals, the predicted gas concentration of at least one of the plurality of target gases, and the concentration in the food or drink of a substance having the same component as the target gas, using the reference signal. The above <9> The food and beverage status management system according to claim 1. <11> The reference signal is a measurement signal output from a gas sensor channel having sensitivity to a concentration of only one type of gas among the plurality of target gases. The above <10> The food and beverage status management system according to claim 1. <12> The prediction unit calibrates at least one of the measurement signals, the predicted gas concentration of at least one of the plurality of target gases, and the concentration in the food or drink of a substance having the same component as a target gas that is at least one of the plurality of target gases, using other information not derived from the measurement signals from the gas sensor channel. The above <1> ~ <11> A food and beverage status management system according to any one of the preceding claims. <13> The gas signal acquisition unit acquires the group of measurement signals in a non-contact state with the food or drink. The above <1> ~ <12> A food and beverage status management system according to any one of the preceding claims. <14> The food and drink temperature acquisition unit acquires the food and drink temperature information in a non-contact state with the food and drink. The above <9> The food and beverage status management system according to claim 1. <15> The prediction unit notifies information on a deviation of at least one of the measured value and the predicted value from a preset range when the deviation is detected. The above <1> ~ <14> A food and beverage status management system according to any one of the preceding claims. <16> the gas signal acquisition unit further acquires time information associated with a time at which the group of measurement signals was acquired; notifying a user of information on a recommended action based on the predicted gas concentration of at least one of the plurality of target gases or the concentration in the food or drink of a substance having the same component as a target gas that is at least one of the plurality of target gases, and the time information; The above <1> ~ <15> A food and beverage status management system according to any one of the preceding claims. <17> The target gas contains at least one of sotolon, polysulfide, isovaleraldehyde, pyrazines, diethyl succinate, furfural, vanillin, and ethylene; The above <1> ~ <16> A food and beverage status management system according to any one of the preceding claims. <18> A food and beverage status management method for managing the storage status of food and beverage, comprising: obtaining a set of sensitivity information including sensitivity information of the gas sensor channel for each of a plurality of target gases; a step of acquiring a group of measurement signals from a plurality of gas sensor channels, at least one of which has sensitivity to concentrations of two or more types of gas among the plurality of target gases, the group of measurement signals including measurement signals output from the gas sensor channels in response to gases generated from the food or drink; a step of predicting a predicted gas concentration indicating a concentration of at least one of the target gases, which is associated with the freshness or maturity of the food or drink, using the intensity of each measurement signal included in the measurement signal group, the intensity ratio between each measurement signal, and the sensitivity information group, and outputting the predicted gas concentration; A food and beverage status management method comprising the steps of: <19> The device, a sensitivity information group including sensitivity information of the gas sensor channel for each of a plurality of target gases; a plurality of gas sensor channels, at least one of which has sensitivity to concentrations of two or more types of gas among the plurality of target gases, and a measurement signal group including measurement signals acquired from the plurality of gas sensor channels and output from the gas sensor channels in response to gases generated from food and drink; Enter A program that executes a process of predicting a predicted gas concentration indicating the concentration of a gas associated with the freshness or maturity of the food or beverage, which is at least one of the multiple target gases, using the intensity of each measurement signal included in the group of measurement signals and the intensity ratio between each measurement signal, and the group of sensitivity information, and outputting the predicted gas concentration. Effect of the Invention

[0008] According to the present invention, it is possible to provide a food and beverage status management system, a food and beverage status management method, and a program that can visualize the freshness and maturity of food and beverages from multiple gases containing aroma components generated from food and beverages such as food and sake, and facilitate the management of the storage conditions of food and beverages and the adjustment of the maturity level. [Brief description of the drawings]

[0009] [Figure 1] 1 is a block diagram showing an overview of a food and drink status management system according to an embodiment of the present invention; [Diagram 2] 2 is a schematic diagram for explaining the hardware configuration of each device that constitutes the food and drink status management system. FIG. [Diagram 3] FIG. 2 is a diagram showing an example of the flow of the food and drink status management system of the present embodiment. [Figure 4] FIG. 1 is a diagram showing an overview of the food and beverage status management system of this embodiment when applied to the storage of sake. [Diagram 5] 1 is a diagram showing an example of a sensitivity information group used in the food and drink status management system of the present embodiment. FIG. [Figure 6] 1A to 1C are diagrams showing a measurement signal group y, an environmental temperature corrected measurement signal group yc, and a reference signal corrected measurement signal group z acquired by the food and drink status management system of this embodiment. [Figure 7] FIG. 2 is a diagram showing predicted gas concentrations of each target gas (analyte gas) predicted by the food and beverage status management system of this embodiment. [Figure 8] FIG. 2 is a diagram showing changes over time in predicted gas concentration of each target gas (analyte gas) predicted by the food and beverage status management system of this embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] Below, the food and drink status management system and each of the constituent elements that make up the food and drink status management system will be described with specific examples. However, these embodiments do not limit the present invention. Furthermore, it does not mean that all of the combinations of features described in the embodiments are essential to the solution of the present invention.

[0011] <Food and beverage status management system> An example of the configuration of the food and beverage status management system of this embodiment (hereinafter, sometimes referred to as "the system of this embodiment") will be described with reference to FIG. 1. FIG. 1 is a block diagram showing an overview of the food and beverage status management system of this embodiment. As shown in FIG. 1, the food and beverage status management system 100 is a system for managing the storage state of food and beverage, and includes at least a gas signal acquisition unit 10 and a prediction unit 20, and is capable of outputting a predicted gas concentration OP1 indicating the concentration of at least one gas among a plurality of target gases from the prediction unit 20 using the intensity of each measurement signal included in the measurement signal group (y)IN2 and the intensity ratio between each measurement signal, and the sensitivity information group IN1.

[0012] The term "target gas" refers to a gas that is the object of management in the food and beverage status management system of this embodiment, and is not particularly limited, but may be, for example, an aroma component related to the freshness or maturity of food and beverage. In this embodiment, at least one of the multiple target gases is a gas related to the freshness or maturity of food and beverage. In addition, the "target gas" in this embodiment refers to a gas for which a sensitivity information group is set. Furthermore, among the target gases, a gas whose predicted gas concentration is output by the prediction unit may be referred to as an "analysis gas". In this embodiment, the target gas and the analysis gas can be treated interchangeably in many cases, but to be precise, the target gas has a broader meaning. Furthermore, among the analysis gases, a gas whose concentration in food and beverage is predicted may be referred to as a "target gas". "Sensitivity" indicates the output change of the gas sensor channel with respect to the change in concentration of each target gas, and may be linear or nonlinear. "Sensitivity information" means information on the sensitivity of each gas sensor channel with respect to the concentration of the target gas, and is a numerical expression of the magnitude of the sensitivity. The sensitivity information may be, for example, the sensitivity of the gas sensor channel with respect to the concentration of a target gas when the target gas exists alone. Even if a background gas exists together with a target gas, the sensitivity of the gas sensor channel with respect to the concentration of the target gas under the background may be treated as the sensitivity information. That is, in any system, the information is not particularly limited as long as it represents the sensitivity of the gas sensor channel when only the concentration of a specific target gas changes. For example, when the sensitivity is linear, a numerical value indicating the slope of the output of the gas sensor channel with respect to the concentration of the target gas may be used as the sensitivity information. In this embodiment, a collection of the sensitivity information of each gas sensor channel with respect to each of a plurality of target gases is referred to as a "sensitivity information group". The sensitivity information group may be a measured value or a representative value measured in advance, and is stored in a prediction unit or a gas signal acquisition unit described later. The set of sensitivity information may be fine-tuned by, for example, relearning using the measured values ​​acquired by the gas signal acquisition unit at an early stage after the system of this embodiment is put into operation. A "measurement signal" is a signal (unit: mV, for example) output from a gas sensor channel in response to a mixed gas (gas generated from food and drink) containing a target gas present in the storage section, and in this embodiment, a collection of the measurement signals is referred to as a "measurement signal group."

[0013] 1, the food and drink status management system 100 can include a storage unit 30 and a display unit 40 in addition to a gas signal acquisition unit 10 and a prediction unit 20. Note that the gas signal acquisition unit 10, the prediction unit 20, the storage unit 30, and the display unit 40 do not need to be physically connected to each other, and may be connected to each other via a wired or wireless network.

[0014] <Gas signal acquisition unit> The gas signal acquisition unit 10 has a plurality of gas sensor channels. In the food and drink status management system 100 shown in Fig. 1, an embodiment having five gas sensor channels GSC1 to GSC5 is shown. Hereinafter, the plurality of gas sensor channels may be collectively referred to as "gas sensor channels (GSC)". The gas sensor channels (GSC) are sensors that output signals related to gas concentrations, and the signals output from each gas sensor channel are referred to as "measurement signals", and in Fig. 1, measurement signals 1 to 5 are output from the gas sensor channels GSC1 to GSC5.

[0015] The gas signal acquiring unit 10 acquires a measurement signal group (y)IN2 responsive to a mixed gas composed of multiple gases present in the storage unit 30 using these sensors. The "measurement signal group" includes measurement signals output from each gas sensor channel in response to gas generated (volatilized) from food and drink in the storage unit 30, and is information that compiles output signals from multiple gas sensor channels (GSC1 to GSC5) possessed by the gas signal acquiring unit 10. The measurement signal group (y)IN2 may include signals from channels other than the gas sensor channels (e.g., signals output from temperature sensors), and may be configured to include measurement signals from multiple types of sensors other than the gas sensor channels.

[0016] In the system of this embodiment, at least one of the gas sensor channels has sensitivity to the concentration of two or more types of gas among the multiple target gases to be managed. Specifically, the gas sensor channels GSC1 to GSC4 have sensitivity to the concentration of two or more types of gas among the multiple target gases. That is, the measurement signals 1 to 4 output from the gas sensor channels GSC1 to GSC4 do not correspond one-to-one to the multiple gases, but one measurement signal is associated with multiple gases and one gas is associated with multiple measurement signals.

[0017] In the food and drink status management system 100, for example, at least one of the multiple gas sensor channels may be sensitive to the concentrations of all target gases, or all of the multiple gas sensor channels may be sensitive to the concentrations of two or more types of target gases. Also, for example, the gas signal acquisition unit 10 may use, as the gas sensor channels GSC1 to GSC4, sensors that are sensitive to the concentrations of all target gases and output measurement signals 1 to 4 in response to all target gases, and, as the gas sensor channel GSC5, a so-called one-to-one type sensor that responds only to the concentration of a specific gas species for a reference signal, as described later.

[0018] The main purpose of the gas sensor channel is to measure the gas concentration, but the format of the output signal is not important as long as it outputs a signal based on a voltage, current, resistance, capacitance, temperature, refractive index, fluorescence intensity, weight, frequency, or the like that can be converted into a gas concentration, in addition to a sensor that directly displays the gas concentration. As a gas sensor having multiple gas sensor channels in which one gas sensor channel responds to multiple gases, for example, a sensor that imitates the principle of the olfactory sense of living organisms, such as an MSS (Membrane-type Surface stress Sensor) olfactory sensor, can be cited. The olfactory sense of living organisms is a "many-to-many" mechanism in which one olfactory receptor recognizes various odor molecules (gases), and one odor molecule is recognized by various olfactory receptors, and the MSS olfactory sensor is a sensor that utilizes this "many-to-many" mechanism. This MSS olfactory sensor or the like can be applied to the gas signal acquisition unit 10.

[0019] Since many kinds of gases are generated during storage of food and drink, it is necessary to manage the concentrations of multiple gases when managing the storage state of food and drink. In addition, the target gas to be managed changes depending on the degree of maturation of the food and drink to be finally achieved. As described above, the gas sensor channel (GSC) used in the gas signal acquisition unit 10 is not a sensor specialized for a specific gas (i.e., a sensor that corresponds one-to-one to a specific gas), but a sensor that can respond to multiple types of gases. For example, when the type of target gas to be managed changes, such as when changing the food and drink to which this system is applied, the gas to be managed can be set as the target gas by having the prediction unit 20, which will be described later, learn the sensitivity information group IN1 of the new gas to be managed before operating the system, and the predicted gas concentration of the gas can be predicted from the measurement signal group of the mixed gas containing the gas obtained by the gas signal acquisition unit 10.

[0020] In order to select the gas to be managed and to change or add the target gas, it is preferable that at least one of the gas sensor channels (GSC) has some sensitivity to many (two or more types) of gases, although the sensitivity may vary from strong to weak, and it is also preferable that all of the gas sensor channels have sensitivity to multiple gases. That is, at least one of the gas sensor channels may be sensitive to the concentrations of all of the target gases, and all of the gas sensor channels may be sensitive to the concentrations of two or more types of gases among the target gases.

[0021] As a combination of the multiple target gases, a combination may be selected in which at least one of the multiple target gases responds to two or more of the multiple gas sensor channels, a combination may be selected in which at least one of the multiple target gases responds to all of the multiple gas sensor channels, or a combination may be selected in which all of the multiple target gases respond to two or more of the multiple gas sensor channels.

[0022] As described above, the gas signal acquiring unit 10 may be provided with a separate "one-to-one" gas sensor channel in which one measurement signal (output signal from one gas sensor channel) corresponds to one gas. The measurement signal output from such a gas sensor channel corresponds one-to-one to one of the target gases, and can be treated as a "reference signal." As described above, the gas signal acquiring unit 10 uses a sensor that outputs a measurement signal in response to the concentration of only one gas among multiple target gases as the gas sensor channel GSC5, and can treat the measurement signal 5 as a reference signal.

[0023] It is preferable that the gas signal acquisition unit 10 acquires a plurality of measurement signals (i.e., a group of measurement signals) at the same time in one measurement. The reason is that the predicted gas concentration of the target gas is predicted in the prediction unit using the intensity of each measurement signal and the intensity ratio between each measurement signal, and the prediction accuracy decreases when data with a large timing difference is used. In the food and drink status management system 100, a difference of 10 seconds or less can be considered as the same time. The reason is that the state change of food and drink takes a long time, and the object to be detected is gas volatilized from food and drink, so the state change does not occur suddenly. As shown in FIG. 1, in the food and drink status management system 100, the gas signal acquisition unit 10 can acquire time information IN3 linked to the time when the group of measurement signals was acquired at the same time as acquiring a plurality of measurement signals. As described below, the prediction unit 20 can notify the user of information on recommended actions based on the predicted gas concentration OP1 of at least one of the multiple target gases, or the concentration in food or beverage of a substance with the same component as a target gas that is at least one of the multiple target gases (concentration in food or beverage OP2), together with time information IN3.

[0024] The gas signal acquiring unit 10 may be installed inside the storage unit 30, or may be installed outside the storage unit 30 with a gas sampling means provided between the gas signal acquiring unit 10 and the storage unit 30. From the viewpoint of hygiene, it is preferable that the measurement signals 1 to 5 acquired by the gas signal acquiring unit 10 are acquired in a state of non-contact with the food and drink in the storage unit 30. For this reason, it is preferable that the gas signal acquiring unit 10 and the food and drink temperature acquiring unit 32 acquire the measurement signal group (y)IN2 and the food and drink temperature information IN6 in a state of non-contact with the food and drink in the storage unit 30.

[0025] 1, the gas signal acquisition unit 10 may further include an environmental temperature acquisition unit 12 that acquires the temperature of the external environment in which the gas signal acquisition unit 10 exists (external environmental temperature information IN5) or the temperature of the internal environment of the gas signal acquisition unit 10 (internal environmental temperature information IN4). The environmental temperature acquisition unit 12 may include, for example, a temperature sensor S1 that acquires the internal environmental temperature information IN4 of the gas signal acquisition unit 10 and a temperature sensor S2 that acquires the external environmental temperature information IN5 of the gas signal acquisition unit 10, and the temperature sensor S1 may be installed inside the gas signal acquisition unit and the temperature sensor S2 may be installed near the outside of the gas signal acquisition unit 10. As will be described later, the prediction unit 20 may correct the measurement signal group (y)IN2 using the external environmental temperature information IN5 or the internal environmental temperature information IN4 to obtain the measurement signal group (yc)OP3.

[0026] <Environmental temperature acquisition section> The environmental temperature acquiring unit 12 acquires the temperature of the external environment in which the gas signal acquiring unit 10 exists, or the temperature of the internal environment of the gas signal acquiring unit 10. The information acquired here can be used for temperature correction of the measurement signal acquired by the gas signal acquiring unit 10 as described above.

[0027] Generally, many sensors have temperature characteristics, and the measurement signal output from the gas sensor channel (GSC) of the gas signal acquiring unit 10 also has temperature dependency. Therefore, by correcting the measurement signal using the temperature of the environment in which the gas signal acquiring unit 10 exists, the prediction accuracy of the system of this embodiment is improved.

[0028] Furthermore, instead of using the environmental temperature (internal environmental temperature information IN4 or external environmental temperature information IN5) acquired by the environmental temperature acquisition unit 12 for a specific purpose such as "to perform temperature correction of the measurement signal", the environmental temperature may be treated as being included in part of the measurement signal group (y)IN2, and the predicted gas concentration OP1 may be predicted from the measurement signal group (y)IN2 including the environmental temperature in the prediction unit 20. Furthermore, when the environmental temperature is included in the measurement signal group (y)IN2, the environmental temperature may be treated as a reference signal for reference signal correction.

[0029] <Prediction Department> The prediction unit 20 outputs a predicted gas concentration OP1 indicating the concentration of at least one of the target gases using the intensity of each measurement signal included in the measurement signal group (y) IN2, the intensity ratio between each measurement signal, and the sensitivity information group IN1. The prediction unit 20 may output storage state information indicating the state of the food or drink during storage (for example, information indicating the freshness or maturity of the food or drink) based on the predicted gas concentration. The prediction unit 20 predicts the concentration of the target gas in the food or drink (concentration OP2 in the food or drink) as information indicating the freshness or maturity of the food or drink in addition to the predicted gas concentration OP1 of each target gas present in the storage unit 30 using the sensitivity information group IN1 (information on the output change of the multiple gas sensor channels with respect to the concentration change of each target gas) set in advance before the system of this embodiment is operated, and each information acquired by the gas signal acquisition unit 10, the environmental temperature acquisition unit 12, and the food and drink temperature acquisition unit 32 described later after the system is operated, and outputs the predicted gas concentration OP1 to the display unit 40 to notify the user. The information acquired by the gas signal acquisition unit 10, the environmental temperature acquisition unit 12, and the food and drink temperature acquisition unit 32 is sent to the prediction unit 20 using any transmission means.

[0030] More specifically, the prediction unit 20 predicts the predicted gas concentration OP1 of the target gas present in the storage unit 30 at that time using the intensity of each measurement signal (measurement signals 1 to 5 in FIG. 1) acquired by the gas signal acquisition unit 10, the intensity ratio between each measurement signal, and a preset sensitivity information group IN1. The prediction by the prediction unit 20 is not limited to a calculation algorithm, such as machine learning or deep learning, and is performed by adopting the composition ratio and concentration of the mixed gas that minimizes the error from the information learned at that time using any algorithm. For example, by using multiple regression analysis on the measurement signal group (y)IN2 of a mixed gas composed of multiple target gases, the predicted gas concentration OP1 of each target gas constituting the mixed gas can be calculated from the measurement signal group (y)IN2 of the mixed gas. In the prediction process, individual restrictions may be used according to the actual usage environment in which the system is operated.

[0031] In the prediction unit 20, the sensitivity information group IN1 set in advance may be fine-tuned by re-learning using the measured values ​​acquired by the gas signal acquisition unit 10 at an early stage after the system of this embodiment is operated. The reason for fine-tuning the sensitivity information group IN1 is that the background gas environment is different between the environment assumed when setting in advance and the actual usage environment, so that the information set in advance may have a more appropriate value in the actual usage environment. The range of fine-tuning the sensitivity information group IN1 is preferably within ±50% of the value set in advance, and more preferably within ±30% of the value set in advance. The calculation algorithm for fine-tuning the sensitivity information group IN1 is not limited, and can be a value that can be matched by any method such as machine learning or deep learning.

[0032] In order to improve the prediction accuracy in the prediction unit 20, it is preferable to increase the number of measurement signals from the gas sensor channel (GSC) relative to the number of types of target gases to be predicted. However, if it is desired to reduce the number of measurement signals while maintaining high accuracy, it is preferable to make the number of types of target gases to be predicted equal to the number of measurement signals from the gas sensor channel (GSC).

[0033] When performing environmental temperature correction (temperature correction of the measurement signal from the gas sensor channel (GSC)), the prediction unit 20 may perform temperature correction on the measurement signal group obtained by the gas signal acquisition unit 10 using the environmental temperature (internal environmental temperature information IN4 and external environmental temperature information IN5) acquired by the environmental temperature acquisition unit 12 before predicting the predicted gas concentration OP of the target gas present in the storage unit 30. In addition, the environmental temperature acquired by the environmental temperature acquisition unit 12 may be included as a part of the measurement signal group, and the prediction unit 20 may predict the predicted gas concentration OP1 while simultaneously handling the measurement signal group (y) IN2 acquired by the gas signal acquisition unit 10 and the environmental temperature acquired by the environmental temperature acquisition unit, thereby substantially performing temperature correction.

[0034] In cases where it is known in advance that a specific gas is present (or not present) in the storage unit 30, or when it is desired to remove the influence of a gas that is a main component of the mixed gas present in the storage unit 30 or a gas that generates noise, the remaining measurement signals may be corrected using a measurement signal (reference signal) that responds only to the specific gas (reference gas) to generate the measurement signal group (z) OP4. A "reference signal" is a signal that responds only to specific information (e.g., a specific gas), and some of the multiple measurement signals may be treated as a reference signal. When performing reference signal correction, it is preferable that the prediction unit 20 performs reference signal correction before predicting the predicted gas concentration OP1 of the target gas present in the storage unit 30. In addition, a measurement signal that responds only to a specific gas may not be treated as a reference signal, but may simply be treated as one signal of the measurement signal group like other measurement signals. For example, the prediction unit 20 uses at least one of the measurement signals (e.g., measurement signal 5) as a "reference signal" and can use the reference signal to correct at least one of the other measurement signals (e.g., measurement signals 1 to 4) among the measurement signals 1 to 5, the predicted gas concentration OP1 of at least one of the target gases, and the concentration in food or beverage of a component substance having the same component as the target gas, which is at least one of the target gases (concentration OP2 in food or beverage).

[0035] Examples of gases for the reference signal include water and ethanol, and a humidity sensor or alcohol sensor may be used to measure the humidity or ethanol gas concentration in the storage unit 30, and the information may be used to correct other measurement signals. Correction using the reference signal may be performed before correction using the environmental temperature.

[0036] The reference signal may be a signal for a gas present outside the storage unit 30. By using the signal for the gas present outside the storage unit 30 as the reference signal, background information for the location where the storage unit 30 is present can be obtained. By correcting the measurement signals using the background information, the prediction accuracy of the system of this embodiment can be improved even when the storage unit 30 is in a unique location.

[0037] As shown in Fig. 1, the food and beverage status management system 100 can be configured to have a food and beverage temperature acquisition unit 32 that acquires food and beverage temperature information IN6 that can be converted into the temperature of the food and beverage. The prediction unit 20 assumes that each target gas present in the food and beverage has volatilized from the food and beverage, and can further predict the concentration in the food and beverage of the same component substance as the target gas (concentration in the food and beverage OP2) using a predicted gas concentration OP1 of a target gas that is at least one of a plurality of target gases present in the storage unit 30 predicted by the prediction unit 20 and food and beverage temperature information IN6 acquired by the food and beverage temperature acquisition unit 32.

[0038] The prediction unit 20 may calibrate each predicted value, etc. For example, the prediction unit 20 may calibrate each predicted value, etc., predicted by the prediction unit 20 using other information acquired by a means different from that of the system of this embodiment (a means not derived from the measurement signal of the gas sensor channel). This calibration is performed to match absolute values ​​of the measurement signal group (y) IN2 acquired by the gas signal acquisition unit 10, the measurement signal group (yc) OP3 after environmental temperature correction, the measurement signal group (z) OP4 after reference signal correction, the predicted gas concentration OP1, the predicted concentration value in food and drink (concentration in food and drink OP2), etc.

[0039] The prediction unit 20 may predict the storage state at that time using the predicted gas concentration OP1 of each target gas, the concentration OP2 of the target gas in food and drink, etc. Furthermore, as described above, the gas signal acquisition unit 10 can notify "information on recommended actions for the user" via the display unit 40 based on the predicted gas concentration OP1 of at least one of the multiple target gases or the concentration OP2 of the same component substance as the target gas, which is at least one of the multiple target gases, in food and drink, and the time information IN3, using the time information IN3 linked to the time when the measurement signal group (y) IN2 was acquired. Specifically, the storage unit 30 may determine the elapsed time of storage from the time information IN3, and further predict recommended actions for the user of the system of this embodiment from the predicted storage state and the elapsed time of storage. The contents of the recommended actions include, for example, temperature adjustment of the storage unit 30, ventilation adjustment, management of the storage period and the expiration date, and control of priority at the time of shipment.

[0040] The prediction unit 20 may have a preset range for at least one of the measured values ​​and predicted values ​​(the intensity of each measured signal, the intensity ratio between each measured signal, the predicted gas concentration OP1 of at least one of the target gases, the concentration OP2 of the same component substance as the target gas which is at least one of the target gases in food and drink, the internal environment temperature information IN4, the external environment temperature information IN5, and the food and drink temperature information IN6), and may detect any deviation from the range as an abnormality. For example, when at least one of the measured values ​​and predicted values ​​deviates from the preset range, the prediction unit 20 may notify the user of information regarding the deviation of the measured value, the predicted value, etc. via the display unit 40.

[0041] <Storage Department> The storage section 30 is a place for storing and storing food and beverages. The storage section 30 is not limited to any place where food and beverages can be stored, such as a sake storage tank, a general-purpose case for storing vegetables, fruits, and grains, or a refrigerator. During storage of food and beverages, multiple gases volatilized from the food and beverages are also present in the storage section 30. For example, in the case of storing sake, the multiple gases include ethanol, water vapor, and aroma components generated by aging. At least one of the multiple target gases is a gas related to the freshness or aging degree of the food and beverage. Examples of this gas include sotolon, polysulfide, isovaleraldehyde, pyrazines, diethyl succinate, furfural, vanillin, and ethylene. Ethylene gas is a typical gas that indicates the freshness of vegetables, fruits, and grains.

[0042] It is preferable that the storage unit 30 has a function of adjusting the temperature in order to control the storage state. In order to operate the system of this embodiment with high accuracy, it is preferable that 50% or more of the gases present in the storage unit 30, excluding nitrogen, oxygen, and carbon dioxide, are composed of the target gases registered in advance in the sensitivity information group IN1. More preferably, 70% or more of the gases are composed of the target gases registered in advance in the sensitivity information group IN1. The higher the content of the target gases registered in advance in the sensitivity information group IN1 among the gases present in the storage unit 30, the higher the prediction accuracy of the system of this embodiment. The reason why nitrogen, oxygen, and carbon dioxide are excluded is that these three types of gases are the main gases that make up the atmosphere, and are often included in the background gas present in the storage unit 30.

[0043] <Food and beverage temperature acquisition section> As described above, the food and beverage status management system 100 further includes a food and beverage temperature acquisition unit 32 that acquires food and beverage temperature information IN6 that can be converted into the temperature of the food and beverage by the temperature sensor S3 installed in the storage unit 30, and the prediction unit 20 can predict the concentration of the same component substance as the target gas in the food and beverage (concentration OP2 in the food and beverage) from the predicted gas concentration OP1 of the target gas, which is at least one of the multiple target gases, and the food and beverage temperature information IN6. Specifically, the food and beverage temperature acquisition unit 32 can acquire the temperature of the food and beverage and information that can be converted into the temperature of the food and beverage. The food and beverage temperature acquisition unit 32 may have a mechanism for controlling the temperature of the food and beverage as well as acquiring the food and beverage temperature information IN6.

[0044] From the viewpoint of hygiene, it is preferable that the food and beverage temperature acquisition unit 32 acquires the food and beverage temperature information IN6 in a non-contact state. For example, an infrared sensor can be used as a method for acquiring the temperature in a non-contact manner. Here, if the member forming the storage unit 30 has a temperature measurement function or a temperature adjustment function, it is the member forming the storage unit 30 itself that is in contact with the food and beverage, and the food and beverage temperature acquisition unit 32 itself can be considered not to be in contact with the food and beverage.

[0045] The food and beverage temperature information IN6 acquired by the food and beverage temperature acquisition unit 32 is used not only to measure and control the temperature of the food and beverage, but also to convert the predicted gas concentration OP1 of the gas present in the storage unit 30 predicted by the prediction unit 20 into the concentration in the food and beverage (i.e., the concentration OP2 in the food and beverage). Since the concentration of the gas volatilizing from the food and beverage depends on the food temperature, by using the temperature information, it is possible to predict the concentration of the same substance in a state before volatilization from the concentration of the volatilized gas.

[0046] <Display section> As shown in FIG. 1, the food and beverage status management system 100 may have a display unit 40 as a means for notifying the user. The display unit 40 can notify the user of the status in the storage unit 30 in real time by displaying the results of the prediction and analysis by the prediction unit 20 (each measurement value, each predicted value, storage status, recommended actions, etc.) on a display or the like. The notification method may be any method that can convey the fact to the user, such as sound, display, email, etc., and may have a function of issuing an alarm to notify the user when an abnormality is detected or when work is required. The display unit 40 may be a display or the like installed in the gas signal acquisition unit 10, the prediction unit 20, or the storage unit 30 in the food and beverage status management system 100, or may be a device that can acquire and display output information from the prediction unit 20 by wireless communication, such as a communication terminal.

[0047] In addition, the food and beverage status management system 100 may not only display and notify, but also be a system that automatically performs recommended actions in conjunction with storage equipment, actuators, etc.

[0048] <Hardware configuration> 2, the hardware configuration of each device constituting the food and drink status management system 100, such as the gas signal acquisition unit 10, the prediction unit 20, and the display unit 40, will be described. For example, like the device 200, the gas signal acquisition unit 10, the prediction unit 20, and the display unit 40 include a processor 210, a communication interface 220, an input / output interface 230, a memory 240, a storage 250, and one or more communication buses 260 for interconnecting these components. However, the hardware configuration of each device constituting the food and drink status management system 100, such as the gas signal acquisition unit 10 and the prediction unit 20, is not limited to the configuration shown in FIG. 2.

[0049] The processor 210 executes processes, functions, or methods realized by codes or instructions included in a program stored in the storage 250. The processor 210 may include, for example and without limitation, one or more central processing units (CPUs), micro processing units (MPUs), graphics processing units (GPUs), microprocessors, processor cores, multiprocessors, application-specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), etc., and may realize the processes, functions, or methods disclosed in each embodiment by logic circuits (hardware) or dedicated circuits formed in integrated circuits (ICs (Integrated Circuits) chips, LSIs (Large Scale Integration)), etc.

[0050] The communication interface 220 transmits and receives various data to and from other devices via a network. The communication may be performed either wired or wirelessly, and any communication protocol may be used as long as the devices can communicate with each other. For example, the communication interface 220 is implemented as hardware such as a network adapter, various communication software, or a combination of these.

[0051] The network N may be, but is not limited to, an ad hoc network, an intranet, an extranet, a virtual private network (VPN), a local area network (LAN), a wireless LAN (WLAN), a wide area network (WAN), a wireless WAN (WWAN), a metropolitan area network (MAN), a part of the Internet, a part of the public switched telephone network (PSTN), a mobile phone network, ISDNs (Integrated Service Digital Networks), wireless LANs, LTE (Long Term Evolution), CDMA (Code Division Multiple Access), Bluetooth (registered trademark), satellite communication, etc., or a combination of these. The network may include one or more networks.

[0052] The input / output interface 230 includes an input device for inputting various operations to the device 200, and an output device for outputting processing results processed by the device 200. For example, the input / output interface 230 includes information input devices such as a keyboard, a mouse, and a touch panel, and an information output device such as a display. Note that the device 200 may receive a predetermined input or execute a predetermined output by connecting an external input / output interface 230.

[0053] For example, the device 200 may be connected to a sensor or another device 200 (for example, the device 200 is the gas signal acquisition unit 10 and the other device 200 is the prediction unit 20) as an external input / output interface 230 via a wired or wireless network N. The other device 200 may be a server or the like that provides information to the device 200 upon request.

[0054] The memory 240 temporarily stores the programs loaded from the storage 250 and provides a working area for the processor 210. The memory 240 also temporarily stores various data generated while the processor 210 is executing the programs. The memory 240 may be, for example, a high-speed random access memory such as a DRAM, an SRAM, a DDR RAM, or another random access solid-state storage device, or may be a combination of these.

[0055] Storage 250 stores programs, each functional unit, and various data. Storage 250 may be, for example, one or more magnetic disk storage devices, optical disk storage devices, flash memory devices, or nonvolatile memories such as other nonvolatile solid-state storage devices, or may be a combination of these. Another example of storage 250 may be one or more storage devices installed remotely from processor 210.

[0056] In one embodiment of the present invention, the storage 250 stores programs, functional units, and data structures, or a subset thereof. The device 200 is configured to function as, for example, the gas signal acquisition unit 10, the prediction unit 20, etc., as shown in FIG. 1, by the processor 210 executing instructions included in the programs stored in the storage 250.

[0057] Operating system 251, for example, handles various basic system services and contains procedures for performing tasks using the hardware.

[0058] The network communications module 252 may be used, for example, to connect the device 200 to other computers via the communications interface 220 and one or more communications networks, such as the Internet, other wide area networks, local area networks, metropolitan area networks, etc.

[0059] <How to manage food and drink status> The food and beverage status management method of this embodiment is a food and beverage status management method for managing the storage status of food and beverage, and includes the steps of: obtaining a sensitivity information group including sensitivity information of the gas sensor channel for each of a plurality of target gases; acquiring a measurement signal group from a plurality of gas sensor channels, at least one of which has sensitivity to the concentrations of two or more types of gas among a plurality of target gases, including measurement signals output from the gas sensor channels in response to gas generated from the food and beverage; and predicting a predicted gas concentration indicating the concentration of a gas associated with the freshness or maturity of the food and beverage, which is at least one of the plurality of target gases, using the sensitivity information group and the intensity ratio between the measurement signals included in the measurement signal group.

[0060] The flow of implementing the food and drink status management method of this embodiment using the food and drink status management system of this embodiment will be described with reference to Fig. 3. Fig. 3 is a diagram showing an example of the flow of the food and drink status management system of this embodiment. However, the flow of the food and drink status management system and food and drink status management method of this embodiment is not limited to the following aspects.

[0061] First, before the system of this embodiment is operated as a food and beverage status management system, for example, a set of sensitivity information of a plurality of gas sensor channels is set in advance for each of a plurality of gases (target gases) to be present in the storage unit (step S1). Although not shown in Fig. 3, this set of sensitivity information may be fine-tuned by re-learning using the measured values ​​acquired by the gas signal acquisition unit at an early stage after the system of this embodiment is operated.

[0062] Next, the user of the system of this embodiment operates the system and starts analysis with the gas signal acquisition unit installed so that the gas present in the storage unit can be detected (step S2).

[0063] When the system of this embodiment is operated, the gas signal acquisition unit acquires a measurement signal group y including a plurality of measurement signals for the mixed gas present in the storage unit (step S3). The output signal from each gas sensor channel becomes a measurement signal, and the measurement signals are collected to become a "measurement signal group."

[0064] Next, it is determined whether or not to perform environmental temperature correction on the measurement signal group acquired by the gas signal acquisition unit (step S4). If environmental temperature correction is to be performed (step S4: Yes), the process proceeds to step S5. If environmental temperature correction is not to be performed (step S4: No), the process proceeds to step S6. When each measurement signal is to be corrected using the environmental temperature acquired by the environmental temperature acquisition unit, a measurement signal group yc is generated from the measurement signal group y (step S5). Note that even if the environmental temperature is acquired, environmental temperature correction is not performed, and the environmental temperature may be included as part of the measurement signal group.

[0065] Next, it is determined whether or not the measurement signal group acquired by the gas signal acquisition unit is corrected using a reference signal (step S6). If the reference signal correction is to be performed (step S6: Yes), the process proceeds to step S7. If the reference signal correction is not to be performed (step S6: No), the process proceeds to step S8. As described above, a "reference signal" is a signal that responds only to specific information (e.g., a specific gas), and some of the multiple measurement signals may be treated as the reference signal. When the reference signal correction is performed using a measurement signal that corresponds only to a specific gas as a reference signal, the measurement signal group z is generated by correcting the remaining measurement signals of the measurement signal group y or the measurement signal group yc (step S7). Note that the reference signal correction may be performed before the environmental temperature correction (step S5), and when the environmental temperature is included in the measurement signal group, the environmental temperature may be treated as a reference signal for the reference signal correction.

[0066] Next, the prediction unit predicts the concentration (predicted gas concentration) of each target gas present in the storage unit using the intensity of each measurement signal and the intensity ratio between each measurement signal of the measurement signal group y acquired by the gas signal acquisition unit (if correction has been performed, the measurement signal group yc after environmental temperature correction or the measurement signal group z after reference signal correction), as well as the sensitivity information group (step S8).

[0067] The prediction unit uses the predicted gas concentration and the temperature information of the food and beverage acquired by the food and beverage temperature acquisition unit to predict the concentration of the target gas in the food and beverage (concentration in the food and beverage) from the predicted gas concentration of the target gas, which is at least one of the target gases present in the storage unit (step S9).

[0068] Next, it is determined whether or not to calibrate the predicted value (step S10). If the predicted value is to be calibrated, the process proceeds to step S11. If the predicted value is not to be calibrated, the process proceeds to step S12. If the predicted value is to be calibrated (step S11), the value predicted by the prediction unit is calibrated using information acquired by a means other than the gas signal acquisition unit. Due to the influence of the environment in which the system is operated (for example, the shape of the storage unit, etc.), the value predicted by the prediction unit may deviate significantly from the actual state, so the predicted value is calibrated to calibrate it. Note that, although calibration is performed on the concentration in food and drink in FIG. 3, this calibration may be performed on any of the values ​​of the measurement signal group y acquired by the gas signal acquisition unit, the measurement signal group yc after correction for environmental temperature, the measurement signal group z after correction for the reference signal, and the predicted gas concentration.

[0069] Next, the display unit notifies the user of the status in real time by displaying the prediction results (each measured value, each predicted value, storage state, recommended actions, etc.) from the prediction unit on a display or the like (step S12).

[0070] The system of this embodiment repeats the above operations until storage is completed, and if storage is not completed (No in step S13), returns to step S3, becoming a system capable of managing the storage state in real time. Furthermore, the system of this embodiment ends the analysis when storage is completed (step S13 process). The intervals at which steps S3 to S13 are repeated may be equal intervals or may vary. When varying the intervals at which steps S3 to S13 are repeated, the intervals may be changed using the prediction results from the prediction unit. For example, when the prediction results from the prediction unit vary greatly, the system may repeat the operations at a high frequency, and when the variations are gentle, the system may repeat the operations at a low frequency.

[0071] In addition, the system of this embodiment may be configured, for example, when it is decided in step S13 to continue managing the storage conditions, to return to step S1 instead of step S3 based on the results up to step S12, and increase / decrease or change the type of analysis gas to continue analyzing the storage conditions.

[0072] <Program> The program of this embodiment inputs to the device a sensitivity information group including sensitivity information of the gas sensor channel for each of a plurality of target gases, and a plurality of gas sensor channels, at least one of which has sensitivity to the concentrations of two or more types of gas among the plurality of target gases, and a measurement signal group including measurement signals acquired from the plurality of gas sensor channels and output from the gas sensor channels in response to gas generated from food or beverage, and executes a process of predicting a predicted gas concentration indicating the concentration of a gas associated with the freshness or maturity of the food or beverage, which is at least one of the plurality of target gases, using the intensity of each measurement signal included in the measurement signal group and the intensity ratio between each measurement signal, and the sensitivity information group, and outputting the predicted gas concentration.

[0073] The program of the present embodiment may be provided in a state stored in a computer-readable storage medium. Here, the storage medium can store the program in a "non-transitory tangible medium." The program includes, but is not limited to, a software program or a computer program.

[0074] The present disclosure is not limited to the above-described embodiment, and various modifications are possible within the scope of the gist of the present disclosure. In other words, the above-described embodiment is merely an example in every respect, and should not be interpreted as being restrictive. For example, the above-described processing steps can be arbitrarily changed in order or executed in parallel within the scope of not causing any inconsistency in the processing contents.

[0075] As described above, according to the food and beverage status management system, food and beverage status management method, and program of the present embodiment, a plurality of gas sensor channels that are sensitive to a plurality of target gases and can transmit measurement signals are used, and information indicating the storage status of food and beverages, such as the predicted target gas and the concentration in the food and beverage, can be visualized and notified to the user using a group of measurement signals and a group of sensitivity information. In addition, according to the system of the present embodiment, by using a plurality of gas sensor channels that are sensitive to a plurality of target gases and can transmit measurement signals and setting a group of sensitivity information, replacement with a dedicated sensor is not required, and the target gas to be managed can be changed according to the food and beverage and the desired maturation state, and the system is versatile for a wide variety of food and beverages, such as sake and food.

[0076] [Embodiment] The food and drink status management system according to the embodiment of the present invention will be described with reference to Figs. 4 to 9, taking the storage of sake (Japanese sake) as an example.

[0077] FIG. 4 is a diagram showing an overview of the food and beverage status management system of this embodiment when applied to the storage of sake. In FIG. 4, the food and beverage status management system 300 includes a gas signal acquisition unit 10, a prediction unit 20, a storage unit 30, and a display unit 40. Sake is present in a storage tank that serves as the storage unit 30. A plurality of target gases (water, ethanol, ethyl caproate, isoamyl acetate, and sotolone in this embodiment) are volatilized from the sake during storage. The gas in the storage tank is drawn into the gas signal acquisition unit 10 using a gas sampling means (tube and pump) 14 so that the gas in the storage tank can be detected by the gas signal acquisition unit 10 installed outside the storage tank. The measurement signals acquired by the gas signal acquisition unit 10 are sent to the prediction unit (cloud) 20 via the Internet or the like, and the prediction unit 20 performs various calculations and predictions, and notifies the user of the results by displaying them on a display unit 40 such as a smartphone.

[0078] The operation of the system of this embodiment when it is used in the manner shown in FIG. 4 will be described below with reference to an example. First, before operating the food and beverage status management system 300 on-site, a set of sensitivity information for each of the target gases to be managed is set. The set of sensitivity information is, for example, sensitivity information of multiple gas sensor channels of the gas signal acquisition unit for the gas concentration when the target gas is present alone, such as a value measured in advance or a representative value, and the number of gas sensor channels of the gas signal acquisition unit is preferably equal to or greater than the number of types of target gas.

[0079] In this embodiment, for the sake of simplicity, the target gas and the analysis gas are five types, namely, water, ethanol, ethyl caproate, isoamyl acetate, and sotolone, and the gas signal acquisition unit has five gas sensor channels. First, since the Liquor Tax Act requires management of the alcohol content of sake, in this example, ethanol is included in the target gas. Ethyl caproate and isoamyl acetate are typical gases that are aroma components of sake, and sotolone is an aroma component that occurs when sake is aged for a long period of time. By detecting the trends in the concentration of these aroma components, the aging state of sake can be monitored. Note that the types of target gas and the gas sensor channels in actual use are not limited to five, and can be increased or decreased. The relationship between the gas species that react with each gas sensor channel (channels 1 to 5) in the food and beverage status management system 300 shown in FIG. 4 and the channel number that reacts with each gas species is shown below.

[0080] [Table 1]

[0081] [Table 2]

[0082] For example, in this embodiment, the target gases are the above five types, but even in the application of managing sake, the aroma components generated are diverse. The aroma of sake is mainly divided into three types: ginjo aroma, raw material aroma, and aged aroma. In this embodiment, ethyl caproate and isoamyl acetate, which are typical aroma components of ginjo aroma, and sotolon, which is a typical aroma component of aged aroma, are included in the target gas. In the process of aging, the volatilization amount of ethyl caproate and isoamyl acetate decreases, and conversely, the volatilization amount of sotolon increases. Note that this example is just one example, and the target gas may be changed if the sake to be finally produced changes. Aroma components generated by aging of sake include, for example, sotolon, polysulfides, isovaleraldehyde, pyrazines, diethyl succinate, furfural, vanillin, etc., and the degree of aging can be created by appropriately selecting the target gas to be monitored. Even if the target gas changes, the system of this embodiment can be operated by resetting the sensitivity information group. Furthermore, when managing the freshness of foods such as vegetables, fruits, and grains rather than sake, it is a good idea to include ethylene in the target gases.

[0083] FIG. 5 shows an example of a set of sensitivity information (a collective term for a plurality of pieces of sensitivity information) that have been set in advance. FIG. 5 shows the sensitivity (sensor output intensity per unit concentration) of each gas sensor channel to the gas concentration when the concentration of only one of the target gases, water, ethanol, ethyl caproate, isoamyl acetate, and sotolon, changes. In this embodiment, an MSS olfactory sensor is used as the sensor, and the output is output in voltage, so the unit of the sensitivity information is mV / ppm. In this embodiment, the output of each gas sensor channel is assumed to change linearly with respect to the gas concentration, but a nonlinear model may be constructed. The information of this set of sensitivity information (the intensity of each piece of sensitivity information and the intensity ratio between each piece of sensitivity information) is stored in advance in the prediction unit of this food and drink state management system.

[0084] In this embodiment, four of the five gas sensor channels (channels 1 to 4) are sensitive to all target gases, and the remaining one (channel 5) is a channel sensitive only to water. That is, water responds to all gas sensor channels, and target gases other than water (ethanol, ethyl caproate, isoamyl acetate, and sotolone) respond only to the four gas sensor channels (channels 1 to 4).

[0085] The sensitivity information group may be adjusted using the measurement signal group at the initial stage after the system is operated. In addition, in the system of this embodiment, the prediction unit predicts the predicted gas concentration of each target gas at the time when the measurement signal group is measured using the information of the sensitivity information group and the measurement signal group, but if the information of the sensitivity information group is significantly different from the actual situation, the correct prediction result is not output. For this reason, when the prediction result is obviously abnormal, when there is no continuity in the prediction result after multiple measurements, when there is an influence of background gas, etc., it is preferable to re-learn the information of the sensitivity information group by setting a limit within ±50% of the value of the sensitivity information group set in advance. The calculation algorithm for re-learning is not limited, and it is possible to drive the regression error to a value that is small by setting an arbitrary limit using any method such as machine learning.

[0086] Next, a user of the system of this embodiment installs the gas signal acquisition unit 10 in a sake storage tank (storage tank 30) that will be the storage unit 30, and operates the system in a form in which the gas in the storage tank 30 can be detected by the gas signal acquisition unit 10. When the system is operated, a measurement signal group y originating from a mixed gas containing the target gas present in the storage tank 30 is measured by the gas signal acquisition unit 10. FIG. 6 shows the measurement signal group y, the measurement signal group yc corrected for environmental temperature, and the measurement signal group z corrected for reference signals acquired by the food and beverage status management system of this embodiment. The solid line in FIG. 6 shows the measurement signal group y measured by the five gas sensor channels in one measurement. The measurements in each gas sensor channel are all performed simultaneously.

[0087] Next, the measurement signal group y is corrected for environmental temperature. The gas signal acquisition unit 10 includes an environmental temperature acquisition unit 12 that measures the internal or external environmental temperature of the gas signal acquisition unit, and the prediction unit 20 performs temperature correction of the measurement signal group y based on the environmental temperature acquired by the environmental temperature acquisition unit 12. The purpose of the temperature correction here is to correct the temperature dependency of the gas sensor channel of the gas signal acquisition unit 10. This temperature correction is performed by setting information on the temperature dependency of each gas sensor channel (change in gas sensor channel output with respect to temperature change) in advance. The environmental temperature correction is a general method of adjusting the output of each gas sensor channel with respect to the measured environmental temperature, so details will be omitted. The dashed line in FIG. 6 indicates the measurement signal group yc after environmental temperature correction.

[0088] Here, each gas sensor channel of the gas signal acquisition unit 10 is calculated based on a measurement signal y of the mixed gas by a linear model such as the following Equation 1. 1 , y 2 , y 3 , y 4 , y 5 In the following, the measurement signal y output from the gas sensor channel 1 is 1 Only Equation 1 corresponding to the gas sensor channels 2 to 5 (measurement signal y 2 ~y 5 The equation corresponding to the measurement signal y 1 , y 2 , y 3 , y 4 , y 5 are collectively referred to as a measurement signal group y. Note that the subscripts indicate the gas sensor channel numbers, and y, a, b, c, d, and e are different values ​​for each gas sensor channel.

[0089]

number

[0090] The measurement signal group y and the measurement signal group yc may be used directly in the prediction section to predict the predicted gas concentration (i.e., A, B, C, D, E) of each target gas. However, in order to further improve the prediction accuracy, in this embodiment, the signal of the gas sensor channel 5 is treated as a reference signal, and the remaining four signals are corrected in the prediction section. Here, since the gas sensor channel 5 is a channel that is sensitive only to water, the measurement signal from this channel indicates the amount of water vapor in the storage tank. Therefore, since the water concentration E can be obtained before machine learning is performed, the remaining four gas sensor channels generate a measurement signal group z composed of measurement signals obtained by removing the contribution of water from the measurement signal of the mixed gas (for example, in the case of the gas sensor channel 1, z 1 =y 1 -e 1 E), i.e. the measurement signals z 1 , z 2 , z 3 , z 4 The model equations for are as shown in Equation 2 to Equation 5. The measurement signal of each gas sensor channel of the measurement signal group z has a value as shown by the thick solid line in FIG. 6. Note that, since the contribution of water is considered to be known from the result of gas sensor channel 5, the measurement signal z 5 has been erased.

[0091]

number

[0092] Next, the prediction unit 20 predicts the predicted gas concentration of each target gas present in the storage tank 30 using the measurement signal group z and the sensitivity information group. This prediction is not limited to a calculation algorithm, and may use machine learning or deep learning, and is performed by adopting the component ratio and concentration of the mixed gas that minimizes the error from the information learned at that time using any algorithm. In this embodiment, predicted gas concentrations A, B, C, and D that minimize the error of Equations 2 to 5 for gas sensor channels 1 to 4 are calculated by regression. Figure 7 shows the predicted gas concentrations of each target gas (the predicted gas concentrations of each target gas predicted by the food and beverage status management system of this embodiment). In this embodiment, all calculations are performed using a linear model, but a nonlinear model may also be used. Note that the concentration of water in Figure 7 is calculated using y 5 or yc 5 The values ​​calculated from are shown.

[0093] Next, the concentration of the gas substance in the sake (i.e., the concentration in the food or beverage) is predicted from the predicted gas concentration of at least one target gas (object gas) using temperature information of the sake measured or predicted by, for example, a food or beverage temperature acquisition unit 32 provided in the storage tank 30. In this embodiment, the target gas is ethanol.

[0094] It is assumed that the concentration of ethanol gas volatilizing from ethanol in sake can be expressed, for example, as Equation 6 using the liquid concentration and ethanol vapor pressure. Ethanol vapor pressure is a function of liquid temperature, and can be expressed, for example, using the Antoine formula, as Equation 7.

[0095]

number

[0096] Coefficient f and Antoine constant A ant , B ant , C antSince the value of varies depending on the units used and the type of the system in which the system is operated, an appropriate value may be set in advance, or an arbitrary value may be set first, and the appropriate value may be obtained by subsequent calibration. In addition, since the above-mentioned formulas 6 and 7 are empirical formulas and examples of models, an original model formula may be used according to the system in which the system is operated.

[0097] Under the Liquor Tax Act, the concentration of ethanol (in a liquid) at a temperature of 15°C is called the alcohol content, so the calculated ethanol concentration in sake converted to the value at a temperature of 15°C is the alcohol content.

[0098] The obtained alcohol content may also be calibrated. In this calibration, the alcohol content predicted by the prediction unit is calibrated using information obtained by a means other than the gas signal acquisition unit. The different means may be, for example, a sample of sake and a measurement using a buoy or a vibration-type density meter. If there is a difference between the alcohol content obtained by the different means and the alcohol content predicted by the prediction unit, the alcohol content predicted by the prediction unit can be calibrated by applying an offset to cancel the difference, or by applying a gain to cancel the slope difference using two or more measurement results by different means.

[0099] In Fig. 4, the display unit 40 notifies the user of the status in real time by displaying the results of the predictive analysis by the prediction unit (each measured value, each predicted value, storage state, recommended actions) on the user's smartphone. The contents of the notification may express information on freshness and maturity in addition to the predicted gas concentration and alcohol content of each target gas. In addition, the notification may include recommended actions for the user, such as instructions for temperature adjustment, instructions for ventilation adjustment, storage period, and shipping priority.

[0100] By repeating the above-mentioned operation at any interval until the storage is completed, the system can manage the storage state in real time. Figure 8 shows the time-dependent changes in each target gas predicted by the prediction unit from the start to the end of the operation of the system of this embodiment.

[0101] As described above, according to an embodiment of the present invention, it is possible to visualize the degree of maturation of sake from a number of gases containing aroma components that are generated during the storage of sake, making it easier to manage and prepare the sake.

[0102] In the embodiment of the present invention, the aging of sake is taken as an example, but the food and drink to be managed does not have to be sake, and the food and drink to be managed may be the freshness management of vegetables, fruits, grains, etc. The storage unit is not limited to a storage tank, but may be any place capable of storing food and drink, such as a general-purpose case or refrigerator, and may be used to manage the storage period, shipping period, and best-before date of food and drink, or to control the shipping order according to freshness. [Explanation of symbols]

[0103] 100, 300: food and beverage status management system, 10: gas signal acquisition unit, 12: environmental temperature acquisition unit, 20: prediction unit, 30: storage unit, 32: food and beverage temperature acquisition unit, 40: display unit, IN1: sensitivity information group, IN2: measurement signal group (y), IN3: time information, IN4: internal environmental temperature information, IN5: external environmental temperature information, IN6: food and beverage temperature information, IN7: other information, OP1: predicted gas concentration, OP2: concentration in food and beverage, OP3: measurement signal group (yc), OP4: measurement signal group (z)

Claims

1. A food and beverage status management system for managing the storage status of food and beverage, a gas signal acquiring unit having a plurality of gas sensor channels, at least one of the plurality of gas sensor channels having sensitivity to concentrations of two or more types of gas among a plurality of target gases; a measurement signal group including measurement signals output from the gas sensor channels in response to gas generated from the food and drink; a sensitivity information group including sensitivity information of the gas sensor channel for each of the plurality of target gases; a prediction unit that outputs a predicted gas concentration indicating a concentration of at least one of the plurality of target gases using the intensity of each measurement signal included in the group of measurement signals and the intensity ratio between each measurement signal and the group of sensitivity information; having A food and beverage status management system, wherein at least one of the plurality of target gases is a gas associated with the freshness or maturity of the food and beverage.

2. the prediction unit outputs information indicating the freshness or maturity of the food or beverage based on the predicted gas concentration. The food and drink status management system according to claim 1 .

3. At least one of the plurality of gas sensor channels is sensitive to concentrations of all of the target gases. The food and drink status management system according to claim 1 .

4. All of the plurality of gas sensor channels are sensitive to concentrations of two or more types of gases among the target gases. The food and drink status management system according to claim 1 .

5. At least one of the plurality of target gases is responsive to two or more of the plurality of gas sensor channels. The food and drink status management system according to claim 1 .

6. At least one of the plurality of target gases is responsive to all of the plurality of gas sensor channels. The food and drink status management system according to claim 1 .

7. all of the plurality of target gases are responsive to two or more of the plurality of gas sensor channels; The food and drink status management system according to claim 1 .

8. an environmental temperature acquisition unit that acquires a temperature of an external environment in which the gas signal acquisition unit exists or a temperature of an internal environment of the gas signal acquisition unit; The prediction unit corrects the group of measurement signals using a temperature of the external environment or a temperature of the internal environment. The food and drink status management system according to claim 1 .

9. a food and drink temperature acquisition unit that acquires food and drink temperature information that can be converted into a temperature of the food and drink; the prediction unit predicts a concentration of a substance having the same component as the target gas in the food or beverage based on the predicted gas concentration of a target gas which is at least one of the plurality of target gases and the food or beverage temperature information; The food and drink status management system according to claim 1 .

10. The prediction unit uses at least one of the plurality of measurement signals as a reference signal, and corrects at least one of the other measurement signals, the predicted gas concentration of at least one of the plurality of target gases, and the concentration in the food or drink of a substance having the same component as the target gas, using the reference signal. The food and drink status management system according to claim 9.

11. The reference signal is a measurement signal output from a gas sensor channel having sensitivity to a concentration of only one type of gas among the plurality of target gases. The food and drink status management system according to claim 10.

12. The prediction unit calibrates at least one of the measurement signals, the predicted gas concentration of at least one of the plurality of target gases, and the concentration in the food or drink of a substance having the same component as a target gas that is at least one of the plurality of target gases, using other information not derived from the measurement signals from the gas sensor channel. The food and drink status management system according to claim 1 .

13. The gas signal acquisition unit acquires the group of measurement signals in a non-contact state with the food or drink. The food and drink status management system according to claim 1 .

14. The food and drink temperature acquisition unit acquires the food and drink temperature information in a non-contact state with the food and drink. The food and drink status management system according to claim 9.

15. The prediction unit notifies information on a deviation of at least one of the measured value and the predicted value from a preset range when the deviation is detected. The food and drink status management system according to claim 1 .

16. the gas signal acquisition unit further acquires time information associated with a time at which the group of measurement signals was acquired; notifying a user of information on a recommended action based on the predicted gas concentration of at least one of the plurality of target gases or the concentration in the food or drink of a substance having the same component as a target gas that is at least one of the plurality of target gases, and the time information; The food and drink status management system according to claim 1 .

17. The target gas contains at least one of sotolon, polysulfide, isovaleraldehyde, pyrazines, diethyl succinate, furfural, vanillin, and ethylene; The food and drink status management system according to claim 1 .

18. A food and beverage status management method for managing the storage status of food and beverage, comprising: obtaining a set of sensitivity information including sensitivity information of the gas sensor channel for each of a plurality of target gases; a step of acquiring a group of measurement signals from a plurality of gas sensor channels, at least one of which has sensitivity to concentrations of two or more types of gas among the plurality of target gases, the group including measurement signals output from the gas sensor channels in response to gases generated from the food or drink; a step of predicting a predicted gas concentration indicating a concentration of at least one of the target gases, which is associated with the freshness or maturity of the food or drink, using the intensity of each measurement signal included in the measurement signal group, the intensity ratio between each measurement signal, and the sensitivity information group, and outputting the predicted gas concentration; A food and beverage status management method comprising the steps of:

19. The device, a sensitivity information group including sensitivity information of the gas sensor channel for each of a plurality of target gases; a plurality of gas sensor channels, at least one of which has sensitivity to concentrations of two or more types of gas among the plurality of target gases, and a measurement signal group including measurement signals acquired from the plurality of gas sensor channels and output from the gas sensor channels in response to gases generated from food and drink; Enter A program that executes a process of predicting a predicted gas concentration indicating the concentration of a gas associated with the freshness or maturity of the food or beverage, which is at least one of the multiple target gases, using the intensity of each measurement signal included in the group of measurement signals and the intensity ratio between each measurement signal, and the group of sensitivity information, and outputting the predicted gas concentration.

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