Estimation system, estimation method, and program

Abstract

The present disclosure addresses the problem of improving the accuracy with which the odor intensity of an odor is estimated for a subject. An estimation system (1) comprises an acquisition unit (11), an estimation unit (12), and an output unit (13). The acquisition unit (11) acquires detection information related to a signal intensity that corresponds to a detected amount of an odor substance from a detection unit that detects the odor substance. The estimation unit (12) estimates the odor intensity of the odor substance for a subject on the basis of the detection information and adaptation information related to adaptation to the odor substance. When the odor intensity estimated by the estimation unit (12) is at or below a threshold value, the output unit (13) outputs an output signal to a discharge unit that discharges the odor substance.

Description

Estimation system, estimation method, and program

[0001] The present disclosure generally relates to an estimation system, an estimation method, and a program, and more particularly to an odor estimation system, an estimation method, and a program for executing the estimation method.

[0002] Patent Literature 1 discloses an odor control device. The odor control device includes a receiving means for receiving a mind and body action purpose, an odor generation unit capable of presenting an odor from an odor generation source, and a control means for controlling the odor generation unit. The control means controls the odor generation unit based on the odor presentation time and odor stop time in the odor generation unit so that the temporal change in the sensory intensity of the odor generated by the odor generation unit matches the target sensory intensity characteristic corresponding to the action purpose received by the receiving means.

[0003] Incidentally, in a device or system (estimation system) that generates an odor as disclosed in Patent Document 1, it is desirable to generate the odor at a more appropriate timing.

[0004] Japanese Patent Application Laid-Open No. 2017-3200

[0005] The present disclosure has been made in consideration of the above-mentioned reasons, and aims to provide an estimation system, estimation method, and program that can improve the accuracy of estimating the odor intensity of a subject's odorous substance.

[0006] An estimation system according to one aspect of the present disclosure includes an acquisition unit, an estimation unit, and an output unit. The acquisition unit acquires detection information regarding signal intensity corresponding to the amount of the detected odorant from a detection unit that detects the odorant. The estimation unit estimates the odor intensity of the subject for the odorant based on the detection information and adaptation information regarding adaptation to the odorant. The output unit outputs an output signal to an emission unit that emits the odorant when the odor intensity estimated by the estimation unit is equal to or less than a threshold.

[0007] An estimation method according to one aspect of the present disclosure is an estimation method executed by one or more processors. The estimation method includes an acquisition step, an estimation step, and an output step. In the acquisition step, detection information regarding signal strength corresponding to the amount of the detected odorant is acquired from a detection unit that detects the odorant. In the estimation step, the odor intensity of the subject to the odorant is estimated based on the detection information and adaptation information regarding adaptation to the odorant. In the output step, if the odor intensity estimated in the estimation step is equal to or less than a threshold, an output signal is output to an emission unit that emits the odorant.

[0008] A program according to one aspect of the present disclosure is a program for causing one or more processors to execute the estimation method.

[0009] FIG. 1 is a schematic diagram showing the configuration of an estimation system according to a first embodiment. FIG. 2 is a schematic diagram showing the configuration of an odor emission system according to a second embodiment. FIG. 3 is a schematic diagram showing an example of the layout of the odor emission system according to the first embodiment. FIG. 4 is a schematic diagram showing an example of time-series changes in odor intensity estimated by the odor emission system according to the first embodiment. FIG. 5 is a flowchart showing the operation of the odor emission system according to the first embodiment. FIGS. 6A to 6E are schematic diagrams showing examples of human odor adaptation patterns.

[0010] Preferred embodiments of the present disclosure will be described in detail below with reference to the drawings. Common elements in the embodiments described below are designated by the same reference numerals, and redundant descriptions of the common elements may be omitted. The following embodiments and modifications are merely a portion of the various embodiments of the present disclosure. Various modifications of the following embodiments and modifications can be made depending on the design, etc., as long as the object of the present disclosure can be achieved. The configurations of the modifications can also be combined as appropriate.

[0011] The drawings described in this disclosure are schematic drawings, and the ratios of the sizes and thicknesses of the components in the drawings do not necessarily reflect the actual dimensional ratios.

[0012] First Embodiment The configuration of an estimation system 1 according to a first embodiment will be described with reference to FIG.

[0013] As shown in FIG. 1 , the estimation system 1 of the first embodiment includes an acquisition unit 11 , an estimation unit 12 , and an output unit 13 .

[0014] The acquisition unit 11 acquires detection information relating to signal strength corresponding to the amount of detected odorous substance from a detection unit that detects odorous substances (for example, the detection unit 32 in FIG. 2).

[0015] In the present disclosure, "odorant" refers to a substance that causes a person to smell, including molecules or compounds that cause a person to smell. "Detection information" includes information on signal strength corresponding to the amount of odorant detected by the detection unit. The strength of the signal strength is based on the amount of odorant detected by the detection unit. In the present disclosure, the greater the amount of odorant detected by the detection unit, the stronger the signal strength.

[0016] The estimation unit 12 estimates the odor intensity of the subject to the odorant based on the detection information acquired by the acquisition unit 11 and adaptation information regarding adaptation to the odorant.

[0017] "Odor intensity" as used in this disclosure is a numerical value that represents a person's sensitivity to an odorant. For example, in a six-level odor intensity indication system, odor intensity is expressed in six levels: "0," "1," "2," "3," "4," and "5." Odor intensity "0" is odorless to humans. Odor intensity "1" is an odor that humans can just barely detect (i.e., detection threshold concentration). Odor intensity "2" is a relatively weak odor that humans can recognize (i.e., recognition threshold concentration). Odor intensity "3" is an odor that humans can easily detect. Odor intensity "4" is a relatively strong odor to humans. Odor intensity "5" is an extremely strong odor to humans.

[0018] The adaptation information also includes pattern information on the adaptation pattern or olfactory fatigue rate pattern for each type of odorant. The pattern information is information that classifies the time series changes in odor intensity in humans for each type of odorant. Each type of odorant has a different adaptation index. The adaptation index takes a value between 0 and 100. The higher the adaptation index, the easier it is for humans to adapt to the odorant, and the lower the adaptation index, the more difficult it is for humans to adapt to the odorant. Table 1 shows an example of the adaptation index for each odorant.

[0019]

[0020] When the odor intensity estimated by the estimation unit 12 is equal to or less than the threshold, the output unit 13 outputs an output signal to an emission unit (for example, emission unit 42 in FIG. 2) that emits an odor substance.

[0021] According to the estimation system 1 of the first embodiment, the odor intensity of the subject for an odorant is estimated based on the detection information acquired from the detection unit and the adaptation information, thereby improving the accuracy of the odor intensity estimation. Furthermore, the estimation system 1 of the first embodiment outputs an output signal to the release unit that releases the odorant when the estimated odor intensity is equal to or less than a threshold value, so that the odorant can be released, for example, at a timing when the subject is less able to detect the odor. In other words, according to the estimation system 1 of the first embodiment, the odorant can be released at a timing that is more suitable for release.

[0022] Second Embodiment The configuration of an odor emission system 100 according to a second embodiment will be described with reference to FIGS.

[0023] (1) Configuration of the Odor Emission System As shown in Figure 2, the odor emission system 100 includes an information device 2, a sensor 3, and an emission device 4. The odor emission system 100 is used, for example, in offices, cars, individual booths, hotels, movie theaters, game centers, event venues, etc. However, the facility in which the emission system 100 is used may be set as appropriate.

[0024] (2) Sensor Configuration The sensor 3 is a sensor configured to be able to detect odorants. More specifically, the sensor 3 is a sensor configured to be able to detect each odorant emitted by the emitter 4. For example, the sensor 3 is placed on a desk 200 (see FIG. 3) used by the subject H1 (see FIG. 3). For example, the sensor 3 is placed between the emitter 4 and the subject H1.

[0025] As shown in FIG. 2 , the sensor 3 includes a communication unit 31 and a detection unit 32 .

[0026] The communication unit 31 includes an interface capable of communicating with the information device 2. Note that "capable of communication" in this disclosure means that signals can be sent and received directly or indirectly via a network, a repeater, or the like, by an appropriate communication method such as wired communication or wireless communication.

[0027] The detection unit 32 of the second embodiment is configured to be able to detect multiple types of odorants. The detection unit 32 transmits detection information of the detected odorants to the acquisition unit 11 of the information device 2 via the communication unit 31. The detection information includes information indicating the type of odorant and information regarding the signal intensity of the odorant. The detection unit 32 of the second embodiment transmits information regarding the signal intensity for each type of odorant to the acquisition unit 11 via the communication unit 31.

[0028] (3) Configuration of the Release Device The release device 4 is a device that releases an odorant. The release device 4 is placed in a position where it can release the odorant within the area A0 where the sensor 3 (or detection unit 32) is placed. Here, the "area A0 where the detection unit 32 is placed" is an area within a predetermined range centered on the detection unit 32. The predetermined range may be set as appropriate. For example, the area A0 where the detection unit 32 is placed is an area within a radius of 3 m centered on the detection unit 32. The release device 4 may be placed within the area A0 or outside the area A0. In the present disclosure, a subject H1 is present within the area A0.

[0029] For example, the release device 4 of the second embodiment is placed on a desk 200 (see FIG. 3 ) used by the subject H1. The release device 4 of the second embodiment is also placed in a position where the sensor 3 is sandwiched between the release device 4 and the subject H1.

[0030] As shown in FIG. 2 , the discharge device 4 includes a communication unit 41 and a discharge unit 42 .

[0031] The communication unit 41 includes an interface capable of communicating with the information device 2 .

[0032] The release unit 42 has a plurality of types of odorants, a compound containing one or more odorants, or a source substance that generates an odorant. The source substance generates an odorant by, for example, vaporizing or atomizing.

[0033] The release section 42 also has a blower fan or air pump that generates an air current to transport the odorous substance to the area A0.

[0034] The emitter 42 emits an odor substance into the area A0 when an output signal output from the output unit 13 of the estimation system 1 is input. The output signal will be described later.

[0035] The release unit 42 of the second embodiment releases, into the region A0, an odorant corresponding to the output signal from among multiple odorants. For example, the release unit 42 releases the odorant in an amount based on the output signal. The release unit 42 of the second embodiment releases, for example, a first odorant and a second odorant. For example, the first odorant is isovaleric acid, and the second odorant is vanillin. Isovaleric acid is an odorant that humans perceive as smelling like sweaty socks. Vanillin is an odorant that humans perceive as smelling like vanilla. It is known that when a person perceives the odors of isovaleric acid and vanillin as a complex odor (or mixed odor), they perceive a chocolate-like odor. As another example of a complex odor, for example, when a person perceives the odors of lemon, cinnamon, and lime as a complex odor, they perceive a cola-like odor.

[0036] (4) Configuration of Information Device The information device 2 of the second embodiment is, for example, a server. The information device 2 may also be a smartphone, a tablet, a personal computer, or the like.

[0037] As shown in FIG. 2, the information device 2 includes a communication unit 21, a storage unit 22, and a processing unit 23.

[0038] The communication unit 21 includes an interface capable of communicating with the sensor 3 and an interface capable of communicating with the discharging device 4. The interface capable of communicating with the sensor 3 and the interface capable of communicating with the discharging device 4 may be the same interface.

[0039] The storage unit 22 is a semiconductor memory such as a writable read-only memory (ROM), a random access memory (RAM), or an electrically erasable programmable read-only memory (EEPROM). Note that the storage unit 22 is not limited to a semiconductor memory and may be a hard disk drive or the like.

[0040] The storage unit 22 stores adaptation information related to the adaptation of odorants. The adaptation information may be, for example, information including a mathematical formula that mathematically expresses the adaptation pattern for each odorant, or information in a table that classifies odorants by their adaptation pattern.

[0041] The processing unit 23 is mainly composed of a computer system having one or more processors and a memory. The functions of the processing unit 23 are realized by the processor of the computer system executing a program recorded in the memory or storage unit 22 of the computer system. The program may be recorded in the memory or storage unit 22, or may be provided via a telecommunications line such as the Internet, or may be recorded on a non-transitory recording medium such as a memory card and provided.

[0042] The processing unit 23 of the second embodiment functions as the estimation system 1. That is, the information device 2 of the second embodiment includes the estimation system 1.

[0043] The processing unit 23 includes an acquisition unit 11 , an estimation unit 12 , and an output unit 13 .

[0044] The acquisition unit 11 acquires odorant detection information from the detection unit 32. Furthermore, when the emitter 42 emits multiple types of odorants, the acquisition unit 11 acquires detection information for each type of odorant emitted by the emitter 42. The acquisition unit 11 of the second embodiment acquires detection information for each type of odorant.

[0045] The estimation unit 12 estimates the odor intensity of the subject H1 for each odorant based on the detection information acquired by the acquisition unit 11 and the adaptation information related to the adaptation to the odorant. The estimation unit 12 of the second embodiment estimates the odor intensity for each type of odorant. For example, the estimation unit 12 estimates the odor intensity for each odorant by performing a calculation using the odorant detection information and the adaptation information. This improves the accuracy of the estimation of the odor intensity for each odorant.

[0046] FIG. 4 is a schematic diagram showing an example of time-series changes in odor intensity estimated by the estimation unit 12. Line L1 in FIG. 4 indicates the time-series changes in the signal intensity of the first odorant acquired by the acquisition unit 11. In other words, line L1 indicates the time-series changes in the signal intensity of the first odorant detected by the detection unit 32. As described above, the first odorant in embodiment 2 is isovaleric acid. Line L2 in FIG. 4 indicates the time-series changes in the signal intensity of the second odorant acquired by the acquisition unit 11. In other words, line L2 indicates the time-series changes in the signal intensity of the second odorant detected by the detection unit 32. As described above, the second odorant in embodiment 2 is vanillin. Line L3 in FIG. 4 indicates the time-series changes in odor intensity of the first odorant for subject H1 estimated by the estimation unit 12. Line L4 in FIG. 4 indicates the time-series changes in odor intensity of the second odorant for subject H1 estimated by the estimation unit 12. When the odor intensity of the first odor substance is equal to or greater than the first threshold and the odor intensity of the second odor substance is equal to or greater than the second threshold, the subject H1 detects a chocolate-like odor. Note that the first threshold and the second threshold may be the same value or different values.

[0047] 4, it is generally known that even if the signal strength of an odorant detected by the detection unit 32 is constant, the odor intensity weakens exponentially as people adapt to the odorant. However, adaptation patterns vary, and not all people adapt to odorants exponentially.

[0048] In Fig. 4, for simplicity of explanation, the signal intensities of the first odorant and the second odorant are constant, but in reality, the signal intensities of the first odorant and the second odorant also increase and decrease. Also, in Fig. 4, for simplicity of explanation, lines L1 and L2 are shown as straight lines, but in reality, lines L1 and L2 will be polygonal or curved due to the influence of external disturbances, etc. The estimation unit 12 estimates odor intensity based on the detection information of the odorant detected by the detection unit 32, so in reality, lines L3 and L4 in Fig. 4 will be lines that follow the changes in lines L1 and L2.

[0049] The output unit 13 outputs a first output signal to the emitter 42 at a predetermined timing to start emitting the odorant. The output signal may include, for example, information for controlling the amount of odorant emitted. The information for controlling the amount of odorant emitted may include information for controlling the intensity of odorant emission or information for controlling the time for odorant emission. Here, the predetermined timing is based on, for example, an operation input performed by the subject H1 present in area A0.

[0050] After outputting the first output signal, if the odor intensity estimated by the estimation unit 12 is equal to or less than the threshold, the output unit 13 re-outputs the output signal to the emission unit 42. Then, when the output signal is input, the emission unit 42 re-emits the odor substance into the area A0 where the detection unit 32 is located. This allows the subject H1 to continue to sense the odor by re-emitting the odor substance to which the subject H1 has become accustomed.

[0051] In the second embodiment, the output unit 13 outputs an output signal corresponding to an odor substance whose odor intensity is below a threshold to the emitter 42. The output signal includes specific information for identifying the odor substance to be emitted. The emitter 42 then re-emits the odor substance corresponding to the output signal from among the multiple odor substances into the area A0. This allows the subject H1 to continue to sense the odor of each odor substance by re-emitting the odor substance to which the subject H1 has become more accustomed.

[0052] The odor intensity threshold may be set as appropriate. Here, the odor intensity threshold may be different for each type of odorant, or may be common regardless of the type of odorant. In the second embodiment, the odor intensity threshold is set common regardless of the type of odorant. In the second embodiment, the odor intensity threshold is, for example, odor intensity 2. This allows the odorants to be released to an extent that at least the subject H1 can detect the odor of each odorant.

[0053] (5) Operation Next, the operation of the odor emission system 100 (or the estimation system 1) according to the second embodiment will be described with reference to Fig. 5. The series of processes shown in Fig. 5 are processes that are continuously performed after the emission unit 42 of the emission system 100 emits an odorant.

[0054] The estimation system 1 acquires odorant detection information from the detection unit 32 (step S1). More specifically, the estimation system 1 of the second embodiment acquires detection information for each type of odorant. The process of step S1 in FIG. 5 corresponds to the acquisition step of the estimation method.

[0055] Next, the estimation system 1 estimates the odor intensity of the odorant for the subject H1 based on the acquired detection information and adaptation information. More specifically, the estimation system 1 of the second embodiment estimates the odor intensity for each type of odorant. The process of step S2 in Figure 5 corresponds to the estimation step of the estimation method.

[0056] Next, the estimation system 1 determines whether the odor intensity is equal to or less than a threshold value (step S3). More specifically, the estimation system 1 of the second embodiment determines whether the odor intensity is equal to or less than a threshold value for each type of odor substance.

[0057] If the estimation system 1 determines that there is no odor substance whose odor intensity is below the threshold (step S3: No), it terminates the series of processes shown in Fig. 5. On the other hand, if the estimation system 1 determines that there is an odor substance whose odor intensity is below the threshold (step S3: Yes), it outputs an output signal to the emitter 42 to emit the odor substance whose odor intensity is below the threshold (step S4), and terminates the series of processes shown in Fig. 5. The processes of steps S3 and S4 in Fig. 5 correspond to the output steps of the estimation method.

[0058] The flowchart shown in FIG. 5 is merely an example, and the order of the processes may be changed as appropriate, and processes may be added or deleted as appropriate.

[0059] (6) Modifications Modifications of the first and second embodiments are listed below.

[0060] (6.1) Variation 1 The estimation unit 12 of variation 1 estimates the odor intensity of the subject H1 against the odorous substance based on the detection information acquired by the acquisition unit 11 from the detection unit 32, adaptation information regarding the adaptation to the odorous substance, and subject information indicating the adaptation pattern of the subject H1.

[0061] It is known that each person perceives odors differently, and the adaptation patterns to odorants also differ from person to person, with multiple adaptation patterns for each odorant.

[0062] Figures 6A to 6E are schematic diagrams showing examples of odor adaptation patterns for each person. Figure 6A shows an exponential adaptation pattern in which odor intensity decreases exponentially over time. Generally, most people are classified as having an exponential adaptation pattern. Figure 6B shows an exponential & rectangular adaptation pattern in which odor intensity decreases exponentially over time and then maintains a certain value. Figure 6C shows a fluctuating adaptation pattern in which the time-series change in odor intensity does not show a fixed trend. Figure 6D shows a constant adaptation pattern in which odor intensity remains relatively constant over time. Figure 6E shows an ascending adaptation pattern in which odor intensity increases over time.

[0063] The subject information is information indicating which adaptation pattern the subject H1 is classified into among multiple adaptation patterns as shown in FIGS. 6A to 6E. Which adaptation pattern the subject H1 is classified into can be determined, for example, by conducting an adaptation pattern evaluation experiment in advance in which the subject H1 is a panel (in other words, a person who smells odors). For example, in an adaptation pattern evaluation experiment, the panel sniffs odors for a predetermined period of time and responds with a value corresponding to each predetermined period of time. For example, in an adaptation pattern evaluation experiment, the panel responds with a "4" if they perceive an odor as strong, and a "2" if they perceive an odor as weak.

[0064] In the first modification, the subject information is information indicating the adaptation pattern of each person including the subject H1. The subject information is stored in the storage unit 22, for example.

[0065] The estimation unit 12 of the first modification estimates the odor intensity of the subject H1 by performing calculations using, for example, the odorant detection information, the adaptation information, and the subject information corresponding to the subject H1. This allows for further improvement in the estimation accuracy of the odor intensity.

[0066] (6.2) Modification 2 In Modification 2, after the output unit 13 has re-emitted multiple odor substances (e.g., the first odor substance and the second odor substance) constituting a predetermined complex odor (first complex odor), if the odor intensity of all of the multiple odor substances constituting the first complex odor becomes equal to or below a threshold, the output unit 13 may output an output signal to the emitter 42 to emit an odor substance (third odor substance) different from the multiple odor substances constituting the first complex odor. This changes the odor sensed by the subject H1, which can refresh the subject H1's mood or promote the subject H1's return to adaptation to the first complex odor.

[0067] Furthermore, after the multiple odor substances constituting the first complex odor (e.g., the first odor substance and the second odor substance) have been re-emitted, if the odor intensity of the subject H1 for all of the multiple odor substances falls below a threshold, the output unit 13 may output an output signal to the emitter 42 to emit a complex odor (second complex odor) different from the first complex odor. Each of the multiple odor substances constituting the second complex odor is a different odor substance from the multiple odor substances constituting the first complex odor.

[0068] (6.3) Modification 3 The odor emission system 100 of Modification 3 detects a complex odor, estimates the odor intensity of the complex odor for subject H1, and emits the complex odor (i.e., the multiple odor substances that make up the complex odor) if the estimated odor intensity is equal to or less than a threshold. While the odor emission system 100 of Embodiment 2 detects each odor substance that makes up the complex odor and performs predetermined processing such as estimating odor intensity for each detected odor substance, the odor emission system 100 of Modification 3 detects a complex odor and performs predetermined processing such as estimating odor intensity for each detected complex odor.

[0069] The detection unit 32 of the third modification is configured to be able to detect complex odors such as natural chocolate, aroma oil (fragrance), and the like.

[0070] The acquisition unit 11 of the third modification acquires detection information of complex odors from the detection unit 32 .

[0071] The estimation unit 12 of the third modification estimates the odor intensity of the subject H1 for the complex odor based on the detection information acquired by the acquisition unit 11 and the adaptation information related to the adaptation to the complex odor. The estimation unit 12 of the third modification estimates the odor intensity for each complex odor. For example, the estimation unit 12 estimates the odor intensity for each complex odor by performing a calculation using the detection information for the complex odor and the adaptation information for the complex odor. Here, the adaptation information for the complex odor is stored, for example, in the storage unit 22. The adaptation information for the complex odor may be, for example, information including a mathematical formula that mathematically expresses the adaptation pattern for each complex odor, or information in a table that classifies complex odors by adaptation pattern.

[0072] In addition, the estimation unit 12 of variant example 3 may estimate the odor intensity of subject H1 for the complex odor based on detection information for the complex odor, adaptation information for the complex odor, and subject information indicating subject H1's adaptation pattern to the complex odor.

[0073] The output unit 13 of the third modification outputs a first output signal to the emission unit 42 at a predetermined timing to start emitting the complex odor. The output signal may include, for example, information for controlling the amount of the complex odor emitted. The information for controlling the amount of the complex odor emitted may include information for controlling the intensity of the complex odor emission or information for controlling the time for emitting the complex odor. Here, the predetermined timing is based on, for example, an operation input performed by a subject H1 present in the area A0.

[0074] After outputting the first output signal, the output unit 13 in Modification 3 re-outputs an output signal to the emitter 42 if the odor intensity estimated by the estimation unit 12 is equal to or less than the threshold. When an output signal is input, the emitter 42 re-emits the complex odor into the area A0 where the detection unit 32 is located. This allows the subject H1 to continue to sense the odor by re-emitting the complex odor to which the subject H1 has adapted.

[0075] (6.4) Other Modifications Functions equivalent to those of the estimation system 1 according to Embodiments 1 and 2 may be embodied as an estimation method, a (computer) program, or a non-transitory recording medium having a program recorded thereon. An estimation method according to one aspect is an estimation method executed by one or more processors. The estimation method includes an acquisition step, an estimation step, and an output step. In the acquisition step, detection information relating to signal intensity corresponding to the amount of the detected odorant is acquired from the detection unit 32 that detects the odorant. In the estimation step, the odor intensity of the subject H1 relative to the odorant is estimated based on the detection information and adaptation information relating to the adaptation to the odorant. In the output step, if the odor intensity estimated in the estimation step is equal to or less than a threshold, an output signal is output to the emission unit 42 that emits the odorant. A program according to one aspect is a program for causing one or more processors to execute the above estimation method.

[0076] The execution entity of the estimation system 1 or estimation method in the present disclosure includes a computer system. The computer system is primarily composed of a processor and memory as hardware. The processor executes a program stored in the memory of the computer system to realize the function of the execution entity of the estimation system 1 or estimation method in the present disclosure. The program may be pre-recorded in the memory of the computer system, provided via a telecommunications line, or provided by being recorded on a non-transitory recording medium readable by the computer system, such as a memory card, optical disk, or hard disk drive. The processor of the computer system is composed of one or more electronic circuits including a semiconductor integrated circuit (IC) or a large-scale integrated circuit (LSI). The integrated circuits, such as ICs or LSIs, are referred to by different names depending on the degree of integration, and include integrated circuits called system LSIs, very large-scale integrations (VLSIs), or ultra-large-scale integrations (ULSIs). Furthermore, field-programmable gate arrays (FPGAs), which are programmed after the LSI is manufactured, or logic devices capable of reconfiguring the connections within the LSI or the circuit partitions within the LSI, can also be used as processors. The electronic circuits may be integrated into one chip or distributed across multiple chips. The chips may be integrated into one device or distributed across multiple devices. The computer system referred to here includes a microcontroller having one or more processors and one or more memories. Therefore, the microcontroller is also composed of one or more electronic circuits including a semiconductor integrated circuit or a large-scale integrated circuit.

[0077] Furthermore, it is not essential for the estimation system 1 that multiple functions are concentrated in one housing, and the components of the estimation system 1 may be distributed across multiple housings. Furthermore, at least some of the functions of the estimation system 1, for example, some of the functions of the information device 2, may be realized by the cloud (cloud computing) or the like.

[0078] In the second embodiment, at least some of the functions of the odor emission system 100 that are distributed among multiple devices may be integrated into a single housing. For example, some of the functions of the odor emission system 100 that are distributed among the information device 2 and the emission device 4 may be integrated into a single housing. For example, all of the functions of the estimation system 1, the functions of the detection unit 32 of the sensor 3, and the functions of the emission unit 42 of the emission device 4 may be integrated into a single housing.

[0079] The output unit 13 may output an output signal so that the odor intensity estimated by the estimation unit 12 falls within a predetermined range. Generally, within the range in which people can distinguish between types of odor, people often find odors that are comfortable between odor intensity 2 and odor intensity 3. The output unit 13 may output an output signal so that the odor intensity of the subject for each odor substance falls between odor intensity 2 and odor intensity 3. This makes it possible to emit an odor at a level that subject H1 finds comfortable.

[0080] (Summary) As is clear from the above-described embodiments and modifications, the estimation system (1) according to the first aspect includes an acquisition unit (11), an estimation unit (12), and an output unit (13). The acquisition unit (11) acquires detection information relating to signal intensity corresponding to the amount of the detected odorant from a detection unit (32) that detects the odorant. The estimation unit (12) estimates the odor intensity of the subject (H1) for the odorant based on the detection information and adaptation information relating to adaptation to the odorant. The output unit (13) outputs an output signal to an emission unit (42) that emits the odorant when the odor intensity estimated by the estimation unit (12) is equal to or less than a threshold.

[0081] According to this aspect, it is possible to improve the accuracy of estimating odor intensity.

[0082] In the estimation system (1) according to the second aspect, in the first aspect, when an output signal is input, the emission unit (42) emits an odor substance toward the area (A0) where the detection unit (32) is located.

[0083] According to this aspect, the subject (H1) can be made to sense the odor continuously.

[0084] In the estimation system (1) according to the third aspect, in the first or second aspect, the detection unit (32) is configured to be able to detect multiple types of odor substances. The acquisition unit (11) acquires detection information for each type of odor substance. The estimation unit (12) estimates odor intensity for each type of odor substance. The output unit (13) outputs an output signal corresponding to an odor substance whose odor intensity is equal to or less than a threshold value, among the multiple types of odor substances, to the emission unit (42).

[0085] According to this aspect, it is possible to improve the accuracy of estimating the odor intensity for each odor substance.

[0086] In the estimation system (1) relating to the fourth aspect, in the third aspect, the emission unit (42) emits an odor substance corresponding to the output signal from among multiple types of odor substances into the area (A0) where the detection unit (32) is located.

[0087] According to this aspect, the odor of each odorous substance can be sensed.

[0088] In the estimation system (1) according to the fifth aspect, in any of the first to fourth aspects, the estimation unit (12) estimates odor intensity based on the detection information, adaptation information, and subject (H1) information indicating the adaptation pattern of the subject (H1).

[0089] According to this aspect, it is possible to further improve the accuracy of estimating odor intensity.

[0090] The configurations other than the first aspect are not essential for the estimation system (1) and can be omitted as appropriate.

[0091] The estimation method according to the sixth aspect is an estimation method executed by one or more processors. The estimation method includes an acquisition step, an estimation step, and an output step. In the acquisition step, detection information regarding signal intensity corresponding to the amount of the detected odorant is acquired from a detection unit (32) that detects the odorant. In the estimation step, the odor intensity of the subject (H1) for the odorant is estimated based on the detection information and adaptation information regarding adaptation to the odorant. In the output step, if the odor intensity estimated in the estimation step is equal to or less than a threshold, an output signal is output to an emission unit (42) that emits the odorant.

[0092] According to this aspect, it is possible to improve the accuracy of estimating odor intensity.

[0093] A program according to a seventh aspect is a program for causing one or more processors to execute the estimation method according to the sixth aspect.

[0094] According to this aspect, it is possible to improve the accuracy of estimating odor intensity.

[0095] REFERENCE SIGNS LIST 1 estimation system 11 acquisition unit 12 estimation unit 13 output unit 32 detection unit 42 emission unit A0 area H1 subject

Claims

1. An estimation system comprising: an acquisition unit that acquires detection information regarding signal strength corresponding to the amount of detected odorant from a detection unit that detects the odorant; an estimation unit that estimates the odor intensity of the subject to the odorant based on the detection information and adaptation information regarding adaptation to the odorant; and an output unit that outputs an output signal to an emission unit that emits the odorant when the odor intensity estimated by the estimation unit is below a threshold.

2. The estimation system according to claim 1, wherein the emitter emits the odor substance into an area where the detector is located when the output signal is input.

3. The estimation system described in claim 1 or 2, wherein the detection unit is configured to be able to detect multiple types of odor substances, the acquisition unit acquires the detection information for each type of odor substance, the estimation unit estimates the odor intensity for each type of odor substance, and the output unit outputs the output signal corresponding to the odor substance, among the multiple types of odor substances, whose odor intensity is below the threshold, to the emission unit.

4. The estimation system according to claim 3, wherein the release unit releases the odor substance corresponding to the output signal from among the plurality of types of odor substances into an area where the detection unit is located.

5. An estimation system according to any one of claims 1 to 4, wherein the estimation unit estimates the odor intensity based on the detection information, the adaptation information, and subject information indicating the adaptation pattern of the subject.

6. An estimation method executed by one or more processors, comprising: an acquisition step of acquiring detection information regarding signal strength corresponding to the amount of detected odorant from a detection unit that detects the odorant; an estimation step of estimating the odor intensity of the subject to the odorant based on the detection information and adaptation information regarding adaptation to the odorant; and an output step of outputting an output signal to an emission unit that emits the odorant if the odor intensity estimated in the estimation step is below a threshold.

7. A program for causing said one or more processors to execute the estimation method according to claim 6.

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