Information processing device, intellectual productivity improvement system, and program

Abstract

An information processing device according to the present invention comprises an information acquisition unit that acquires environment information for an indoor space in which a user is present, an estimation unit that inputs the environment information into an estimation model to estimate a reaction index that is an index obtained by quantifying the degree to which a physical reaction or a psychological reaction that increases the intellectual productivity of the user has occurred in the user, and a control unit that performs environment control for the indoor space on the basis of the reaction index. The estimation model is built on the basis of subjective data, behavioral response data, and / or physiological response data for the user for an intellectual production activity.

Description

Information Processing Device, Intellectual Productivity Improvement System, and Program

[0001] The present disclosure relates to an information processing device, an intellectual productivity improvement system, and a program used for environmental control of an indoor space.

[0002] In order to realize an environment comfortable for the human body in an indoor space, a method of performing information processing using output values of various sensors and performing environmental control of the indoor space is generally implemented. For example, Patent Document 1 discloses an environmental control system that estimates a person's state using human information about people in an indoor space, the indoor environment, and a human model that simulates a person, and controls an air conditioning system so that the person's state becomes a target state.

[0003] Japanese Patent Application Laid-Open No. 2023-071097

[0004] The human model used in the environmental control system of Patent Document 1 simulates physical parts and movements such as the human body's skeleton, joints, and skin, and the input human information is biological information such as weight, age, and gender, and information such as ethnicity or geographical information. However, the state of the person represented by the human model of Patent Document 1 has nothing to do with the user's intellectual productivity, and there are cases where the conventional environmental control system cannot achieve an improvement in intellectual productivity.

[0005] The present disclosure solves the above problems, and an object thereof is to provide an information processing device, an intellectual productivity improvement system, and a program capable of realizing an environment for improving the intellectual productivity of a user in an indoor space.

[0006] The information processing device according to the present disclosure includes an information acquisition unit that acquires environmental information of an indoor space where a user exists, and an estimation unit that estimates a reaction index, which is an index obtained by quantifying the degree to which a physical or psychological reaction that enhances the user's intellectual productivity occurs in the user by inputting the environmental information into an estimation model, and a control unit that performs environmental control of the indoor space based on the reaction index. The estimation model is constructed based on at least any one of subjective data, behavioral response data, and physiological response data of the user regarding intellectual production activities.

[0007] The intellectual productivity improvement system relating to this disclosure comprises an information processing device, an environmental information measuring device that measures environmental information and transmits it to the information processing device, and an environmental control device that controls the environment of an indoor space based on environmental control information estimated by the information processing device.

[0008] The program relating to this disclosure is a program that causes a computer to execute an information acquisition step of acquiring environmental information of the indoor space in which a user is present, an estimation step of inputting the environmental information into an estimation model to estimate a response index, which is an index that quantifies the extent to which the user experiences physical or psychological responses that enhance the user's intellectual productivity, and a control step of controlling the indoor space environment based on the response index, wherein the estimation model is constructed based on at least one of the user's subjective data, behavioral response data, and physiological response data regarding intellectual production activities.

[0009] According to this disclosure, the information processing device estimates response indicators related to the user's intellectual productivity using an estimation model constructed based on at least one of the user's subjective data, behavioral response data, and physiological response data regarding intellectual production activities, and controls the indoor environment based on the estimated response indicators. Therefore, it is possible to create an environment that improves the user's intellectual productivity in the indoor space.

[0010] This is a schematic diagram of the intelligent productivity improvement system according to Embodiment 1. This is a schematic diagram of the information processing device according to Embodiment 1. This is a hardware configuration diagram showing an example of the configuration of the control device according to Embodiment 1. This is a hardware configuration diagram showing an example of the configuration of the control device according to Embodiment 1. This is a flowchart showing the operation flow of the information processing device according to Embodiment 1.

[0011] Hereinafter, embodiments of the information processing device 1 and the intelligent productivity improvement system 100 equipped with the information processing device 1 according to this disclosure will be described with reference to the drawings. In each figure, components denoted by the same reference numerals are the same or equivalent components, and this is common throughout the entire specification.

[0012] Embodiment 1. Figure 1 is a schematic diagram of the intellectual productivity improvement system 100 according to Embodiment 1. The intellectual productivity improvement system 100 of this embodiment improves the intellectual productivity of the user by controlling the environment of the indoor space R where the user is located. Intellectual productivity refers to the efficiency of producing results from intellectual production activities such as intellectual labor in an office. As shown in Figure 1, the intellectual productivity improvement system 100 of this embodiment consists of an information processing device 1, environmental information measuring devices 2a to 2c, and environmental control devices 3a to 3c. The information processing device 1 is connected to the environmental information measuring devices 2a to 2c and the environmental control devices 3a to 3c via wired or wireless communication. For wired or wireless communication, an interface conforming to a communication standard such as Bluetooth®, Wi-Fi®, ZigBee®, LTE®, or LoRaWAN® is used.

[0013] The information processing device 1 is a terminal device such as a PC, smartphone, or tablet, or a server device. Based on various data obtained from the environmental information measuring devices 2a to 2c, the information processing device 1 realizes a virtual space that functions as a digital twin of the indoor space R. Functioning as a digital twin means that the virtual space virtually reproduces the environment of the indoor space R on a computer, like a twin of the indoor space R. As will be described in detail later, in the virtual space reproduced as a digital twin, the information processing device 1 estimates the user's response index related to the user's intellectual productivity and controls the environmental control devices 3a to 3c to improve the response index.

[0014] Environmental information measuring devices 2a to 2c are devices that measure environmental information of the indoor space R in which the user is present. Environmental information represents physical quantities that are measured and quantified in the indoor space R. Environmental information includes indoor temperature, humidity, CO2 ２ The data includes at least one of the following: concentration, dust concentration, illuminance, light spectrum, odor intensity, odor pattern, sound pressure level, and sound spectrum. The environmental information measuring devices 2a to 2c include a temperature sensor for measuring the room temperature, a humidity sensor for measuring humidity, and CO2. ２ Measuring CO concentration ２The sensor is at least one of the following: a dust sensor for measuring dust concentration, a light sensor for measuring illuminance and light spectrum, an odor sensor for measuring odor intensity and odor pattern, and a sound volume sensor for measuring sound pressure level and sound spectrum. ２ Alternatively, a gas sensor may be provided to measure the gas concentration of other pre-set types of gases. Each of the environmental information measuring devices 2a to 2c may measure different types of environmental information from the above-mentioned environmental information, or they may measure the same type of environmental information. Hereinafter, unless otherwise distinguished, the environmental information measuring devices 2a to 2c will be referred to as environmental information measuring device 2. Figure 1 shows three environmental information measuring devices 2, but the number of environmental information measuring devices 2 may be two or fewer, or four or more. The environmental information measured by the environmental information measuring devices 2 is converted from an analog signal to a digital signal using AD conversion and then transmitted to the information processing device 1.

[0015] Environmental control devices 3a to 3c are devices that control the environment of the indoor space R where the user is present. Specifically, environmental control devices 3a to 3c are at least one of the following: an air conditioner, a humidifier, a dehumidifier, a ventilation system, an air purifier, a lighting system, an acoustic device such as a speaker (including a sound-dampening device), an aroma diffuser that emits a fragrance, and an odor-removing device. The air conditioner, humidifier, dehumidifier, and ventilation system control the temperature and humidity of the room. The ventilation system and air purifier control the CO2 in the room. ２ The system controls the concentration, dust concentration, odor intensity, and odor pattern. The lighting system controls the illuminance and light spectrum in the room. The acoustic system controls the sound pressure level and sound spectrum in the room. The fragrance diffuser and deodorizer control the odor intensity and odor pattern in the room. Hereinafter, unless otherwise specified, environmental control devices 3a to 3c will be referred to as environmental control device 3. Figure 1 shows three environmental control devices 3, but the number of environmental control devices 3 may be two or fewer, or four or more. However, it is desirable that the intelligent productivity improvement system 100 has environmental control devices 3 that correspond to the type of environmental information measured by the environmental information measuring device 2.

[0016] The intelligent productivity improvement system 100 according to Embodiment 1 is characterized in that, firstly, the information processing device 1 estimates the user's response index based on the estimation model 123 (described later), environmental information measured by the environmental information measuring device 2, spatial information, user information, and scene information. Secondly, the information processing device 1 calculates environmental control information based on the response index and controls the environmental control device 3 based on the estimated environmental control information.

[0017] The response index is a numerical indicator that quantifies the extent to which a user experiences physical and psychological responses that enhance their current or expected future intellectual productivity. The elements on which the response index is estimated differ depending on the situation in which the user is spending time. Furthermore, the required level of the response index (target value) also differs depending on the situation in which the user is spending time. The situations in which a user spends time in the indoor space R change over time, depending on the user's state, such as the user's position and activities within the indoor space R, as well as changes in the conditions of the indoor space R. While numerous situations can be envisioned for a user, this disclosure assumes the following three situations related to intellectual productivity activities as examples.

[0018] The first scenario is one in which the user is highly focused on a task. Specifically, the first scenario is assumed to be a situation in which the user is performing simple manual labor tasks such as manual calculations or editing in spreadsheet software. The first scenario also includes situations in which the user is engaged in non-creative activities. The desired outcome in the first scenario is, for example, the progress of the task. The response indicator in the first scenario is an indicator that measures the user's current intellectual productivity. For example, if the user's concentration is high, the user can be expected to complete the task in a short time, so the response indicator in the first scenario is said to be high. Also, if the user's psychological stress is low, the user can easily tackle difficult tasks, so the response indicator in the first scenario is said to be high.

[0019] The second scenario is one in which users are generating ideas. Specifically, this scenario includes situations where users are using their ingenuity to generate ideas, or engaging in conversations and discussions to generate ideas. Here, ingenuity refers to the preliminary stages of idea generation, such as implementing means to generate ideas or providing others with effective triggers for idea generation. The second scenario also includes situations where users are not fully engaged in the activity. The desired outcomes in the second scenario are the coming up with ideas and effective methods or tools for generating ideas, and the activation of conversations and discussions. The response index in the second scenario is an index that measures the user's current intellectual productivity. For example, a relaxed state of mind makes it easier for ideas to come to mind, so the response index in the second scenario can be said to be high. Similarly, a low level of tension in the user allows for more active participation in meetings, so the response index in the second scenario can also be said to be high.

[0020] The third scenario is one in which the user is resting. In the third scenario, although no results are produced during the rest period, it is expected that intellectual productivity will increase in the future (after the rest period) as a result of the intellectual productivity being carried out efficiently after the rest period. In other words, the third scenario is a situation in which the information processing device 1 aims to produce the results described in the first or second scenario after the rest period. The response index in the third scenario is an index that targets the user's future intellectual productivity. For example, if the user's fatigue level is low, it is expected that the work will be completed in a short time after the rest period, and therefore the response index in the third scenario is high.

[0021] Spatial information refers to the physical information of the indoor space R to be controlled, and includes, for example, the volume of the indoor space R, the shape of the indoor space R, and the ceiling height. Spatial information may be input to the information processing device 1 by the user when estimating the response index, or it may be input to the information processing device 1 when the room in which the user will stay is determined.

[0022] User information is information used to identify a user, and may include, for example, the user's name, ID, and an image showing part or all of the user's body (e.g., face and fingerprints). User information is input to the information processing device 1 by the user when estimating response indicators. Alternatively, when estimating response indicators, the user may be identified by analyzing an image of the user taken by a camera connected to the information processing device 1 that photographs the indoor space R.

[0023] Scene information is information used to identify the scenes in which the user spends time. The scene information only needs to be able to identify at least the first to third scenes described above. Scene information is input into the information processing device 1 by the user when estimating response indicators. Alternatively, when estimating response indicators, the scenes in which the user spends time may be identified by analyzing images captured by a camera that photographs the indoor space R connected to the information processing device 1. Furthermore, the scenes in which the user spends time may be identified by analyzing schedules stored on a PC terminal or other device used by the user.

[0024] Figure 2 is a schematic diagram of the information processing device 1 according to Embodiment 1. As shown in Figure 2, the information processing device 1 comprises a control device 11, a storage device 12, and an input device 13.

[0025] The control device 11 has, as functional units, a model building unit 111, an information acquisition unit 112, an estimation unit 113, and a control unit 114. Figures 3 and 4 are hardware configuration diagrams showing an example of the configuration of the control device 11 according to Embodiment 1. As shown in Figures 3 and 4, the control device 11 is composed of a processor 602 such as a CPU (Central Processing Unit), a DSP (Digital Signal Processor), or a GPU (Graphics Processing Unit) that executes a program stored in dedicated hardware or memory 603.

[0026] As shown in Figure 3, when the control device 11 is dedicated hardware, the control device 11 is composed of a processing circuit 601. The processing circuit 601 may be, for example, a single circuit, a composite circuit, an ASIC (application specific integrated circuit), an FPGA (field-programmable gate array), or a combination thereof. The model building unit 111, information acquisition unit 112, estimation unit 113, and control unit 114 of the control device 11 may be implemented with separate hardware or with a single piece of hardware.

[0027] As shown in Figure 4, when the control device 11 is configured with a processor 602, the model building unit 111, information acquisition unit 112, estimation unit 113, and control unit 114 of the control device 11 are realized by software, firmware, or a combination of software and firmware. The software or firmware is written as a program and stored in the memory 603 that constitutes the storage device 12. The processor 602 and the memory 603 are connected to each other so as to be able to communicate via a bus 604. The processor 602 realizes the model building unit 111, information acquisition unit 112, estimation unit 113, and control unit 114 by reading and executing the program stored in the memory 603. Note that the control device 11 may have multiple processors 602 and multiple memories 603, which work together to realize each function of the control device 11. Alternatively, some of the functions of the control device 11 may be realized by dedicated hardware, and some may be realized by software or firmware.

[0028] Returning to Figure 2, the model construction unit 111 constructs the estimation model 123. The estimation model 123 is a model that hypothetically assumes the physical and mental (psychological) responses of a user when a stimulus is applied. Here, it is assumed that environmental conditions are determined by a combination of values ​​of various environmental information. The estimation model 123 generalizes the relationship between multiple environmental conditions and the user's response index I under each environmental condition. As an example, suppose the variables that define the environmental conditions are temperature T, illuminance S, odor intensity O, and sound pressure level P. In this case, the response index I can be expressed by a linear function as shown in equation (1) below. Equation (1) is the sum of terms obtained by multiplying each of temperature T, illuminance S, odor intensity O, and sound pressure level P by the weighted first correlation coefficient k1, second correlation coefficient k2, third correlation coefficient k3, and fourth correlation coefficient k4, respectively. It is assumed that the larger the value of the response index I, the stronger the response that increases intellectual productivity is experienced by the user. I = k1・T + k2・S + k3・O + k4・P ... (1) Below, we will describe an example of how the model building unit 111 constructs the estimated model 123.

[0029] First, as described above, the response index I is an index that quantifies the extent to which physical and mental responses that enhance current or expected future intellectual productivity are occurring in the user. The extent to which physical and mental responses that enhance intellectual productivity are occurring in the user is evaluated based on at least one of subjective data, behavioral response data, and physiological response data. That is, the model building unit 111 constructs an estimation model 123 for estimating the response index I based on at least one of subjective data, behavioral response data, and physiological response data.

[0030] Subjective data, behavioral response data, and physiological response data are data obtained by conducting experiments on multiple subjects who were users in the indoor space R in the past. Subjective data, behavioral response data, and physiological response data are stored in the index DB (database) 121. The index DB 121 records the acquired subjective data, behavioral response data, and physiological response data for each of the multiple users in a matrix format.

[0031] Subjective data is data that quantifies the subjective mood and emotions of users regarding their intellectual productivity activities when they are exposed to various stimuli. Specifically, subjective data consists of multiple environmental conditions and scores that indicate the user's subjective mood and emotions under each environmental condition. Subjective data should show higher scores the better the user's subjective mood and emotions are. Subjective data is obtained using survey methods such as POMS (Profile of Mood States), self-awareness questionnaires, SD (Semantic Differential) method, and MMSE (Mini Mental State Examination), which are used in the field of psychology.

[0032] Behavioral response data is quantitative data that shows the results of a user's behavioral responses related to their intellectual productivity activities when given various stimuli. Specifically, behavioral response data consists of multiple environmental conditions and scores indicating the user's memory and cognitive abilities under each environmental condition. The higher the user's memory and cognitive abilities, the higher the score in the behavioral response data. Behavioral response data is acquired using methods such as the Advanced Trail Making Test (ATMT), the flicker method, and the N-back task.

[0033] Physiological response data is quantitative data that shows an index of the physiological response results related to the user's intellectual productivity when the user is subjected to various stimuli. Specifically, physiological response data consists of multiple environmental conditions and a score indicating the user's mental state under each environmental condition. The higher the score in the physiological response data, the greater the degree of mental stability of the user. Physiological response data can be obtained, for example, by measuring electroencephalogram (EEG), R-R interval, heart rate variability, and the electrical potential of parts of the user's body (e.g., eyes, muscles, and skin).

[0034] As described above, the index DB 121 stores subjective data, behavioral response data, and physiological response data under multiple environmental conditions. The model building unit 111 calculates a response index I corresponding to several sample environmental conditions by referring to the scores under each sample environmental condition. The method for calculating the response index I is not particularly limited, but as an example, the response index I is calculated by multiplying each of the subjective data, behavioral response data, and physiological response data by a coefficient to adjust the scale between the data, and then adding these together.

[0035] The model building unit 111 analyzes the relationship between the sampled environmental conditions and the calculated response index I, and calculates highly valid setting values ​​for the first to fourth correlation coefficients k1 to k4 so that the user's response index I in the indoor space R can be accurately estimated for environmental conditions other than those sampled. The method of analysis is not particularly limited, but for example, by changing only the value of one piece of environmental information included in the environmental conditions and fixing the values ​​of the other pieces of environmental information, it is possible to estimate the setting values ​​that should be set for the correlation coefficients multiplied by the environmental information whose value has been changed. Alternatively, linear interpolation may be performed based on the relationship between the sampled environmental conditions and the calculated response index I. In this way, the model building unit 111 generalizes the relationship between multiple environmental conditions and the response index I.

[0036] Furthermore, the response index I may be calculated by changing the variables that define the environmental conditions (environmental information) depending on the situation in which the user is experiencing. For example, in the first and second situations, the variables that define the environmental conditions may be changed to CO ２ In contrast to adding concentration, in the third scenario, CO is derived from the variables that define the environmental conditions. ２The concentration may be adjusted. Furthermore, the type of data used as the basis for constructing the estimation model 123 may be changed depending on the situation in which the user is spending time. For example, in the first and second situations, the estimation model 123 may be constructed based on subjective data, behavioral response data, and physiological data, while in the third situation, the estimation model 123 may be constructed based only on subjective data. For this reason, the model construction unit 111 constructs multiple estimation models 123 with different variables that define environmental conditions (environmental information) and different types of data used as the basis for constructing the estimation model, depending on the situation in which the user is spending time. The model construction unit 111 stores the multiple estimation models 123 in the storage device 12.

[0037] The model building unit 111 performs the above procedure for each user and calculates a unique first to fourth correlation coefficient k1 to k4 for each user. The model building unit 111 stores the calculated settings for the first to fourth correlation coefficients k1 to k4 in the coefficient DB (database) 122 of the storage device 12 for each user. Furthermore, if, as a result of analyzing the relationship between the sampled environmental conditions and the response index I, the model building unit 111 calculates multiple correlation coefficient settings that are considered highly valid for a particular user for some or all of the first to fourth correlation coefficients k1 to k4, it stores the multiple calculated settings in the coefficient DB 122 for each user as candidates to set for the first to fourth correlation coefficients k1 to k4. At this time, matrix-format data showing the correspondence between the first to fourth correlation coefficients k1 to k4 and the multiple settings that can be set for the first to fourth correlation coefficients k1 to k4 is stored in the coefficient DB 122.

[0038] The information acquisition unit 112 communicates with the environmental information measuring device 2 via wired or wireless communication to acquire current environmental information of the indoor space R from the environmental information measuring device 2. The information acquisition unit 112 also acquires spatial information, user information, and scene information input via the input device 13. The information acquisition unit 112 transmits the acquired environmental information, spatial information, user information, and scene information to the estimation unit 113.

[0039] The estimation unit 113 estimates the user's reaction index using the environmental information, spatial information, user information, and scene information acquired by the information acquisition unit 112, the estimation model 123 stored in the storage device 12, and the correlation coefficients stored in the storage device 12. To explain in more detail, first, the estimation unit 113 determines, from a plurality of estimation models 123, an estimation model 123 corresponding to the scene in which the user spends time based on the scene information. Next, the estimation unit 113 determines, based on the user information, the set value of each correlation coefficient to be set in the estimation model 123 from the coefficient DB 122, or candidates for the set values of each correlation coefficient.

[0040] Subsequently, the estimation unit 113 sets the set values of each correlation coefficient determined based on the user information in the estimation model 123 determined based on the scene information. Then, by inputting the environmental information into the estimation model 123, the estimation model 123 outputs the reaction index of the user in the current indoor space R. At this time, if the physical information of the indoor space R indicated by the spatial information has an impact on the reaction index, the reaction index is adjusted. For example, if the ceiling height of the indoor space R is low, the user may feel a sense of oppression, so the reaction index is decreased. Also, if the number of people in the indoor space R can be grasped by a camera or an infrared sensor provided in the indoor space R, when the number of people is large relative to the size of the indoor space R, the user may be concerned about others, so the reaction index is decreased.

[0041] In addition, when the estimation unit 113 acquires candidates for the set values of the correlation coefficients to be set in the estimation model 123 from the coefficient DB 122, the estimation unit 113 sets all the set values that are candidates for each correlation coefficient in the estimation model 123 and outputs a plurality of reaction indexes. Then, the estimation unit 113 determines the most appropriate set value among all the set values that are candidates for each correlation coefficient by comparing the calculated plurality of reaction indexes. The method for obtaining the most appropriate set value is not particularly limited. For example, the set value that maximizes the reaction index when set for each correlation coefficient may be determined as the most appropriate set value.

[0042] The control unit 114 estimates environmental control information to bring the current reaction index, estimated by the estimation unit 113, to a target value. Different target values ​​for the reaction index are pre-set for each user scenario and stored in the storage device 12. The control unit 114 uses a table or formula representing the correspondence between the difference between the target value and the current reaction index and the adjustment value for environmental information to estimate the environmental control information to be instructed to the environmental control device 3. The adjustment value for environmental information is the amount of change in environmental information required to bring the current reaction index to its target value. The control unit 114 obtains the environmental control information by adding or subtracting the adjustment value from the current environmental information measured by the environmental information measuring device 2. The control unit 114 then transmits the obtained environmental control information to the environmental control device 3 and controls the environmental control device 3 to perform environmental control of the indoor space R. Specifically, the control unit 114 uses the indoor temperature, humidity, and CO2 levels included in the environmental control information to control the indoor environment. ２ The environmental control device 3 is controlled to target one of the following: concentration, dust concentration, illuminance, light spectrum, odor intensity, odor pattern, sound pressure level, or sound spectrum. The control unit 114 may change the type of environmental information to be controlled each time it transmits environmental control information to the environmental control device 3 until the reaction index reaches the target value. In this case, the type of environmental information to be controlled may be changed in a predetermined order (for example, in order of greatest influence on the reaction index). Alternatively, the control unit 114 may control only a predetermined type of environmental information until the reaction index reaches the target value. In this case, for example, the environmental information with the greatest influence on the reaction index may be the one to be controlled.

[0043] The storage device 12 is composed of, for example, a volatile or non-volatile semiconductor memory such as a RAM (Random Access Memory), a ROM (Read Only Memory), a flash memory, an EPROM (Erasable and Programmable ROM), an EEPROM (Electrically Erasable and Programmable ROM), an HDD (Hard Disk Drive) or an SSD (Solid State Drive), a tape drive, or a combination thereof. The storage device 12 stores programs used for estimating reaction indices by the control device 11 and for controlling the environment control device 3, as well as various data such as calculation formulas and threshold values used for executing the programs. Further, an index DB 121, a coefficient DB 122, and an estimation model 123 are stored in the storage device 12. Furthermore, spatial information, user information, and scene information may be recorded in the storage device 12.

[0044] The input device 13 is a device for a user to input information to the control device 11 by performing operations, such as a keyboard or a mouse.

[0045] Figure 5 is a flowchart showing the operation flow of the information processing device 1 according to Embodiment 1. When a user performs an operation to start estimating a reaction index via the input device 13, the information processing device 1 starts operating. First, the information acquisition unit 112 acquires spatial information input from the user via the input device 13 (step S1). Next, the information acquisition unit 112 acquires user information input from the user via the input device 13 (step S2). Subsequently, the information acquisition unit 112 acquires scene information input from the user via the input device 13 (step S3). For steps S1 to S3, the spatial information, user information, and scene information may be recorded in the storage device 12 in advance, so that the information acquisition unit 112 can automatically acquire each piece of information from the storage device 12 without receiving an operation from the user. In this case, the information processing device 1 may start operating when a time set in advance by a timer (for example, 30 minutes) has elapsed. Alternatively, spatial information, user information, and scene information may be stored in the storage device 12, while the other information may be input by the user via the input device 13 when the user initiates the estimation of the response index.

[0046] Once spatial information, user information, and scene information are acquired, the estimation unit 113 determines an estimation model 123 corresponding to the scene in which the user is spending time, and candidate setting values ​​to be set for the correlation coefficient of the estimation model 123, based on the scene information and user information (step S4). Subsequently, the information acquisition unit 112 acquires environmental information measured by the environmental information measuring device 2 and inputs the environmental information into the estimation model 123 for which the candidate setting values ​​have been set (step S5). Next, the estimation unit 113 acquires a plurality of reaction indices, which are output results of the estimation model 123 and differ depending on the candidate setting values ​​(step S6), and by comparing the plurality of reaction indices, determines the most appropriate setting value among the candidate setting values ​​to be set for the correlation coefficient (step S7). After that, the estimation unit 113 acquires the reaction indices estimated by the estimation model 123 for which the determined correlation coefficient setting value has been set, corrects them according to the content of the spatial information, updates the user's reaction indices in the current indoor space R, and transmits them to the control unit 114 (step S8).

[0047] The control unit 114 then determines whether the updated reaction index is within the range of the target value (step S9). If the reaction index is within the range of the target value (step S9: YES), the control unit 114 terminates the process without transmitting environmental control information to the environmental control device 3. If the reaction index is outside the range of the target value (step S9: NO), the control unit 114 transmits environmental control information calculated based on the difference between the target value of the reaction index and the current reaction index to the environmental control device 3 (step S10) and attempts to control the environmental information obtained from the indoor space R. After that, the process from step S5 is repeated until the reaction index is within the range of the target value.

[0048] As described above, the information processing device 1 of this embodiment estimates response indicators related to the user's intellectual productivity using an estimation model constructed based on at least one of the user's subjective data, behavioral response data, and physiological response data regarding intellectual production activities, and controls the indoor environment based on the estimated response indicators. Therefore, it is possible to create an environment that improves the user's intellectual productivity in the indoor space.

[0049] Furthermore, technologies for controlling indoor spaces based on indicators such as PMV (Mean Expected Thermal Value) are known. While such technologies can improve user comfort, improving comfort does not necessarily equate to improving intellectual productivity. For example, it is known that intellectual productivity can sometimes be increased by reducing comfort to a certain extent. According to this embodiment, since the indoor environment is controlled based on response indicators related to the user's intellectual productivity, it is possible to create an environment that improves the user's intellectual productivity in the indoor space.

[0050] The above describes the embodiments, but this disclosure is not limited to the above embodiments and can be modified in various ways without departing from the spirit of this disclosure. Furthermore, this disclosure includes all possible combinations of the configurations shown in the above embodiments. For example, the affiliation of each functional unit in the control device 11 of the information processing device 1 is not limited to the examples of the above embodiments. For example, each functional unit of the control device 11 may be divided and implemented in multiple control devices 11, or a part of the functional unit of the control device 11 may be implemented in an external device that can communicate with the information processing device 1. Also, the estimated model 123 stored in the storage device 12 of the information processing device 1 may be stored in an external storage device 12 such as online storage.

[0051] In Embodiment 1, the case where the estimation model 123 is a linear function showing the relationship between multiple environmental information multiplied by a correlation coefficient and a response index was described. However, the estimation model 123 may have other configurations. For example, the estimation model 123 may be a trained model that takes spatial information, user information, scene information, and multiple environmental information as input data and outputs a response index or environmental control information as output data. In this case, the estimation model 123 is trained, for example, by supervised learning using a neural network.

[0052] 1 Information processing device, 2, 2a-2c Environmental information measuring device, 3, 3a-3c Environmental control device, 11 Control device, 12 Storage device, 13 Input device, 100 Intelligent productivity improvement system, 111 Model construction unit, 112 Information acquisition unit, 113 Estimation unit, 114 Control unit, 121 Index DB, 122 Coefficient DB, 123 Estimation model, 601 Processing circuit, 602 Processor, 603 Memory, 604 Bus.

Claims

1. An information processing device comprising: an information acquisition unit that acquires environmental information of an indoor space in which a user is present; an estimation unit that inputs the environmental information into an estimation model to estimate a response index, which is a numerical indicator of the extent to which the user experiences physical or mental responses that enhance the user's intellectual productivity; and a control unit that controls the environment of the indoor space based on the response index, wherein the estimation model is constructed based on at least one of the user's subjective data, behavioral response data, and physiological response data regarding intellectual production activities.

2. The information processing apparatus according to claim 1, wherein the control unit sets different target values ​​for the reaction index according to the situation in which the user is spending time.

3. The information processing apparatus according to claim 2, wherein the situation in which the user spends time is one of the following: a situation in which the user is highly focused, a situation in which the user is generating ideas, or a situation in which the user is resting.

4. The information processing apparatus according to any one of claims 1 to 3, wherein the environmental information includes at least one of temperature, humidity, gas concentration, dust concentration, illuminance, light spectrum, sound pressure level, sound spectrum, odor intensity, and odor pattern.

5. The information processing apparatus according to any one of claims 1 to 4, wherein the estimation model is a linear function in which the reaction index is expressed by a term obtained by multiplying the environmental information by a predetermined coefficient.

6. The information processing apparatus according to any one of claims 1 to 5, wherein the control unit controls an environmental control device that controls the environment of the indoor space, and the environmental control device includes at least one of an air conditioner, a humidifier, a dehumidifier, a ventilation device, an air purifier, a lighting device, a sound device, an aroma diffuser, and a deodorizing device.

7. An intelligent productivity improvement system comprising: an information processing device according to any one of claims 1 to 6; an environmental information measuring device that measures the environmental information and transmits it to the information processing device; and an environmental control device that controls the environment of the indoor space based on environmental control information estimated by the information processing device.

8. A program that causes a computer to perform the following steps: an information acquisition step of acquiring environmental information of an indoor space in which a user is present; an estimation step of inputting the environmental information into an estimation model to estimate a response index, which is an index that quantifies the extent to which the user experiences physical or mental responses that enhance the user's intellectual productivity; and a control step of controlling the environment of the indoor space based on the response index, wherein the estimation model is constructed based on at least one of the user's subjective data, behavioral response data, and physiological response data regarding intellectual production activities.

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