Information processing apparatus, information processing method and program

Abstract

[Problem] To provide an arrangement that improves the quality of user experience. [Solution] An information processing apparatus includes a control unit for generating control information for use by an inhalation device that generates an aerosol by heating an aerosol source based on the control information, the control information defining a time-series transition of parameters corresponding to the temperature at which the aerosol source is heated, wherein the control unit extracts multiple feature values ​​from a first image and generates the control information based on the extracted multiple feature values.

Description

Technical Field

[0001] This disclosure relates to an information processing apparatus, information processing method, and procedure. Background Technology

[0002] Inhalation devices that generate substances to be inhaled by a user are widely used. For example, an inhalation device employs an aerosol source for generating an aerosol, and a matrix (including a flavor source, etc.) for imparting flavor components to the generated aerosol to produce a flavor-imparted aerosol. The user can enjoy the flavor by inhaling the flavor-imparted aerosol produced by the inhalation device. The act of inhaling the aerosol is also referred to below as "inhalation" or "inhalation action." Devices that can be classified as inhalation devices include those used as alternatives to cigarettes, such as heated tobacco products. It should be noted that heated tobacco products are inhalation devices that generate an aerosol by heating an aerosol source.

[0003] In recent years, various technologies related to inhalation devices have been developed to further improve the quality of user experience. For example, PTL 1 indicated below discloses a technology for displaying curves that indicate time-series changes in parameters related to aerosol generation operations, and that the curves are customized based on user manipulation of the displayed curves. Citation List

[0004] Patent documents

[0005] PTL 1: WO 2022 / 101955 A1 Summary of the Invention

[0006] The problem to be solved by the present invention

[0007] However, in the aforementioned technology disclosed in PTL 1, users must painstakingly set the parameters manually.

[0008] Therefore, this disclosure is designed in response to the above-mentioned problems, and the purpose of this disclosure is to provide an arrangement that can improve the quality of user experience. Solution to the problem

[0009] To address the aforementioned problems, one aspect of this disclosure provides an information processing apparatus comprising a control unit for generating control information for use by an inhalation device that generates an aerosol by heating an aerosol source based on the control information, the control information defining a time-series transition of parameters corresponding to the temperature at which the aerosol source is heated, wherein the control unit extracts a plurality of feature values ​​from a first image and generates the control information based on the extracted plurality of feature values.

[0010] Based on each of the plurality of feature values ​​extracted from the first image, the control unit can set the time series transformation of the parameter within each of the plurality of time periods defined in the control information.

[0011] The control unit can divide the first image into multiple second images and extract multiple feature values ​​from the corresponding multiple second images.

[0012] The control unit can set a unit time period corresponding to these second images based on the characteristics of these second images, and can set the time series transformation of the parameter within the unit time period corresponding to these second images based on the feature values ​​in these second images.

[0013] The control unit can set the sequence of unit time periods corresponding to these second images based on the positions of these second images in the first image.

[0014] The control unit can set the length of a unit time period corresponding to these second images based on the area of ​​these second images in the first image.

[0015] The control unit can also set the time series transformation of the parameter within the unit time corresponding to these second images based on the conditions set within these unit time periods.

[0016] The control unit can set the time series transformation of the parameter within a portion of the multiple unit time periods included in the control information based on the multiple feature values ​​extracted from the first image, and can set the time series transformation of the parameter within another portion of these unit time periods according to a preset.

[0017] These feature values ​​can be correlated with RGB (red-green-blue) values.

[0018] The higher the R value, the more the control unit can set the time series transformation of this parameter corresponding to higher temperatures.

[0019] The first image may be a still image, and the control unit may divide the first image into a plurality of second images by dividing the first image in a predetermined direction.

[0020] The first image can be a dynamic image, and the control unit can divide the first image into multiple second images by dividing the first image in the time direction.

[0021] Furthermore, to address the aforementioned issues, another aspect of this disclosure provides an information processing method implemented by a computer and comprising generating control information for use by an inhalation device that generates an aerosol by heating an aerosol source based on the control information. The control information defines a time-series transition of parameters corresponding to the temperature at which the aerosol source is heated. Generating the control information includes extracting multiple feature values ​​from a first image and generating the control information based on the extracted multiple feature values.

[0022] Furthermore, to address the aforementioned issues, another aspect of this disclosure provides a program for enabling a computer to act as a control unit for generating control information for use by an inhalation device that generates an aerosol by heating an aerosol source based on the control information. The control information defines a time-series transition of parameters corresponding to the temperature at which the aerosol source is heated, wherein the control unit extracts multiple feature values ​​from a first image and generates the control information based on the extracted multiple feature values. Advantages of the present invention

[0023] As described above, this disclosure provides an arrangement that can improve the quality of user experience. Attached Figure Description

[0024] [ Figure 1 [Illustration 1] is a view illustrating an example configuration of a system according to an embodiment of this disclosure.

[0025] [ Figure 2 [This is a schematic diagram illustrating an example configuration of an inhalation device according to an embodiment.]

[0026] [ Figure 3 [ ] is a block diagram illustrating an example configuration of a terminal device according to an embodiment.

[0027] [ Figure 4 [ ] is a block diagram illustrating an example configuration of a server according to an embodiment.

[0028] [ Figure 5 [] is a graph of the heating curves shown in Table 1.

[0029] [ Figure 6 [Illustration] is a diagram illustrating the process for generating a heating curve according to an embodiment.

[0030] [ Figure 7 [ ] is a sequence diagram illustrating an example of a processing flow for generating a heating curve implemented by a system according to an embodiment.

[0031] [ Figure 8 [Illustration 1] is a diagram illustrating a first specific example of a process for generating a heating curve according to an embodiment.

[0032] [ Figure 9 [Illustration 1] is a diagram illustrating a second specific example of a process for generating a heating curve according to an embodiment. Detailed Implementation

[0033] The preferred embodiments of this disclosure will now be described in detail with reference to the accompanying drawings. It should be noted that the same reference numerals will be assigned to components having substantially the same functional configuration in the specification and drawings to avoid repetitive descriptions.

[0034] <1. Configuration Example>

[0035] (1) System Configuration Example

[0036] Figure 1 This is a view illustrating a configuration example of system 1 according to an embodiment of this disclosure. Figure 1 As shown, system 1 includes multiple inhalation devices 100 (100A and 100B), multiple terminals 200 (200A and 200B), and server 300.

[0037] Inhalation device 100 is an apparatus for generating a substance to be inhaled by a user. Hereinafter, the substance generated by inhalation device 100 will be described as an aerosol. Inhalation device 100 is an example of an aerosol generating apparatus. Alternatively, the substance generated by inhalation device 100 may be a gas. Inhalation device 100 is capable of containing a rod-shaped matrix 150 (150A and 150B) containing an aerosol source. Inhalation device 100 generates an aerosol by heating the rod-shaped matrix 150 contained therein.

[0038] Terminal device 200 is a device used by a user of inhalation device 100. Terminal device 200 is associated with inhalation device 100. Inhalation device 100 and terminal device 200 may be pre-paired for wireless communication, or the fact that inhalation device 100 and terminal device 200 are the same user may be pre-registered in server 300. Terminal device 200 can be any device, such as a smartphone, tablet, wearable device, or personal computer (PC). Alternatively, terminal device 200 can be a charger for charging inhalation device 100.

[0039] Server 300 is an information processing device that manages information about each device included in System 1. Server 300 communicates with terminal device 200 via network 900. In particular, server 300 communicates indirectly with inhalation device 100 via terminal device 200. Server 300 can perform various types of processing based on information collected from inhalation device 100 via terminal device 200. Alternatively, server 300 can perform various types of processing based on user operations performed on terminal device 200.

[0040] (2) Configuration example of inhalation device 100

[0041] Figure 2 This is a schematic diagram illustrating an example configuration of the inhalation device 100 according to this embodiment. Figure 2 As shown, the inhalation device 100 according to this configuration example includes: a power supply unit 111, a sensor unit 112, a notification unit 113, a memory unit 114, a communication unit 115, a control unit 116, a heating unit 121, a receiving portion 140, and a heat insulation portion 144.

[0042] The power supply unit 111 stores electricity. The power supply unit 111 then supplies power to each component of the inhalation device 100 according to the control executed by the control unit 116. The power supply unit 111 may be configured, for example, by a rechargeable battery (such as a lithium-ion secondary battery).

[0043] Sensor unit 112 acquires various types of information related to inhalation device 100. As an example, sensor unit 112 is configured with a pressure sensor (such as a capacitive microphone, flow sensor, or temperature sensor) and acquires values ​​associated with user inhalation. As another example, sensor unit 112 is configured with an input device (such as a button or switch) for receiving information input from the user.

[0044] The notification unit 113 notifies the user of information. For example, the notification unit 113 may be configured with a light-emitting device that emits light, a display device that displays an image, a sound output device that outputs sound, a vibration device that vibrates, etc.

[0045] Memory unit 114 stores various types of information for operating the inhalation device 100. For example, memory unit 114 is configured with a non-volatile storage medium (such as flash memory).

[0046] Communication unit 115 is a communication interface capable of performing communication conforming to any wired or wireless communication standard. Examples of communication standards that can be used include those employing Wi-Fi (registered trademark), Bluetooth (registered trademark), BLE (Bluetooth Low Energy) (registered trademark), NFC (Near Field Communication), or LPWA (Low Power Wide Area).

[0047] The control unit 116 acts as an arithmetic processing device and a control device, and controls the overall operation within the inhalation device 100 according to various programs. For example, the control unit 116 is implemented by a CPU (central processing unit) or electronic circuitry (such as a microprocessor).

[0048] The receiving portion 140 has an internal space 141 and holds a rod-shaped substrate 150, while a portion of the rod-shaped substrate 150 is housed within the internal space 141. The receiving portion 140 has an opening 142 to allow communication between the internal space 141 and the outside, and to accommodate the rod-shaped substrate 150 that has been inserted into the internal space 141 through the opening 142. For example, the receiving portion 140 is a cylindrical body that includes the opening 142 and a bottom portion 143 serving as a bottom surface, and defines a cylindrical internal space 141. An airflow path for supplying air to the internal space 141 is connected to the receiving portion 140. For example, an air inlet is provided on the side of the suction device 100, which serves as an inlet for air to enter the airflow path. For example, an air outlet is provided on the bottom portion 143, which serves as an outlet for air to exit from the airflow path to the internal space 141.

[0049] The stick-shaped matrix 150 includes a matrix portion 151 and a mouthpiece portion 152. The matrix portion 151 contains an aerosol source. The aerosol source includes tobacco-derived or non-tobacco-derived flavor components. If the inhalation device 100 is a medical inhaler (such as a nebulizer), the aerosol source may include a drug. For example, the aerosol source may be a liquid containing tobacco-derived or non-tobacco-derived flavor components, such as water or a polyol (e.g., glycerol or propylene glycol), or it may be a solid containing tobacco-derived or non-tobacco-derived flavor components. With the stick-shaped matrix 150 held in the receiving portion 140, at least a portion of the matrix portion 151 is received in the internal space 141, and at least a portion of the mouthpiece portion 152 protrudes from the opening 142. Thus, when a user holds the mouthpiece portion 152 protruding from the opening 142 in their mouth and inhales, air flows into the internal space 141 through an airflow path (not shown) and reaches the user's mouth along with the aerosol generated by the matrix portion 151.

[0050] Heating unit 121 heats the aerosol source to atomize it, thereby generating an aerosol. Figure 2In the example shown, the heating unit 121 has a membrane-like form and is arranged to cover the outer circumference of the receiving portion 140. Thus, when the heating unit 121 generates heat, the matrix portion 151 of the rod-shaped matrix 150 is heated from the outer circumference, generating an aerosol. The heating unit 121 generates heat when powered by the power supply unit 111. For example, power can be supplied when the sensor unit 112 detects that the user has begun inhalation and / or has entered predetermined information. Then, power supply can be stopped when the sensor unit 112 detects that the user has finished inhaling and / or has entered predetermined information.

[0051] The heat insulation portion 144 prevents heat from being transferred from the heating unit 121 to other components. For example, the heat insulation portion 144 is made of vacuum insulation material or aerogel insulation material.

[0052] The configuration examples of the inhalation device 100 have been described above. Of course, the inhalation device 100 is not limited to the above configurations and can adopt various configurations, such as those shown below by way of example.

[0053] As an example, the heating unit 121 may be in the form of a blade and may be arranged to protrude from the bottom portion 143 of the receiving portion 140 into the internal space 141. In this case, the blade-shaped heating unit 121 is inserted into the matrix portion 151 of the rod-shaped matrix 150 and heats the matrix portion 151 of the rod-shaped matrix 150 from the inside. As another example, the heating unit 121 may be arranged to cover the bottom portion 143 of the receiving portion 140. Furthermore, the heating unit 121 may be configured by a combination of two or more heating units: a first heating unit covering the outer circumference of the receiving portion 140, a blade-shaped second heating unit, and a third heating unit covering the bottom portion 143 of the receiving portion 140.

[0054] As another example, the receiving portion 140 may include an opening and closing mechanism (such as a hinge) for opening and closing a portion of the housing forming the internal space 141. Thus, by opening and closing the housing, the receiving portion 140 can receive and clamp the rod-shaped substrate 150 that has been inserted into the internal space 141. In this case, a heating unit 121 may be disposed on the portion of the receiving portion 140 that clamps the rod-shaped substrate 150, and can heat the rod-shaped substrate 150 while it is being pressed.

[0055] Furthermore, the means for atomizing the aerosol source is not limited to heating provided by the heating unit 121. For example, the means for atomizing the aerosol source can be induction heating. In this case, the inhalation device 100 includes at least an electromagnetic induction source (such as a coil) for generating a magnetic field, instead of the heating unit 121. A sensor for generating heat by means of induction heating can be provided in the inhalation device 100 or can be included in the rod-shaped matrix 150.

[0056] (3) Configuration example of terminal device 200

[0057] Figure 3 This is a block diagram illustrating an example configuration of a terminal device 200 according to an embodiment. (As shown...) Figure 3 As shown, the terminal device 200 includes an input unit 210, an output unit 220, a detection unit 230, a communication unit 240, a memory unit 250, and a control unit 260.

[0058] Input unit 210 has the function of receiving various types of information input. Input unit 210 may include an input device for receiving information input from a user. Examples of input devices include buttons, keyboards, touch panels, and microphones. Alternatively, input unit 210 may include various types of sensors, such as image sensors.

[0059] Output unit 220 has the function of outputting information. Output unit 220 may include an output device for outputting information to a user. Examples of output devices include: a display device for displaying information, a light-emitting device for emitting light, a vibration device for vibrating, and a sound output device for outputting sound. A display is an example of a display device. A light-emitting diode (LED) is an example of a light-emitting device. An eccentric motor is an example of a vibration device. A speaker is an example of a sound output device. Output unit 220 outputs information input from control unit 260 to notify the user of that information.

[0060] The detection unit 230 has the function of detecting information related to the terminal device 200. The detection unit 230 can detect the location information of the terminal device 200. For example, the detection unit 230 receives GNSS signals from GNSS (Global Navigation Satellite System) satellites (e.g., GPS signals from GPS (Global Positioning System) satellites) and detects location information including the longitude and latitude of the device. The detection unit 230 can detect the movement of the terminal device 200. For example, the detection unit 230 includes a gyroscope sensor and an accelerometer sensor, and detects angular velocity and acceleration.

[0061] Communication unit 240 is a communication interface for sending and receiving information between terminal device 200 and another device. Communication unit 240 performs communication conforming to any wired or wireless communication standard. Examples of communication standards that can be used include standards employing USB (Universal Serial Bus), Wi-Fi (trademarked), Bluetooth (trademarked), NFC (Near Field Communication), or LPWA (Low Power Wide Area).

[0062] Memory cell 250 stores various types of information. For example, memory cell 250 is configured with a non-volatile storage medium (such as flash memory).

[0063] The control unit 260 functions as an arithmetic processing device or control device, thereby controlling the overall operation within the terminal device 200 according to various programs. For example, the control unit 260 may be implemented by a CPU (Central Processing Unit) or electronic circuitry (such as a microprocessor). The control unit 260 may also include ROM (Read-Only Memory) for storing the programs used and calculation parameters, and RAM (Random Access Memory) for temporarily storing parameters that change appropriately. The terminal device 200 implements various types of processing based on the control executed by the control unit 260. Examples of processing controlled by the control unit 260 include: processing information input via input unit 210, outputting information via output unit 220, detecting information via detection unit 230, sending and receiving information via communication unit 240, and storing / retrieving information via memory unit 250. Other processing implemented by the terminal device 200 (such as processing based on information input to and output from each component) is also controlled by the control unit 260.

[0064] It should be noted that the functions of control unit 260 can be implemented using an application. This application can be pre-installed or downloaded. Furthermore, the functions of control unit 260 can be implemented using a PWA (Progressive Web Application).

[0065] (4) Server configuration example

[0066] Figure 4 This is a block diagram illustrating an example configuration of server 300 according to an embodiment. Figure 4 As shown, server 300 includes communication unit 310, memory unit 320 and control unit 330.

[0067] Communication unit 310 is a communication interface used for sending and receiving information between server 300 and another device. Communication unit 310 performs communication conforming to any wired or wireless communication standard.

[0068] Memory unit 320 stores various types of information for the operation of server 300. Memory unit 320 is constructed of non-volatile storage media (e.g., HDD (hard disk drive) and SSD (solid state drive)).

[0069] The control unit 330 serves as an arithmetic processing and control device, thereby controlling the overall operation within the server 300 according to various programs. For example, the control unit 330 is implemented by a CPU (Central Processing Unit) and electronic circuitry (such as a microprocessor). The control unit 330 may also include ROM (Read-Only Memory) for storing the programs used and calculation parameters, and RAM (Random Access Memory) for temporarily storing parameters that change appropriately. The server 300 implements various types of processing based on the control executed by the control unit 330. Examples of processing controlled by the control unit 330 include sending and receiving information by the communication unit 310 and storing / retrieving information by the memory unit 320. Other processing implemented by the server 300 (such as processing based on information input to and output from each component) is also controlled by the control unit 330.

[0070] <2. Technical Features>

[0071] (1) Heating curve

[0072] Control unit 116 controls the operation of heating unit 121 based on the heating curve. The operation of heating unit 121 is controlled by controlling the power supply from power supply unit 111 to heating unit 121. Heating unit 121 uses the power supplied from power supply unit 111 to heat rod substrate 150.

[0073] A heating profile is control information used to control the temperature at which the aerosol source is heated. The heating profile defines target values ​​for parameters corresponding to the temperature at which the aerosol source is heated. The temperature of heating unit 121 is an example of a parameter. That is, the heating profile can also define a target value for the temperature of heating unit 121 (hereinafter also referred to as the "target temperature"). The target temperature can vary based on the time elapsed since heating began; in this case, the heating profile includes information defining the time-series transition of the target temperature. As another example, the heating profile may include parameters defining how power is supplied to heating unit 121 (hereinafter also referred to as power supply parameters). Power supply parameters include, for example, the voltage applied to heating unit 121, the on / off state of power supply to heating unit 121, or the feedback control method to be employed. The on / off state of power supply to heating unit 121 can be considered as the on / off state of heating unit 121.

[0074] Control unit 116 controls the operation of heating unit 121 such that the temperature of heating unit 121 changes in the same manner as the target temperature defined in the heating profile. The heating profile is typically designed such that the flavor experienced by the user is optimized when the user inhales the aerosol generated from the rod matrix 150. Therefore, the flavor experienced by the user can be optimized by controlling the operation of heating unit 121 based on the heating profile.

[0075] For example, temperature control of heating unit 121 can be achieved using known feedback control. Feedback control can be, for example, PID control (proportional-integral-derivative controller). Control unit 116 can supply power from power supply unit 111 to heating unit 121 in pulse form using pulse width modulation (PWM) or pulse frequency modulation (PFM). In this case, control unit 116 can perform temperature control of heating unit 121 by adjusting the pulse width or frequency of the power pulses to control the duty cycle in the feedback control. Alternatively, control unit 116 can perform simple on / off control in the feedback control. For example, control unit 116 can perform heating via heating unit 121 until the temperature of heating unit 121 reaches a target temperature, interrupt heating of heating unit 121 when the temperature of heating unit 121 reaches the target temperature, and resume heating of heating unit 121 when the temperature of heating unit 121 drops below the target temperature.

[0076] It should be noted that the temperature of the heating unit 121 can be quantified by measuring or estimating the resistance value of the heating unit 121 (more precisely, the resistance heating element constituting the heating unit 121). This is because the resistance value of the resistance heating element changes with temperature. For example, the resistance value of the resistance heating element can be estimated by measuring the amount of voltage drop at the resistance heating element. The amount of voltage drop at the resistance heating element can be measured by a voltage sensor that measures the potential difference applied to the resistance heating element. In another example, the temperature of the heating unit 121 can be measured by a temperature sensor (such as a thermistor mounted near the heating unit 121).

[0077] The period from the start to the end of the process for generating aerosols using the rod-shaped matrix 150 is also referred to hereinafter as the heating phase. In other words, the heating phase is the time period during which the operation of the heating unit 121 is controlled based on a heating profile. The heating phase includes a preheating phase and a suction-feasible phase following the preheating phase. The suction-feasible phase is the period during which a sufficient amount of aerosol is expected to be generated. The preheating phase is the period from the start of heating until the start of the suction-feasible phase. Heating performed during the preheating phase is also referred to as preheating.

[0078] The following will refer to Table 1 and Figure 5 Here are some examples of heating curves. Table 1 shows an example of a heating curve. Figure 5 It is a graph of the heating curves shown in Table 1. Figure 5 The horizontal axis of graph 20 represents time (seconds). The vertical axis of graph 20 represents the target temperature of heating unit 121. Line 21 indicates the change in the target temperature of heating unit 121.

[0079] [Table 1]

[0080] Table 1. Examples of heating curves

[0081]

[0082] As shown in Table 1, the heating phase is divided into multiple unit time periods. The heating curve then defines the time-series changes of the target temperature and the power supply parameters within each unit time period. In the example shown in Table 1, the heating phase is divided into a total of eight unit time periods, namely steps 0 to 7. Figure 5 As shown, steps 0 to 1 are the preheating period, while steps 2 to 7 are the suction feasible period.

[0083] As shown in Table 1, the multiple unit time periods included in the heating stage are divided into the initial temperature rise period, the intermediate temperature decrease period, the temperature rise period again, and the heating end period.

[0084] The initial temperature rise period is the period during which the temperature of the heating unit 121 rises from or is maintained from a predetermined temperature.

[0085] In the example shown in Table 1, the initial temperature rise period includes steps 0 through 2. Figure 5 As shown, during the initial temperature rise period, the temperature of heating unit 121 rapidly increases to 295°C and remains at that temperature. By rapidly increasing the temperature of heating unit 121 and maintaining it at a high temperature during the initial temperature rise period, the rod-shaped substrate 150 can be heated quickly and thoroughly. This allows for a shorter preheating period.

[0086] The intermediate temperature decrease period is the period during which the temperature of heating unit 121 decreases after the initial temperature increase period. In the example shown in Table 1, the intermediate temperature decrease period includes step 3. Figure 5 As shown, during the intermediate temperature reduction period, the temperature of heating unit 121 subsequently drops to 230°C. During this intermediate temperature reduction period, the power supply to heating unit 121 is turned off. Therefore, the temperature of heating unit 121 can be reduced at the maximum rate. Reducing the temperature of heating unit 121 in this manner during the heating phase prevents rapid consumption of the aerosol source. Therefore, it is possible to prevent the aerosol source from being depleted midway through the heating phase.

[0087] The temperature re-rise period is the period during which the temperature of heating unit 121 rises or is maintained after the intermediate temperature decrease period. In the example shown in Table 1, the temperature re-rise period includes steps 4 to 6. Figure 5 As shown, during the temperature re-rise period, the temperature of heating unit 121 gradually rises to 260°C. This gradual temperature increase during the temperature re-rise period allows for limiting power consumption throughout the heating phase while maintaining aerosol generation.

[0088] The heating end phase is the period after the temperature of heating unit 121 decreases following the temperature re-increase phase. In the example shown in Table 1, the heating end phase includes step 7. Figure 5 As shown, during the final stage of heating, the temperature of heating unit 121 subsequently decreases. During the final stage of heating, the power supply to heating unit 121 is turned off. Simultaneously, during the final stage of heating, sufficient aerosol can be generated by the residual heat in the rod-shaped matrix 150.

[0089] Time control can be implemented in each step. Time control is a control triggered by the elapsed time (i.e., the duration set for each step) to terminate the step. It should be noted that when time control is implemented, the rate of temperature change of heating unit 121 can be controlled so that the temperature of heating unit 121 reaches the target temperature at the end of the step. Alternatively, the target temperature can be considered as gradually changing throughout the step. Furthermore, when time control is implemented, the temperature of heating unit 121 can be controlled so that the temperature of heating unit 121 reaches the target temperature midway through the duration, and thereafter the temperature of heating unit 121 remains at the target temperature until the duration has elapsed. In the example shown in Table 1, time control is implemented in steps 1, 2, and steps 4 through 7.

[0090] In some cases, time control is not implemented in any step. When time control is not implemented, the end of a step is triggered when the temperature of the heating unit 121 reaches a predetermined temperature (i.e., a target temperature set for each step). Therefore, the duration of a step without time control is extended or shortened depending on the rate of temperature change. In the example shown in Table 1, time control is not implemented in step 0 or step 3.

[0091] The notification unit 113 can notify the user of information indicating the end of preheating. For example, the notification unit 113 may notify the user of the end of the preheating period before it ends, or it may notify the user of the end of preheating at the moment it has ended. The notification may be given to the user by illuminating an LED or by means of vibration. By referring to such notification, the user can begin suction immediately after preheating has ended.

[0092] Similarly, notification unit 113 can notify the user of information indicating when the feasible suction period ends. For example, notification unit 113 may notify the user of the announcement of the end of the feasible suction period before it ends, or notify the user of information indicating that the feasible suction period has ended when it has already ended. For example, the notification can be given to the user by illuminating an LED or by means of vibration. By referring to such notification, the user can continue suctioning until the feasible suction period ends.

[0093] It should be noted that the heating curves described above are merely examples, and various other examples can be conceived. For instance, the number of steps, the duration of each step, and the target temperature can be varied appropriately.

[0094] (2) Processing for generating heating curves

[0095] Figure 6 This is a diagram illustrating the process used to generate a heating curve according to this embodiment. Appropriate reference will be made below. Figure 6 The process for generating a heating curve according to this embodiment will be described below.

[0096] Server 300 (e.g., control unit 330) generates a heating curve to be used by inhalation device 100. Specifically, server 300 extracts multiple feature values ​​from a source image (an example of a first image) and generates the heating curve based on these extracted feature values. Figure 6 In the example shown, server 300 extracts multiple feature values ​​F1 to F3 from the source image G, which is a still image, and generates a heating curve P based on the extracted feature values ​​F1 to F3. The heating curve P is shown in Table 1 and... Figure 5 As shown. For example, if a user selects any image as the source image using terminal device 200, server 300 generates a heating curve based on the selected source image. Compared to generating a heating curve by manually setting a time series transition of the target temperature, this configuration reduces the burden on the user. In other words, the quality of the user experience can be improved because the desired heating curve can be automatically generated simply by the user intuitively selecting the source image.

[0097] Based on each of several feature values ​​extracted from the source image, server 300 sets the time-series transformation of the target temperature within each of several time intervals defined in the heating curve. Figure 6In the example shown, server 300 sets the time-series transition of the target temperature in each of steps 4, 5, and 6 of the heating curve P based on each of the feature values ​​F1, F2, and F3 extracted from the source image G. With this configuration, the generated heating curve is expected to exhibit multiple variations, with different target temperatures within each unit time period. Therefore, the quality of the user experience can be improved. Note that the time-series transition of setting the target temperature within a unit time period will also be referred to below as setting the target temperature within a unit time period.

[0098] Server 300 can divide the source image into multiple segmented images (example of the second image), and can extract multiple feature values ​​from the corresponding segmented images. Figure 6 In the example shown, server 300 divides the source image G into three images at equal intervals in the horizontal direction, and extracts feature values ​​F1 to F3 from each of the three segmented images G1 to G3. With this configuration, there is a one-to-one correspondence between the segmented images and unit time periods. Therefore, a heating curve can be generated in which the features in each segmented image reflect the time-series change of the target temperature within each unit time period.

[0099] Server 300 can set a unit time period corresponding to the segmented image based on the characteristics of the segmented image. Then, server 300 can set the time series transformation of the target temperature within the unit time period corresponding to the segmented image based on the feature values ​​of the segmented image. With this configuration, a heating curve can be generated in which the characteristics of the segmented image are reflected in the time series transformation of the target temperature within the unit time period corresponding to the characteristics of the segmented image.

[0100] As an example, server 300 can set the order of unit time periods corresponding to the segmented images based on their positions within the source images. For instance, server 300 can assign the order of unit time periods in the heating phase sequentially from the segmented images located on the left to the segmented images located on the right. Figure 6 In the example shown, server 300 assigns the leftmost segmented image G1 to step 4, the middle segmented image G2 to step 5, and the rightmost segmented image G3 to step 6. That is, server 300 sets the time series transition of the target temperature in step 4 based on the feature value F1 in segmented image G1, sets the time series transition of the target temperature in step 5 based on the feature value F2 in segmented image G2, and sets the time series transition of the target temperature in step 6 based on the feature value F3 in segmented image G3.

[0101] Server 300 can set the length of a unit time period corresponding to the segmented image based on the area of ​​the segmented image within the source image. For example, the larger the area of ​​the segmented image, the longer the duration of the unit time period corresponding to that segmented image can be set by server 300; conversely, the smaller the area of ​​the segmented image, the shorter the duration of the unit time period corresponding to that segmented image can be set by server 300. Figure 6 In the example shown, the segmented images G1 to G3 have equal areas, so steps 4 to 6 corresponding to the segmented images G1 to G3 are set to have equal durations.

[0102] Server 300 can also set the time series transition of the target temperature within a unit time period corresponding to the segmented image, based on conditions set within that unit time period. For example, a settable target temperature range can be defined within each unit time period. In this case, server 300 sets the time series transition of the target temperature within the relevant range. This configuration helps to limit drawbacks such as inappropriately setting the target temperature.

[0103] Server 300 can set the time series transition of the target temperature within a portion of the multiple time intervals included in the heating curve based on multiple feature values ​​extracted from the source image. Simultaneously, server 300 can set the time series transition of the target temperature within another portion of these time intervals according to a preset. Figure 6 In the example shown, server 300 sets the time series transition of the target temperature in steps 4 to 6 (the temperature re-increase period) of steps 0 to 7 based on multiple feature values ​​F1 to F3 extracted from the source image G. Simultaneously, server 300 sets the time series transition of the target temperature in steps 0 to 3 and step 7 (the initial temperature increase period, the intermediate temperature decrease period, and the end of heating period) according to presets. Therefore, server 300 can exclude those periods that have a significant impact on the entire heating phase (i.e., the initial temperature increase period and the intermediate temperature decrease period) from the target temperature setting based on the source image. This configuration ensures that the target temperature setting based on the source image does not have an excessive impact.

[0104] These feature values ​​can be correlated with RGB (red-green-blue) values. Specifically, the higher the R value, the more likely the server 300 is to set a time-series transition of the target temperature corresponding to a higher temperature. Considering that red is naturally associated with high temperatures, this configuration allows for the generation of heating curves consistent with the user's impression of the source image.

[0105] Next, we will refer to Figure 7 Here is an example to describe the process described above for generating the heating curve. Figure 7This is a sequence diagram illustrating an example of a processing flow for generating a heating curve implemented by system 1 according to this embodiment. The sequence involves an inhalation device 100, a terminal device 200, and a server 300.

[0106] like Figure 7 As shown, the terminal device 200 first selects a source image (step S102). For example, the terminal device 200 selects an image stored in the terminal device 200 or on the network as the source image based on user operation.

[0107] Next, the terminal device 200 sends the selected source image to the server 300 (step S104).

[0108] Next, server 300 segments the source image (step S106).

[0109] Next, server 300 extracts feature values ​​from each of the multiple segmented images obtained by dividing the source image (step S108). For example, server 300 extracts feature values ​​related to the RGB values ​​of the segmented image.

[0110] Next, server 300 generates a heating curve based on the characteristics and feature values ​​of the segmented image (step S110). For example, server 300 sets the order and duration of the unit time period corresponding to the segmented image based on the position and area of ​​the segmented image. Then, server 300 sets the time series transition of the target temperature within the unit time period corresponding to the segmented image based on the feature values ​​of the segmented image.

[0111] Next, the server 300 sends the generated heating curve to the terminal device 200 (step S112).

[0112] Next, the terminal device 200 forwards the received heating curve to the inhalation device 100 (step S114). Thereafter, the inhalation device 100 stores the received heating curve. This enables the inhalation device 100 to use the heating curve generated based on the source image when heating the rod-shaped substrate 150 again.

[0113] <3. Specific Examples>

[0114] (1) Example of setting a target temperature for time series transformation

[0115] The following section will describe a specific example of the time series transformation for setting a target temperature.

[0116] Server 300 first calculates feature values ​​for the segmented image based on the RGB values ​​of the segmented image. As an example, server 300 can calculate the R value of the segmented image as a feature value. As another example, server 300 can calculate the proportion of the R value to the RGB values ​​of the segmented image as a feature value. As yet another example, the maximum value among the R, G, and B values ​​of the segmented image can be calculated as a feature value. It should be noted that the RGB values ​​of the segmented image refer to statistical values, such as the median or average of the RGB values ​​of the multiple pixels constituting the segmented image. Alternatively, the RGB values ​​of the segmented image can refer to the RGB value of a specific pixel (e.g., the center pixel) in the segmented image.

[0117] Next, server 300 sets the time series transformation of the target temperature within a unit time period corresponding to the segmented image based on the feature values ​​of the segmented image. As an example, server 300 can set the target temperature within a unit time period corresponding to the segmented image based on the feature values ​​of the segmented image. As another example, server 300 can set the rate of change of the target temperature within a unit time period corresponding to the segmented image based on the feature values ​​of the segmented image.

[0118] Server 300 can set the time series transition of the target temperature by referring to a setting table, which defines the combination of feature values ​​of the segmented image and the method used to set the time series transition of the target temperature. Specific examples of the setting table are shown in Tables 2 and 3 below.

[0119] [Table 2]

[0120] Table 2. Example of a target temperature setting table based on the proportion of R value to RGB value.

[0121]

[0122] [Table 3]

[0123] Table 3. Example of a target temperature setting table based on the maximum value in the RGB values

[0124]

[0125] According to Table 2 above, for example, when the R value accounts for 80% of the RGB values, server 300 sets the target temperature to 320°C and / or sets the target temperature change rate to 0.5°C / second. According to Table 3 above, for example, when the maximum value in the RGB values ​​is the R value, server 300 sets the target temperature to 320°C and / or sets the target temperature change rate to 0.5°C / second. As shown in Tables 2 and 3, the larger the R value, the higher the temperature should be set or the higher the temperature rise rate. It should be noted that the target temperature change rate that can be defined in the setting curve is not limited to 0 or greater (i.e., temperature rises or maintains the temperature), and it can also be less than 0 (i.e., temperature falls).

[0126] Additionally, server 300 can also set the time series transition of the target temperature within a unit time period corresponding to the segmented image based on a combination of multiple feature values ​​extracted from the segmented image. As an example, server 300 can define a rough target temperature range based on the maximum value among the RGB values, and can set the target temperature from this range based on the proportion of the R value to the RGB values. Table 4 below shows a specific example of such a setting table.

[0127] [Table 4]

[0128] Table 4. Example of a target temperature setting table based on the maximum value in the RGB values ​​and the proportion of the R value in the RGB values.

[0129]

[0130] (2) A first specific example of the processing used to generate the heating curve

[0131] The following will refer to Figure 8 Table 5 is used to describe a first specific example of the process used to generate the heating curve. Figure 8 This is a diagram illustrating a first specific example of the process for generating a heating curve according to this embodiment. Figure 8 The table at the top shows the method for segmenting the source image and the feature values ​​of the segmented image. Figure 8 The table in the middle shows the heating curves generated based on the source image. Figure 8 The curve at the bottom is Figure 8 The table in the middle shows the heating curve as a graph. Table 5 below shows an example of the target temperature setting table used in this specific example.

[0132] [Table 5]

[0133] Table 5. Example of a target temperature setting table based on R value

[0134]

[0135] like Figure 8 As shown, steps 0 to 3 are unit time periods excluded from the target temperature setting based on the source image. Therefore, server 300 sets the time series transition of the target temperature in steps 0 to 3 according to a preset. Specifically, server 300 sets the target temperatures in steps 0 to 3 to 260°C, 320°C, 320°C, and 230°C, respectively.

[0136] Simultaneously, steps 4 to 8 define the target temperature over a unit time period based on the source image. Therefore, server 300 defines the time-series transition of the target temperature in steps 4 to 8 based on the source image. Specifically, as... Figure 8 As shown, assume server 300 divides the source image into five segmented images G1 to G5. The R values ​​of segmented images G1 to G5 are 80, 98, 172, 210, and 230, respectively. Server 300 sets the time series transition of the target temperature in steps 4 to 8 corresponding to segmented images G1 to G5 according to the corresponding R values ​​of segmented images G1 to G5 in the setting table shown in Table 5. Specifically, server 300 sets the target temperatures in steps 4 to 8 corresponding to segmented images G1 to G5 to 260°C, 260°C, 290°C, 310°C, and 320°C, respectively, with the corresponding R values ​​of segmented images G1 to G5 being 80, 98, 172, 210, and 230.

[0137] (3) A second specific example of the processing used to generate the heating curve

[0138] The following will refer to Figure 9 Table 6 describes a second specific example of the process used to generate the heating curve. Figure 9 This is a diagram illustrating a second specific example of the process for generating a heating curve according to this embodiment. Figure 9 The table at the top shows the method for segmenting the source image and the feature values ​​of the segmented image. Figure 9 The table in the middle shows the heating curves generated based on the source image. Figure 9 The curve at the bottom is Figure 9 The table in the middle shows the heating curve in graph form. Table 6 below shows an example of the target temperature setting table used in this specific example.

[0139] [Table 6]

[0140] Table 6. Example of a target temperature setting table based on the proportion of R value to RGB value

[0141]

[0142] like Figure 9As shown, steps 0 to 3 are unit time periods excluded from the target temperature setting based on the source image. Therefore, server 300 sets the time series transition of the target temperature in steps 0 to 3 according to a preset. Specifically, server 300 sets the target temperatures in steps 0 to 3 to 260°C, 320°C, 320°C, and 230°C, respectively.

[0143] Simultaneously, steps 4 to 8 define the target temperature over a unit time period based on the source image. Therefore, server 300 defines the time-series transition of the target temperature in steps 4 to 8 based on the source image. Specifically, as... Figure 9 As shown, assume server 300 divides the source image into three segmented images G1 to G3. Segmented image G1 has RGB values ​​of (40, 100, 100) and an R-value ratio of 15.4%. Segmented image G2 has RGB values ​​of (50, 70, 100) and an R-value ratio of 22.7%. Segmented image G3 has RGB values ​​of (180, 50, 60) and an R-value ratio of 62.1%. Server 300 sets the time series transition of the target temperature in steps 4 to 6 corresponding to segmented images G1 to G3 according to the corresponding R-values ​​in the setting table shown in Table 6. Specifically, server 300 sets the rate of change of the target temperature in steps 4 to 6 corresponding to segmented images G1 to G3 to 0.25°C / second, 0.5°C / second, and 1.5°C / second, respectively.

[0144] The condition set here is that the upper limit of the target temperature should be set at 320°C throughout the entire heating phase. Therefore, the increase in the target temperature in step 6 stops at the upper limit of 320°C, and then this temperature is maintained, as follows: Figure 9 As shown.

[0145] <4. Supplementary Information>

[0146] The preferred embodiments of this disclosure have been described in detail above with reference to the accompanying drawings; however, this disclosure is not limited to these examples. It will be apparent to those skilled in the art to which this disclosure pertains that numerous variations or modifications within the scope of the technical concept disclosed in the claims will be conceived, and it should be understood that any such variations or modifications fall within the technical scope of this disclosure.

[0147] (1) First supplementary information

[0148] The above embodiments describe examples of unit time periods falling into the initial temperature rise period, the intermediate temperature decrease period, and the heating end period that are excluded from the target temperature setting based on the source image; however, this disclosure is not limited to such examples. At least a portion of the unit time periods falling into this category may be affected by the target temperature setting based on the source image.

[0149] However, it is preferable to set conditions that should be met during the initial temperature rise period. For example, during the initial temperature rise period, the maximum temperature should be set to 290°C to 320°C, and this maximum temperature should be maintained for at least 10 seconds. Then, in addition to the feature values ​​of the source image, the server 300 preferably sets the time series transition of the target temperature during the initial temperature rise period based on these conditions. It is also preferable to set conditions that should be met during the intermediate temperature decrease period. For example, during the intermediate temperature decrease period, the temperature should drop to 250°C or lower.

[0150] (2) Second Supplementary Information

[0151] The source image can be a still image, as referenced above. Figure 6 The server 300 can then divide the source image (which is a still image) into multiple segmented images by dividing it in a predetermined direction. The predetermined direction is not limited to the horizontal direction. The predetermined direction can also be the vertical direction, or the source image can be divided in two or more directions (such as the horizontal and vertical directions).

[0152] It can generate any number of segmented images from a source image, and is not limited to... Figure 6 The three segmented images shown are shown below. Furthermore, the areas of these segmented images do not need to be the same, and the source image can be divided into segmented images of different areas.

[0153] Image segmentation is not limited to rectangular shapes. Segmented images can have various shapes, such as triangles, circles, or ellipses.

[0154] Any method for segmenting the source image is feasible. For example, the source image can be segmented such that the segmented images have the same or similar shapes, such as... Figure 6 As shown. Alternatively, the source image can be divided into background / foreground, or the source image can be divided by the objects included as subjects in the source image.

[0155] It is not necessary to extract feature values ​​from the entire region of the source image. That is, feature values ​​can be extracted from a portion of the source image. For example, server 300 can divide the source image into upper and lower parts, then cut out multiple segmented images from the upper part of the source image and extract feature values ​​from them.

[0156] (3) Third Supplementary Information

[0157] The source image can be a dynamic image. Then, server 300 can divide the source image (which is a dynamic image) into multiple segmented images by dividing it in the time direction. In this case, server 300 preferably sets the order of the unit time periods corresponding to these segmented images based on their time positions within the source image. For example, when the source image is a 3-minute dynamic image, server 300 can set the target temperature in step 4 based on feature values ​​extracted from the first minute, the target temperature in step 5 based on feature values ​​extracted from the next minute, and the target temperature in step 6 based on feature values ​​extracted from the last minute.

[0158] For example, if dynamic images obtained from fixed-point observations of a mountain landscape from summer to spring are used as source images, server 300 sets the time series transition of the target temperature based on the changes in the mountain landscape in each season. That is, server 300 sets the target temperature to, for example, 295°C, 230°C, 250°C, and 270°C based on the changes in the R value of the mountain landscape from summer to spring.

[0159] (4) Fourth Supplementary Information

[0160] The feature values ​​extracted from a segmented image are not limited to those related to RGB values. As an example, these feature values ​​can be any feature values ​​that can be extracted from the image, such as texture feature values, scale-invariant feature transform (SIFT) feature values, speed-up robust feature (SURF) feature values, or moment feature values.

[0161] As another example, these feature values ​​can represent the facial expressions or behaviors of the people who act as subjects included in the image. For instance, when a person in a segmented image is running, server 300 can set the target temperature for the corresponding unit of time period to 295°C; when the person is walking, server 300 can set the target temperature for the corresponding unit of time period to 260°C; and when the person is sleeping, server 300 can set the target temperature for the corresponding unit of time period to 250°C.

[0162] Furthermore, multiple feature values ​​can be extracted from a single segmented image. Based on the combination of multiple feature values ​​extracted from a single segmented image, a time series transition of the target temperature within a unit time period corresponding to that segmented image can be defined.

[0163] The above embodiments describe an example of dividing a source image into multiple segmented images, but this disclosure is not limited to this example. That is, the source image does not need to be divided, as long as multiple feature values ​​can be extracted from the source image. For example, the server 300 can set the target temperature in step 4 based on the RGB values ​​in the entire source image, set the target temperature in step 5 based on SIFT feature values, and set the target temperature in step 6 based on the facial expression of the person acting as the subject.

[0164] (5) Fifth Supplementary Information

[0165] The above embodiments describe an example where the source image is selected by the user, but this disclosure is not limited to this example. The source image can also be generated by the user.

[0166] For example, terminal device 200 can customize existing images based on user operations. That is, terminal device 200 can generate source images by introducing new characters into existing images, by changing the characters' expressions or behaviors, by changing colors, or by creating dynamic images with time-series changes from existing still images. Then, server 300 can generate heating curves based on the source images generated by terminal device 200.

[0167] This configuration allows users to indirectly customize the heating curve by customizing the image. Therefore, the heating curve desired by the user can be generated more intuitively.

[0168] (6) Other matters

[0169] The above embodiments describe an example of server 300 generating a heating curve, but this disclosure is not limited to this example. For example, terminal device 200 can generate a heating curve.

[0170] The above embodiments describe an example where the temperature of the heating unit 121 is a parameter corresponding to the temperature at which the aerosol source is heated (as defined in the heating curve), but this disclosure is not limited to this example. The resistance value of the heating unit 121 can be cited as a parameter corresponding to the temperature at which the aerosol source is heated. Furthermore, when the method for heating the aerosol source is induction heating, the temperature of the sensor or the resistance value of the electromagnetic induction source, etc., can be cited as parameters corresponding to the temperature at which the aerosol source is heated.

[0171] The above embodiments describe an example of an inhalation device 100 generating an aerosol by heating a rod-shaped matrix 150, but this disclosure is not limited to this example. The inhalation device 100 can also be configured as a so-called liquid atomizing aerosol generating device, which generates an aerosol by heating and atomizing a liquid aerosol source. The technology according to this disclosure can also be applied to liquid atomizing aerosol generating devices.

[0172] It should be noted that the series of processes performed by each device described in this specification can be implemented using software, hardware, or any combination of software and hardware. For example, the program constituting the software is pre-stored on a recording medium (more specifically, a non-transitory computer-readable storage medium) located inside or outside each device. Then, when these programs are executed, for example, by a computer used to control each device described in this specification, these programs are read into random access memory (RAM) and executed by means of processing circuitry such as a central processing unit (CPU). The recording medium is, for example, a magnetic disk, optical disk, magneto-optical disk, or flash memory. Furthermore, the computer program can be distributed, for example, via a network without using a recording medium. Additionally, the computer can be an application-specific integrated circuit (ASIC), a general-purpose processor that performs functions by reading software programs, or a computer on a server used for cloud computing. Furthermore, the series of processes performed by each device described in this specification can be centrally processed by a single computer or processed in a distributed manner by multiple computers. Additionally, in the above embodiments, two or more communication means existing in a single device can be physically implemented using a single medium.

[0173] Furthermore, the processes described using flowcharts or sequence diagrams in this specification do not necessarily have to be implemented in the order depicted. Some processing steps can be implemented in parallel. In addition, additional processing steps can be used, and some processing steps can be omitted.

[0174] The following configurations also fall within the technical scope of this disclosure.

[0175] (1) An information processing device, comprising:

[0176] A control unit is configured to generate control information for use by an inhalation device that generates an aerosol by heating an aerosol source based on the control information. This control information defines a time-series transitions of parameters corresponding to the temperature at which the aerosol source is heated.

[0177] in,

[0178] The control unit extracts multiple feature values ​​from the first image and generates the control information based on the extracted feature values.

[0179] (2) The information processing apparatus as disclosed in (1) above, wherein,

[0180] Based on each of the plurality of feature values ​​extracted from the first image, the control unit sets the time series transformation of the parameter within each of the plurality of time periods defined in the control information.

[0181] (3) The information processing apparatus as disclosed in (2) above, wherein,

[0182] The control unit divides the first image into multiple second images and extracts the corresponding multiple feature values ​​from the corresponding multiple second images.

[0183] (4) The information processing apparatus as disclosed in (3) above, wherein,

[0184] The control unit sets a unit time period corresponding to these second images based on the characteristics of these second images, and sets the time series transformation of the parameter within the unit time period corresponding to these second images based on the feature values ​​in these second images.

[0185] (5) The information processing apparatus as disclosed in (4) above, wherein,

[0186] The control unit sets the sequence of unit time periods corresponding to these second images based on their positions within the first image.

[0187] (6) The information processing apparatus as disclosed in (4) or (5) above, wherein,

[0188] The control unit sets the length of the unit time period corresponding to these second images based on the area of ​​these second images in the first image.

[0189] (7) The information processing apparatus as disclosed in any one of (4) to (6) above, wherein,

[0190] The control unit also sets the time series transformation of the parameter within the unit time corresponding to these second images based on the conditions set within these unit time periods.

[0191] (8) The information processing apparatus as disclosed in any one of (4) to (7) above, wherein,

[0192] The control unit sets the time series transformation of the parameter within a portion of the multiple unit time periods included in the control information based on the multiple feature values ​​extracted from the first image, and sets the time series transformation of the parameter within another portion of these unit time periods according to a preset.

[0193] (9) The information processing apparatus as disclosed in any one of (1) to (8) above, wherein,

[0194] These feature values ​​are related to RGB (red-green-blue) values.

[0195] (10) The information processing apparatus as disclosed in (9) above, wherein,

[0196] The higher the R value, the more the control unit will set the time series transition of this parameter corresponding to higher temperatures.

[0197] (11) The information processing apparatus as disclosed in any one of (1) to (10) above, wherein,

[0198] The first image is a still image, and

[0199] The control unit divides the first image into multiple second images by dividing the first image in a predetermined direction.

[0200] (12) The information processing apparatus as disclosed in any one of (1) to (11) above, wherein,

[0201] The first image is a moving image, and

[0202] The control unit divides the first image into multiple second images by dividing the first image in the time direction.

[0203] (13) An information processing method, implemented by means of a computer and including

[0204] Control information is generated for use by an inhalation device that produces aerosols by heating an aerosol source based on the control information. This control information defines a time-series transition of parameters corresponding to the temperature at which the aerosol source is heated.

[0205] in,

[0206] Generating the control information includes extracting multiple feature values ​​from the first image and generating the control information based on the extracted multiple feature values.

[0207] (14) A program for enabling a computer to act as

[0208] A control unit is configured to generate control information for use by an inhalation device that generates an aerosol by heating an aerosol source based on the control information. This control information defines a time-series transitions of parameters corresponding to the temperature at which the aerosol source is heated.

[0209] in,

[0210] The control unit extracts multiple feature values ​​from the first image and generates the control information based on the extracted feature values.

[0211] List of reference numerals

[0212] 1 System

[0213] 100 Inhalation Device

[0214] 111 Power Supply Unit

[0215] 112 Sensor Unit

[0216] 113 Notification Unit

[0217] 114 memory cells

[0218] 115 Communication Unit

[0219] 116 Control Unit

[0220] 121 Heating Unit

[0221] 140 Capacity Section

[0222] 141 Interior Space

[0223] 142 Opening

[0224] 143 Bottom section

[0225] 144 Thermal Insulation Components

[0226] 150 rod-shaped substrate

[0227] 151 Matrix Part

[0228] 152 Suction nozzle section

[0229] 200 terminal devices

[0230] 210 Input Unit

[0231] 220 Output Unit

[0232] 230 detection units

[0233] 240 communication units

[0234] 250 memory units

[0235] 260 Control Unit

[0236] 300 server

[0237] 310 Communication Unit

[0238] 320 memory cells

[0239] 330 Control Unit

[0240] 900 Network.

Claims

1. An information processing apparatus comprising: a control unit operable to generate control information used by an inhalation apparatus to generate an aerosol by heating an aerosol source based on the control information, the control information defining a time series transition of a parameter corresponding to a temperature at which the aerosol source is heated, wherein the control unit extracts a plurality of feature values from a first image, and generates the control information based on the extracted plurality of feature values. 2.The information processing apparatus according to claim 1, wherein based on each of the plurality of feature values extracted from the first image, the control unit sets the time series transition of the parameter within each of a plurality of unit time periods defined in the control information. 3.The information processing apparatus according to claim 2, wherein the control unit divides the first image into a plurality of second images, and extracts the corresponding plurality of feature values from the corresponding plurality of second images. 4.The information processing apparatus according to claim 3, wherein the control unit sets the unit time periods corresponding to the second images based on characteristics of the second images, and sets the time series transition of the parameter within the unit time periods corresponding to the second images based on the feature values in the second images. 5.The information processing apparatus according to claim 4, wherein the control unit sets the order of the unit time periods corresponding to the second images based on positions of the second images in the first image. 6.The information processing apparatus according to claim 4 or 5, wherein the control unit sets the length of the unit time periods corresponding to the second images based on areas of the second images in the first image. 7.The information processing apparatus according to any one of claims 4 to 6, wherein the control unit sets the time series transition of the parameter within the unit time periods corresponding to the second images also based on conditions set within the unit time periods. 8.The information processing apparatus according to any one of claims 4 to 7, wherein the control unit sets the time series transition of the parameter within a part of the plurality of unit time periods included in the control information based on the plurality of feature values extracted from the first image, and sets the time series transition of the parameter within another part of the unit time periods according to a preset. 9.The information processing apparatus according to any one of claims 1 to 8, wherein the feature values are related to RGB (Red-Green-Blue) values. 10.The information processing apparatus according to claim 9, wherein the higher an R value is, the higher the control unit sets the time series transition of the parameter corresponding to a temperature. 11.The information processing apparatus according to any one of claims 1 to 10, wherein the first image is a still image, and the control unit divides the first image into a plurality of second images by dividing the first image in a predetermined direction. 12.The information processing apparatus according to any one of claims 1 to 11, wherein the first image is a dynamic image, and the control unit divides the first image into a plurality of second images by dividing the first image in a predetermined direction. The control unit divides the first image into a plurality of second images by dividing the first image in a time direction.

13. An information processing method, which is implemented by means of a computer and includes generating control information used by an inhalation device that generates an aerosol by heating an aerosol source based on the control information, the control information defining a time series transition of a parameter corresponding to a temperature at which the aerosol source is heated, wherein generating the control information includes extracting a plurality of feature values from a first image and generating the control information based on the extracted plurality of feature values.

14. A program for causing a computer to function as a control unit for generating control information used by an inhalation device that generates an aerosol by heating an aerosol source based on the control information, the control information defining a time series transition of a parameter corresponding to a temperature at which the aerosol source is heated, wherein the control unit extracts a plurality of feature values from a first image and generates the control information based on the extracted plurality of feature values.

Images