Certification for aerosol generators

Abstract

An aerosol generating system comprising an aerosol generating device, an image acquisition sensor configured to capture, in an unlocked state, an aerosol from an aerosol forming substrate and at least one image of the user of the aerosol generating device, and at least one processor, configured to determine, based on an estimated value and the at least one image of the user, the user's age, whether the estimated age of the user exceeds or is equal to a threshold, and to unlock the aerosol generating device when the estimated age exceeds the threshold, an aerosol generating device according to any one of Examples 1 to 11.

Description

Technical Field

[0004] , ,

[0001] The present disclosure relates to an aerosol generation system. In particular, the present disclosure relates to a system for unlocking an aerosol generator.

Background Art

[0002] An aerosol generator may include an electrically operated heat source configured to heat an aerosol-forming substrate to generate an aerosol such as a nicotine-containing aerosol. However, such electronic devices should not be accessed by unauthorized users. Therefore, there is a need for a system that allows only authorized users to access the electronic device.

[0003] A user may be granted the right to use an aerosol generator when the user reaches the legal minimum age. Depending on legal requirements, the age of the user may need to be verified. The age of the user may be verified by selling aerosol generators only to users of sufficient age. For example, the user's ID may be checked based on an ID card, and the age may be verified based on the ID card. However, such age verification mechanisms are vulnerable to attempts at fraud, especially when the ID card is uploaded via an online platform and not physically checked in the presence of the presented owner of the ID card. Furthermore, such systems for verifying the age of a user may be inefficient or error-prone. Additionally, some commercially available aerosol generators can be used if stolen by an unauthorized person, but the age of the unauthorized person cannot be verified. Therefore, there is a need for an efficient and reliable method for verifying user authentication for using an aerosol generator.

Summary of the Invention

[0004] According to one aspect of the present invention, an aerosol generating system is provided, comprising an aerosol generating device, an image acquisition sensor configured to capture at least one image of the user of the aerosol generating device, and at least one processor configured to estimate, and based on at least one image of the user, the user's age, the estimated age of the user, is above or equal to a threshold, and unlocks the aerosol generating device when the estimated age is above or equal to a threshold.

[0005] An improved aerosol generating system is provided for granting access to an aerosol generating device in a reliable and efficient manner by estimating the user's age based on at least one image of the user to unlock the aerosol generating device. Specifically, an aerosol generating system equipped with an image acquisition sensor that estimates the user's age based on the image makes it possible to restrict access to the aerosol generating device to authorized users only. The aerosol generating device may be in one of at least two states, such as a locked state and an unlocked state. The aerosol generating device can transition from a locked state to an unlocked state. Alternatively, or additionally, the aerosol generating device may transition from an unlocked state to a locked state. The "locked state" may be a state in which the aerosol generating device is prevented from generating aerosols from an aerosol-forming substrate or is configured not to generate aerosols. The "unlocked state" may be a state in which the aerosol generating device is configured to generate aerosols from an aerosol-forming substrate.

[0006] The step of determining whether the user's estimated age is above a threshold includes outputting the user's estimated age range, outputting the estimated minimum age and optionally the user's estimated minimum age, determining that the user's estimated age is above the threshold, and, if the estimated minimum age is above the threshold, determining an accuracy score indicating the accuracy of the user's age estimation. The aerosol generator can only be unlocked if the accuracy score is above the accuracy threshold.

[0007] Furthermore, the aerosol generation system may include a microphone configured to record the user's voice, and at least one processor may be configured to estimate the user's age based on at least one image of the user and the recorded user's voice.

[0008] An improved system is provided for granting access only to authenticated users using multiple levels of authentication by estimating the user's age based on at least one image of the user and the user's recorded voice. At least one image of the user may be at least one image of the user's face. At least one image of the user may be a selfie or other self-portrait photograph. At least one image of the user may be captured according to instructions presented to the user, such as at least one of the user's distance to the image acquisition sensor, the position of the user or the user's head in at least one image, and / or the orientation of the user or the user's head. The image area of ​​at least one image defining the user's face may be at least 10%, 20%, 30%, 40%, 50%, 60%, or 70% of the total image area. At least one image may be captured within 1 hour, 2 hours, 6 hours, 12 hours, or 24 hours of determining whether the user's estimated age is above or equal to a threshold.

[0009] The aerosol generation system may include a user's mobile computing device equipped with an image acquisition sensor. The user's mobile computing device may be located away from the aerosol generation system. At least one processor may be configured to convert at least one image of the user into at least one corresponding anonymized pixel map on the mobile computing device and to send the anonymized pixel map from the mobile computing device to a server, where the user's age is estimated based on the anonymized pixel map. The process of converting at least one image of the user into at least one corresponding anonymized pixel map includes blurring one or more parts of the at least one image (e.g., the image of at least one image and / or the part of the image containing the face), pixelating (e.g., reducing the resolution) one or more parts of the at least one image (e.g., the part containing the image of the face), and obscuring (e.g., replacing with a solid color) one or more parts of the at least one image (e.g., the part containing the image of the face). At least one image of the user may be converted into at least one corresponding pixel map such that the user's ID cannot be determined from the pixel map. At least one image of the user may be converted into at least one corresponding anonymized pixel map by using at least one neural network, such as a generative adversarial network. At least one neural network may be used to obtain information about the user's age from an anonymized pixel map. The anonymized pixel map may be a feature map of at least one neural network. The feature map may be obtained from a layer of at least one neural network, such as a deep convolutional neural network. The layer may be in the middle of at least one neural network, and / or an edge layer, such as the first or last layer of at least one neural network.

[0010] At least one image of the user and at least one of the anonymized pixel maps may be deleted after determining the user's estimated age and / or after unlocking the aerosol generator. Only the anonymized pixel maps may be sent to the server. At least one image of the user may not be sent to the server. At least one image of the user may be deleted after the anonymized pixel map has been generated, or after at least one image of the user has been converted to at least one corresponding anonymized pixel map.

[0011] Personal data can be protected by sending an anonymized pixel map from a mobile computing device to a server and / or by deleting at least one of the user's images and at least one of the anonymized pixel maps.

[0012] At least one of the user's images can be verified as authentic by analyzing the user's image using a neural network for recognizing presentation attacks, thereby determining whether the user's image has been tampered with, determining whether detected user sounds correspond to the user's image, and determining the user's muscle movements in at least two of the user's images.

[0013] According to another aspect of the present invention, a computer implementation method for unlocking an aerosol generator is provided, which includes: acquiring at least one image of the user of the aerosol generator; estimating the user's age based on at least one image of the user; determining whether the estimated age of the user exceeds a threshold; and, if it is determined that the estimated age exceeds the threshold, unlocking the aerosol generator for generating aerosols from an aerosol-forming substrate.

[0014] An improved method is provided for authenticating the user's age via an image acquisition sensor when it is determined that the estimated age exceeds a threshold, by unlocking an aerosol generator for generating aerosols from an aerosol-forming substrate.

[0015] As used herein, the term “aerosol generator” refers to a device that interacts with an aerosol-forming substrate to generate an aerosol. An aerosol generator may interact with either or both an aerosol-generating article containing an aerosol-forming substrate and / or a cartridge containing an aerosol-forming substrate. In some embodiments, the aerosol generator may heat the aerosol-forming substrate to facilitate the release of volatile compounds from the substrate. An electrically operated aerosol generator may include an atomizer, such as an electric heater, for heating the aerosol-forming substrate to form an aerosol.

[0016] As used herein, the term “aerosol-forming substrate located within and / or engaged with an aerosol-generating device” refers to the combination of an aerosol-generating device and an aerosol-forming substrate. When the aerosol-forming substrate forms part of an aerosol-generating article, the aerosol-forming substrate located within and / or engaged with an aerosol-generating device refers to the combination of an aerosol-generating device and an aerosol-generating article. The aerosol-forming substrate and the aerosol-generating device can cooperate to generate aerosols.

[0017] As used herein, the term “aerosol-forming substrate” refers to a substrate capable of releasing volatile compounds that can form aerosols. The volatile compounds may be released by heating the aerosol-forming substrate. As an alternative to heating, in some cases, the volatile compounds may be released by chemical reactions or by mechanical stimuli such as ultrasound. The aerosol-forming substrate may be solid or may contain both solid and liquid components. The aerosol-forming substrate may be part of an aerosol-generating article.

[0018] As used herein, the term “aerosol-generating article” refers to an article comprising an aerosol-forming substrate having the ability to release volatile compounds capable of forming aerosols. The aerosol may contain nicotine. Aerosol-generating articles may be disposable. Aerosol-generating articles comprising an aerosol-forming substrate containing tobacco may be referred to herein as tobacco sticks.

[0019] The aerosol-forming substrate may contain nicotine. The aerosol-forming substrate may contain tobacco, for example, a tobacco-containing material containing volatile tobacco-flavored compounds released from the aerosol-forming substrate upon heating. In a preferred embodiment, the aerosol-forming substrate may contain homogenized tobacco material, such as cast-leaf tobacco. The aerosol-forming substrate may contain both solid and liquid components. The aerosol-forming substrate may contain a tobacco-containing material containing volatile tobacco-flavored compounds released from the substrate upon heating. The aerosol-forming substrate may contain non-tobacco materials. The aerosol-forming substrate may further contain aerosol-forming bodies. Suitable examples of aerosol-forming bodies are glycerin and propylene glycol.

[0020] The present invention is defined in the claims. However, a non-exclusive list of non-limiting embodiments is provided below. One or more features of these embodiments may be combined with one or more features of other embodiments, forms, or aspects described herein.

[0021] Example 1: An aerosol generating system comprising an aerosol generating device, an image acquisition sensor configured to capture, in an unlocked state, an aerosol from an aerosol forming substrate and at least one image of the user of the aerosol generating device, and at least one processor configured to estimate, and a determination based on at least one image of the user whether the user's age and the estimated age of the user exceed or equal a threshold, and unlocking the aerosol generating device when the estimated age exceeds the threshold.

[0022] Example 2: The aerosol generating system according to Example 1, further comprising a microphone configured to record a user's voice, and at least one processor configured to estimate the user's age based on at least one image of the user and the recorded user's voice.

[0023] Example 3: An aerosol generation system according to one of Examples 1 and 2, comprising a user's mobile computing device, wherein the mobile computing device is equipped with an image acquisition sensor.

[0024] Example 4: The aerosol generating system according to Example 3, wherein at least one processor is configured to convert at least one image of a user into at least one corresponding anonymized pixel map on a mobile computing device, and to send the anonymized pixel map from the mobile computing device to a server, and the user's age is estimated based on the anonymized pixel map on the server.

[0025] Example 5: The aerosol generating system according to Example 4, wherein at least one processor is configured to determine the estimated age of the user and / or delete at least one of the user's images and an anonymized pixel map after unlocking the aerosol generating device.

[0026] Example 6: An aerosol generation system according to any one of Examples 1 to 5, wherein the age of the user is estimated by using a machine learning model, such as a neural network, preferably a deep neural network.

[0027] Example 7: An aerosol generation system according to any one of Examples 1 to 6, wherein at least one processor is configured to determine whether at least one image of the user has been tampered with, analyze at least one image of the user using a neural network for recognizing a presentation attack, determine that the detected voice of the user corresponds to at least one image of the user, and determine the muscle movement of the user in at least two of the at least one image of the user.

[0028] Example 8: An aerosol generation system according to any one of Examples 1 to 7, wherein the threshold value is preferably predefined by the manufacturer of the aerosol generator.

[0029] Example 9: An aerosol generation system according to any one of Examples 1 to 8, wherein the threshold value is at least N years higher than the first age, the first age is set to approve the use of the aerosol generator, preferably N = 1 or more, 2 or more, 3 or more, 4 or more, or 5 or more, or the threshold value is the first age threshold, and the first age threshold is 18 years or more, 19 years or more, 20 years or more, 25 years or more, and 30 years or more.

[0030] Example 10: An aerosol generation system according to any one of Examples 1 to 9, wherein at least one processor is configured to determine the user profile of the user based on at least one image of the user, and optionally, the aerosol generator is configured according to the user profile.

[0031] Example 11: An aerosol generating system according to one of Examples 1 to 10, wherein at least one processor is configured to verify the identity of the user based on at least one image of the user.

[0032] Example 12: An aerosol generating system according to one of Examples 1 to 11, further comprising an aerosol generating article containing an aerosol generating substrate.

[0033] Example 13: The aerosol generating system according to Example 12, wherein the aerosol generating substrate contains nicotine.

[0034] Example 14: An aerosol generating system according to one of Examples 12 and 13, wherein the aerosol generator is configured to fully or partially receive an aerosol generating substrate, and / or the surface of the aerosol generator is configured to be attached to the aerosol generating substrate.

[0035] Example 15: An aerosol generating system according to one of Examples 1 to 14, wherein the aerosol generating device is configured to be in one of the following states: locked or unlocked.

[0036] Example 16: The aerosol generating system according to Example 15, wherein the locked state is a state in which the aerosol generating device is prevented from generating aerosols from the aerosol forming substrate.

[0037] Example 17: An aerosol generating system according to Example 15 or Example 16, wherein unlocking the aerosol generator when the estimated age exceeds a threshold includes instructing the aerosol generator to transition from a locked state to an unlocked state.

[0038] Example 18: An aerosol generating system according to one of Examples 1 to 17, wherein determining whether the user's estimated age is above or equal to a threshold includes outputting the user's estimated age range.

[0039] Example 19: An aerosol generating system according to one of Examples 1 to 18, wherein determining whether the user's estimated age is above or equal to a threshold includes outputting the estimated minimum age.

[0040] Example 20: An aerosol generating system according to one of Examples 1 to 19, wherein determining whether the user's estimated age is above or equal to a threshold includes outputting the user's estimated age.

[0041] Example 21: The aerosol generating system according to Example 19, wherein determining whether the user's estimated age is above a threshold includes determining that the user's estimated age is above a threshold if the estimated minimum age is above a threshold.

[0042] Example 22: An aerosol generating system according to one of Examples 1 to 21, wherein determining whether the estimated age of the user is above or equal to a threshold is a precision score indicating the accuracy of the user's age estimation.

[0043] Example 23: The aerosol generating system according to Example 22, wherein the aerosol generator remains locked when the accuracy score falls below the accuracy threshold.

[0044] Example 24: The aerosol generating system according to Example 22, wherein the aerosol generator is unlocked only when the accuracy score is equal to or greater than the accuracy threshold.

[0045] Example 25: An aerosol generating system according to one of Examples 1 to 24, wherein at least one image of the user includes at least one image of the user's face.

[0046] Example 26: An aerosol generating system according to one of Examples 1 to 24, wherein at least one image of the user includes a self-port photograph.

[0047] Example 27: An aerosol generating system according to one of Examples 1 to 26, wherein at least one image of the user is captured in accordance with a command presented to the user.

[0048] Example 28: The aerosol generation system according to Example 27, wherein the command presented to the user includes the distance for the user to the image acquisition sensor.

[0049] Example 29: An aerosol generating system according to one of Examples 27 and 28, wherein the instructions provided to the user include the position of the user or the user's head in at least one image.

[0050] Example 30: An aerosol generating system according to one of Examples 27 to 29, wherein the instructions provided to the user include the orientation of the user or the user's head.

[0051] Example 31: An aerosol generating system according to one of Examples 1 to 30, wherein the area of ​​at least one image defining the user's face is at least 10%, 20%, 30%, 40%, 50%, 60%, or 70% of the total area of ​​the images.

[0052] Example 32: An aerosol generating system according to one of Examples 1 to 31, wherein at least one image is captured within 1 hour, 2 hours, 6 hours, 12 hours, or 24 hours prior to determining whether the user's estimated age is above a threshold.

[0053] Example 33: An aerosol generating system according to Example 3, or any prior embodiment including Example 3, wherein the user's mobile computing device is remote from the aerosol generating device.

[0054] Example 34: An aerosol generating system according to Example 4 or any prior embodiment including Example 4, wherein the step of converting at least one user image into at least one corresponding anonymized pixel map includes blurring one or more portions of at least one image.

[0055] Example 35: An aerosol generating system according to Example 4 or any prior embodiment including Example 4, wherein the step of converting at least one user image into at least one corresponding anonymized pixel map includes reducing the resolution of one or more portions of at least one image.

[0056] Example 36: An aerosol generating system according to Example 4 or any prior embodiment including Example 4, wherein the step of converting at least one user image into at least one corresponding anonymized pixel map includes obscuring one or more portions of at least one image.

[0057] Example 37: An aerosol generating system according to one of Examples 34 to 36, wherein at least one portion of one image includes the user's face or an image of a face.

[0058] Example 38: An aerosol generating system according to Example 4, or any prior example including Example 4, wherein the user's identity is not determined from at least the pixel map.

[0059] Example 39: An aerosol generating system according to Example 4 or any prior embodiment including Example 4, wherein at least one image of a user is converted into at least one corresponding anonymized pixel map by using at least one neural network.

[0060] Example 40: The aerosol generating system according to Example 39, wherein at least one neural network is used to obtain information about the user's age from an anonymized pixel map.

[0061] Example 41: An aerosol generation system according to Example 4 or any prior example including Example 4, wherein the anonymized pixel map includes a feature map of at least one neural network.

[0062] Example 42: The aerosol generation system according to Example 41, wherein the feature map is obtained from at least one layer of a neural network.

[0063] Example 43: The aerosol generation system according to Example 42, wherein the layer is not a layer at the edge of at least one neural network.

[0064] Example 44: An aerosol generation system according to one of Examples 41 to 43, wherein the feature map includes a convolutional operation of at least one neural network.

[0065] Example 45: An aerosol generating system according to Example 4 or any prior example including Example 4, wherein only anonymized pixel maps are sent to the server.

[0066] Example 46: An aerosol generating system according to Example 4 or any prior embodiment including Example 4, wherein at least one image of the user is deleted after at least one image of the user has been converted into at least one corresponding anonymized pixel map.

[0067] Example 47: A computer implementation method for unlocking an aerosol generator, comprising: acquiring at least one image of the user of the aerosol generator; estimating the user's age based on at least one image of the user; determining whether the estimated age of the user exceeds a threshold; and, when it is determined that the estimated age exceeds a threshold, unlocking the aerosol generator for generating aerosols from an aerosol-forming substrate.

[0068] Example 48: The computer implementation method according to Example 47, further comprising acquiring user voice data, wherein the user's age is estimated based on at least one image of the user and the acquired user voice data.

[0069] Example 49: A computer implementation method according to one of Examples 47 and 48, further comprising converting at least one image of a user into at least one corresponding anonymized pixel map, and sending the anonymized pixel map to a server in order to estimate the user's age, wherein the user's age is estimated based on the anonymized pixel map on the server.

[0070] Example 50: A computer implementation method according to one of Examples 47 to 49, further comprising determining whether at least one image of the user has been tampered with, determining that a detected voice of the user corresponds to at least one image of the user by analyzing at least one image of the user using a neural network for recognizing presentation attacks, and determining the user's muscle movements in at least two of the at least one images of the user.

[0071] Here, we will further describe the examples with reference to the figures. [Brief explanation of the drawing]

[0072] [Figure 1A] Figure 1A shows a schematic diagram of an aerosol generation system according to one embodiment. [Figure 1B] Figure 1B shows a schematic diagram of an aerosol generation system according to one embodiment. [Figure 1C] Figure 1C shows a schematic diagram of an aerosol generation system according to one embodiment. [Figure 2] Figure 2 shows a flowchart illustrating the method for unlocking the aerosol generator. [Modes for carrying out the invention]

[0073] Figure 1 shows an aerosol generating system 100. The aerosol generating system comprises an aerosol generator 120 configured to generate an aerosol from an aerosol-forming substrate. The aerosol generator 120 may be a heated non-combustible (HNB) device. The aerosol generating system 100 may be used to unlock the aerosol generator 120 for use by the user 110. The aerosol-forming substrate may be located inside the aerosol generator 100 and / or engaged with the aerosol generator 100. Alternatively, the aerosol-forming substrate (e.g., a liquid in a cartridge) may be attached to the aerosol generator 120. The aerosol generating system comprises an image acquisition sensor 130 configured to capture at least one image of the user 110.

[0074] The image acquisition sensor may be located within the aerosol generator 120. Alternatively, the image acquisition sensor may be located away from the aerosol generator 120. For example, the image acquisition sensor may be part of a mobile computing device, such as a smartphone or other computing device 130. The computing device 130 and the aerosol generator 120 may be connected via a first network. The first network may be a wireless network such as a Bluetooth network.

[0075] The aerosol generating system 100 may include a server 140. The server 140 may be connected to at least one of the aerosol generating device 120 and the computing device 130 via a second network. The second network may be a wireless network such as a WiFi network.

[0076] Image acquisition sensors may be configured to capture one or more images of the user. Image acquisition sensors may be configured to capture depth information or multiple depth values ​​of the user from a single or multiple viewpoints. Examples of image acquisition sensors may include LiDAR (light detection and positioning) sensors, wide-angle cameras, action cameras, closed-circuit television (CCTV) cameras, camcorders, digital cameras, camera phones, time-of-flight (ToF) cameras, night vision cameras, image sensors, and / or other image acquisition devices.

[0077] At least one captured image may be sent to server 140. Alternatively, at least one captured image may be converted into at least one corresponding anonymized pixel map, and at least one anonymized pixel map may be sent to server 140. At least one captured image may be converted into at least one corresponding anonymized pixel map in aerosol generator 120 or computing device 130, and at least one anonymized pixel map may be sent from aerosol generator 120 or computing device 130 to server 140.

[0078] The user's age may be estimated based on at least one captured image or an anonymized pixel map on server 140. The user's age may also be estimated by a machine learning model such as a neural network. The neural network may be a deep neural network.

[0079] Whether the user's estimated age is above or equal to a threshold may be determined by at least one of the aerosol generator 120, computing device 130, and server 140. When the estimated age is above the threshold, the aerosol generator transitions from a locked state to an unlocked state. The "locked state" may be a state in which the aerosol generator is prohibited from generating aerosols.

[0080] In one embodiment, the determination of whether the age exceeds a threshold is made by the server 140 or the computing device 130, which sends a signal to unlock the aerosol generator 120. The aerosol generator 120 may be in a first state, such as a locked state, in which the aerosol generator 120 is prohibited or prevented from generating aerosols. A signal from the computing device 130 may instruct the aerosol generator to switch from the locked state to the unlocked state or to transition to it. For example, the aerosol generator 120 may be sold or purchased in a locked state in which the aerosol generator 120 cannot generate aerosols. Only after transitioning to the unlocked state can the aerosol generator 120 generate aerosols from the aerosol-forming substrate.

[0081] The threshold may be predefined or selected by the manufacturer of the aerosol generator. The threshold may be at least N years above the first age (or first age threshold). The threshold may be set to permit the use of the aerosol generator, and N = 1 or greater, 2 or greater, 3 or greater, 4 or greater, or 5 or greater. The first age threshold may be one of 18 years or older, 19 years or older, 20 years or older, 21 years or older, 25 years or older, and 30 years or older.

[0082] At least one of the aerosol generator 120 and the computing device 130 may be equipped with a microphone configured to record the voice or sound of user 110. Server 140 may be configured to estimate the user's age based on at least one image of the user and the recorded voice or sound of user 110.

[0083] At least one of the aerosol generator 120, computing device 130, and server 140 may be configured to verify that at least one image of the user is authentic or depicts a living human being. For example, at least one of the aerosol generator 120, computing device 130, and server 140 may include (i) analyzing the at least one image of the user using a neural network for determining whether the at least one image of the user has been tampered with and for recognizing presentation attacks, (ii) determining that the detected voice of the user corresponds to the at least one image of the user, and (iii) determining the muscle movements of the user in at least two of the at least one image of the user to verify that at least one image of the user is authentic.

[0084] To protect the personal information of user 110, at least one of the user's images and at least one of the anonymized pixel maps may be deleted after determining the user's estimated age and / or after unlocking the aerosol generator on server 140 and / or computing device 130.

[0085] In one embodiment, the user profile of a user is determined based on at least one image of the user 110. The aerosol generator 120 may be configured according to the user profile. In one embodiment, the user profile may include information about increased substance content, such as nicotine content, compared to different substance content, such as flavor content, of consumables placed in and / or engaged with the aerosol generator, such as aerosol-forming substrates. Additionally, or by other means, the identification of the user 110 may be verified based on at least one image of the user.

[0086] The aerosol generation system 100 may be configured to unlock the aerosol generator 120. Unlocking the aerosol generator 120 may include setting the aerosol generator 120 to a state in which it is configured to generate aerosols from an aerosol-forming substrate in response to user action.

[0087] In Figure 1B, the aerosol generation system comprises only an aerosol generator 120 and a computing device 130. The computing device 130 may be configured to perform the same operations as the server in Figure 1A. Furthermore, the computing device 130 may be configured to perform all operations performed by the server in Figure 1A.

[0088] For example, a user may connect a mobile computing device 130 to an aerosol generator 120 via a network such as a wireless network. After connecting devices 120 and 130, user 110 may take a photograph with user 110's computing device 130. The computing device 130 may be configured to estimate user 110's age based on the photograph of user 110. The computing device 130 may be configured to determine whether user 110's estimated age is above or equal to a threshold. If the estimated age is above the threshold, the computing device may instruct the aerosol generator 120 to unlock itself.

[0089] In one embodiment, the aerosol generating system comprises a smart device (e.g., a smartphone) and an aerosol generating device. The aerosol generating device may be locked at the time of sale. To unlock it, the user uses the smartphone. The smartphone may be configured to scan the user's face. Once the smartphone estimates the user's age based on the facial scan, the aerosol generating device may be automatically unlocked if the estimated age exceeds a certain threshold.

[0090] In one embodiment, a user of an aerosol generator, e.g., a consumer, takes a selfie using a mobile phone or desktop camera and transmits the image with consent that the image may be used to verify the user's age. A pixel map of the user's image, including the user's face, may be generated. The pixel map may contain information about the user's image in an anonymized form. An age estimate for the user's image may be provided by using an artificial intelligence (AI) model. Any image data associated with the user's image can be deleted immediately after processing of the user's image is complete. The solution ensures that the transmitted face is immediately "forgotten". The estimated age may be returned to the mobile phone or computing device and compared to a threshold, which may be determined and / or configured by the manufacturer of the aerosol generator. The system does not have to receive, process, or store the user's biometric data or the user's personal data or ID attributes (e.g., last name, address, date of birth).

[0091] To minimize the risk of users under the legal age accessing restricted content, such as through the use of aerosol generators, the threshold may be configured or set to exceed the legal age by more than one year. Only users with an estimated age above the threshold will be able to access the restricted content. The threshold may be set to exceed one, two, three, four, or five years above the legal age to reduce the risk of false positives and improve the overall effectiveness of the solution.

[0092] In Figure 1C, the aerosol generation system comprises only an aerosol generator 120 and a server 140. The aerosol generator 120 may be configured to perform the same operations as the computing device 130 in Figure 1A, or at least some of the operations. In one embodiment, the aerosol generator 120 may be configured to perform all the operations performed by the computing device 130 and server 140 in Figure 1A.

[0093] For example, the aerosol generator 120 may include an image acquisition sensor configured to capture at least one image of the user 110 of the aerosol generator 120. At least one image of the user 110, or at least one anonymized pixel map based on at least one image of the user 110, may be sent to the server 140. The server 140 may be configured to estimate the user's age based on at least one image of the user 110 or the anonymized pixel map, determine whether the estimated age of the user is above a threshold, and instruct the aerosol generator 120 to unlock the aerosol generator 120 if the estimated age is above the threshold.

[0094] In one embodiment, at least one of the aerosol generator 120, computing device 130, and server 140 may include an embedded neural network-based processor configured to communicate with the device including the image acquisition sensor for basic interactions associated with the image acquisition sensor. The neural network may include electronic data such as, for example, a software program, code, libraries, applications, scripts, or other logic or instructions to be executed by a processing device such as at least one of the aerosol generator 120, computing device 130, and server 140. The neural network may also include code and routines configured to enable the computing device, such as at least one of the aerosol generator 120, computing device 130, and server 140, to perform one or more actions for the classification of one or more inputs. Furthermore, the neural network may also be implemented using hardware including a processor, a microprocessor (for example, to perform or control the performance of one or more actions), a field-programmable gate array (FPGA), or an application-specific integrated circuit (ASIC). Alternatively, in some embodiments, the neural network may be implemented using a combination of hardware and software.

[0095] In another embodiment, the aerosol generator 120 is configured to interact with a smartphone for advanced interaction associated with an image acquisition sensor. For example, the image acquisition sensor may be included in a smartphone or other handheld computing device, and the smartphone may be configured to process images acquired from the image acquisition sensor. The smartphone may be configured to determine at least one of the user 110's age and identification information based on at least one of the user's images. At least one of the user 110's age and identity may be transmitted to the aerosol generator 120 for further processing. Alternatively, the smartphone may be configured to receive further information, such as the user's voice or information related to the voice, for further processing. The results of such further processing may be transmitted to the aerosol generator 120 to unlock the aerosol generator 120. In one embodiment, the smartphone acquires at least one image of the user and transmits at least one image of the user to the aerosol generator 130 for further processing.

[0096] Acoustic sensors, such as microphones, may be configured to capture the user's voice signal. The acoustic sensors may be further configured to convert the captured voice signal into an electrical signal to determine the user's age. For example, the user's age may be determined by analyzing the voice signal, which contains information about the user's voice.

[0097] The captured audio signal may include multiple audio parameters such as loudness parameters, intonation parameters, overtonation intensity, speech modulation parameters, pitch parameters, tone parameters, speech rate parameters, voice quality parameters, telephone parameters, pronunciation parameters, prosody parameters, timbre parameters, and one or more psychoacoustic parameters that can be converted into electrical signals to determine the user's age. Examples of acoustic sensors may include recording devices, electric microphones, dynamic microphones, carbon microphones, piezoelectric microphones, fiber microphones, MEMS (micro-electromechanical systems) microphones, or other microphones known in the art.

[0098] During operation, the aerosol generator may compare information associated with one or more captured images, such as estimated age, with information set by the manufacturer of the aerosol generator 120, such as the legal age or first age for use of the aerosol generator 120. The manufacturer-set information may be stored integrally in the aerosol generator 120, or it may be obtained remotely from a server 140 (e.g., a cloud server) or a smartphone via a suitable communication network (e.g., via a high-quality wireless communication (Wi-Fi) network).

[0099] In one embodiment, an image acquisition sensor may capture one or more images of a first user 110. The aerosol generating system 100 may estimate the age of the first user based on the captured images. If, based on the estimated age, the first user 110 (e.g., a child) is not an authorized user, the aerosol generator 120 may be kept locked and / or turned off to prevent use by an unauthorized user. The aerosol generating system 100 may also generate an alarm. For example, the alarm may be provided to a second user or device or service associated with the aerosol generator 120, such as the service of the manufacturer of the aerosol generator 120. The alarm may include information about an unauthorized user of the aerosol generator. The alarm may include information associated with an unauthorized user attempt on the aerosol generator. The alarm may include at least one of an audible alarm, a visual alarm, an audible-visual alarm, or a vibration alarm.

[0100] In response to a determination that the user's use of the aerosol generator 120 has not been verified or authorized, the user 110 may be prompted to verify their age using an ID card. The image acquisition sensor may be configured to capture at least one image of the ID card. The user's ID corresponding to the ID on the ID card may be verified based on the user's image or an anonymized pixel map of the user's image, and the ID card image or an anonymized pixel map of the ID card image.

[0101] In another embodiment, if, based on the determined characteristics, the captured image indicates that the certified user is fatigued, drunk, stressed, or emotionally unstable, such as the user being sad, crying, or frightened, the aerosol generator may automatically turn off the aerosol generator 100 based on the user's condition. Thus, the user's age may also be verified by a second method using the user's ID card.

[0102] If the second user is an authorized user, such as an adult owner of the device, the aerosol generator may be unlocked after the user has been authenticated to be of sufficient age to use the aerosol generator. In one embodiment, if the second user does not meet the age requirement for using the aerosol generator 120 estimated from microphone measurements, for example, if the user's age estimated from the user's voice is lower than the user's age estimated from the captured image, the aerosol generator may remain locked and / or be turned off to prevent use by the second user, who may then be considered an unauthorized user.

[0103] This order of operation for the image acquisition sensor and the acoustic sensor is provided merely as an example. The order of operation may be modified, reversed, or omitted to achieve the same purpose. For example, the acoustic sensor may detect the user's voice before the image acquisition sensor captures the user's image, or the acoustic sensor may detect the user's sound at the same time as the image acquisition sensor detects the user's image.

[0104] Figure 2 is a flowchart showing a method 200 for unlocking the aerosol generator. Each of the aerosol generator 120, computing device 130, and server 140 may have at least one processor such that the aerosol generating system 100 has at least one processor for performing at least one step of method 200.

[0105] For example, Method 200 may be carried out by an electronic device or electronic system. The aerosol generating system 100 described in relation to Figures 1A to 1C can carry out Method 200. In one embodiment, Method 200 is carried out by a system, and any of the features of the aerosol generating system described in relation to Figures 1A to 1C can be part of the system in which Method 200 is carried out.

[0106] Method 200 includes, in step 210, that at least one captured image of the user is acquired by at least one of an aerosol generator, a computing device, and a server. For example, at least one captured image of the user may be acquired by a computing device, such as a mobile computing device that includes an image acquisition sensor. The image acquisition sensor may be used to acquire at least one image of the user. The user may request the use of an aerosol generator. For example, the user may provide input to the aerosol generator or the computing device, which instructs the image acquisition sensor to acquire at least one image of the user. The image acquisition sensor may be part of the aerosol generator or may be separate from the aerosol generator.

[0107] In step 220, the user's voice data is acquired by at least one of the aerosol generator, the computing device, and the server. The voice data may be acquired by measuring or capturing the user's sounds, such as the user's voice. For example, the computing device may measure the sounds produced by the user's voice in order to acquire the voice data. The computing device may then send the voice data to the server for further processing. The voice data may be anonymized voice data.

[0108] In step 230, at least one image of the user is converted into at least one corresponding anonymized pixel map. This may be done by a computing device that captures at least one image of the user. A neural network may be used to anonymize at least one image of the user.

[0109] In step 240, the anonymized pixel map is sent to the server to estimate the user's age. The server may process the anonymized pixel map.

[0110] In step 242, at least one image of the user is verified as authentic, for example, at least one image of the user depicts a living human being. For example, verifying the authenticity of at least one image of the user may include determining whether at least one image of the user has been tampered with by analyzing at least one image of the user using a neural network to recognize presentation attacks. Additionally or alternatively, verifying the authenticity of at least one image of the user may include determining that a detected sound of the user corresponds to at least one image of the user. Additionally or alternatively, verifying the authenticity of at least one image of the user may include determining the user's muscle movements in at least two of the captured images of the user. Verification may be performed by at least one of the aerosol generator, computing device, and server.

[0111] In step 250, the user's age is estimated based on at least one image of the user. Estimating the user's age based on at least one image of the user may include estimating the user's age based on an anonymized pixel map on a server. The user's age may be estimated by at least one of the aerosol generator, the computing device, and the server. The user's age may be estimated based on at least one image of the user and the user's acquired voice data. In one embodiment, the user's age estimated based on at least one image of the user is validated using the user's acquired voice data.

[0112] Step 260 includes determining whether the user's estimated age exceeds a threshold. This determination may be performed by the aerosol generator, computing device, or server.

[0113] In step 270, the aerosol generator is unlocked to generate aerosols from the aerosol-forming substrate when it is determined that the estimated age exceeds a threshold. Unlocking the aerosol generator may involve the computing device instructing the aerosol generator to switch from a locked state to an unlocked state.

[0114] In step 280, the aerosol generator remains locked when it is determined that the estimated age is below the threshold. In the locked state, the aerosol generator cannot generate aerosols from the aerosol-forming substrate.

[0115] In step 290, at least one image of the user and at least one of the anonymized pixel maps are deleted after determining the user's estimated age and / or unlocking the aerosol generator.

[0116] For the purposes of this specification and the appended claims, unless otherwise indicated, all numbers representing amounts, quantities, proportions, etc., are understood to be modified in all cases by the term “approximately.” Furthermore, all ranges include the disclosed maximum and minimum points and any intermediate ranges therewith, which may or may not be specifically listed herein. In this context, the digit A may be considered to include a number that falls within the general standard error of the measurement of the characteristic that digit A modifies. In some cases as used in the appended claims, digit A may deviate by the proportions listed above, provided that the amount of deviation of A does not substantially affect the basic and novel characteristics of the claimed invention. Furthermore, all ranges include the disclosed maximum and minimum points and any intermediate ranges therewith, which may or may not be specifically listed herein.

Claims

1. Aerosol generation system, An aerosol generator configured to generate aerosols from an aerosol-forming substrate in an unlocked state, An image acquisition sensor configured to capture at least one image of the user of the aerosol generator, At least one processor, Based on the aforementioned image of the user, the user's age is estimated. Determine whether the estimated age of the user exceeds the threshold or is equal to the threshold. The at least one processor is configured to unlock the aerosol generator when the estimated age exceeds or equals the threshold, Aerosol generators, including those mentioned above.

2. The aerosol generating system according to claim 1, comprising a microphone configured to record the voice of the user, wherein at least one processor is configured to estimate the user's age based on at least one image of the user and the recorded voice of the user.

3. The aerosol generating system according to any one of claims 1 and 2, comprising the user's mobile computing device, wherein the mobile computing device is equipped with the image acquisition sensor.

4. The at least one processor, Converting the user's at least one image into at least one corresponding anonymized pixel map on the mobile computing device, The anonymized pixel map is transmitted from the mobile computing device to the server. The aerosol generating system according to claim 3, wherein the user's age is estimated based on the anonymized pixel map on the server.

5. The aerosol generating system according to claim 4, wherein the at least one processor is configured to determine the estimated age of the user and / or to delete at least one of the user's at least one image and at least one of the anonymized pixel map after unlocking the aerosol generating device.

6. The aerosol generating system according to any one of claims 1 to 5, wherein the user's age is estimated by using a machine learning model, for example, a neural network, preferably a deep neural network.

7. The at least one processor, the at least one image of the user, By analyzing at least one of the user's images using a neural network to recognize presentation attacks, it is possible to determine whether at least one of the user's images has been tampered with, The detected voice of the user is determined to correspond to at least one image of the user, The aerosol generating system according to any one of claims 1 to 6, configured to confirm that it is authenticated by at least one, including determining the muscle movements of the user in at least two of the at least one images of the user.

8. The aerosol generating system according to any one of claims 1 to 7, wherein the threshold is preferably predetermined by the manufacturer of the aerosol generating device.

9. The aerosol generating system according to any one of claims 1 to 8, wherein the threshold is at least N years higher than the first age set for approving the use of the aerosol generating device, preferably N = 1 or more, 2 or more, 3 or more, 4 or more, or 5 or more.

10. The aerosol generating system according to any one of claims 1 to 9, wherein the at least one processor is configured to determine the user profile of the user based on the at least one image of the user, and optionally the aerosol generating device is configured according to the user profile.

11. The aerosol generating system according to any one of claims 1 to 10, wherein the at least one processor is configured to verify the identity of the user based on the at least one image of the user.

12. A computer implementation method for unlocking an aerosol generator, To obtain at least one image of the user of the aerosol generator, Estimating the user's age based on at least one of the user's images, Determining whether the estimated age of the user exceeds a threshold, A computer implementation method comprising: unlocking the aerosol generating device for generating aerosols from an aerosol-forming substrate when it is determined that the estimated age exceeds the threshold.

13. The computer implementation method according to claim 12, further comprising acquiring the user's voice data, wherein the user's age is estimated based on the user's at least one image and the user's acquired voice data.

14. Converting the user's at least one image into at least one corresponding anonymized pixel map, The anonymized pixel map is sent to the server to estimate the user's age, The computer implementation method according to one of claims 12 and 13, wherein the user's age is estimated based on the anonymized pixel map on the server.

15. The user's at least one image is To determine whether at least one of the user's images has been tampered with by analyzing the user's at least one image using a neural network for recognizing presentation attacks, The determination that the sound detected by the user corresponds to at least one of the user's images, A computer implementation method according to one of claims 12 to 14, comprising determining the muscle movements of the user in at least two of the at least one images of the user.

Images