Method, device, computer program, and computer-readable recording medium for generating and providing sleep content based on user sleep information

Abstract

The present invention relates to a method, device, computer program, and computer-readable recording medium for generating and providing sleep content based on user sleep information. More particularly, the present invention relates to generating and providing sleep images or sleep videos that can visually provide a user with an image or video of the user's sleep last night, generating and providing imagery induction information, or generating and providing sleep content based on user sleep information using generative artificial intelligence.

Description

[Technical Field]

[0001] The present invention relates to a method, device, computer program, and computer-readable recording medium for generating and providing sleep content based on a user's sleep information, and more specifically, to a method for generating sleep-related content based on sleep information acquired from a user's sleeping environment and providing the content to the user. [Background technology]

[0002] There are various ways to maintain and improve health, such as exercise and dietary therapy, but the most important thing is to manage sleep well, which accounts for more than 30% of our daily time. However, even though modern people have more money and money to spend on daily tasks thanks to the increasing use of machines to replace manual labor, they are unable to get a good night's sleep due to irregular eating habits, lifestyle habits, and stress, and suffer from sleep disorders such as insomnia, excessive sleep, sleep apnea syndrome, nightmares, night terrors, and sleepwalking.

[0003] According to the National Health Insurance Service, the number of people with sleep disorders in Korea increased by an average of 8% per year from 2014 to 2018, and the number of people who received treatment for sleep disorders in Korea in 2018 reached approximately 570,000.

[0004] Additionally, a 2019 sleep-related survey found that 62% of adults worldwide are unable to get as much sleep as they would like, and 67% experience sleep disorders at least once each night. Eight out of ten adults worldwide want to improve their sleep, but 60% are unable to seek medical help. Research also shows that 44% of adults worldwide have experienced a decline in sleep quality over the past five years.

[0005] Deep sleep is recognized as an important factor affecting physical and mental health, and interest in deep sleep is increasing. However, in order to improve sleep disorders, patients must visit specialized medical institutions in person, which requires additional testing fees, and continuous management is difficult, so users are not making enough effort to seek treatment.

[0006] As sleep problems become increasingly serious, the need for sleep health management is increasing, and the sleep tech market, which aims to solve sleep problems with technology, is also growing rapidly.

[0007] In addition, when analyzing and inferring information about sleep for sleep health management, more accurate inference is required through multimodal learning of various types of data rather than using only one type of data.

[0008] Korean Patent Publication No. 10-2003-0032529 discloses a sleep induction device and sleep induction method that receives input of a user's physical information and outputs vibrations and / or ultrasound waves in a frequency band detected through repetitive learning according to the user's physical condition during sleep, thereby enabling optimal sleep induction.

[0009] However, conventional technologies can reduce sleep quality due to the inconvenience caused by body-worn devices and require periodic management of the device (e.g., charging, etc.).As a result, research is currently being conducted into contactless monitoring of the user's sleep, estimating their sleep state, and managing the user's sleep according to the estimated sleep state.

[0010] In particular, a method for analyzing a user's sleep using a wearable device has recently been proposed. Korean Patent Publication No. 10-2022-0015835 relates to an electronic device for evaluating sleep quality and an operating method thereof, and proposes a method for identifying sleep cycles based on sleep-related information acquired by a wearable device during sleep time, thereby evaluating sleep quality.

[0011] However, conventional sleep analysis methods using wearable devices have problems in that sleep analysis is impossible when the wearable device is not in proper contact with the user's body or when the user is not wearing the wearable device. Also, when multiple users sleep in the same space, the movements of those not wearing the wearable device can interfere with sleep analysis of those wearing the wearable device, and sleep analysis of those not wearing the wearable device is impossible.

[0012] Therefore, there may be a demand for a technology that can easily acquire acoustic information related to a sleep environment through a user terminal (e.g., a mobile terminal) carried by a user without requiring additional equipment, and that can analyze a user's sleep stage based on the acquired acoustic information and other sleep environment information to detect the sleep state.

[0013] As a result, research has been progressing recently into a non-contact method of estimating sleep stages by monitoring breathing patterns and the degree of activation of the autonomic nervous system based on body movements during the night, and creating a sleep environment for the user based on the estimated sleep state.

[0014] Meanwhile, conventionally, sleep reports containing user sleep information are provided via applications (or apps) installed on the user's device. The presented sleep reports mostly contain quantitative information. Such quantitative sleep reports can cause users to feel psychologically uncomfortable, and low sleep scores can cause discomfort to the user.

[0015] Thus, there may be a need for a technique that provides other information in addition to quantitative information when providing sleep information.

[0016] On the other hand, as confirmed by sound therapy and the like, sound can have a significant effect on the quality of sleep, so there may be a demand for technology that provides sound information based on sleep information.

[0017] Additionally, a new field of artificial intelligence called generative artificial intelligence (Generation AI) is gaining attention. In 2018, OpenAI announced a series of large-scale language models called Generative Pre-trained Transformer (GPT), and subsequently announced the CHATGPT service on November 30, 2022. Therefore, there may be a demand for generating content related to users' sleep by utilizing new large-scale AI models to solve the technical issues in the sleep field mentioned above. [Prior art documents] [Patent documents]

[0018] [Patent Document 1] Korean Patent Publication No. 2003-0032529 [Patent Document 2] Korean Patent Publication No. 2022-0015835 Summary of the Invention [Problem to be solved by the invention]

[0019] The present invention has been devised in consideration of the above-mentioned problems of the prior art, and an object of the present invention is to provide a method, device, and computer-readable recording medium for generating and providing a sleep image or sleep video that can convert a user's mood and feelings about last night's sleep into a sleep image or sleep video and provide it to the user.

[0020] Another object of the present invention is to generate and provide sleep content for a user's sleep using generative artificial intelligence based on information about the user's sleep obtained through a sleep sensor.

[0021] Another object of the present invention is to improve the accuracy of sleep analysis by utilizing sleep information, provide useful sleep-related content to users, and improve the quality of their sleep.

[0022] Another object of the present invention is to provide a method for generating and providing imagery guidance information that can induce sleep or improve the quality of sleep.

[0023] The problems to be solved by the present invention are not limited to those mentioned above, and other problems not mentioned will be clearly understood by those skilled in the art from the description below. [Means for solving the problem]

[0024] A method for generating and providing a sleep image or a sleep video according to an embodiment of the present invention includes: a text input window providing step of providing a text input window on a display screen of a user terminal; a text transmitting step of transmitting, when text relating to a user's sleep mood, feeling, or memory of a dream is input through the text input window, the input text to an external terminal; a receiving step of receiving a sleep image or a sleep video corresponding to the text from the external terminal; and a sleep image or a sleep video providing step of providing the received sleep image or sleep video on the display screen.

[0025] In the providing of the text input window, example text may be provided in the text input window.

[0026] In the sleep image or sleep video providing step, the sleep image or sleep video may further include at least one quantitative indicator or one-line review of the user's sleep, and the one-line review may be derived in a lookup table manner pre-mapped according to the quantitative indicator.

[0027] In the sleep image or sleep video providing step, the entire sleep image or sleep video can be displayed on the display screen, or the sleep image or sleep video can be displayed on a portion of the display screen and a quantitative indicator or calendar of the user's sleep can be displayed on the remainder.

[0028] The method may further include a candidate option providing step of providing candidate options corresponding to the user's sleep mood on the display screen before the text input window providing step, and the text input window providing step may be performed when at least one of the candidate options is selected.

[0029] When at least one of the candidate options is selected, an example image corresponding to the selected option may be displayed on the display screen, and in the text input window providing step, the text input window may be displayed together with the example image.

[0030] The method may further include a sleep image or sleep video setting step of setting at least one of the style, color, background image, and partially blank image of the sleep image or sleep video after the text related to the user's sleep mood is input through the text input window.

[0031] A method for generating and providing a sleep image or a sleep video according to another embodiment of the present invention includes a candidate group providing step of providing a candidate group of keywords for a user's sleep mood, feeling, or dream memory on a display screen of a user terminal; a text transmitting step of transmitting text of the selected candidate group of keywords to an external terminal when at least one of the candidate group of keywords is selected; a receiving step of receiving a sleep image or a sleep video corresponding to the text from the external terminal; and a sleep image or a sleep video providing step of providing the received sleep image or sleep video on the display screen.

[0032] In the sleep image or sleep video providing step, the sleep image or sleep video may further include at least one quantitative indicator or one-line review of the user's sleep, and the one-line review may be derived in a lookup table manner pre-mapped according to the quantitative indicator.

[0033] In the sleep image or sleep video providing step, the entire sleep image or sleep video can be displayed on the display screen, or the sleep image or sleep video can be displayed on a portion of the display screen and a quantitative indicator or calendar of the user's sleep can be displayed on the remainder.

[0034] The method may further include a sleep image or sleep video setting step of setting at least one of the style, color, background image, and partially blank image of the sleep image or sleep video after at least one of the keyword candidate group is selected.

[0035] A method for generating and providing a sleep image or a sleep video according to another embodiment of the present invention includes a receiving step of receiving text regarding a user's sleep mood, feeling, or memory of a dream from a user terminal; a sleep image or sleep video output step of inputting the text as a learning model stored in a memory and outputting a sleep image or sleep video corresponding to the text from the learning model; and a sleep image or sleep video transmission step of transmitting the output sleep image or sleep video to the user terminal or a computing device.

[0036] The receiving step may further include a step of receiving environmental sensing information from the user terminal and classifying and measuring quantitative indicators of the user's sleep from the environmental sensing information, and the sleep image or sleep video output step may change the style or color of the output sleep image or sleep video based on the quantitative indicators.

[0037] The sleep image or sleep video output step may calculate a sleep score for the quantitative index and change a style or color of the sleep image or sleep video according to the calculated sleep score.

[0038] A computer-readable recording medium according to yet another embodiment of the present invention stores a computer program for executing the method for generating and providing a sleep image or a sleep video described above.

[0039] According to another embodiment of the present invention, a user terminal includes a display unit, a wireless communication unit, a control unit, and a memory for storing program commands to be executed by the control unit to perform operations, the operations including: providing a text input window on a display screen of the display unit; when text related to a user's sleep mood, feeling, or memory of a dream is input through the text input window, transmitting the input text to an external terminal through the wireless communication unit; receiving the sleep image or sleep video corresponding to the text from the external terminal through the wireless communication unit; and providing the received sleep image or sleep video on the display screen.

[0040] According to another embodiment of the present invention, a user terminal includes a display unit, a wireless communication unit, a control unit, and a memory for storing program commands to be executed by the control unit to perform operations, the operations including: providing a group of keyword candidates for a user's sleep mood, feeling, or memory of dreams on a display screen of the display unit; if at least one of the keyword candidates is selected, transmitting text of the selected keyword candidates to an external terminal via the wireless communication unit; receiving the sleep image or sleep video corresponding to the text from the external terminal via the wireless communication unit; and providing the received sleep image or sleep video on the display screen.

[0041] According to yet another embodiment of the present invention, an external terminal includes a communication module, a processor, and a memory storing program instructions to be executed by the processor to perform operations and storing a learning model trained by machine learning to output a predetermined sleep image or sleep video in response to input text, the operations including: receiving the text regarding a user's sleep mood, feeling, or memory of a dream from a user terminal via the communication module; inputting the text into the learning model and outputting a sleep image or sleep video corresponding to the text from the learning model; and transmitting the output sleep image or sleep video to the user terminal or computing device via the communication module.

[0042] Meanwhile, a method for generating and providing mind-guiding information according to one embodiment of the present invention may include a preparation step of preparing mind-guiding information, a preparation information provision step of providing the prepared mind-guiding information to a user, an acquisition step of acquiring sleep state information from the user, an extraction step of extracting user features based on the mind-guiding information provided to the user and the sleep state information acquired from the user, and a generation step of generating feature-based mind-guiding information based on the extracted user features.

[0043] Furthermore, according to an embodiment of the present invention, there may be provided a method for generating and providing imagery-guiding information, wherein the preparing step includes preparing the imagery-guiding information based on a look-up table.

[0044] Furthermore, according to an embodiment of the present invention, there may be provided a method for generating and providing imagery guidance information, wherein the preparing step includes preparing the imagery guidance information based on the feature-based imagery guidance information.

[0045] Furthermore, according to one embodiment of the present invention, a method for generating and providing imagery-guiding information may be provided, wherein the step of providing the prepared information includes a step of providing one or more of prepared imagery-guiding audio information, prepared imagery-guiding visual information, prepared imagery-guiding text information, and prepared imagery-guiding text audio information, or a step of providing a combination of two or more of these.

[0046] In addition, according to one embodiment of the present invention, a method for generating and providing imagery induction information may be provided, wherein the preparation information providing step includes a step of providing one or more of prepared time-series imagery induction audio information having an imagery induction scenario, prepared time-series imagery induction visual information, prepared time-series imagery induction text audio information, and prepared time-series imagery induction text information, or a step of providing a combination of two or more of these.

[0047] In addition, in the method for generating and providing image-guiding information according to an embodiment of the present invention, there may be provided a method for generating and providing image-guiding information, which includes a generated information providing step of providing the generated feature-based image-guiding information to a user.

[0048] In addition, according to one embodiment of the present invention, a method for generating and providing imagery-guiding information may be provided, wherein the generating and providing step includes a step of providing one or more of feature-based imagery-guiding audio information, feature-based imagery-guiding visual information, feature-based imagery-guiding text information, and feature-based imagery-guiding text audio information, or a step of providing a combination of two or more of these.

[0049] In addition, according to one embodiment of the present invention, a method for generating and providing imagery-guiding information may be provided, wherein the generating and providing step includes providing one or more of feature-based time-series imagery-guiding audio information having an imagery-guiding scenario, feature-based time-series imagery-guiding visual information, feature-based time-series imagery-guiding text audio information, and feature-based time-series imagery-guiding text information, or providing a combination of two or more of these.

[0050] Meanwhile, in a method for generating and providing imagery-guiding information according to an embodiment of the present invention, there may be provided a method for generating and providing imagery-guiding information, including an information preparation step of preparing information related to a user, an extraction step of extracting features of the user based on the prepared information, and a generation step of generating feature-based imagery-guiding information based on the extracted features of the user.

[0051] In addition, according to one embodiment of the present invention, a method for generating and providing image-guiding information may be provided, in which the information preparation step includes an input step of receiving information related to the user from the user.

[0052] In addition, according to one embodiment of the present invention, a method for generating and providing image-guiding information may be provided, in which the information related to the user input by the user in the input step is one or more of content selected by a swipe method, text input by the user, and keywords selected by the user from presented keywords, or a combination of two or more of these.

[0053] In addition, according to one embodiment of the present invention, there may be provided a method for generating and providing imagery guidance information, including a generating information providing step of providing the generated feature-based imagery guidance information to a user, or an acquiring step of acquiring sleep state information from a user.

[0054] In addition, according to one embodiment of the present invention, a method for generating and providing imagery induction information may be provided, wherein the feature-based imagery induction information provided in the generating and providing step is one or more of feature-based imagery induction audio information, feature-based imagery induction visual information, feature-based imagery induction text information, and feature-based imagery induction text audio information, or a combination of two or more of these.

[0055] In addition, according to one embodiment of the present invention, a method for generating and providing imagery induction information can be provided, wherein the feature-based imagery induction information provided in the generating and providing step is one or more of feature-based time-series imagery induction audio information having an imagery induction scenario, feature-based time-series imagery induction visual information, feature-based time-series imagery induction text information, and feature-based time-series imagery induction text audio information, or a combination of two or more of these.

[0056] Furthermore, according to one embodiment of the present invention, there may be provided a method for generating and providing imagery guidance information, wherein the extracting step includes extracting user features based on at least one of the provided feature-based imagery guidance information and the acquired sleep state information, or based on a combination thereof.

[0057] Meanwhile, an electronic device according to an embodiment of the present invention may include: a memory in which mind-guiding information is recorded; an output unit that outputs the recorded mind-guiding information; an acquisition unit that acquires sleep state information from a user; and a processor that extracts user features based on the output mind-guiding information and the acquired sleep state information, wherein the processor generates feature-based mind-guiding information based on the extracted user features.

[0058] In addition, according to one embodiment of the present invention, an electronic device may be provided in which, when the acquisition unit acquires sleep state information from a user in another electronic device, the acquired sleep state information is received from the other electronic device.

[0059] According to an embodiment of the present invention, an electronic device can be provided in which the imagery guidance information recorded in the memory is based on a look-up table.

[0060] According to an embodiment of the present invention, an electronic device can be provided in which the imagery guidance information recorded in the memory is based on the feature-based imagery guidance information.

[0061] Furthermore, according to one embodiment of the present invention, an electronic device can be provided in which the recorded imagery-guiding information output from the output unit is any one or more of recorded imagery-guiding audio information, recorded imagery-guiding visual information, recorded imagery-guiding text information, and recorded imagery-guiding text audio information, or a combination of two or more of these.

[0062] In addition, according to one embodiment of the present invention, an electronic device can be provided in which the recorded imagery induction information output from the output unit is any one or more of recorded time-series imagery induction audio information having an imagery induction scenario, recorded time-series imagery induction visual information, recorded time-series imagery induction text audio information, and recorded time-series imagery induction text information, or a combination of two or more of these.

[0063] In addition, according to an embodiment of the present invention, the output unit may provide an electronic device that outputs the generated feature-based image guidance information.

[0064] In addition, according to one embodiment of the present invention, an electronic device may be provided in which the feature-based imagery induction information output from the output unit is one or more of feature-based imagery induction audio information, feature-based imagery induction visual information, feature-based imagery induction text information, and feature-based imagery induction text audio information, or a combination of two or more of these.

[0065] In addition, according to one embodiment of the present invention, an electronic device can be provided in which the feature-based imagery induction information output from the output unit is one or more of feature-based time-series imagery induction audio information having an imagery induction scenario, feature-based time-series imagery induction visual information, feature-based time-series imagery induction text audio information, and feature-based time-series imagery induction text information, or a combination of two or more of these.

[0066] Meanwhile, an electronic device according to an embodiment of the present invention may include a memory in which information related to a user is recorded, and a processor that extracts features of the user based on the recorded information, and the processor generates feature-based imagery guidance information based on the extracted features of the user.

[0067] According to an embodiment of the present invention, an electronic device may further include an input unit that receives information related to the user from the user.

[0068] In addition, according to one embodiment of the present invention, an electronic device may be provided in which the information related to the user input to the input unit is one or more of content selected by a swipe, text input by the user, and keywords selected by the user from presented keywords, or a combination of two or more of these.

[0069] According to an embodiment of the present invention, an electronic device may further include an output unit that outputs the generated feature-based image guidance information or an acquisition unit that acquires sleep state information from a user.

[0070] In addition, according to one embodiment of the present invention, an electronic device may be provided in which, when the acquisition unit acquires sleep state information from a user in another electronic device, the acquired sleep state information is received from the other electronic device.

[0071] In addition, according to one embodiment of the present invention, an electronic device may be provided in which the feature-based imagery induction information output from the output unit is one or more of feature-based imagery induction audio information, feature-based imagery induction visual information, feature-based imagery induction text information, and feature-based imagery induction text audio information, or a combination of two or more of these.

[0072] In addition, according to one embodiment of the present invention, an electronic device can be provided in which the feature-based imagery induction information output from the output unit is one or more of feature-based time-series imagery induction audio information having an imagery induction scenario, feature-based time-series imagery induction visual information, feature-based time-series imagery induction text information, and feature-based time-series imagery induction text audio information, or a combination of two or more of these.

[0073] Furthermore, according to one embodiment of the present invention, an electronic device may be provided in which the processor extracts features of a user based on one or more of the output feature-based image guidance information and the acquired sleep state information, or based on a combination thereof.

[0074] Meanwhile, an electronic device according to an embodiment of the present invention may include a memory in which mind-guiding information is recorded, an output unit that outputs the recorded mind-guiding information, an acquisition unit that acquires sleep state information from a user, means for transmitting the output mind-guiding information and the acquired sleep state information to a server, means for receiving the extracted user features if the server extracts user features based on the transmitted mind-guiding information and the transmitted sleep state information, and means for generating feature-based mind-guiding information based on the received user features.

[0075] Meanwhile, in an electronic device according to an embodiment of the present invention, an electronic device may be provided that includes: a memory in which information related to a user is recorded; means for transmitting the recorded information to a server; means for receiving the extracted user features when the server extracts user features based on the transmitted information; and means for generating feature-based image guidance information based on the received user features.

[0076] Meanwhile, an electronic device according to an embodiment of the present invention may include a memory in which mind-guiding information is recorded, an output unit that outputs the recorded mind-guiding information, an acquisition unit that acquires sleep state information from a user, means for transmitting the output mind-guiding information and the sleep state information to a server, and means for the server to extract user features based on the transmitted mind-guiding information and the transmitted sleep state information, and, if the server generates feature-based mind-guiding information based on the extracted user features, receiving the generated feature-based mind-guiding information.

[0077] Meanwhile, in an electronic device according to an embodiment of the present invention, there may be provided an electronic device including: a memory in which information related to a user is recorded; means for transmitting the recorded information to a server; and means for the server to extract user features based on the transmitted information, and if the server generates feature-based image guidance information based on the extracted user features, receiving the generated feature-based image guidance information.

[0078] Meanwhile, an electronic device according to an embodiment of the present invention may include a memory in which mind-guiding information is recorded, an output unit that outputs the recorded mind-guiding information, an acquisition unit that acquires sleep state information from a user, a processor that extracts user features based on the output mind-guiding information and the acquired sleep state information, means for transmitting the extracted user features to a server, and means for receiving the generated feature-based mind-guiding information if the server generates feature-based mind-guiding information based on the transmitted user features.

[0079] Meanwhile, in an electronic device according to an embodiment of the present invention, there may be provided an electronic device including: a memory in which information related to a user is recorded; a processor that extracts user features based on the recorded information; means for transmitting the extracted user features to a server; and means for receiving the generated feature-based image guidance information when the server generates feature-based image guidance information based on the transmitted user features.

[0080] Meanwhile, in a server device implemented with a model for generating and providing imagery guidance information according to one embodiment of the present invention, the model for generating and providing imagery guidance information may extract user features based on user sleep state information acquired through an acquisition unit of the electronic device and imagery guidance information output through an output unit of the electronic device, and generate feature-based imagery guidance information based on the extracted user features.

[0081] Meanwhile, in a server device in which a model for generating and providing imagery guidance information according to one embodiment of the present invention is implemented, the model for generating and providing imagery guidance information may extract user features based on information about the user's sleep state acquired through an acquisition unit of the electronic device and information related to the user recorded in a memory of the electronic device, and generate feature-based imagery guidance information based on the extracted user features.

[0082] Alternatively, according to one embodiment of the present invention, a method for generating and providing sleep content based on user sleep information using generative artificial intelligence may be provided, including a sleep information acquisition step of acquiring sleep information from one or more sleep information sensor devices (the sleep information includes user sleep acoustic information), a step of generating one or more data arrays related to the user's sleep based on the acquired sleep information, a step of inputting the generated user sleep features into a content-generating artificial intelligence, and a step of generating user sleep content based on the output of the content-generating artificial intelligence.

[0083] In addition, according to one embodiment of the present invention, there may be provided a method for generating and providing sleep content based on user sleep information using generative artificial intelligence, wherein the sleep information acquiring step includes a step of converting the frequency components of the user's sleep acoustic information into information including changes in time axis and performing an analysis on the changed information.

[0084] In addition, according to one embodiment of the present invention, the converted information visualizes changes in frequency components of the sleep acoustic information over time, and a method for generating and providing sleep content based on user sleep information using generative artificial intelligence can be provided.

[0085] In addition, according to one embodiment of the present invention, the sleep information acquisition step may include a sleep information inference step of inferring information about sleep using the user's sleep acoustic information as an input of a sleep information inference deep learning model, and a method for generating and providing sleep content based on user sleep information using generative artificial intelligence may be provided.

[0086] In addition, according to one embodiment of the present invention, a method for generating and providing sleep content based on user sleep information using generative artificial intelligence can be provided, in which the sleep information acquisition step includes a step of outputting the inferred sleep information as a hypnogram in the time domain.

[0087] In addition, according to one embodiment of the present invention, there may be provided a method for generating and providing sleep content based on user sleep information using generative artificial intelligence, wherein the step of generating one or more data sequences related to the user's sleep includes a step of generating one or more data sequences related to the user's sleep based on the inferred sleep information.

[0088] In addition, according to one embodiment of the present invention, there is provided a method for generating and providing sleep content based on user sleep information using generative artificial intelligence, wherein in the step of generating one or more data sequences related to the user's sleep, the one or more data sequences related to the user's sleep are tensors.

[0089] In addition, according to one embodiment of the present invention, there may be provided a method for generating and providing sleep content based on user sleep information using generative artificial intelligence, wherein the step of generating one or more data sequences related to the user's sleep includes a step of generating one or more data sequences related to the user's sleep by inputting the inferred sleep information into a large language model to generate one or more data sequences related to the user's sleep.

[0090] In addition, according to one embodiment of the present invention, the large language model is a generative artificial intelligence model based on a GPT model, and a method for generating and providing sleep content based on user sleep information using generative artificial intelligence can be provided.

[0091] In addition, according to one embodiment of the present invention, the large language model is a generative artificial intelligence model based on the BERT model, and a method for generating and providing sleep content based on user sleep information using generative artificial intelligence can be provided.

[0092] In addition, according to one embodiment of the present invention, there may be provided a method for generating and providing sleep content based on user sleep information using generative artificial intelligence, wherein the step of generating one or more data arrays related to the user's sleep includes a step of generating one or more data arrays related to the user's sleep in a lookup table based on the inferred sleep information to generate one or more data arrays related to the user's sleep.

[0093] In addition, according to one embodiment of the present invention, in the step of generating one or more data arrays related to the user's sleep, the one or more data arrays related to the user's sleep may be generated based on the user's sleep-related preference information, thereby providing a method for generating and providing sleep content based on user sleep information using generative artificial intelligence.

[0094] In addition, according to one embodiment of the present invention, in the step of generating one or more data arrays related to the user's sleep, the one or more data arrays related to the user's sleep may be generated based on the user's sleep index information.

[0095] In addition, according to one embodiment of the present invention, in the step of generating one or more data arrays related to the user's sleep, the one or more data arrays related to the user's sleep may be generated based on the user's sleep score.

[0096] In addition, according to one embodiment of the present invention, a method for generating and providing sleep content based on user sleep information using generative AI may be provided, wherein the step of inputting to the content-generating AI includes a data sequence processing step for inputting one or more generated data sequences related to the user's sleep to the content-generating AI.

[0097] In addition, according to one embodiment of the present invention, a method for generating and providing sleep content based on user sleep information using generative AI may be provided, wherein the data array processing step further includes a step of receiving user keywords to input to the content generating AI.

[0098] In addition, according to one embodiment of the present invention, a method for generating and providing sleep content based on user sleep information using generative AI may be provided, wherein the step of inputting to the content-generating AI includes a step of generating one or more keywords related to the user's sleep based on one or more data sequences related to the user's sleep.

[0099] In addition, according to one embodiment of the present invention, there may be provided a method for generating and providing sleep content based on user sleep information using generative artificial intelligence, wherein the step of generating one or more keywords related to the user's sleep includes a step of generating one or more keywords related to the user's sleep based on a lookup table corresponding to one or more data sequences related to the user's sleep.

[0100] In addition, according to one embodiment of the present invention, there may be provided a method for generating and providing sleep content based on user sleep information using generative artificial intelligence, wherein the step of generating one or more keywords related to the user's sleep includes a step of generating one or more keywords related to the user's sleep by inputting one or more data sequences related to the user's sleep into a large-scale language model.

[0101] In addition, according to one embodiment of the present invention, a method for generating and providing sleep content based on user sleep information using generative AI may be provided, wherein the feature processing step includes a step of inputting a method for interpreting one or more data sequences related to the user's sleep to input into the content generating AI.

[0102] In addition, according to one embodiment of the present invention, the content-generating artificial intelligence is an artificial intelligence model based on a large-scale language model, and a method for generating and providing sleep content based on user sleep information using generative artificial intelligence can be provided.

[0103] In addition, according to one embodiment of the present invention, the large-scale language model-based content generating artificial intelligence can provide a method for generating and providing sleep content based on user sleep information using generative artificial intelligence, which is a GPT model-based generative artificial intelligence model.

[0104] In addition, according to one embodiment of the present invention, the large-scale language model-based content generating artificial intelligence can provide a method for generating and providing sleep content based on user sleep information using generative artificial intelligence, which is a generative artificial intelligence model based on a BERT model.

[0105] In addition, according to one embodiment of the present invention, a method for generating and providing sleep content based on user sleep information using generative AI may be provided, wherein the step of generating the user sleep content includes a step of generating sleep text content based on an output of the content-generating AI.

[0106] In addition, according to one embodiment of the present invention, a method for generating and providing sleep content based on user sleep information using generative AI may be provided, wherein the step of generating sleep text content includes a step of generating basic sleep sentences based on an output of the content-generating AI.

[0107] In addition, in one embodiment of the present invention, a method for generating and providing sleep content based on user sleep information using generative AI may be provided, wherein the step of generating sleep text content further includes a step of extracting key sleep keywords based on the basic sleep sentences and a step of receiving user input keywords.

[0108] In one embodiment of the present invention, a method for generating and providing sleep content based on user sleep information using generative AI may be provided, wherein the step of generating the user sleep content includes a step of generating sleep sound source content based on an output of the content-generating AI.

[0109] In addition, in one embodiment of the present invention, the sleep sound content generating step may include a step of measuring similarities between the generated sleep sentences and sound samples, and combining the one or more sound samples based on the similarities to generate sleep sound content.

[0110] In one embodiment of the present invention, a method for generating and providing sleep content based on user sleep information using generative artificial intelligence may be provided, wherein the step of generating the user sleep content includes a step of generating sleep visual content based on the output of the content-generating artificial intelligence.

[0111] In addition, in one embodiment of the present invention, a method for generating and providing sleep content based on user sleep information using generative artificial intelligence may be provided, wherein the step of generating the user sleep content includes a step of providing the generated sleep text content and the generated sleep sound content to a user.

[0112] In one embodiment of the present invention, the step of generating the user's sleep content may further include a step of providing the generated sleep visual content to the user, and a method for generating and providing sleep content based on user's sleep information using generative artificial intelligence may be provided.

[0113] In addition, in one embodiment of the present invention, there is provided a method for generating and providing sleep content based on user sleep information using generative artificial intelligence, in which keywords and titles of the generated sleep sound content and the generated sleep text content are chronologically consistent.

[0114] Meanwhile, in a method for generating and providing sleep content based on user sleep information using generative AI according to an embodiment of the present invention, there may be provided a method for generating and providing sleep content based on user sleep information using generative AI, including: a user keyword input step; a step of generating base sentences using the input user keywords as inputs of a large-scale language model; a sleep sentence keyword refining step of selecting sleep sentence keywords based on the generated base sentences; a sleep content theme selection step based on the selected sentence keywords; and a step of generating sleep content based on the selected sleep content theme.

[0115] In addition, in one embodiment of the present invention, the user keyword input step may include a step of receiving the user keyword directly from the user, and a method for generating and providing sleep content based on user sleep information using generative artificial intelligence may be provided.

[0116] In one embodiment of the present invention, the user keyword input step may include a step of receiving the user keyword from user information, and a method for generating and providing sleep content based on user sleep information using generative artificial intelligence may be provided.

[0117] In addition, in one embodiment of the present invention, the sleep sentence keyword refining step may include a step of extracting sleep sentence keywords by using the generated base sentences as inputs of a large-scale language model, and a method for generating and providing sleep content based on user sleep information using generative artificial intelligence may be provided.

[0118] In one embodiment of the present invention, the sleep content theme selection step may include a step of measuring a first similarity, which is a similarity between a title of a sound sample in a sound sample list and the selected sentence keyword and the input user keyword, and a step of selecting a theme of the sleep content based on the measured first similarity.

[0119] In addition, in one embodiment of the present invention, there may be provided a method for generating and providing sleep content based on user sleep information using generative AI, wherein the step of selecting the sleep content theme further includes a step of selecting one or more sleep content events based on the selected sleep sentence keywords and the input user keywords.

[0120] In one embodiment of the present invention, a method for generating and providing sleep content based on user sleep information using generative artificial intelligence may be provided, wherein the step of selecting one or more sleep content events includes a step of removing adjectives from the input user keywords, a second similarity measurement step of measuring a second similarity, which is the similarity between the user keywords from which the adjectives have been removed and the titles of the sound source samples in the sound source sample list, and a step of selecting sleep content events based on the measured second similarity.

[0121] In addition, in one embodiment of the present invention, a method for generating and providing sleep content based on user sleep information using generative artificial intelligence may be provided, wherein the step of measuring the second similarity includes a step of determining that the second similarity exists if there is a common word between the sound source sample title and the user keyword from which the adjectives have been removed.

[0122] In one embodiment of the present invention, the step of selecting one or more sleep content events may include a step of measuring a third similarity, which is a similarity between a sound sample title in the sound sample list and the selected sentence keyword and the input user keyword, and a step of selecting a sound sample title in the sound sample list excluding the selected sleep content theme as a sleep content event based on the measured third similarity.

[0123] In addition, in one embodiment of the present invention, a method for generating and providing sleep content based on user sleep information using generative artificial intelligence may be provided, wherein the step of generating sleep content based on the selected sleep content theme and the selected content event includes: generating sleep content sentences using the generated basic sentences, the selected sleep content theme, and the selected sleep content event as inputs to a large-scale language model; and generating sleep sound source content based on the generated sleep content sentences.

[0124] In addition, in the step of generating the sleep sound content according to an embodiment of the present invention, the generated sleep sound content may correspond to the order of the generated sleep content sentences, thereby providing a method for generating and providing sleep content based on user sleep information using generative artificial intelligence.

[0125] Meanwhile, in a storage medium for generating and providing sleep content based on user sleep information using generative artificial intelligence according to one embodiment of the present invention, a non-transitory computer-readable storage medium storing one or more programs configured to be executed by one or more processors for generating and providing sleep content based on user sleep information using generative artificial intelligence may be provided, wherein the one or more programs include instructions to perform one or more of the above-mentioned methods.

[0126] Meanwhile, in an apparatus for generating and providing sleep content based on user sleep information using generative artificial intelligence according to one embodiment of the present invention, a device for generating and providing sleep content based on user sleep information using generative artificial intelligence can be provided, which includes a display unit, one or more processors, and a memory for storing one or more programs configured to be executed by the one or more processors (the one or more programs include instructions for performing one or more of the above-mentioned methods). [Effects of the Invention]

[0127] The method for generating and providing a sleep image or sleep video according to an embodiment of the present invention has the advantage that the user does not feel any resistance or discomfort from the quantitative value because the quality of last night's sleep is not directly provided to the user.

[0128] In addition, by creating and sharing sleep images or videos, it is possible to retain existing users and attract new users.

[0129] Another advantage is that qualitative sleep data of the user can be obtained through text about the user's sleep last night.

[0130] In addition, according to the present invention, one or more data sequences are generated based on sleep information, and the data sequences are input into a content-generating artificial intelligence to generate sleep-related sleep content, provide user-customized sleep content, enhance the user's intuitive understanding of sleep, and contribute to improving the quality of the user's sleep.

[0131] According to the present invention, by generating and providing imagery guidance information, it is possible to induce sleep in a user and improve the quality of sleep.

[0132] The effects of the present invention are not limited to those mentioned above, and other effects not mentioned will be clearly understood by those skilled in the art from the following description. [Brief explanation of the drawings]

[0133] [Figure 1a] 1 is a conceptual diagram illustrating a system in which various aspects of a sleep content generating device or a sleep content providing device based on user sleep information can be implemented according to an embodiment of the present invention. [Figure 1b] 1 is a conceptual diagram illustrating a system in which various aspects of a sleep content generating device or a sleep content providing device based on user sleep information can be implemented according to an embodiment of the present invention. [Figure 1c] 1 is a conceptual diagram illustrating a system in which sleep content generation and provision based on user sleep information is implemented in a user terminal 300 according to an embodiment of the present invention. [Figure 1d] 1 is a conceptual diagram illustrating a system of an apparatus 100a for generating imagery-guiding information based on sleep state information according to an embodiment of the present invention. [Figure 1e] 1 is a conceptual diagram illustrating a system of an apparatus 200a for providing imagery guidance information based on sleep state information according to an embodiment of the present invention. [Figure 1f] 1 illustrates a conceptual diagram showing a system in which various aspects of a computing device for creating a sleep environment based on sleep state information can be implemented, according to an embodiment of the present invention. [Figure 1g] 10 shows a conceptual diagram illustrating a system in which various aspects of a sleep environment adjusting device can be implemented according to still another embodiment of the present invention. [Figure 1h] 10 is a conceptual diagram illustrating a system in which various aspects of various electronic devices according to still another embodiment of the present invention can be implemented. [Figure 1i] 1 is a diagram illustrating a system for generating and providing a sleep image according to an embodiment of the present invention; [Figure 2a] 7 is a block diagram illustrating a configuration of a sleep content generating device 700 / providing device 800 based on user sleep information according to an embodiment of the present invention. [Figure 2b] FIG. 6 is a block diagram showing the configuration of an electronic device 600 according to the present invention. [Figure 2c] 1 is an exemplary view showing a space related to a user's sleep environment according to an embodiment of the present invention; [Figure 2d] 1 is a block diagram illustrating a computing device 100 according to one embodiment of the present invention. [Figure 2e] 1 is a block diagram illustrating an external terminal 200 according to an embodiment of the present invention. [Figure 2f] 1 is a block diagram illustrating a user terminal 300 according to an embodiment of the present invention. [Figure 2g] 1 shows an exemplary block diagram of a sleep environment adjusting device according to an embodiment of the present invention. [Figure 2h] 2 shows an exemplary block diagram of a receiving module and a transmitting module according to one embodiment of the present invention; [Figure 2i]1 is an exemplary view illustrating a second sensor unit that detects whether a user is located in an area (or sleep detection area) 11a where environmental sensing information can be obtained, according to an embodiment of the present invention. [Figure 3a] 1 is a graph verifying the performance of the sleep analysis method according to the present invention, which compares polysomnography (PSG) results with analysis results using the AI ​​algorithm according to the present invention. [Figure 3b] 1 is a graph verifying the performance of the sleep analysis method according to the present invention, which compares polysomnography (PSG) results with analysis results using the AI ​​algorithm according to the present invention. [Figure 3c] 1 is a graph verifying the performance of the sleep analysis method according to the present invention, which compares the results of polysomnography (PSG) testing (PSG results) with the analysis results (AI results) using the AI ​​algorithm according to the present invention in relation to sleep apnea and hypopnea. [Figure 4] 1 is a diagram showing an experimental process for verifying the performance of a sleep analysis method according to the present invention; [Figure 5] 1 is an exemplary diagram illustrating a process of acquiring sleep sound information from environmental sensing information according to an embodiment of the present invention; [Figure 6a] 1 is an exemplary diagram illustrating a method for acquiring a spectrogram corresponding to sleep acoustic information according to an embodiment of the present invention; [Figure 6b] 1 is a diagram illustrating a sleep stage analysis using a spectrogram in a sleep analysis method according to the present invention; [Figure 6c] 1 is a diagram illustrating a sleep disorder determination using a spectrogram in a sleep analysis method according to the present invention; [Figure 7] 1 is an exemplary diagram illustrating time-point environment creation information generated based on a user's sleep state according to an embodiment of the present invention; [Figure 8]1 illustrates an exemplary flowchart for providing a method for creating a sleep environment based on sleep state information, according to an embodiment of the present invention. [Figure 9] FIG. 2 is a schematic diagram illustrating one or more network functions according to an embodiment of the present invention. [Figure 10] 1 is a diagram illustrating the structure of a sleep analysis model that utilizes deep learning to analyze a user's sleep according to an embodiment of the present invention. [Figure 11] 4 is a conceptual diagram for explaining the operation of the environment creating device according to the present invention. FIG. [Figure 12] 1 is a block diagram showing the configuration of an environment creating device according to the present invention; [Figure 13] 10 is a flowchart illustrating an example of a process of acquiring sleep state information through a sleep measurement mode of an environment creating device according to an embodiment of the present invention. [Figure 14] 4 is a flowchart illustrating an example of a process for creating an environment that induces a user to fall asleep according to an embodiment of the present invention. [Figure 15] 1 is a flowchart illustrating an example of a process for changing a user's sleep environment during sleep and immediately before waking up according to an embodiment of the present invention. [Figure 16] 10 is a diagram illustrating yet another example of a hypnogram displaying sleep stages within a user's sleep period according to an embodiment of the present invention. [Figure 17a] 1 is a diagram illustrating a non-numerical evaluation of a user's sleep according to an embodiment of the present invention; [Figure 17b] 1 is a diagram for explaining a sleep score, which is a numerical evaluation of a user's sleep. [Figure 18] 1 is a diagram for explaining the structure of a Transformer model that forms the basis of a large language model. [Figure 19] 1 is a diagram illustrating an inverter model of a diffusion model in a content generating artificial intelligence according to an embodiment of the present invention. [Figure 20] 1 is a diagram illustrating a generator and a discriminator of a generative adversarial network (GAN) in a content generating artificial intelligence according to an embodiment of the present invention. [Figure 21] 1 is a flow chart illustrating steps for generating a sleep plot. [Figure 22] 1 is a diagram illustrating sleep sound source content generated by a content generating artificial intelligence according to an embodiment of the present invention. [Figure 23] 1 is a diagram illustrating sleep content generated by a content-generating artificial intelligence according to an embodiment of the present invention. [Figure 24] 1 is a diagram illustrating keyword matching between sleep sound source content and sleep text content generated by a content generation type artificial intelligence according to an embodiment of the present invention. [Figure 25] 3 is a diagram illustrating an embodiment of a user terminal 300 that provides image guidance information based on sleep state information according to an embodiment of the present invention. [Figure 26a] 1 is a diagram illustrating a method in which a user swipes to check certain content in an emotional modeling method according to the present invention; [Figure 26b] 1 is a diagram illustrating a method for receiving input of text preferred by a user in an emotional modeling method according to the present invention; [Figure 26c] 1 is a diagram illustrating a method for selecting keywords for content preferred by a user in an emotional modeling method according to the present invention; [Figure 27] 1 is a flowchart illustrating an example of a method for generating and providing a sleep image according to an embodiment of the present invention. [Figure 28] The flowchart of FIG. 27 shows an example of an actual screen that is specifically implemented in the user terminal 300. [Figure 29]The flowchart of FIG. 27 shows an example of an actual screen that is specifically implemented in the user terminal 300. [Figure 30] The flowchart of FIG. 27 shows an example of an actual screen that is specifically implemented in the user terminal 300. [Figure 31] The flowchart of FIG. 27 shows an example of an actual screen that is specifically implemented in the user terminal 300. [Figure 32] The flowchart of FIG. 27 shows an example of an actual screen that is specifically implemented in the user terminal 300. [Figure 33] The flowchart of FIG. 27 shows an example of an actual screen that is specifically implemented in the user terminal 300. [Figure 34] The flowchart of FIG. 27 shows an example of an actual screen that is specifically implemented in the user terminal 300. [Figure 35] The flowchart of FIG. 27 shows an example of an actual screen that is specifically implemented in the user terminal 300. [Figure 36] The flowchart of FIG. 27 shows an example of an actual screen that is specifically implemented in the user terminal 300. [Figure 37] 1 is a diagram illustrating an example of a sleep image according to an embodiment of the present invention; [Figure 38] 10 is a diagram illustrating a sleep image according to another embodiment; [Figure 39] 10 is a diagram illustrating a sleep image according to another embodiment; [Figure 40] 10 is a diagram illustrating a sleep image according to another embodiment; [Figure 41] The flowchart of FIG. 27 shows an example of an actual screen that is specifically implemented in the user terminal 300. [Figure 42] 10 is a flowchart illustrating a sleep image providing method according to another embodiment of the present invention. [Figure 43] 10 is a flowchart illustrating a sleep image providing method according to another embodiment of the present invention. [Figure 44]10 is a flowchart illustrating a sleep image providing method according to another embodiment of the present invention. [Figure 45] 1 is a diagram illustrating consistency training according to an embodiment of the present invention; [Figure 46] 1 is a flowchart illustrating a method for analyzing sleep state information, including a process of combining sleep acoustic information and sleep environment information into multimodal data, according to an embodiment of the present invention. [Figure 47] 1 is a flowchart illustrating a method for analyzing sleep state information including combining inferred sleep acoustic information and inferred sleep environment information into multimodal data according to an embodiment of the present invention. [Figure 48] 1 is a flowchart illustrating a method for analyzing sleep state information including combining inferred sleep acoustic information with sleep environment information and multimodal data according to an embodiment of the present invention. [Figure 49] 1 is a diagram illustrating a linear regression analysis function used to analyze AHI, which is a sleep apnea occurrence index, through sleep events occurring during sleep, according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0134] The advantages and features of the present invention, and methods for achieving them, will become apparent from the following detailed description of the embodiments in conjunction with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below, and may be embodied in various different forms. The present embodiments are provided solely to ensure that the disclosure of the present invention is complete and to fully convey the scope of the present invention to those skilled in the art. The present invention is defined only by the scope of the claims.

[0135] The terms used in this specification are for the purpose of describing embodiments and are not intended to limit the present invention. In this specification, the singular includes the plural unless otherwise specified. The terms "comprises" and / or "comprising" used in this specification do not exclude the presence or addition of one or more other elements other than the elements listed. The same reference numerals refer to the same elements throughout this specification, and "and / or" includes each and every combination of one or more of the listed elements. Although terms such as "first," "second," etc. are used to describe various elements, these elements are not limited by these terms. These terms are used merely to distinguish one element from another. Therefore, a first element referred to below may of course be a second element within the technical spirit of the present invention.

[0136] Unless otherwise defined, all terms (including technical and scientific terms) used herein may be used in the sense commonly understood by a person of ordinary skill in the art to which the present invention belongs. Furthermore, commonly used and predefined terms are not to be interpreted ideally or excessively unless expressly defined otherwise.

[0137] The terms "module" and "module" used herein refer to software or hardware components, such as FPGAs or ASICs, that perform a certain function. However, "module" and "module" are not limited to software or hardware. A "module" or "module" may be configured to reside on an addressable storage medium or to execute on one or more processors. Thus, by way of example, a "module" or "module" includes components such as software components, object-oriented software components, class components, and task components, as well as processes, functions, attributes, procedures, subroutines, program code segments, drivers, firmware, microcode, circuits, data, databases, data structures, tables, arrays, and variables. The components and functionality provided within a "module" or "module" may be combined into fewer components and "modules" or "modules" or further separated into additional components and "modules" or "modules."

[0138] In this specification, the term "computer" refers to any type of hardware device including at least one processor, and may also encompass software configurations operating on such hardware devices according to embodiments. For example, the term "computer" may refer to, but is not limited to, smartphones, tablet PCs, desktops, laptops, and user clients and applications running on each device.

[0139] Those skilled in the art should further recognize that the various illustrative logical blocks, components, modules, circuits, means, logic, and algorithm steps described in connection with the embodiments disclosed herein may be embodied in electronic hardware, computer software, or any combination of both. To clearly illustrate the interchangeability of hardware and software, the various illustrative components, blocks, components, means, logic, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is embodied as hardware or software depends on the particular application and design constraints imposed on the overall system. Skilled artisans may implement the described functionality in various ways for each particular application. However, such implementation decisions should not be interpreted as causing a departure from the scope of the present subject matter.

[0140] The following description sets forth example methods, parameters, etc. However, it should be recognized that such description is not intended as a limitation on the scope of the present invention, but is instead provided as a description of example embodiments.

[0141] Embodiments of electronic devices, user interfaces for such devices, and associated processes for using such devices are described. In some embodiments, the devices may include portable communication devices (e.g., mobile phones, smart watches) that include functionality other than that of a PDA and music player.

[0142] Meanwhile, there is a need for a method for generating and providing sleep content based on user sleep information using generative artificial intelligence. This is because the importance of sleep to human life has been emphasized in modern society, resulting in an increased need for sleep-related content. Providing sleep-related content to a user can provide the user with information for understanding the user's sleep evaluation from a medical perspective in a friendly manner, thereby providing sleep-related content that is more tailored to the user. Furthermore, providing content to an individual user using generative artificial intelligence can improve the tailoring of sleep content to the user and provide intuitive content, thereby improving the user's sleep quality. Additionally, this technique can provide feedback on sleep through generating and providing sleep-related content to the user, thereby providing an indirect diagnosis of the user's nighttime sleep health.

[0143] [Overall structure]

[0144] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, a method, apparatus, and system for generating and / or providing sleep content according to embodiments of the present invention will be described in detail with reference to the accompanying drawings.

[0145] Although each step described in this specification is described as being performed by a computer, the subject of each step is not limited to this, and at least some of each step may be performed by different devices depending on the embodiment.

[0146] 1a and 1b are conceptual diagrams illustrating a system in which various aspects of a sleep content generating device or sleep content providing device based on user sleep information according to an embodiment of the present invention can be implemented.

[0147] 1a, a system according to an embodiment of the present invention may include a computing device 100, a user terminal 300, an external server 20, and a network. Here, as shown in FIG. 1a, a sleep content generation device 700 and / or a sleep content providing device 800 based on user sleep information may be embodied as the computing device 100.

[0148] Also, as shown in FIG. 1a, the image-guiding information generating device 100a and / or the image-guiding information providing device 200a may be embodied as a computing device 100.

[0149] Alternatively, as shown in FIG. 1a, the sleep image generating device and / or the sleep image providing device may be embodied as a computing device 100.

[0150] Here, the system in which the user sleep information-based sleep content generation and / or provision device shown in Figure 1a is embodied is according to one embodiment, and its components are not limited to the embodiment shown in Figure 1a, and may be added, changed, or deleted as necessary.

[0151] Meanwhile, as shown in Fig. 1b, a system according to an embodiment of the present invention may include a user terminal 300, an external server 20, and a network. Here, as shown in Fig. 1b, a sleep content generating device 700 or a sleep content providing device 800 based on user sleep information may be implemented as the user terminal 300 or the external server 20 without a separate computing device 100.

[0152] As shown in FIG. 1b, the sleep content generating device based on user sleep information according to an embodiment of the present invention may be implemented as a user terminal 300, and the sleep content providing device based on user sleep information may be implemented as an external server 20.

[0153] Alternatively, as shown in FIG. 1b, the sleep content generating device based on user sleep information according to an embodiment of the present invention may be implemented as an external server 20, and the sleep content providing device based on user sleep information may be implemented as a user terminal 300.

[0154] Alternatively, as shown in FIG. 1B, the sleep content generating device based on user sleep information and the sleep content providing device based on user sleep information according to an embodiment of the present invention may both be implemented as a user terminal 300.

[0155] Alternatively, as shown in FIG. 1B, the sleep content generating device based on user sleep information and the sleep content providing device based on user sleep information according to an embodiment of the present invention may both be implemented as an external server 20.

[0156] Meanwhile, as shown in FIG. 1b, the image-guiding information generating device 100a and / or the image-guiding information providing device 200a may be embodied as a user terminal 300 or an external server 20.

[0157] Meanwhile, as shown in FIG. 1b, the sleep image generating device and / or the sleep image providing device may be implemented as a user terminal 300 or an external server 20.

[0158] Here, the system in which the user sleep information-based sleep content generating and / or providing device shown in Figure 1b is embodied is according to one embodiment, and its components are not limited to the embodiment shown in Figure 1b, and may be added, changed, or deleted as necessary.

[0159] Meanwhile, according to an embodiment of the present invention, the external server 20 may be configured as a single server or a plurality of servers. Also, according to an embodiment of the present invention, the external server 20 may be embodied as an external terminal 200.

[0160] Meanwhile, according to an embodiment of the present invention, a sleep content generating device based on user sleep information can generate sleep content using generative artificial intelligence. Also, according to an embodiment of the present invention, a sleep content providing device based on user sleep information can provide sleep content generated using generative artificial intelligence.

[0161] 1c is a conceptual diagram illustrating a system in which sleep content generation and provision based on user sleep information according to an embodiment of the present invention is implemented in a user terminal 300. As shown in FIG. 1c, sleep content may be generated and provided based on user sleep information in the user terminal 300 without a separate generating device 700 and / or a separate providing device 800.

[0162] Meanwhile, according to an embodiment of the present invention, a sleep content generating device based on user sleep information can generate sleep content using generative artificial intelligence. Also, according to an embodiment of the present invention, a sleep content providing device based on user sleep information can provide sleep content generated using generative artificial intelligence.

[0163] As shown in Figures 1a and 1b, when the sleep content generating and / or providing device based on user sleep information according to an embodiment of the present invention is embodied in a computing device 100, the computing device 100 can transmit and receive data for the system according to an embodiment of the present invention with a user terminal 300 via a network.

[0164] Also, as shown in Figures 1a and 1b, when the sleep content generating and / or providing device based on user sleep information according to an embodiment of the present invention is embodied in a computing device 100, the computing device 100 can transmit and receive data for the system according to an embodiment of the present invention with a user terminal 300 and / or an external server 20 via a network.

[0165] As shown in FIG. 1c, even if the sleep content generating device 700 and the providing device 800 based on user sleep information according to an embodiment of the present invention are not separately provided, the user terminal 300 can perform the role of the sleep content generating device 700 and / or the providing device 800 based on user sleep information via a network and mutually transmit and receive data for the system according to an embodiment of the present invention.

[0166] Also, as shown in FIG. 1c, even if the imagery guidance information generating device 100a and the imagery guidance information providing device 200a are not separately provided, the user terminal 300 can perform the role of the imagery guidance information generating device 100a and / or the imagery guidance information providing device 200a via a network and mutually transmit and receive data for the system according to one embodiment of the present invention.

[0167] Also, as shown in FIG. 1c, even if a sleep image generating device and a sleep image providing device are not separately provided, the user terminal 300 can perform the role of a sleep image generating device and / or a sleep image providing device via a network and mutually transmit and receive data for the system according to one embodiment of the present invention.

[0168] FIG. 2a is a block diagram illustrating the configuration of a device 700 for generating / providing sleep content based on user sleep information according to an embodiment of the present invention.

[0169] According to one embodiment of the present invention, a device 700 for generating sleep content based on user sleep information utilizing generative artificial intelligence may include a display 720, a memory 740 storing one or more programs configured to be executed by one or more processors 760.

[0170] Additionally, according to one embodiment of the present invention, a device 800 for providing sleep content based on user sleep information utilizing generative artificial intelligence may include a display 820, a memory 840 storing one or more programs configured to be executed by one or more processors, and one or more processors 860.

[0171] According to one embodiment of the present invention, memory 740 or memory 840 storing one or more programs may include high-speed random access memory such as DRAM, SRAM, DDR RAM, or other random access solid-state memory devices, or non-volatile memory such as one or more magnetic disk storage devices, optical disk storage devices, flash memory devices, or other non-volatile solid-state storage devices. The memory may also store instructions for performing a method of providing one or more graphical user interfaces that display information about a user's sleep.

[0172] According to an embodiment of the present invention, the processor 760 or 860 may be implemented by one or more processor means, and the processor may be capable of executing a memory that stores one or more programs.

[0173] Meanwhile, as described above, the device 700 for generating / device 800 for providing sleep content based on user sleep information according to an embodiment of the present invention can perform the operation of generating / providing sleep content based on user sleep information by utilizing generative artificial intelligence.

[0174] 1d is a conceptual diagram showing a system of an apparatus 100a for generating imagery guidance information based on sleep state information according to an embodiment of the present invention. As shown in FIG. 1d, the system of the present invention may include an apparatus 100a for generating imagery guidance information, a user terminal 300, and a network.

[0175] 1e is a conceptual diagram showing a system of an apparatus 200a for providing image guidance information based on sleep state information according to an embodiment of the present invention. As shown in FIG. 1e, the system may include an apparatus 200a for providing image guidance information of the present invention, a user terminal 300, and a network.

[0176] As shown in Figures 1d and 1e, the device 100a for generating imagery guidance information and the device 200a for providing imagery guidance information of the present invention can mutually transmit and receive data for a system according to an embodiment of the present invention via a user terminal 300 and a network.

[0177] Meanwhile, FIG. 1c is a conceptual diagram showing a system of a method for generating and providing image-guided information based on state information according to an embodiment of the present invention.

[0178] As shown in FIG. 1c, even if the device 100a for generating image guidance information and the device 200a for providing image guidance information of the present invention are not separately provided, the user terminal 300 can perform the roles of the device 100a for generating image guidance information and the device 200a for providing image guidance information via a network, and can mutually transmit and receive data for the system according to one embodiment of the present invention.

[0179] Alternatively, even if the device 700 for generating / providing sleep content based on user sleep information according to one embodiment of the present invention is not separately provided, the user terminal 300 can perform the role of the device 700 for generating / providing sleep content 800 via a network and mutually transmit and receive data for the system according to one embodiment of the present invention.

[0180] Alternatively, even if a device for generating a sleep image and a device for providing a sleep image according to one embodiment of the present invention are not separately provided, the user terminal 300 can perform the roles of a device for generating a sleep image and a device for providing a sleep image via a network, and can mutually transmit and receive data for the system according to one embodiment of the present invention.

[0181] 1f is a conceptual diagram illustrating a system in which various aspects of a computing device for creating a sleep environment based on sleep state information can be implemented according to an embodiment of the present invention. The system according to an embodiment of the present invention may include a computing device 100, a user terminal 300, an external server 20, an environment creation device 30, and a network. As shown in FIG. 1f, the computing device 100, the user terminal 300, the external server 20, and the environment creation device 30 can mutually transmit and receive data for the system according to an embodiment of the present invention via the network.

[0182] Here, the system for implementing the method for creating a sleep environment based on sleep state information shown in Figure 1f is according to one embodiment, and its components are not limited to the embodiment shown in Figure 1f, and may be added, changed, or deleted as necessary.

[0183] Meanwhile, Fig. 1g is a conceptual diagram showing a system in which various aspects of a sleep environment adjusting device can be implemented according to yet another embodiment of the present invention. The system according to the embodiment of the present invention may include a sleep environment adjusting device 400, a user terminal 300, an external server 20, and a network. Here, the system for implementing a method for creating a sleep environment based on sleep state information shown in Fig. 1g is according to one embodiment, and its components are not limited to those of the embodiment shown in Fig. 1g, and may be added, changed, or deleted as necessary.

[0184] 1h is a conceptual diagram illustrating a system in which various aspects of various electronic devices according to further embodiments of the present invention can be implemented. As shown in FIG. 1h, the electronic device shown in FIG. 1h can perform at least one of the operations performed by various devices according to embodiments of the present invention.

[0185] For example, operations performed by various electronic devices according to embodiments of the present invention may include an operation of acquiring environmental sensing information and sleep information, an operation of performing learning for sleep analysis, an operation of performing inference for sleep analysis, and an operation of acquiring sleep state information.

[0186] Alternatively, the operations performed by various devices according to embodiments of the present invention may include an operation of generating image-guided information, an operation of providing image-guided information, an operation of acquiring environmental sensing information, an operation of learning a sleep analysis model, an operation of learning sleep state information, an operation of inferring sleep state information, and an operation of displaying sleep state information.

[0187] Alternatively, for example, the system may include an operation of receiving information related to a user's sleep, transmitting or receiving at least one of environmental sensing information and sleep information, performing preprocessing on the environmental sensing information, distinguishing between the environmental sensing information and the sleep information, extracting acoustic information from the environmental sensing information and the sleep information, processing or manipulating data, processing services, providing services, constructing a learning dataset based on the environmental sensing information or the user's sleep information, storing acquired data or a plurality of data to be input into a neural network, transmitting or receiving various information, mutually transmitting and receiving data for a system according to an embodiment of the present invention via a network, generating and providing sleep content based on the user's sleep information, generating and providing imagery guidance information, generating and providing sleep images, and generating and providing sleep content using generative artificial intelligence based on the user's sleep information.

[0188] The electronic device shown in FIG. 1h may perform the operations performed by various electronic devices according to embodiments of the present invention individually, or may perform one or more operations simultaneously or sequentially.

[0189] 1h, the electronic devices (1a-1d) shown in FIG. 1h may be electronic devices located within an area (or sleep detection area) 11a from which environmental sensing information can be acquired. Hereinafter, for convenience, the area (or sleep detection area) 11a from which environmental sensing information can be acquired will be referred to as "area 11a."

[0190] On the other hand, referring to FIG. 1h, the electronic device (1a and 1d) may be a device consisting of a combination of two or more electronic devices.

[0191] Meanwhile, referring to FIG. 1h, the electronic devices (1a and 1b) may be electronic devices connected to a network within the area 11a.

[0192] On the other hand, referring to FIG. 1h, the electronic devices (1c and 1d) may be electronic devices that are not connected to the network within the area 11a.

[0193] On the other hand, referring to FIG. 1h, the electronic devices (2a-2b) may be electronic devices outside the range of the area 11a.

[0194] On the other hand, referring to FIG. 1h, there may be networks that interact with electronic devices within the area 11a, and there may be networks that interact with electronic devices outside the area 11a.

[0195] Here, the network interacting with electronic devices within the area 11a can serve to transmit and receive information for controlling smart home appliances.

[0196] Also, the network that interacts with the electronic devices within the area 11a may be, for example, a short-range network or a local network, whereas the network that interacts with the electronic devices within the area 11a may be, for example, a long-range network or a global network.

[0197] The detailed description of the operation of the network shown in FIG. 1h will be omitted as it will be explained later.

[0198] 1h, the number of electronic devices connected via a network outside the area 11a may be one or more, and in this case, the electronic devices may process data in a distributed manner or perform one or more operations separately. Here, the electronic device connected via a network outside the area 11a may include a server device.

[0199] Alternatively, if there are one or more electronic devices connected via a network outside the area 11a, the electronic devices may perform various operations independently of each other.

[0200] As shown in FIG. 1h, various electronic devices according to the present invention can mutually transmit and receive data for a system according to an embodiment of the present invention via a network.

[0201] FIG. 1i is a diagram illustrating a system for generating and providing a sleep image according to an embodiment of the present invention.

[0202] 1i, a system according to an embodiment of the present invention includes a computing device 100, an external terminal 200, and a user terminal 300 connected to a network. Hereinafter, basic hardware structures of the computing device 100, the external terminal 200, and the user terminal 300 will be described.

[0203] [Computing device 100]

[0204] FIG. 2d is an illustrative block diagram of a computing device 100 according to one embodiment of the present invention.

[0205] Referring to FIG. 2d, the computing device 100 may include at least one or more processors 110, memory 120, output devices 130, input devices 140, input / output interfaces 150, sensor modules 160, and communication modules 170.

[0206] According to an embodiment of the present invention, the computing device 100 can acquire sleep state information of a user and adjust the user's sleep environment based on the sleep state information. Specifically, the computing device 100 can acquire sleep state information related to whether the user is before sleep, during sleep, or after sleep based on environmental sensing information, and can adjust the sleep environment of the space in which the user is located according to the sleep state information.

[0207] For example, when the computing device 100 acquires sleep state information indicating that the user is about to sleep, the computing device 100 may generate environment creation information related to light intensity and illuminance for inducing sleep (e.g., 3000K white light, 30 lux illuminance) and air quality (fine dust concentration, hazardous gas concentration, air humidity, air temperature, etc.) based on the sleep state information. The computing device 100 may transmit the environment creation information related to light intensity, illuminance, and air quality for inducing sleep to the environment creation device 30. In this case, the environment creation device 30 may adjust the light intensity and illuminance of the space where the user is located to an appropriate intensity and illuminance for inducing sleep (e.g., 3000K white light, 30 lux illuminance) based on the environment creation information received from the computing device 100. That is, the environment creation information generated by the computing device 100 may be transmitted to a lighting device, which is one embodiment of the environment creation device 30, to adjust the illuminance in the sleep space.

[0208] In addition, the computing device 100 may generate various information related to the environment creation, such as removing fine dust particles, removing harmful gases, activating allergy care, activating deodorizing / sterilizing, adjusting dehumidifying / humidifying, adjusting airflow intensity, adjusting air purifier operating noise, and turning on LEDs, based on the user's sleep state information. The environment creation information generated by the computing device 100 may be transmitted to an air purifier, which is one embodiment of the environment creation device 30, to adjust the air quality in a room, a vehicle, or a sleeping space.

[0209] The above-described specific descriptions regarding the sleep state information and the environment creation information are merely examples, and the present invention is not limited thereto.

[0210] According to one embodiment, the environmental sensing information utilized by the computing device 100 for sleep state analysis may include acoustic information non-invasively acquired during a user's activity or sleep in a space. For specific examples, the environmental sensing information may include sounds generated by a user turning over in their sleep, sounds related to muscle movements, or sounds related to a user's breathing during sleep. According to an embodiment, the environmental sensing information may include sleep acoustic information, which may refer to acoustic information related to the movement patterns and breathing patterns generated during the user's sleep.

[0211] In an embodiment, the environmental sensing information may be acquired through a user terminal 300 carried by a user. For example, environmental sensing information related to a user's activity in a space may be acquired through a microphone module provided in the user terminal 300.

[0212] Generally, a microphone module installed in a user terminal 300 carried by a user may be configured with a Micro-Electro Mechanical System (MEMS) since it must be installed in a relatively small user terminal 300. Such a microphone module can be manufactured in a very small size, but may have a lower signal-to-noise ratio (SNR) than a condenser microphone or a dynamic microphone. A low SNR may mean that the sound is difficult to identify (i.e., unclear) due to a high ratio of noise, which is sound that cannot be identified at the sound ratio to be identified.

[0213] The environmental sensing information to be analyzed in the present invention may include acoustic information related to the user's breathing and movements acquired during sleep, i.e., sleep acoustic information. Such sleep acoustic information is information about very small sounds (i.e., sounds that are difficult to distinguish), such as the user's breathing and movements, and is acquired together with other sounds during sleep. Therefore, if it is acquired through the above-mentioned microphone module with a low signal-to-noise ratio, it may be very difficult to detect and analyze.

[0214] According to an embodiment of the present invention, the computing device 100 may acquire sleep state information based on environmental sensing information acquired via a microphone module configured with MEMS. Specifically, the computing device 100 may convert and / or adjust the environmental sensing information, which is acquired unclearly due to a large amount of noise, to enable analysis, and may perform training on an artificial neural network using the converted and / or adjusted data. Once pre-training of the artificial neural network is complete, the trained neural network (e.g., an acoustic analysis model) may acquire sleep state information of a user based on data (e.g., a spectrogram) acquired (e.g., converted and / or adjusted) corresponding to the sleep acoustic information. In an embodiment, the sleep state information may include not only information related to whether the user is sleeping, but also sleep stage information related to changes in the user's sleep stage during sleep. For example, the sleep state information may include sleep stage information indicating that the user was in REM sleep at a first time point and was in light sleep at a second time point different from the first time point. In this case, the sleep state information can reveal that the user fell into a relatively deep sleep at the first time point and fell into a lighter sleep at the second time point.

[0215] That is, when the computing device 100 acquires sleep sound information having a low signal-to-noise ratio through a commonly used user terminal for collecting sound (e.g., an AI speaker, a bedroom IoT device, a mobile phone, etc.), it processes the acquired data into data suitable for analysis and can provide sleep state information related to changes in sleep stages by processing the processed data. This eliminates the need for a microphone that contacts the user's body to acquire clear sound, and also provides the advantage of increasing convenience by enabling the monitoring of sleep states in a typical home environment with just a software update, without the need to purchase a separate additional device with a high signal-to-noise ratio.

[0216] In FIG. 1f, the computing device 100 and the environment creation device 30 are shown as separate entities, but according to an embodiment of the present invention, the environment creation device 30 may be included within the computing device 100, and the sleep state measurement and environment adjustment operation functions may be performed in a single integrated device.

[0217] In an embodiment, the computing device 100 may be a terminal or a server, and may include any type of device. The computing device 100 may be a digital device equipped with a processor, memory, and computing capabilities, such as a laptop computer, notebook computer, desktop computer, web pad, or mobile phone. The computing device 100 may be a web server that processes services. The types of servers described above are merely examples, and the present invention is not limited thereto.

[0218] According to an embodiment of the present invention, the computing device 100 may be a server that provides a cloud computing service. More specifically, the computing device 100 may be a server that provides a cloud computing service, a type of Internet-based computing, in which information is processed by another computer connected to the Internet, rather than the user's computer. The cloud computing service may store data on the Internet and allow users to access the data or programs they need anytime and anywhere via an Internet connection without having to install them on their own computers. The cloud computing service may also allow users to easily share and transfer data stored on the Internet with simple operations and clicks. The cloud computing service may not only simply store data on an Internet server, but also allow users to perform desired tasks using the functions of web-based applications without installing additional programs, and may allow various users to share documents and work simultaneously. The cloud computing service may be implemented in at least one form of Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS), a virtual machine-based cloud server, or a container-based cloud server. That is, the computing device 100 of the present invention may be implemented in at least one form of the above-mentioned cloud computing services. The specific description of the cloud computing service mentioned above is merely an example and may include any platform that builds the cloud computing environment of the present invention.

[0219] Meanwhile, the computing device 100 according to an embodiment of the present invention may perform an operation of generating sleep content based on user sleep information and / or an operation of providing sleep content based on user sleep information. In this case, the device 700 for generating sleep content based on user sleep information and / or the device 800 for providing sleep content based on user sleep information may not be separately provided, and a sleep content generating and providing system including the computing device 100 may be embodied.

[0220] Furthermore, the computing device 100 according to an embodiment of the present invention may perform an operation of generating and / or providing a sleep image. In this case, a sleep content generating and providing system may be implemented by including the computing device 100, without requiring a separate device for generating and / or providing a sleep image.

[0221] Furthermore, the computing device 100 according to an embodiment of the present invention may perform an operation of generating and / or providing mood-guiding information. In this case, a sleep content generating and providing system including the computing device 100 may be embodied without separately providing the device 100a for generating mood-guiding information based on sleep state information and / or the device 200a for providing mood-guiding information based on sleep state information.

[0222] [Processor 110]

[0223] The processor 110 may include one or more application processors (AP), one or more communication processors (CP), or at least one artificial intelligence processor (AI processor). The application processor, communication processor, and AI processor may be included in different integrated circuit (IC) packages or may be included in a single IC package.

[0224] The application processor may run an operating system or application, control multiple hardware or software components connected to the application processor, and perform various data processing / calculations, including multimedia data. For example, the application processor may be implemented as a system on chip (SoC). The processor 110 may further include a graphics processing unit (GPU, not shown).

[0225] The communication processor may perform functions such as managing data links and converting communication protocols for communications between the computing device 100 and other computing devices connected to a network. For example, the communication processor may be implemented in an SoC. The communication processor may perform at least a portion of a multimedia control function.

[0226] The communication processor may also control data transmission and reception by the communication module 170. The communication processor may be embodied as being included in at least a part of the application processor.

[0227] The application processor or communication processor may load instructions or data received from the non-volatile memory or at least one of the other components connected thereto into the volatile memory for processing, and may store data received from or generated by at least one of the other components in the non-volatile memory.

[0228] The computer program may include one or more instructions that, when loaded into memory 120, cause processor 110 to perform methods / operations according to various embodiments of the present invention. That is, processor 110 may perform methods / operations according to various embodiments of the present invention by executing one or more instructions.

[0229] In one embodiment, the computer program may include one or more instructions for performing a method for creating a sleep environment based on sleep state information, including acquiring sleep state information of a user, generating environment creation information based on the sleep state information, and transmitting the environment creation information to an environment creation device.

[0230] According to one embodiment of the present invention, the processor 110 may be configured with one or more cores and may include a central processing unit (CPU) of a computing device, a general purpose graphics processing unit (GPGPU), a tensor processing unit (TPU), or other processors for data analysis, deep learning, etc.

[0231] The processor 110 may read a computer program stored in the memory 120 to perform data processing for machine learning according to an embodiment of the present invention. According to an embodiment of the present invention, the processor 110 may perform calculations for neural network training. The processor 110 may perform calculations for neural network training, such as processing input data for training in deep learning (DL), extracting features from the input data, calculating errors, and updating neural network weights using backpropagation. In addition, at least one of the CPU, GPGPU, and TPU of the processor 110 may process network function training. For example, the CPU and the GPGPU may both process network function training and data classification using the network function. In addition, according to an embodiment of the present invention, processors of multiple computing devices may be used together to process network function training and data classification using the network function. In addition, a computer program executed by a computing device according to an embodiment of the present invention may be a CPU, GPGPU, or TPU executable program.

[0232] As used herein, a network function may be used interchangeably with an artificial neural network or a neural network. As used herein, a network function may include one or more neural networks, in which case the output of the network function may be an ensemble of the outputs of the one or more neural networks.

[0233] As used herein, a model may include a network function. A model may include one or more network functions, in which case the output of the model may be an ensemble of the outputs of the one or more network functions.

[0234] The processor 110 may read a computer program stored in the memory 120 to provide a sleep analysis model according to an embodiment of the present invention. According to an embodiment of the present invention, the processor 110 may perform calculations to calculate environment creation information based on sleep state information. According to an embodiment of the present invention, the processor 110 may perform calculations to train the sleep analysis model. The sleep analysis model will be described in more detail below. Sleep information related to the user's sleep quality may be inferred based on the sleep analysis model. Environmental sensing information acquired from the user in real time or periodically is input as an input value to the sleep analysis model, and data related to the user's sleep is output.

[0235] The learning of the sleep analysis model and inference based thereon may be performed by the computing device 100. That is, both the learning and inference may be designed to be performed by the computing device 100. However, in another embodiment, the learning may be performed by the computing device 100, but the inference may be performed by the user terminal 300. Also, the learning may be performed by the computing device 100, but the inference may be performed by the environment creating device 30 embodied in a smart home appliance (TV, lighting, refrigerator, air purifier), etc. Also, in another embodiment, the learning may be performed by the sleep environment adjusting device 400 of FIG. 1g. That is, the learning and inference may be performed by the sleep environment adjusting device 400. Or, the learning may be performed by the computing device 100, but the inference may be performed by the external terminal 200.

[0236] According to one embodiment of the present invention, the processor 110 may generally handle the overall operation of the computing device 100. The processor 110 may process signals, data, information, etc. input or output via the components detailed above, or may run applications stored in the memory 120, thereby providing or processing appropriate information or functions to the user terminal.

[0237] According to an embodiment of the present invention, processor 110 may acquire sleep state information of a user. According to an embodiment of the present invention, acquiring the sleep state information may involve acquiring or loading sleep state information stored in memory 120. Furthermore, acquiring the sleep sound information may involve receiving or loading data from another storage medium, another computing device, or another processing module within the same computing device, based on wired or wireless communication means.

[0238] The specific configuration, technical features, and effects of the technical features of the computing device 100 of the present invention will be described with reference to the accompanying drawings.

[0239] FIG. 2c illustrates a block diagram of a computing device for creating a sleep environment based on sleep state information in accordance with an embodiment of the present invention.

[0240] 2c, the computing device 100 may include a network unit 180, a memory 120, and a processor 110. The computing device 100 is not limited to the components included therein. That is, additional components may be included or some of the components may be omitted depending on the implementation of the embodiments of the present invention.

[0241] 1f and 2c, the computing device 100 according to an embodiment of the present invention may include a network unit 180 that transmits and receives data to and from the user terminal 300, the external server 20, and the environment creation device 30. The network unit 180 may transmit and receive data, etc., for performing the method for creating a sleep environment using sleep state information according to an embodiment of the present invention, with other computing devices, servers, etc. That is, the network unit 180 may provide a communication function between the computing device 100, the user terminal 300, the external server 20, and the environment creation device 30.

[0242] For example, the network unit 180 may receive sleep examination records and electronic health records for multiple users from a hospital server. As another example, the network unit 180 may receive environmental sensing information related to the space in which the user is active from the user terminal 300.

[0243] As another example, the network unit 180 may transmit environment creation information for adjusting the environment of the space where the user is located to the environment creation device 30. Additionally, the network unit 180 may allow information transmission between the computing device 100, the user terminal 300, and the external server 20 by calling a procedure in the computing device 100.

[0244] Meanwhile, the computing device 100 according to an embodiment of the present invention may be configured to include both the network unit 180 and the communication module 170, or may be configured to include only one of the network unit 180 and the communication module 170. In addition, the communication module 170 may perform the operations of the network unit 180 described above.

[0245] [Memory 120]

[0246] The memory 120 may include internal memory or external memory. The internal memory may include at least one of volatile memory (e.g., dynamic RAM (DRAM), static RAM (SRAM), synchronous dynamic RAM (SDRAM), etc.) or non-volatile memory (e.g., one time programmable ROM (OTPROM), programmable ROM (PROM), erasable and programmable ROM (EPROM), electrically erasable and programmable ROM (EEPROM), mask ROM, flash ROM, NAND flash memory, NOR flash memory, etc.). According to one embodiment, the internal memory may take the form of a solid state drive (SSD). The external memory may further include a flash drive, such as a compact flash (CF), secure digital (SD), micro secure digital (Micro-SD), mini secure digital (Mini-SD), extreme digital (xD), or memory stick.

[0247] According to an embodiment of the present invention, the memory 120 may store a computer program for performing a method for creating a sleep environment based on sleep state information according to an embodiment of the present invention, and the stored computer program may be read and driven by the processor 110. The memory 120 may also store any type of information generated or determined by the processor 110 and any type of information received by the network unit 180. The memory 120 may also store data related to the user's sleep. For example, the memory 120 may temporarily or permanently store input / output data (e.g., environmental sensing information related to the user's sleep environment, sleep state information corresponding to the environmental sensing information, or environment creation information based on the sleep state information).

[0248] According to an embodiment of the present invention, the memory 120 may include at least one type of storage medium selected from the group consisting of flash memory, hard disk, micro multimedia card, card-type memory (e.g., SD or XD memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, and optical disk. The computing device 100 may also operate in conjunction with web storage that performs the storage function of the memory 120 over the Internet. The above description of memory is for illustrative purposes only, and the present invention is not limited thereto.

[0249] [Output Device 130]

[0250] The output device 130 may include at least one of a display module and / or a speaker, and may display or output various data, including multimedia data, text data, and audio data, to a user.

[0251] [Input Device 140]

[0252] The input device 140 may include a touch panel, a digital pen sensor, keys, an ultrasonic input device, etc. As an example, the input device 140 may be an input / output interface 150.

[0253] The touch panel can recognize touch input using at least one of electrostatic, pressure-sensitive, infrared, and ultrasonic methods. The touch panel may further include a controller (not shown). The electrostatic type allows for proximity recognition as well as direct touch. The touch panel may further include a tactile layer. In this case, the touch panel can provide a tactile response to the user. The digital pen sensor may be implemented using the same or similar method as that for receiving a user's touch input, or a separate recognition layer. Keys may be keypads or touch keys. An ultrasonic input device is a device that detects microwaves at a terminal via a pen that generates an ultrasonic signal, enabling wireless recognition. The computing device 100 can also receive user input from an external device (e.g., a network, computer, or server) connected thereto using the communication module 170.

[0254] The input device 140 may further include a camera module and / or a microphone. The camera module may include one or more image sensors, an image signal processor (ISP), or a flash LED as a device capable of capturing images and videos. The microphone can receive audio signals and convert them into electrical signals.

[0255] [Input / Output Interface 150]

[0256] The input / output interface 150 may transmit commands or data input by a user via the input device 140 or the output device 130 to the processor 110, the memory 120, the communication module 170, etc. via a bus (not shown). For example, the input / output interface 150 may provide data corresponding to a user's touch input input via a touch panel to the processor 110. For example, the input / output interface 150 may output commands or data received from the processor 110, the memory 120, the communication module 170, etc. via the bus via the output device 130. For example, the input / output interface 150 may output audio data processed by the processor 110 to the user via a speaker.

[0257] [Sensor Module 160]

[0258] The sensor module 160 may include at least one of a gesture sensor, a gyro sensor, a barometric pressure sensor, a magnetic sensor, an acceleration sensor, a grip sensor, a proximity sensor, an RGB (red, green, blue) sensor, a biometric sensor, a temperature / humidity sensor, an illuminance sensor, or a UV (ultra violet) sensor. The sensor module 160 may measure a physical quantity or sense the operating state of the computing device 100 and convert the measured or sensed information into an electrical signal. Additionally or alternatively, the sensor module 160 may include an olfactory sensor (E-nose sensor), an electromyography sensor (EMG sensor), an electroencephalogram sensor (EEG sensor, not shown), an electrocardiogram sensor (ECG sensor), a photoplethysmography sensor (PPG sensor), a heart rate monitor sensor (HRM sensor), a perspiration sensor, or a fingerprint sensor. The sensor module 160 may further include a control circuit for controlling at least one sensor included therein.

[0259] [Communication Module 170]

[0260] The communication module 170 may include a wireless communication module or an RF module, for example, Wi-Fi, BT, GPS, or NFC.

[0261] For example, the wireless communication module may provide wireless communication functionality using radio frequencies. Additionally or alternatively, the wireless communication module may include a network interface, a modem, or the like for connecting computing device 100 to a network (e.g., the Internet, a LAN, a WAN, a telecommunication network, a cellular network, a satellite network, a POTS, or a 5G network, etc.).

[0262] The RF module may be responsible for transmitting and receiving data, such as RF signals or called electronic signals. For example, the RF module may include a transceiver, a power amplifier (PAM), a frequency filter, or a low noise amplifier (LNA). The RF module may also include components, such as conductors or wires, for transmitting and receiving electromagnetic waves in free space in wireless communication.

[0263] The computing device 100 may include at least one of a server, a TV, a smart TV, a refrigerator, an oven, a clothing styler, a robot vacuum cleaner, a drone, an air conditioner, an air purifier, a PC, a speaker, a home CCTV, a light, a washing machine, and a smart plug. The components of the computing device 100 illustrated in FIG. 2d are examples of components typically included in a computing device, and therefore the computing device 100 is not limited to the above-described components, and certain components may be omitted and / or added as necessary.

[0264] [Network Section 180]

[0265] The network unit 180 according to an embodiment of the present invention can use various wired communication systems such as a Public Switched Telephone Network (PSTN), x Digital Subscriber Line (xDSL), Rate Adaptive DSL (RADSL), Multi Rate DSL (MDSL), Very High Speed ​​DSL (VDSL), Universal Asymmetric DSL (UADSL), High Bit Rate DSL (HDSL), and a Local Area Network (LAN).

[0266] In addition, the network unit 180 presented in this specification can use various wireless communication systems that can be realized now and in the future, such as mobile communication systems such as 4G and 5G (LTE), and satellite communication systems such as Starlink.

[0267] In the present invention, the network unit 180 may be configured regardless of the communication method, such as wired or wireless, and may be configured as various communication networks such as a short-range communication network (PAN: Personal Area Network) or a short-range communication network (WAN: Wide Area Network). In addition, the network may be a public World Wide Web (WWW), or may use wireless transmission technology used for short-range communication, such as Infrared Data Association (IrDA) or Bluetooth (registered trademark). The technology described herein may be used in other networks as well as the networks mentioned above.

[0268] Meanwhile, the computing device 100 implemented in the system according to the embodiment of the present invention may be configured to include both the communication module 170 and the network unit 180, or may be configured to include only one of the communication module 170 and the network unit 180. In this case, the operations of the communication module 170 described above may be performed by the network unit 180, or the operations of the network unit 180 described above may be performed by the communication module 170.

[0269] [network]

[0270] Networks according to embodiments of the present invention can use various wired communication systems such as Public Switched Telephone Network (PSTN), x Digital Subscriber Line (xDSL), Rate Adaptive DSL (RADSL), Multi Rate DSL (MDSL), Very High Speed ​​DSL (VDSL), Universal Asymmetric DSL (UADSL), High Bit Rate DSL (HDSL), and Local Area Network (LAN). In addition, the networks presented herein can use various wireless communication systems such as Code Division Multi Access (CDMA), Time Division Multi Access (TDMA), Frequency Division Multi Access (FDMA), Orthogonal Frequency Division Multi Access (OFDMA), Single Carrier-FDMA (SC-FDMA), and other systems.

[0271] The network according to an embodiment of the present invention may be configured regardless of its communication mode, such as wired or wireless, and may be configured as various communication networks such as a short-range communication network (PAN: Personal Area Network) or a short-range communication network (WAN: Wide Area Network). The network may be a public World Wide Web (WWW) or may use wireless transmission technologies used for short-range communication, such as Infrared Data Association (IrDA) or Bluetooth (registered trademark). The technology described herein may be used in other networks as well as the networks mentioned above.

[0272] [External terminal 200]

[0273] FIG. 2e is a block diagram illustrating an external terminal 200 according to an embodiment of the present invention.

[0274] The external terminal 200 may include a processor 210 , a memory 220 , and a communication module 270 .

[0275] The external terminal 200 may be an external server 20 or a cloud server. The external server 20 may be a digital device equipped with a processor, memory, and computing power, such as a laptop computer, notebook computer, desktop computer, web pad, or mobile phone. The external server 20 may be a web server that processes services. The types of servers described above are merely examples, and the present invention is not limited thereto.

[0276] [Processor 210]

[0277] The processor 210 performs overall control of the external terminal 200. The processor 210 may include an AI processor 215.

[0278] The AI ​​processor 215 can train a neural network using a program stored in the memory 220. In particular, the AI ​​processor 215 can train a neural network to recognize data related to the operation of the user terminal 300. Here, the neural network may be designed to simulate the structure of a human brain (e.g., the neuron structure of a human neural network) on a computer. The neural network may include an input layer, an output layer, and at least one hidden layer. Each layer may include at least one neuron having a weight, and the neural network may include synapses connecting neurons. In the neural network, each neuron may output an activation function value for a weight and / or bias of an input signal input via a synapse.

[0279] The various network modes can exchange data according to their respective connections, simulating the synaptic activity of neurons, where neurons exchange signals through synapses. Here, the neural network may include a deep learning model developed from a neural network model. In a deep learning model, multiple network nodes are located in different layers and can exchange data according to convolutional connections. Examples of neural network models include various deep learning techniques such as deep neural networks (DNNs), convolutional neural networks (CNNs), recurrent neural networks, restricted Boltzmann machines, deep belief networks, and deep Q-networks, and can be applied in fields such as vision recognition, speech recognition, natural language processing, and speech / signal processing.

[0280] Meanwhile, the processor 210 performing the above-described functions may be a general-purpose processor (e.g., CPU), or may be an AI-dedicated processor (e.g., GPU, TPU) for artificial intelligence learning.

[0281] [Memory 220]

[0282] The memory 220 may store various programs and data necessary for the operation of the user terminal 300 and / or the external terminal 200. The memory 220 may be accessed by the AI ​​processor 215, and data may be read, recorded, modified, deleted, updated, etc. by the AI ​​processor 215. The memory 220 may also store a neural network model (e.g., a deep learning model) generated through a learning algorithm for data classification / recognition. The memory 220 may also store input data, learning data, learning history, etc., in addition to the learning model 221.

[0283] Meanwhile, the AI ​​processor 215 may include a data learning unit 215a that learns a neural network for data classification / recognition. The data learning unit 215a can learn criteria regarding what training data to use to determine data classification / recognition and how to classify and recognize data using the training data. The data learning unit 215a can learn the deep learning model by acquiring training data to be used for learning and applying the acquired training data to the deep learning model.

[0284] The data learning unit 215a may be fabricated in the form of at least one hardware chip and installed in the external device 200. For example, the data learning unit 215a may be fabricated in the form of a dedicated hardware chip for artificial intelligence, or may be fabricated as part of a general-purpose processor (CPU) or a graphics processing unit (GPU) and installed in the external device 200. The data learning unit 215a may also be embodied as a software module. If embodied as a software module (or a program module including instructions), the software module may be stored in a non-transitory computer-readable medium that can be read by a computer. In this case, at least one software module may be provided by an operating system (OS) or an application.

[0285] The data learning unit 215a may use the acquired training data to train the neural network model to have criteria for how to classify / recognize predetermined data. The learning method used by the model learning unit may be classified into supervised learning, unsupervised learning, and reinforcement learning. Here, supervised learning refers to a method of training an artificial neural network when a label for the training data is given. The label may refer to a correct answer (or result value) that the artificial neural network must infer when training data is input to the artificial neural network. Unsupervised learning may refer to a method of training an artificial neural network when a label for the training data is not given. Reinforcement learning may refer to a method of training an agent defined in a specific environment to select an action or an action sequence that maximizes cumulative compensation in each state. The model learning unit may also train the neural network model using a learning algorithm, such as backpropagation or gradient decent. Once the neural network model is trained, the trained neural network model can be referred to as a trained model 221. The trained model 221 is stored in memory 220 and can be used to infer results for new input data that is not training data.

[0286] The AI ​​processor 215 may further include a data preprocessing unit 215b and / or a data selection unit 215c to improve analysis results using the learning model 221 or to save resources or time required to generate the learning model 221. The data preprocessing unit 215b may preprocess acquired data so that the acquired data can be used for learning / inference for situational judgment. As an example, the data preprocessing unit 215b may extract feature information as preprocessing from input data received via the communication module 270, and the feature information may be extracted in a format such as a feature vector, feature points, or feature map.

[0287] The data selector 215c may select data required for learning from the learning data or the learning data preprocessed by the preprocessor. The selected learning data may be provided to the model learning unit. For example, the data selector 215c may detect a specific area in an image acquired through a camera of the computing device and select only data on objects included in the specific area as learning data. In addition, the data selector 215c may select data required for inference from input data acquired through an input device or input data preprocessed by the preprocessor.

[0288] The AI ​​processor 215 may further include a model evaluation unit 215d to improve the analysis results of the neural network model. The model evaluation unit 215d inputs evaluation data to the neural network model, and if the analysis results output from the evaluation data do not satisfy a predetermined criterion, the model evaluation unit 215d may cause the model training unit to perform re-training. In this case, the evaluation data may be pre-set data for evaluating the training model 221. For example, the model evaluation unit 215d may evaluate the neural network model as not satisfying the predetermined criterion if the number or ratio of evaluation data whose analysis results are inaccurate among the analysis results of the trained neural network model for the evaluation data exceeds a predetermined critical value.

[0289] [Communication Module 270]

[0290] The communication module 270 can transmit the AI ​​processing results from the AI ​​processor 215 to the user terminal 300. It can also transmit the results to the computing device 100 shown in FIG. 1i.

[0291] [User terminal 300]

[0292] FIG. 2f is a block diagram illustrating a user terminal 300 according to an embodiment of the present invention.

[0293] According to an embodiment of the present invention, the user terminal 300 may refer to a terminal carried by a user that can receive information related to the user's sleep through information exchange with the computing device 100. For example, the user terminal 300 may be a terminal associated with a user who wishes to improve their health through information related to their sleep habits. The user may obtain monitoring information related to their sleep through the user terminal 300. The sleep-related monitoring information may include, for example, sleep state information related to the time when the user fell asleep, the time when they fell asleep, the time when they woke up, etc., or sleep stage information related to changes in sleep stages during sleep. For example, the sleep stage information may refer to information on whether the user's sleep changed to light sleep, normal sleep, deep sleep, REM sleep, etc., at each time point during the user's eight hours of sleep last night. The specific description of the sleep stage information described above is merely exemplary, and the present invention is not limited thereto.

[0294] The user terminal 300 may include a mobile phone, a smartphone, a laptop computer, a personal digital assistant (PDA), a portable multimedia player (PMP), a navigation system, a tablet PC, an ultrabook, a wearable device (e.g., a smartwatch, smart glass, or a head mounted display (HMD)), etc.

[0295] The user terminal 300 may include a wireless communication unit 310, an input unit 320, a sensing unit 340, an output unit 350, an interface unit 360, a memory 370, a control unit 380, and a power supply unit 390. The components shown in Fig. 2f are not essential for implementing a user terminal, and the user terminal described herein may have more or fewer components than those listed above.

[0296] [Wireless communication unit 310]

[0297] The wireless communication unit 310 may include one or more modules that enable wireless communication between the user terminal 300 and a wireless communication system, between the user terminal 300 and a computing device 100, or between the user terminal 300 and an external terminal 200. The wireless communication unit 310 may also include one or more modules that connect the user terminal 300 to one or more networks.

[0298] The wireless communication unit 310 may include at least one of a broadcast receiving module 311 , a mobile communication module 312 , a wireless Internet module 313 , a short-range communication module 314 , and a location information module 315 .

[0299] [Input section 320]

[0300] The input unit 320 may include a camera 321 or a video input unit for inputting a video signal, a microphone or an audio input unit for inputting an audio signal, and a user input unit 323 (e.g., touch keys, mechanical keys, etc.) for receiving information input from a user. The voice data and image data collected by the input unit 320 may be analyzed and processed according to a user's control command.

[0301] [Sensing unit 340]

[0302] The sensing unit 340 may include one or more sensors for sensing at least one of information within the user terminal, information about the environment surrounding the user terminal, and user information. For example, the sensing unit 340 may include at least one of a proximity sensor 341, an illumination sensor 342, a touch sensor, an acceleration sensor, a magnetic sensor, a gravity sensor (G-sensor), a gyroscope sensor, a motion sensor, an RGB sensor, an infrared sensor (IR sensor), a fingerprint sensor, an ultrasonic sensor, an optical sensor (see, for example, the camera 321), a battery gauge, an environmental sensor (e.g., a barometer, a hygrometer, a thermometer, a radiation sensor, a heat sensor, a gas sensor, etc.), and a chemical sensor (e.g., an electronic nose, a healthcare sensor, a biometric sensor, etc.). Meanwhile, the user terminal disclosed in this specification can utilize information sensed by at least two of these sensors in combination.

[0303] [Output section 350]

[0304] The output unit 350 is for generating an output related to vision, hearing, touch, or the like, and may include at least one of a display unit 351, an audio output unit 352, a haptic module 353, and an optical output unit 354. The display unit 351 may be formed as a layered structure or integrally with a touch sensor to implement a touch screen. The touch screen may function as a user input unit 323 that provides an input interface between the user terminal 300 and the user U, and may also provide an output interface between the user terminal 300 and the user U.

[0305] [Interface section 360]

[0306] The interface unit 360 serves as a passageway for various types of external devices connected to the user terminal 300. The interface unit 360 may include at least one of a wired / wireless headset port, an external charger port, a wired / wireless data port, a memory card port, a port for connecting a device equipped with an identification module, an audio I / O (Input / Output) port, a video I / O (Input / Output) port, and an earphone port. In response to an external device (e.g., computing device 100) being connected to the interface unit 360, the user terminal 300 can perform appropriate control related to the connected external device.

[0307] [Memory 370]

[0308] The memory 370 stores data supporting various functions of the user terminal 300. The memory 370 may store a number of application programs (or applications) run by the user terminal 300, as well as data, commands, or instructions for the operation of the user terminal 300. At least some of these applications may be downloaded from an external server via wireless communication. At least some of these applications may be present on the user terminal 300 from the time of delivery for the basic functions of the user terminal 300 (e.g., incoming call, outgoing call, message reception, outgoing call functions). Meanwhile, applications may be stored in the memory 370, installed on the user terminal 300, and driven by the control unit 380 to perform the operation (or function) of the user terminal. The memory 370 may store instructions for the operation of the control unit 380.

[0309] [Control unit 380]

[0310] In addition to the operations related to the applications, the control unit 380 typically controls the overall operation of the user terminal 300. The control unit 380 processes signals, data, information, etc. input or output via the components detailed above, and drives applications stored in the memory 370 to provide or process appropriate information or functions to the user.

[0311] The control unit 380 may control at least some of the components detailed in Fig. 2f to run the application stored in the memory 370. Furthermore, the control unit 380 may operate at least two or more components included in the user terminal 300 in combination with each other to run the application.

[0312] [Power supply section 390]

[0313] The power supply unit 390 receives an external power source or an internal power source under the control of the control unit 380 and supplies power to each component included in the user terminal 300. The power supply unit 390 includes a battery, which may be a built-in battery or a replaceable battery.

[0314] At least some of the components may cooperate with each other to implement the operation, control, or control method of the user terminal according to various embodiments described below. In addition, the operation, control, or control method of the user terminal may be implemented on the user terminal by running at least one application stored in the memory 370.

[0315] [Environment creation device 30]

[0316] According to an embodiment of the present invention, the environment creation device 30 may adjust a user's sleep environment. Specifically, the environment creation device 30 may include one or more environment creation modules, and may adjust the user's sleep environment by operating an environment creation module related to at least one of air quality, illuminance, temperature, wind direction, humidity, and sound in a space where the user is located based on environment creation information received from the computing device 100.

[0317] The environment creating device 30 may be embodied as an air purifier capable of controlling air quality, a lighting device capable of controlling light intensity (illuminance), a cooler / heater capable of controlling temperature, a humidifier / dehumidifier capable of controlling humidity, an audio / speaker capable of controlling sound, etc.

[0318] FIG. 8 illustrates an exemplary flowchart for providing a method for creating a sleep environment based on sleep state information according to an embodiment of the present invention.

[0319] According to one embodiment of the present invention, the method may include a step of acquiring sleep state information of a user (S1000).

[0320] According to an embodiment of the present invention, the method may include generating environment creation information based on sleep state information (S2000).

[0321] According to an embodiment of the present invention, the method may include a step of transmitting environment creation information to the environment creation device 30 (S3000).

[0322] 8 may be reordered, and at least one step may be omitted or added, as necessary. That is, the above-described steps are merely one embodiment of the present invention, and the scope of the present invention is not limited thereto.

[0323] [Environmental creation information]

[0324] According to an embodiment of the present invention, the processor 110 may generate environment creation information based on sleep state information and / or sleep stage information. The sleep state information is information related to whether the user is sleeping or not, and may include at least one of first sleep state information indicating that the user is about to fall asleep, second sleep state information indicating that the user is sleeping, and third sleep state information indicating that the user has fallen asleep.

[0325] More specifically, the processor 110 may generate the first environment creation information based on the first sleeping state information. Specifically, when the processor 110 acquires the first sleeping state information indicating that the user is before sleeping, the processor 110 may generate the first environment creation information based on the first sleeping state information.

[0326] According to an embodiment, the first environment creation information may be information regarding light intensity and illuminance for inducing natural sleep. Specifically, the first environment creation information may be control information for supplying 3000K white light at an illuminance of 30 lux from a sleep induction point until the second sleep state information is acquired.

[0327] According to an embodiment, the sleep induction time point may be determined by the processor 110. Specifically, the processor 110 may determine the sleep induction time point through information exchange with the user's user terminal 300. For a specific example, the user may set the time point at which they intend to sleep via the user terminal 300 and transmit the time point to the processor 110. The processor 110 may determine the sleep induction time point based on the time point at which the user intends to sleep from the user terminal 300. For example, the processor 110 may determine the sleep induction time point to be 20 minutes before the time point at which the user intends to sleep. For a specific example, if the time point at which the user intends to sleep set by the user is 11:00, the processor 110 may determine 10:40 as the sleep induction time point. The specific numerical values ​​for the above-mentioned time points are merely examples, and the present invention is not limited thereto.

[0328] Furthermore, according to an embodiment, the processor 110 may acquire sleep intention information of the user based on the environmental sensing information and determine a sleep induction time point based on the sleep intention information. The sleep intention information may be information indicating the user's intention to sleep as a quantitative value. For example, the higher the user's intention to sleep, the closer the calculated sleep intention information is to 10, and the lower the intention to sleep, the closer the calculated sleep intention information is to 0. The specific numerical values ​​for the sleep intention information described above are merely examples, and the present invention is not limited thereto.

[0329] The environment creation information may be a signal generated from the computing device 100 based on the determination of the user's sleep state information. For example, the environment creation information may include information on lowering or increasing illuminance. If the environment creation device 30 is a lighting device, the environment creation information may include control information for gradually increasing the illuminance of 3000K white light from 0 lux to 250 lux 30 minutes before the predicted time of waking up. If the environment creation device 30 is an air purifier, the environment creation information may include various information related to removing fine dust (fine dust, ultrafine dust, and ultra-ultrafine dust), removing harmful gases, activating an allergy care function, activating a deodorizing / sterilizing function, adjusting dehumidifying / humidifying functions, adjusting airflow intensity, adjusting the operating noise of the air purifier, turning on an LED, managing smog-causing substances (SO2, NO2), and removing household odors, based on the user's real-time sleep state.

[0330] For example, the environment creation information may include control information for adjusting at least one of temperature, humidity, wind direction, and sound. The above-described specific descriptions of the environment creation information are merely examples, and the present invention is not limited thereto.

[0331] The one or more environment creation modules included in the environment creation device 30 may include, for example, at least one of a light control module, a temperature control module, a wind direction control module, a humidity control module, and a sound control module. However, without being limited thereto, the one or more environment creation modules may further include various environment creation modules that can bring about changes in the user's sleep environment. That is, the environment creation device 30 can adjust the user's sleep environment by driving one or more environment creation modules based on an environment control signal from the computing device 100.

[0332] [Determining environmental creation information based on sleep state]

[0333] [Time for sleep induction]

[0334] According to an embodiment, the processor 110 may determine a sleep induction time point based on the sleep intention information. Specifically, the processor 110 may identify a time point at which the sleep intention information exceeds a predetermined threshold as a sleep induction time point. That is, when high sleep intention information is obtained, the processor 110 may identify this as a time point appropriate for sleep induction, i.e., a sleep induction time point.

[0335] As described above, the processor 110 can determine the time point at which the user is induced to sleep. Accordingly, when the processor 110 acquires first sleep state information indicating that the user is about to fall asleep, the processor 110 can generate first environment creation information (supplying 3000K white light at an illuminance of 30 lux) that adjusts the light based on the sleep induction time point until the time point at which the second sleep state information is acquired.

[0336] [Before going to bed]

[0337] That is, when the user is in a pre-sleep state, the processor 110 may generate first environment creation information for adjusting light from the time when the user is predicted to prepare for sleep (e.g., the sleep induction time) to the time when the user falls asleep (i.e., the time when the second sleep state information is acquired), and may determine to transmit the first environment creation information to the environment creation device 30. As a result, 3000K white light at an illuminance of 30 lux may be supplied from 20 minutes before the user falls asleep (e.g., the sleep induction time) until the moment the user falls asleep. This light is excellent for melatonin secretion before the user falls asleep, and by using this light, the user's sleep efficiency may be improved by naturally inducing sleep.

[0338] Furthermore, when the user is in a pre-sleep state, the processor 110 may generate first environment creation information for controlling the air purifier from the time when the user is predicted to prepare for sleep (e.g., the sleep induction time) to the time when the user falls asleep (i.e., the time when the second sleep state information is acquired). Specifically, the processor 110 may generate first environment creation information for controlling the air purifier to pre-remove fine dust and harmful gases until a predetermined time (e.g., 20 minutes) before the user falls asleep. The first environment creation information may include information for controlling the air purifier to induce noise (white noise) sufficient to induce sleep just before falling asleep, adjusting the airflow intensity to a level lower than a preset intensity, or lowering the intensity of an LED. In addition, the first environment creation information may include information for controlling the air purifier to dehumidify / humidify based on temperature and humidity information within the sleep space. The first environment creation information may also include control information for adjusting the airflow intensity and noise in a personalized manner according to the air purifier's operation history and the acquired sleep state (sleep quality).

[0339] [Sleep state 2]

[0340] According to an embodiment of the present invention, the processor 110 may generate second environment creation information based on the second sleep state information. The second environment creation information may be control information for minimizing illuminance to create a dark room environment without light. For example, if there is light interference during sleep, the probability of fragmented sleep increases, making it difficult to achieve good, deep sleep.

[0341] In addition, the processor 110 may generate second environment creation information for controlling the air purifier to turn off the LED of the air purifier based on the second sleep state information, operate the air purifier at a noise level below a pre-set level, adjust the airflow intensity below a pre-set intensity, adjust the airflow temperature within a pre-set range, or maintain the humidity in the sleep space at a predetermined temperature.

[0342] The second environment creation information may include control information for increasing the airflow strength to improve air quality when a person is in deep sleep according to a sleep stage, since there is less risk of waking up.

[0343] That is, when the processor 110 detects that the user has entered sleep (or a sleep stage) (when the processor 110 acquires the second sleep state information), it can generate control information, i.e., second environment creation information, that prevents light from being supplied or minimizes the operation of the air purifier, thereby increasing the probability that the user will fall into deep sleep and improving the quality of sleep.

[0344] [Wake-up induction time]

[0345] According to an embodiment of the present invention, the processor 110 may generate third environment creation information based on the wake-up induction time point. The third environment creation information may be control information for supplying 3000K white light at an illuminance that gradually increases from 0 lux to 250 lux from the wake-up induction time point to the wake-up time point. For example, the third environment creation information may be control information related to gradually increasing the illuminance starting 30 minutes before the user wakes up (i.e., the wake-up induction time point). Here, the wake-up induction time point may be determined based on the predicted wake-up time point.

[0346] In one embodiment, the wake-up guidance time may be determined based on a predicted wake-up time. The predicted wake-up time may be information about the time when the user is expected to wake up. For example, the predicted wake-up time may be 7:00 for a first user. The above-mentioned specific description of the predicted wake-up time is merely an example, and the present invention is not limited thereto.

[0347] The third environment creation information may include information for controlling the air purifier to lower the airflow intensity and noise at the time of waking up to induce waking up. The third environment creation information may also include control information for controlling the air purifier to generate white noise to gradually induce waking up. The third environment creation information may also include control information for controlling the air purifier to maintain the noise of the air purifier at or below a preset level after waking up. The third environment creation information may also include control information for controlling the air purifier in conjunction with a predicted wake-up time and a recommended wake-up time. The recommended wake-up time may be a time automatically determined according to the user's sleep pattern, and the predicted wake-up time is the same as described below.

[0348] [Determining the predicted time for waking up]

[0349] In one embodiment, the predicted wake-up time may be determined in advance through information exchange between the user and the user terminal 300. For example, the user may set the time at which they intend to wake up through the user terminal 300 and transmit the set time to the processor 110. That is, the processor 110 may acquire the predicted wake-up time based on the time set by the user of the user terminal 300. For example, when the user sets an alarm time through the user terminal 300, the processor 110 may determine the set alarm time as the predicted wake-up time.

[0350] In another embodiment, the predicted wake-up time may be determined based on the sleep onset time identified through the second sleep state information. Specifically, the processor 110 may determine the user's sleep onset time through the second sleep state information indicating that the user is asleep. The processor 110 may determine the predicted wake-up time based on the sleep onset time identified through the second sleep state information. For example, the processor 110 may determine the predicted wake-up time to be a time 8 hours or later, which is the appropriate sleep time, from the sleep onset time. As a specific example, if the sleep onset time is 11:00, the processor 110 may determine the predicted wake-up time to be 7:00. The specific numerical values ​​for each time point described above are merely examples, and the present invention is not limited thereto. That is, the processor 110 may determine the predicted wake-up time based on the time when the user falls asleep.

[0351] In another embodiment, the recommended wake-up time may be determined based on the user's sleep stage information. For example, if the user wakes up in the REM stage, the user is likely to wake up refreshed. During one night's sleep, the user may have a sleep cycle consisting of light sleep, deep sleep, light sleep, and REM sleep in that order, and may wake up refreshed when waking up in the REM sleep stage. Preferably, the recommended sleep time may be determined taking into account the user's appropriate or desired sleep time while minimally satisfying the appropriate or desired sleep time.

[0352] Thus, the processor 110 can determine the predicted wake-up time of the user based on sleep stage information related to the sleep stage of the user. For example, the processor 110 can determine the time when the user changes from the REM stage to another sleep stage (preferably, the time immediately before the transition from the REM stage to another sleep stage) as the recommended wake-up time based on the sleep stage information. That is, the processor 110 can determine the predicted wake-up time based on the sleep stage information (i.e., the REM sleep stage) from which the user can wake up most refreshed.

[0353] As described above, the processor 110 may determine the predicted wake-up time of the user based on at least one of the user setting, the sleep onset time, and the sleep stage information. Furthermore, if the processor 110 determines the predicted wake-up time as the time when the user intends to wake up, it may determine the wake-up induction time based on the predicted wake-up time. For example, the processor 110 may determine the wake-up induction time to be 30 minutes before the time when the user intends to wake up. For example, if the time when the user intends to wake up (i.e., the predicted wake-up time) is 7:00, the processor 110 may determine 6:30 as the wake-up induction time. The above-described specific examples of the time are merely examples, and the present invention is not limited thereto.

[0354] That is, the processor 110 may determine the predicted wake-up time when the user is expected to wake up, determine the wake-up guidance time, and generate third environment creation information for supplying 3000K white light at a gradually increasing illuminance from 0 lux to 250 lux from the wake-up guidance time to the wake-up time (e.g., until the user actually wakes up). The processor 110 may determine to transmit the third environment creation information to the environment creation device 30, which may then perform a light-related adjustment operation in the space where the user is located based on the third environment creation information. For example, the environment creation device 30 may control the light supply module to gradually increase the illuminance of 3000K white light from 0 lux to 250 lux starting 30 minutes before waking up.

[0355] [4th environment creation information]

[0356] According to an embodiment of the present invention, the processor 110 may acquire fourth environment creation information based on the third sleep state information. Specifically, the processor 110 may acquire sleep disorder information of the user. In one embodiment, the sleep disorder information may include delayed sleep phase syndrome. Delayed sleep phase syndrome is a sleep disorder symptom in which a user is unable to fall asleep at a desired time and their ideal sleep time shifts later. According to an embodiment, blue-light therapy is one of the methods for treating delayed sleep phase syndrome, and is a treatment that provides blue light for approximately 30 minutes after the user wakes up at their desired wake-up time. If this blue light is provided every morning, the circadian rhythm can be restored to its original state, preventing the user from becoming sleepy later in the night compared to normal people.

[0357] Accordingly, the processor 110 may generate the fourth environment creation information based on the sleeping disorder information and the third sleeping state information. For example, when the processor 110 acquires the sleeping disorder information indicating that the user has a delayed sleep phase syndrome and the third sleeping state information indicating that the user has fallen asleep (i.e., woken up) via the user terminal 300, the processor 110 may generate the fourth environment creation information. In this case, the fourth environment creation information may be control information for supplying blue light with an illuminance of 300 lux, a hue of 221 degrees, a saturation of 100%, and a brightness of 56% for a preset time period from the time of waking up.

[0358] In one embodiment, blue light with an illuminance of 300 lux, a hue of 221 degrees, a saturation of 100%, and a brightness of 56% may represent blue light for treating delayed sleep phase syndrome. For example, if a user with delayed sleep phase syndrome wakes up at 7:00 a.m., the processor 110 may determine the wake-up time as 7:00 a.m. based on the third sleep state information and generate fourth environment creation information to provide blue light with an illuminance of 300 lux, a hue of 221 degrees, a saturation of 100%, and a brightness of 56% from the wake-up time of 7:00 a.m. to a preset time (e.g., 7:30 a.m.). This allows the user's circadian rhythm to be adjusted to a range of a normal person (e.g., falling asleep around midnight and waking up around 7:00 a.m.). In other words, generating the fourth environment creation information may improve the quality of sleep for a user with a specific sleep disorder.

[0359] According to an embodiment of the present invention, the processor 110 may determine to transmit the environment creation information to the environment creation device 30. Specifically, the processor 110 may generate environment creation information related to illuminance adjustment, and may control the illuminance adjustment operation of the environment creation device 30 by determining to transmit the environment creation information to the environment creation device 30.

[0360] According to an embodiment, light may be one of the major factors that can affect sleep quality. For example, light may have a positive or negative effect on sleep quality depending on its illuminance, color, and exposure level. Therefore, the processor 110 can adjust the illuminance to improve the user's sleep quality. For example, the processor 110 can monitor the situation before and after falling asleep and adjust the illuminance accordingly to effectively wake up the user. That is, the processor 110 can maximize sleep quality by identifying the sleep state (e.g., sleep stage) and automatically adjusting the illuminance.

[0361] [Sleep plan information]

[0362] In one embodiment, the processor 110 may receive sleep plan information from the user terminal 300. The sleep plan information is information generated by the user via the user terminal 300 and may include, for example, information about a bedtime and a wake-up time. The processor 110 may generate external environment creation information based on the sleep plan information. For example, the processor 110 may identify the user's bedtime through the sleep plan information and generate external environment creation information based on the bedtime. For example, as shown in FIG. 7, the processor 110 may generate first environment creation information that provides 3000K white light with an illuminance of 30 lux based on the position of the bed 20 minutes before bedtime. In other words, an illuminance that induces the user to fall asleep naturally may be created in relation to bedtime.

[0363] [Actions based on when you fall asleep]

[0364] Further, for example, the processor 110 may determine the time when the user falls asleep, i.e., the sleep onset time, through the second sleep state information and may generate second environment creation information based on the second sleep state information. For example, as shown in FIG. 7, the processor 110 may generate second environment creation information that minimizes light or controls an air purifier to a sleep mode from the time when the user falls asleep, thereby creating a quiet, dark room-like atmosphere. Such second environment creation information has the effect of helping the user enter deep sleep and improving sleep quality. In an embodiment, the processor 110 may generate external environment creation information based on the sleep stage information. In an embodiment, the sleep stage information may include information regarding changes in the user's sleep stages obtained over time through analysis of sleep acoustic information.

[0365] [Action based on sleep stage information]

[0366] For example, when processor 110 determines that the user has entered a sleep stage (e.g., light sleep) based on the user's sleep stage information, it can generate external environment creation information such as minimizing illuminance to create a dark room environment without light, or controlling an air purifier to remove fine dust / harmful gases, adjust air temperature and humidity, turn on LEDs, adjust driving noise levels, and generate airflow volume to enable deep sleep. In other words, by creating optimal illuminance for each user's sleep stage, i.e., an optimal sleep environment, it is possible to improve the user's sleep efficiency.

[0367] In addition, the processor 110 may generate environmental creation information to provide appropriate illumination or adjust air quality according to changes in the user's sleep stage during sleep. For example, various external environment creation information may be generated according to changes in sleep stage, such as providing subtle red light when changing from light sleep to deep sleep, or reducing illumination or providing blue light when changing from REM sleep to light sleep. This may maximize the quality of the user's sleep by automatically considering not only the situation before sleep or immediately after waking up but also the situation during sleep, thereby considering the entire sleep experience rather than just a part of it.

[0368] In addition, for example, the processor 110 may identify the user's wake-up time through the sleep plan information, generate a predicted wake-up time based on the wake-up time, and generate environment creation information accordingly. For example, as shown in Fig. 7, the processor 110 may generate third environment creation information that gradually increases the illuminance of 3000K white light from 0 lux to 250 lux based on the position of the bed starting 30 minutes before the predicted wake-up time. Such third environment creation information may encourage the user to wake up naturally and refreshed according to the desired wake-up time.

[0369] The processor 110 may also determine to transmit the environment creation information to the environment creation device 30. That is, the processor 110 may improve the quality of the user's sleep by generating external environment creation information that allows the user to easily fall asleep or wake up naturally when going to bed or waking up based on the sleep plan information.

[0370] In a further embodiment, the processor 110 may generate recommended sleep plan information based on the sleep stage information. Specifically, the processor 110 may acquire information regarding changes in the user's sleep stages (e.g., sleep cycles) through the sleep stage information and set an expected wake-up time based on this information. For example, a typical day's sleep cycle may include light sleep, deep sleep, light sleep, and REM sleep. The processor 110 may determine that the time after REM sleep is the time when the user can wake up most refreshed and may determine a wake-up time after the REM time, thereby generating the recommended sleep plan information. The processor 110 may also generate environment creation information based on the recommended sleep plan information and determine to transmit the environment creation information to the environment creation device 30. Thus, the user may wake up naturally according to the recommended sleep plan information recommended by the processor 110. This may have the advantage of improving the user's sleep efficiency because the processor 110 recommends a wake-up time for the user according to changes in the user's sleep stages, which may be a time when the user's fatigue level is minimized.

[0371] [Sleep environment control device 400]

[0372] The sleep environment adjusting device shown in Fig. 1g will be described in more detail below. As shown in Fig. 1g, the sleep environment adjusting device 400, the user terminal 300, and the external server 20 can mutually transmit and receive data for the system according to an embodiment of the present invention via a network.

[0373] The network according to the embodiment of the present invention is the same as that described in detail above, so a repeated description will be omitted.

[0374] According to an embodiment of the present invention, the user terminal 300 may refer to a terminal carried by a user that can receive information related to the user's sleep through information exchange with the sleep environment controlling device 400. The general configuration and functions of the user terminal 300 may be the same as those described above.

[0375] The user terminal 300 according to an embodiment of the present invention may acquire acoustic information related to a space in which a user is located. For example, the acoustic information may refer to acoustic information acquired from the space in which the user is located. The acoustic information may be acquired in a contactless manner in connection with the user's activity or sleep. For example, the acoustic information may be acquired from the space while the user is sleeping. According to an embodiment, the acoustic information acquired through the user terminal 300 may serve as a basis for acquiring the user's sleep state information in the present invention. For example, sleep state information related to whether the user is before, during, or after sleep may be acquired through acoustic information acquired in connection with the user's movement or breathing. Furthermore, for example, information regarding changes in the user's sleep stage during sleep may be acquired through the acoustic information.

[0376] The sleep environment adjusting device 400 of the present invention can receive health checkup information or sleep examination information from the external server 20 and create a learning data set based on the received information. The external server 20 has been described in detail above, and therefore, a detailed description thereof will be omitted here.

[0377] According to an embodiment, the acoustic information utilized by the sleep environment adjusting device 400 for sleep state analysis may be non-invasively acquired during a user's activity or sleep in a space. For specific examples, the acoustic information may include sounds generated by the user turning over in their sleep, sounds related to muscle movements, or sounds related to the user's breathing during sleep. According to an embodiment, the environmental sensing information may include sleep acoustic information, which may refer to sounds related to the movement patterns and breathing patterns generated during the user's sleep.

[0378] In an embodiment, the acoustic information may be acquired through at least one of the user terminal 300 carried by the user and the acoustic collector 414. For example, environmental sensing information related to the user's activity in a space may be acquired through a microphone module provided in the user terminal 300 and the acoustic collector 414.

[0379] The configuration of the microphone module provided in the user terminal 300 or the sound collecting unit 414 is the same as that described above.

[0380] The acoustic information analyzed in the present invention is related to the user's breathing and movements acquired during sleep, and is information about very small sounds (i.e., sounds that are difficult to distinguish). Since it is acquired along with other sounds during sleep, it can be very difficult to detect and analyze if acquired through the above-mentioned microphone module with a low signal-to-noise ratio.

[0381] According to an embodiment of the present invention, the sleep environment controlling device 400 may acquire sleep state information based on acoustic information acquired through a microphone module configured with MEMS. Specifically, the sleep environment controlling device 400 may convert and / or adjust unclearly acquired acoustic information containing a lot of noise into analyzable data and perform training on an artificial neural network using the converted and / or adjusted data. Once pre-training of the artificial neural network is complete, the trained neural network (e.g., an acoustic analysis model) may acquire sleep state information of a user based on data (e.g., a spectrogram) acquired (e.g., converted and / or adjusted) corresponding to the acoustic information. In an embodiment, the sleep state information may include not only information related to whether the user is sleeping, but also sleep stage information related to changes in the user's sleep stage during sleep. For example, the sleep state information may include sleep stage information indicating that the user was in REM sleep at a first time point and in light sleep at a second time point different from the first time point. In this case, information may be obtained through the sleep state information that the user was in a relatively deep sleep at a first time point and in a lighter sleep at a second time point.

[0382] That is, when the sleep environment controlling device 400 acquires sleep sound information having a low signal-to-noise ratio from a commonly used user terminal for collecting sound (e.g., an AI speaker, a bedroom IoT device, a mobile phone, etc.) or the sound collecting unit 414, it processes the acquired sleep sound information into data suitable for analysis and processes the processed data to provide information on whether the user is before, during, or after sleep, as well as sleep state information related to changes in sleep stages. This eliminates the need for a microphone that contacts the user's body to acquire clear sound, and also provides the effect of increasing convenience by enabling the monitoring of sleep states in a general home environment through a software update without purchasing a separate additional device with a high signal-to-noise ratio.

[0383] In an embodiment, the sleep environment adjusting device 400 may be a terminal or a server, and may include any type of device. The sleep environment adjusting device 400 may be a digital device equipped with a processor, memory, and computing capabilities, such as a laptop computer, notebook computer, desktop computer, web pad, or mobile phone. The sleep environment adjusting device 400 may be a web server that processes services. The types of servers described above are merely examples, and the present invention is not limited thereto.

[0384] According to an embodiment of the present invention, the sleep environment adjusting device 400 may be a server that provides cloud computing services, which has been described in detail above and will not be described here.

[0385] FIG. 2g illustrates an exemplary block diagram of a sleep environment control device in accordance with an embodiment of the present invention.

[0386] As shown in FIG. 2g, the sleep environment adjusting device 400 may include a receiving module 410 and a transmitting module 420.

[0387] According to an embodiment of the present invention, the sleep environment adjusting device 400 may include a transmitting module 420 that transmits a wireless signal and a receiving module 410 that receives the transmitted wireless signal. In one embodiment, the wireless signal may refer to an orthogonal frequency division multiplexing (OFDM) signal. For example, the wireless signal may be a Wi-Fi-based OFDM sensing signal. The transmitting module 420 may be implemented as a laptop, smartphone, tablet PC, smart speaker (AI speaker), etc., and the receiving module 410 may be implemented as a Wi-Fi receiver. According to an embodiment, the receiving module 410 may be implemented as various computing devices such as a laptop, smartphone, tablet PC, etc. For example, the transmitting module 420 and the receiving module 410 may be equipped with a wireless chip conforming to Wi-Fi 802.11n, 802.11ac, or other standards supporting OFDM. In other words, the sleep environment adjusting device 400 that reliably acquires object state information may be implemented using relatively low-cost equipment.

[0388] In one embodiment, the transmitting module 420 can transmit a radio signal in one direction where the object is located, and the receiving module 410 is provided at a predetermined separation distance from the transmitting module 420 and can receive the radio signal transmitted from the transmitting module 420. Such a radio signal may be transmitted or received via multiple subcarriers according to an orthogonal frequency division multiplexing signal.

[0389] The transmitting module 420 and the receiving module 410 may be provided with a predetermined separation distance. In this case, the predetermined separation distance may refer to a space where an object is active or located. In a specific embodiment, the transmitting module 420 and the receiving module 410 may be provided at positions opposite each other based on a pre-defined area. Here, the pre-defined area 11a may be, for example, an area related to a user's sleeping position, such as an area where a bed is located, as shown in FIG. 2i. The transmitting module 420 and the receiving module 410 may be provided on both sides of the bed where the user is sleeping. In this case, the sleep environment controlling device 400 of the present invention may acquire object state information, such as information on whether the user is located in the pre-defined area and information on the user's movement or breathing, based on the Wi-Fi-based OFDM signals transmitted and received via the transmitting module 420 and the receiving module 410.

[0390] According to one embodiment, the transmitting module 420 and the receiving module 410 may transmit and receive wireless signals (e.g., OFDM signals) via one or more antennas. For example, if the transmitting module 420 and the receiving module 410 each have three antennas, channel state information related to a total of 192 (i.e., 3×64) channels may be acquired for each frame via the three antennas and 64 subcarriers. The specific numerical values ​​for the antennas and subcarriers described above are merely examples, and the present disclosure is not limited thereto.

[0391] According to an embodiment, a plurality of transmitting modules 420 and receiving modules 410 may be provided. More specifically, three transmitting modules and four receiving modules may be provided at predetermined intervals. In this case, the wireless signals transmitted and received by the plurality of transmitting modules and receiving modules may be different from each other.

[0392] In an embodiment, the wireless signal received via the receiving module 410 may be a wireless signal that has passed through a channel corresponding to a pre-established area and may include information indicating characteristics of the channel. The receiving module 410 may acquire channel state information from the wireless signal. The channel state information is information indicating characteristics related to a channel associated with a space where a user is located, and may be calculated based on the wireless signal transmitted from the transmitting module 420 and the wireless signal received via the receiving module.

[0393] Specifically, the wireless signal transmitted from the transmitting module 420 may pass through a specific channel (i.e., the space where the user is located) and be received via the receiving module 410. In this case, the wireless signal may be transmitted via multiple subcarriers corresponding to each multipath. Thus, the wireless signal received via the receiving module 410 may be a signal reflecting the user's movement in the pre-defined area 11a. The processor may acquire channel state information related to the channel characteristics experienced by the wireless signal as it passes through the channel (i.e., the space where the user is located) via the received wireless signal. Such channel state information may be composed of amplitude and phase. That is, the sleep environment controlling device 400 may acquire channel state information related to the characteristics of the space (e.g., the pre-defined area) between the transmitting module 420 and the receiving module 410 based on the wireless signal transmitted from the transmitting module 420 and the wireless signal received via the receiving module 410 (i.e., the signal reflecting the object's movement).

[0394] According to an embodiment, when the receiving module 410 receives a wireless signal transmitted from the transmitting module 420, the receiving module 410 may detect user movement based on the received wireless signal. The receiving module 410 may acquire information regarding whether the user is located in a pre-defined area through a change in channel state information. According to an embodiment, during the process of transmitting and receiving a wireless signal via the transmitting module 420 and the receiving module 410, channel state information acquired when the user is located or not between the transmitting module 420 and the receiving module 410 may differ. According to a specific embodiment, the transmitting module 420 and the receiving module 410 may be arranged to maximize the difference between the channel state information acquired when the user is located in the area between the transmitting module 420 and the receiving module 410 (e.g., the pre-defined area) and when the user is not located. According to an additional embodiment, a directional patch antenna may be provided corresponding to each of the transmitting module 420 and the receiving module 410. Here, the directional patch antenna may be an antenna module configured with m×n patches (i.e., m horizontal patches and n vertical patches). For example, the antenna beam may be preset to increase the signal difference when the user is positioned between the transmitting module 420 and the receiving module 410. The antenna beam width may be preset to be optimal, and the transmitting module 420 and the receiving module 410 may be positioned so that the user is lying down in the direction of transmitting and receiving signals using such directional patch antennas. That is, a wireless link that is directly secured by line-of-sight may be formed between the directional patch antennas of the transmitting module 420 and the receiving module 410. With this configuration, the antenna of each module may be operated as a directional antenna, thereby forming a wireless link corresponding to a smaller area (e.g., a pre-defined area).

[0395] That is, a wireless link may be formed between the antennas of the transmitting module 420 and the receiving module 410, and if a user is located between the wireless link, the user's body may block the wireless link, distorting the wireless link and significantly changing the signal level (i.e., channel state information). In an embodiment, the change in the signal level may be detected through changes in a received signal strength indicator (RSSI) and channel state information (CSI), and the receiving module 410 may determine, based on these changes, whether the user is located in the previously set area 11a.

[0396] In an embodiment, information regarding whether the user is located in the previously set area 11a may be used to determine whether to activate the environment creation unit 415 or to understand the user's sleep intention.

[0397] According to an embodiment of the present invention, the receiving module 410 can calculate sleep state information of a user and adjust the user's sleep environment based on the sleep state information. Specifically, the receiving module 410 can acquire sleep state information related to whether the user is about to fall asleep, asleep, or asleep based on the acquired sensing information, and can adjust the sleep environment of the space where the user is located based on the sleep state information. For example, if the receiving module 410 acquires sleep state information indicating that the user is about to fall asleep, the receiving module 410 can generate environment creation information related to light intensity and illuminance for inducing sleep (e.g., 3000K white light, 30 lux illuminance) based on the sleep state information. Furthermore, the receiving module 410 can adjust the light intensity and illuminance of the space where the user is located to an appropriate intensity and illuminance for inducing sleep (e.g., 3000K white light, 30 lux illuminance) based on the environment creation information related to light intensity and illuminance for inducing sleep.

[0398] Furthermore, when the receiving module 410 acquires sleep state information indicating that the user is about to fall asleep, the receiving module 410 may generate environment creation information for controlling the air purifier from the time when the user is predicted to prepare for sleep (e.g., the sleep induction time) to the time when the user falls asleep (i.e., the time when the second sleep state information is acquired). Specifically, the receiving module 410 may generate environment creation information for controlling the air purifier to pre-remove fine dust and harmful gases until a predetermined time (e.g., 20 minutes) before the user falls asleep. The environment creation information may include information for controlling the air purifier to induce sleep-inducing noise (white noise) just before sleep, adjusting the airflow intensity to a level lower than a preset intensity, or lowering the intensity of the LED. In addition, the first environment creation information may include information for controlling the air purifier to dehumidify / humidify based on temperature and humidity information within the sleep space. The first environment creation information may also include control information for adjusting the airflow intensity and noise in a personalized manner according to the air purifier's operation history and the acquired sleep state (sleep quality).

[0399] The above-described specific descriptions regarding the sleep state information and the environment creation information are merely examples, and the present invention is not limited thereto.

[0400] FIG. 2h illustrates an exemplary block diagram of a receive module and a transmit module associated with one embodiment of the present invention.

[0401] 2h, the receiving module 410 may include a network unit 411, a memory 412, a sensor unit 413, a sound collecting unit 414, an environment creating unit 415, and a reception control unit 416. The receiving module 410 is not limited to the above-mentioned components. That is, additional components may be included or some of the above-mentioned components may be omitted depending on the implementation of the present invention.

[0402] 2h, the transmission module 420 may include a transmitter 421 that transmits a wireless signal and a transmission control unit 422 that controls a wireless signal transmission operation of the transmitter 421. In the embodiment, the transmission control unit 422 may determine a time point at which the wireless signal is transmitted via the transmitter 421. For example, the transmission control unit 422 may control the transmitter 421 to transmit a wireless signal in response to a time point at which the sleep measurement mode is started.

[0403] According to an embodiment of the present invention, the receiving module 410 may include a network unit 411 that transmits and receives data to and from the transmitting module 420, the user terminal 300, and the external server 20. The network unit 411 may transmit and receive data, etc., for performing the method for adjusting a sleep environment based on sleep state information according to an embodiment of the present invention, with other computing devices, servers, etc. That is, the network unit 411 may provide a communication function between the receiving module 410, the transmitting module 420, the user terminal 300, and the external server 20.

[0404] For example, the network unit 411 may receive sleep examination records and electronic health records for a plurality of users from a hospital server. As another example, the network unit 411 may receive acoustic information related to a space in which a user is active from the user terminal 300. As another example, the network unit 411 may transmit environment creation information for adjusting the environment of a space in which a user is located to the environment creation unit 415. Additionally, the network unit 411 may allow information transmission between the sleep environment adjusting device 400, the user terminal 300, and the external server 20 by calling a procedure in the sleep environment adjusting device 400.

[0405] The network unit 411 according to an embodiment of the present invention may be configured using any one of the various wired and wireless communication systems described above, or a combination thereof.

[0406] According to an embodiment of the present invention, the memory 412 may store a computer program for performing a sleep environment adjusting method based on sleep state information according to an embodiment of the present invention, and the stored computer program may be read and driven by the reception control unit 416. The memory 412 may also store any type of information generated or determined by the reception control unit 416 and any type of information received by the network unit 411. The memory 412 may also store data related to the user's sleep. For example, the memory 412 may temporarily or permanently store input / output data (e.g., acoustic information related to the user's sleep environment, sleep state information corresponding to the acoustic information, or environment creation information based on the sleep state information).

[0407] According to an embodiment of the present invention, the memory 412 may include at least one type of storage medium selected from the group consisting of flash memory, hard disk, micro multimedia card, card-type memory (e.g., SD or XD memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, and optical disk. The sleep environment controlling device 400 may also operate in association with web storage that performs the storage function of the memory 412 over the Internet. The above description of the memory is for illustrative purposes only, and the present invention is not limited thereto.

[0408] The computer program may include one or more instructions that, when loaded into memory 412, cause reception control unit 416 to perform methods / operations according to various embodiments of the present invention. That is, reception control unit 416 can perform methods / operations according to various embodiments of the present invention by executing one or more instructions.

[0409] According to an embodiment of the present invention, the receiving module 410 may include a sensor unit 413 that acquires one or more pieces of sensing information related to a space. In the present invention, a space refers to a space where a user lives, such as a bedroom where the user sleeps.

[0410] According to an embodiment, the sensor unit 413 may include a first sensor unit that detects user movement within a space. The first sensor unit may include at least one of a PIR sensor (Passive Infrared Sensor) and an ultrasonic sensor. The PIR sensor can detect user movement within a detection range by detecting changes in infrared rays emitted from the user's body. For example, the PIR sensor can detect user movement within a bedroom by identifying infrared rays of 8 μm to 14 μm emitted from the user's body. The ultrasonic sensor can detect object movement by generating sound waves and detecting signals reflected by a specific object. For example, the ultrasonic sensor can generate sound waves within a bedroom space and detect user movement within the bedroom through the sound waves reflected by the user's body when the user enters the bedroom.

[0411] In addition, in the embodiment, the sensor unit 413 may include a second sensor unit that detects whether the user is located in a pre-defined area of ​​the one space based on a wireless signal. The second sensor unit may receive a wireless signal transmitted from the transmission module 420 and detect whether the user is located in a pre-defined area based on the received wireless signal. In the embodiment, the pre-defined area is related to an area within the one space where the user lies down to sleep, and may refer to an area where a bed is provided, for example. For example, in the present invention, the one space may refer to the interior space of a bedroom, and the pre-defined area may refer to the space where the bed is located.

[0412] In the embodiment, the second sensor unit may be provided at a position facing the transmitting module 420 based on the preset area. For example, the transmitting module 420 and the second sensor unit may be provided on both sides of the bed where the user sleeps. In this case, the sleep environment adjusting device 400 of the present invention may acquire information on whether the user is located in the preset area and object state information, which is information on the user's movement or breathing, based on the Wi-Fi based OFDM signals transmitted and received via the transmitting module 230 and the receiving module 240.

[0413] According to one embodiment, when the receiving module 410 determines through the second sensor that the user is located in a previously set area, it may allow the operation of the environment creating unit 415. In other words, the receiving module 410 may allow the operation of the environment creating unit 415 only when it detects that the user is located in a previously set area 11a. That is, the receiving module 410 may control the operation of the environment creating unit 415, which performs an environment adjustment operation, only when the user is located in a previously set area. The environment creating unit 415 may not perform an operation to change the sleeping environment if the user is not located in a specific position.

[0414] In an additional embodiment, the sensor unit 413 may include one or more environmental sensing modules for acquiring indoor environment information related to the user's sleep environment, such as the user's body temperature, indoor temperature, indoor airflow, indoor humidity, and indoor illuminance. The indoor environment information may be information related to the user's sleep environment, such as information that serves as a reference for considering the influence of external factors on the user's sleep through a sleep state related to changes in the user's sleep stage. The one or more environmental sensing modules may include, for example, at least one sensor module selected from the group consisting of a temperature sensor, an airflow sensor, a humidity sensor, an acoustic sensor, and an illuminance sensor. However, the sensor unit 413 is not limited thereto, and may further include various sensors that can measure the external environment that may affect the user's sleep.

[0415] According to an embodiment of the present invention, the receiving module 410 may include an acoustic collector 414. The acoustic collector 414 may include a small microphone module and may acquire information about acoustics generated in a space where a user sleeps. According to an embodiment, the microphone module included in the acoustic collector 414 may be a relatively small-sized MEMS (Micro-Electro-Mechanical Systems). Such a microphone module is advantageous in terms of cost and can be manufactured in a very small size, but may have a lower signal-to-noise ratio (SNR) than a condenser microphone or a dynamic microphone. A low SNR may mean that a high ratio of noise, which is acoustics that prevent the desired acoustic ratio from being identified, makes it difficult to identify the acoustics (i.e., unclear). Information to be analyzed in the present invention may be acoustic information related to the user's breathing and movements acquired during sleep, i.e., sleep acoustic information. Since such sleep sound information is information about very subtle sounds such as the user's breathing and movements and is acquired together with other sounds during sleep, it may be very difficult to detect and analyze if acquired through the microphone module having a low signal-to-noise ratio. Therefore, when sleep sound information having a low signal-to-noise ratio is acquired, the reception control unit 416 may process it into data for processing and / or analysis.

[0416] According to an embodiment of the present invention, the receiving module 410 may include an environment creation unit 415. The environment creation unit 415 may adjust the user's sleep environment. Specifically, the environment creation unit 415 may adjust at least one of air quality, illuminance, temperature, wind direction, humidity, and sound in the space where the user is located based on the environment creation information. The environment creation information may be a signal generated from the receiving control unit 416 based on the determination of the user's sleep state information. For example, the environment creation information may include information on lowering or increasing illuminance. As a further example, the environment creation information may include control information for adjusting at least one of temperature, humidity, wind direction, and sound. The environment creation information may include various information related to fine dust removal, harmful gas removal, allergy care activation, deodorization / sterilization activation, dehumidification / humidification adjustment, airflow intensity adjustment, air purifier noise adjustment, and LED illumination based on the user's real-time sleep state. The above-mentioned specific description of the environment creation information is merely an example, and the present invention is not limited thereto.

[0417] The environment creating unit 415 may perform at least one of illumination control, temperature control, wind direction control, humidity control, and sound control. However, without being limited thereto, the environment creating unit may further perform various control operations that may bring about changes in the user's sleep environment. That is, the environment creating unit 415 may adjust the user's sleep environment by performing various control operations based on the environment control signal from the reception control unit 416. In an additional embodiment, the environment creation unit 415 may be implemented through connection via the Internet of Things (IoT). Specifically, the environment creation unit 415 may be implemented through connection with various devices that can change the indoor environment in relation to the space where the user is located. For example, the environment creation unit 415 may be implemented as a smart air conditioner, a smart heater, a smart boiler, a smart window, a smart humidifier, a smart dehumidifier, and smart lighting, etc., based on connection via the Internet of Things. The specific description of the environment creation unit described above is merely an example, and the present invention is not limited thereto.

[0418] According to one embodiment of the present invention, the reception control unit 416 may be configured with one or more cores and may include a processor for data analysis and deep learning, such as a central processing unit (CPU) of a computing device, a general purpose graphics processing unit (GPGPU), or a tensor processing unit (TPU).

[0419] The reception control unit 416 can read a computer program stored in the memory 412 and perform data processing for machine learning according to an embodiment of the present invention.

[0420] According to an embodiment of the present invention, the receiving control unit 416 may perform calculations for neural network learning, such as processing input data for learning using deep learning (DL), extracting features from the input data, calculating errors, and updating weights of the neural network using backpropagation.

[0421] In addition, at least one of the CPU, GPGPU, and TPU of the reception control unit 416 may process network function learning. For example, the CPU and GPGPU may both process network function learning and data classification using the network function. In addition, in an embodiment of the present invention, processors of multiple computing devices may be used together to process network function learning and data classification using the network function. In addition, a computer program executed in a computing device according to an embodiment of the present invention may be a program executable by a CPU, a GPGPU, or a TPU.

[0422] The reception control unit 416 may read a computer program stored in the memory 412 to provide a sleep analysis model according to an embodiment of the present invention. According to an embodiment of the present invention, the reception control unit 416 may perform calculations to calculate environment creation information based on sleep state information. According to an embodiment of the present invention, the reception control unit 416 may perform calculations to train the sleep analysis model.

[0423] According to an embodiment of the present invention, the reception control unit 416 may generally process the overall operation of the sleep environment adjusting device 400. The reception control unit 416 may process signals, data, information, etc. input or output via the components described in detail above, or may run applications stored in the memory 412, thereby providing or processing appropriate information or functions to the user terminal.

[0424] According to an embodiment of the present invention, the reception control unit 416 may acquire acoustic information related to the space in which the user sleeps. Acquiring the acoustic information according to an embodiment of the present invention may involve acquiring or loading acoustic information stored in the memory 412. Acquiring the acoustic information may also involve receiving or loading data from another storage medium, another computing device, or a separate processing module within the same computing device based on wired or wireless communication means.

[0425] According to an embodiment, the reception control unit 416 may acquire sleep sound information from the environmental sensing information. Here, the environmental sensing information may be sound information acquired in the user's daily life. For example, the environmental sensing information may include various sound information acquired in the user's daily life, such as sound information related to cleaning, sound information related to cooking, and sound information related to watching TV.

[0426] According to an embodiment of the present invention, the reception control unit 416 may identify a singular point at which pre-defined pattern information is detected in the environmental sensing information. Here, the pre-defined pattern information may be related to breathing and movement patterns associated with sleep. For example, in a wakeful state, the entire nervous system is activated, resulting in irregular breathing patterns and frequent body movements. Furthermore, the throat muscles may not relax, resulting in very little breathing noise. On the other hand, when the user is asleep, the autonomic nervous system is stabilized, resulting in regular breathing, less body movements, and louder breathing noise. That is, the reception control unit 416 may identify a time point at which pre-defined pattern sound information associated with regular breathing, less body movements, or less breathing noise is detected in the environmental sensing information as a singular point. Furthermore, the reception control unit 416 may acquire sleep sound information based on the environmental sensing information acquired based on the identified singular point. The reception control unit 416 may identify a singular point related to the user's sleep time point from the environmental sensing information acquired in a time series manner, and acquire sleep sound information based on the singular point.

[0427] According to an embodiment of the present invention, the reception control unit 416 may identify a singular point associated with a time point at which a previously established pattern is identified from the environmental sensing information, and may acquire sleep sound information based on sound information acquired after the identified singular point.

[0428] According to an embodiment of the present invention, the reception control unit 416 can extract and acquire only sleep sound information from a vast amount of sound information by identifying singular points related to the user's sleep from the environmental sensing information. In other words, it can acquire only sounds related to sleep (i.e., sleep sound information) from sounds generated in a certain space. This automates the process of the user recording their sleep time, providing convenience and contributing to improving the accuracy of the acquired sleep sound information.

[0429] According to the embodiment, the reception control unit 416 may calculate the sleep state information based on the acoustic information. Specifically, the reception control unit 416 may calculate the sleep state information based on the sleep acoustic information of the user acquired via the acoustic collection unit 414.

[0430] In one embodiment, the sleep state information may include information related to whether the user is sleeping. Specifically, the sleep state information may include at least one of first sleep state information indicating that the user is about to fall asleep, second sleep state information indicating that the user is sleeping, and third sleep state information indicating that the user has fallen asleep.

[0431] The sleep state information may be acquired based on sleep acoustic information, which may include acoustic information acquired while the user is sleeping in a space where the user is located in a non-contact manner.

[0432] In an embodiment, the reception control unit 416 may acquire sleep state information related to whether the user is asleep or not based on a singular point identified from the acoustic information. Specifically, the reception control unit 416 may determine that the user is not asleep if a singular point is not identified, and may determine that the user is asleep after the singular point if a singular point is identified. Furthermore, the reception control unit 416 may identify a time point (e.g., a wake-up time) at which a previously set pattern is not observed after the singular point is identified, and may determine that the user has fallen asleep, i.e., woken up, if the time point is identified.

[0433] According to one embodiment of the present invention, the reception control unit 416 can acquire sleep state information related to whether the user is before sleep, during sleep, or after sleep, based on whether a singular point is identified from the acoustic information and whether a previously set pattern is continuously detected after the singular point is identified.

[0434] According to an embodiment of the present invention, the reception control unit 416 may generate environment creation information based on sensing information and sleep state information. Specifically, the reception control unit 416 may generate the environment creation information based on sensing information acquired through the sensor unit 413 and sleep state information acquired as a result of acoustic analysis. The reception control unit 416 generates the environment creation information based on the sensing information and sleep state information, and transmits the generated environment creation information to the environment creation unit 415, thereby controlling the sleep environment change operation of the environment creation unit 415.

[0435] In an embodiment, the reception control unit 416 may generate environment creation information based on the sleep state information. The reception control unit 416 may generate first environment creation information based on the first sleep state information. Specifically, when the reception control unit 416 acquires first sleep state information indicating that the user is about to fall asleep, the reception control unit 416 may generate first environment creation information based on the first sleep state information. That is, when the user's sleep state is about to fall asleep, the reception control unit 416 may generate first environment creation information for supplying a preset white light for a certain period of time.

[0436] According to an embodiment of the present invention, the first environment creation information may be control information for controlling the air purifier to remove fine dust and harmful gases in advance until a predetermined time (e.g., 20 minutes) before the user goes to sleep. The first environment creation information may include information for controlling the air purifier to generate noise (white noise) sufficient to induce sleep just before sleep, adjusting the airflow intensity to a level lower than a preset intensity, or lowering the intensity of an LED. In addition, the first environment creation information may include information for controlling the air purifier to perform dehumidification / humidification based on temperature and humidity information within the sleep space.

[0437] According to an embodiment, the sleep induction time point may be determined by the reception control unit 416. Specifically, the reception control unit 416 may determine the sleep induction time point through information exchange with the user's user terminal 300. For example, the user may generate sleep plan information by setting the time the user intends to go to sleep and the time the user intends to wake up via the user terminal 300, and may transmit the generated sleep plan information to the reception control unit 416. In this case, the sleep plan information may include desired bedtime information and desired wake-up time information. The reception control unit 416 may identify the sleep induction time point based on the desired bedtime information.

[0438] Furthermore, according to the embodiment, the reception control unit 416 can acquire the user's sleep intention information based on the environmental sensing information and determine the sleep induction time point based on the sleep intention information.

[0439] According to an embodiment of the present invention, the reception control unit 416 can acquire sleep intention information based on the environmental sensing information. According to an embodiment, the reception control unit 416 can identify the types of sounds included in the environmental sensing information. The reception control unit 416 can also calculate the sleep intention information based on the number of identified types of sounds. The reception control unit 416 can calculate the sleep intention information to be lower as the number of types of sounds increases, and can calculate the sleep intention information to be higher as the number of types of sounds decreases.

[0440] That is, the reception control unit 416 may acquire sleep intention information related to the user's intention to sleep based on the number of types of sounds included in the environmental sensing information. For example, the more types of sounds are identified, the lower the sleep intention information indicating the user's low intention to sleep (i.e., sleep intention information with a low score) may be output.

[0441] In addition, in an embodiment, the reception control unit 416 may generate an intention score table by pre-matching different intention scores for each of a plurality of pieces of sound information. The reception control unit 416 may acquire sleep intention information based on the environmental sensing information and the intention score table. Specifically, the reception control unit 416 may record an intention score matched to the identified sound corresponding to a time point when at least one of a plurality of sounds included in the intention score table is identified in the environmental sensing information.

[0442] In an embodiment, the reception control unit 416 may acquire sleep intention information based on the total intention score acquired over a predetermined period of time (e.g., 10 minutes). That is, the reception control unit 416 may acquire sleep intention information related to the user's intention to sleep based on characteristics of sound included in the environmental sensing information. For example, the more sounds related to the user's activity are identified, the lower the sleep intention information indicating the user's low sleep intention (i.e., sleep intention information with a low score) may be output.

[0443] According to an embodiment, the reception control unit 416 may determine a sleep induction time point based on the sleep intention information. Specifically, the reception control unit 416 may identify a time point at which the sleep intention information exceeds a predetermined threshold as a sleep induction time point. That is, when high sleep intention information is acquired, the reception control unit 416 may identify this as a time point appropriate for sleep induction, i.e., a sleep induction time point.

[0444] In addition, in an embodiment, the reception control unit 416 may calculate sleep intention weighting information based on sensing information acquired through the sensor unit 413. Specifically, if the reception control unit 416 detects that a user's movement occurs in a space through the first sensor unit and then identifies that the user is located in a previously set area through the second sensor unit, the reception control unit 416 may determine that the user has a strong intention to sleep and may correspondingly calculate sleep intention weighting information related to 1. If the reception control unit 416 detects that no user movement occurs in a space or a previously set area through the first and second sensor units and that the user is not located, the reception control unit 416 may determine that the user does not have an intention to sleep and may correspondingly calculate sleep intention weighting information related to 0. That is, if the reception control unit 416 detects that the user is located in a specific space (e.g., a bed space) through the sensor unit 413, the reception control unit 416 may calculate sleep intention weighting information related to 1, and if it detects that the user is not located in the specific space, the reception control unit 416 may calculate sleep intention weighting information related to 0. In other words, the reception control unit 416 can calculate sleep intention weighting information related to 0 or 1 depending on whether the user is located in a space and a pre-defined area.

[0445] According to an embodiment, the reception control unit 416 may determine a sleep induction time point based on the sensing information and the sleep state information. Specifically, the reception control unit 416 may determine a sleep induction time point based on the sensing information acquired through the sensor unit 413 and the sleep state information acquired as a result of the acoustic analysis.

[0446] The reception control unit 416 may determine a sleep induction time point based on sleep intention information calculated based on the environmental sensing information and sleep intention weighting information calculated based on the sensing information. For example, final sleep intention information may be obtained based on the sleep intention information and the sleep intention weighting information, and the time point at which the final sleep intention information exceeds a threshold value equal to or greater than the schedule may be determined as the sleep induction time point.

[0447] For example, the reception control unit 416 may calculate final sleep intention information by multiplying the sleep intention information and the sleep intention weighting information. For a specific example, if the sleep intention information calculated based on the environmental sensing information is “9” and the sleep intention weighting information calculated based on the sensing information is “0,” the final sleep intention information may be calculated as “0,” and the reception control unit 416 may determine that the final sleep intention information does not exceed a predetermined threshold (e.g., 8). For another example, if the sleep intention information is “9” and the sleep intention weighting information is “1,” the final sleep intention information may be calculated as “9,” and the reception control unit 416 may determine that the final sleep intention information exceeds a predetermined threshold (e.g., 8) and determine that the corresponding time point is a sleep induction time point. The specific numerical values ​​related to the sleep intention information, sleep intention weighting information, and final sleep intention information described above are merely examples, and the present invention is not limited thereto.

[0448] As described above, even if high sleep intention information is acquired through acoustic information, the final sleep intention information may change depending on whether the user is in a certain position. For example, even if high sleep intention information (e.g., 10) is calculated based on environmental sensing information, if the user is not in a certain position, the final sleep intention information becomes 0, and it can be determined that the user's sleep intention is ultimately low.

[0449] As described above, the reception control unit 416 can determine the time point at which the user is induced to sleep. Accordingly, when the reception control unit 416 acquires first sleep state information indicating that the user is about to fall asleep, the reception control unit 416 can generate first environment creation information (supplying 3000K white light at an illuminance of 30 lux) that adjusts the light based on the sleep induction time point until the time point at which the second sleep state information is acquired.

[0450] That is, when the user is in a pre-sleep state, the reception control unit 416 may generate first environment creation information for adjusting light from the time when the user is predicted to prepare for sleep (e.g., the sleep induction time) to the time when the user falls asleep (i.e., the time when the second sleep state information is acquired), and may determine to transmit the first environment creation information to the environment creation unit 415. As a result, 3000K white light at an illuminance of 30 lux may be supplied from 20 minutes before the user falls asleep (e.g., the sleep induction time) until the moment the user falls asleep. This light is excellent for melatonin secretion before the user falls asleep, and by using this to induce natural sleep, the user's sleep efficiency may be improved.

[0451] According to an embodiment of the present invention, the reception control unit 416 may generate second environment creation information based on the second sleep state information. The second environment creation information may be control information for minimizing illuminance to create a dark room environment without light. That is, when the user's sleep state is during sleep, the reception control unit 416 may minimize illuminance to create a dark room environment without light. For example, if there is light interference during sleep, the probability of fragmented sleep increases, making it difficult to achieve good, deep sleep.

[0452] In addition, the second environment creation information may be control information based on the second sleep state information for controlling the air purifier to turn off the LED of the air purifier, operate the air purifier at a noise level below a pre-set level, adjust the airflow intensity below a pre-set level, set the airflow temperature within a pre-set range, or maintain the humidity in the sleep space at a predetermined temperature. The user may be induced to sleep by airflow, white noise, etc. in a sleep space that is free of fine dust and harmful gases just before falling asleep, and after falling asleep, the user may sleep soundly in an environment where the optimal temperature, humidity, etc. are controlled.

[0453] That is, when the reception control unit 416 detects that the user has entered sleep (or a sleep stage) (when the second sleep state information is acquired), it can generate control information to stop the supply of light, i.e., second environment creation information, thereby increasing the probability that the user will fall into a deep sleep and improving the quality of their sleep.

[0454] According to an embodiment of the present invention, the reception control unit 416 may generate third environment creation information based on the wake-up induction time. For example, the third environment creation information may be control information related to gradually increasing the illumination starting 30 minutes before the user wakes up (i.e., the wake-up induction time). Here, the wake-up induction time may be determined based on the predicted wake-up time.

[0455] In one embodiment, the wake-up induction time point may be determined based on desired wake-up time information. The desired wake-up time information may be information regarding a wake-up time desired by the user.

[0456] In one embodiment, the desired wake-up time information may be acquired through information exchange with the user's user terminal 300. The user may set the time when he or she intends to go to bed and the time when he or she intends to wake up through the user terminal 300 and transmit the set time to the reception control unit 416. The reception control unit 416 may acquire the desired wake-up time information based on the time when the user of the user terminal 300 intends to wake up.

[0457] In another embodiment, the wake-up induction time may be determined based on the predicted wake-up time. Here, the predicted wake-up time may be determined based on the sleep onset time identified through the second sleep state information. Specifically, the reception control unit 416 may determine the user's sleep onset time through the second sleep state information indicating that the user is asleep. The reception control unit 416 may determine the predicted wake-up time based on the sleep onset time identified through the second sleep state information.

[0458] In another embodiment, the predicted wake-up time may be determined based on the user's sleep stage information. For example, the user may wake up most refreshed if they wake up in the REM sleep stage. During one night's sleep, the user may have a sleep cycle that includes light sleep, deep sleep, light sleep, and REM sleep, and the user may wake up most refreshed if they wake up in the REM sleep stage.

[0459] As a result, the reception control unit 416 can determine the predicted wake-up time of the user based on sleep stage information related to the user's sleep stage. For example, the reception control unit 416 can determine the time at which the user changes from the REM sleep stage to another sleep stage based on the sleep stage information as the predicted wake-up time. That is, the reception control unit 416 can determine the predicted wake-up time based on sleep stage information (i.e., the REM sleep stage) from which the user can wake up most refreshed.

[0460] As described above, the reception control unit 416 can determine the predicted wake-up time of the user based on at least one of the sleep plan information, the sleep onset time, and the sleep stage information acquired from the user terminal. Furthermore, if the reception control unit 416 determines the predicted wake-up time as the time when the user intends to wake up, it can determine the wake-up guidance time based on the predicted wake-up time. For example, the reception control unit 416 can determine the wake-up guidance time to be 30 minutes before the time when the user intends to wake up.

[0461] According to an embodiment of the present invention, the reception control unit 416 may determine the predicted wake-up time when the user is expected to wake up, identify the wake-up guidance time, and generate third environment creation information to supply 3000K white light with gradually increasing illuminance from 0 lux to 250 lux from the wake-up guidance time to the wake-up time (e.g., until the user actually wakes up). The reception control unit 416 may determine to transmit the third environment creation information to the environment creation unit 415, which may then perform a light-related adjustment operation in the space where the user is located based on the third environment creation information. For example, the environment creation unit 415 may gradually increase illuminance of 3000K white light from 0 lux to 250 lux starting 30 minutes before waking up.

[0462] Alternatively, according to an embodiment of the present invention, the third environment creation information may include information for controlling an air purifier to lower the airflow intensity and noise at the time of waking up to induce waking up. Alternatively, the third environment creation information may include control information for controlling an air purifier to generate white noise to gradually induce waking up. The third environment creation information may include control information for controlling the air purifier to maintain the noise of the air purifier at or below a previously set level after waking up. Furthermore, the third environment creation information may include control information for controlling the air purifier in conjunction with the predicted wake-up time and the recommended wake-up time.

[0463] According to an embodiment of the present invention, the sleep stage information may be acquired through a sleep analysis model that analyzes the sleep stage of a user based on acoustic information acquired during sleep (i.e., sleep acoustic information). That is, the sleep stage information of the present invention may be acquired through a sleep analysis model.

[0464] According to an embodiment of the present invention, the reception control unit 416 may acquire environmental sensing information and acquire sleep sound information based on the acquired sound information. In this case, the sleep sound information is information related to sound acquired while the user is sleeping, and may include, for example, sound generated by the user turning over in their sleep, sound related to muscle movement, or sound related to the user's breathing while sleeping.

[0465] According to an embodiment, the reception control unit 416 may perform preprocessing on the sleep audio information. The preprocessing on the sleep audio information may be preprocessing related to noise reduction. Specifically, the reception control unit 416 may classify the sleep audio information into one or more audio frames having a predetermined time unit. Furthermore, the reception control unit 416 may identify a minimum audio frame having a minimum energy level based on the energy levels of each of the one or more audio frames. The reception control unit 416 may perform noise reduction on the sleep audio information based on the minimum audio frame.

[0466] For example, the reception control unit 416 may classify 30 seconds of sleep audio information into one or more audio frames each having a very short amplitude of 40 ms. The reception control unit 416 may also compare the amplitudes of a plurality of audio frames associated with the amplitude of 40 ms to identify a minimum audio frame having a minimum energy level. The reception control unit 416 may remove the minimum audio frame component identified from the entire sleep audio information (i.e., 30 seconds of sleep audio information). For example, preprocessed sleep audio information may be obtained by removing the minimum audio frame component from the sleep audio information. That is, the reception control unit 416 may perform preprocessing related to noise removal by identifying the minimum audio frame as a background noise frame and removing it from the original signal (i.e., sleep audio information).

[0467] 6a, the reception control unit 416 may generate a spectrogram SP corresponding to the sleep sound information SS. Here, the sleep sound information SS may mean pre-processed sleep sound information. That is, the reception control unit 416 may generate information or a spectrogram including changes in frequency components of the sleep sound information along the time axis, corresponding to the pre-processed sleep sound information.

[0468] According to an embodiment of the present invention, the spectrogram generated by the reception controller 416 in response to the sleep audio information SS may include a Mel spectrogram. The reception controller 416 can acquire the Mel spectrogram by applying a Mel filter bank to the spectrogram. Generally, different parts of the human cochlea vibrate depending on the frequency of audio data. The human cochlea has a characteristic of being sensitive to frequency changes in low frequency bands and insensitive to frequency changes in high frequency bands. Therefore, the Mel spectrogram can be acquired from the spectrogram using the Mel filter bank to have a recognition capability similar to the characteristics of the human cochlea for audio data. That is, the Mel filter bank may apply fewer filter banks to low frequency bands and wider filter banks to higher frequency bands. In other words, the reception controller 416 can acquire the Mel spectrogram by applying the Mel filter bank to the spectrogram to recognize audio data in a manner similar to the characteristics of the human cochlea. The mel spectrogram may include frequency components that reflect the human auditory characteristics. That is, the spectrogram generated in accordance with the sleep acoustic information and subjected to analysis using a neural network in the present invention may include the mel spectrogram described above.

[0469] The reception control unit 416 may also acquire sleep stage information by processing time-axis information or spectrogram SP of frequency components of the sleep audio information as input to a sleep analysis model. Here, the sleep analysis model is a model for acquiring sleep stage information related to changes in a user's sleep stage, and may input sleep audio information acquired during the user's sleep and output sleep stage information. In an embodiment, the sleep analysis model may include a neural network model configured via one or more network functions.

[0470] As described above, the reception control unit 416 may acquire information or a spectrogram including changes in frequency components of the sleep audio information over time based on the sleep audio information. In this case, converting the information or spectrogram including changes in frequency components of the sleep audio information over time may facilitate analysis of breathing or movement patterns associated with relatively small sounds. The reception control unit 416 may also generate sleep stage information based on the information or spectrogram including changes in frequency components of the acquired sleep audio information over time using a sleep analysis model including a feature extraction model and a feature classification model. In this case, the sleep analysis model can perform sleep stage prediction using information or a spectrogram including changes in frequency components of the sleep audio information over time corresponding to multiple epochs as input so that both past and future information can be taken into account, thereby outputting more accurate sleep stage information.

[0471] That is, the reception control unit 416 may output sleep stage information or sleep stage probability information corresponding to the sleep acoustic information by utilizing the sleep analysis model as described above. According to an embodiment, the sleep stage information may be information related to sleep stages that change during the user's sleep.

[0472] According to an embodiment of the present invention, the reception control unit 416 may perform data augmentation based on the preprocessed sleep acoustic information. Such data augmentation is intended to enable the sleep analysis model to output sleep state information (e.g., sleep stage information) that is robust to sounds measured in various domains (e.g., other bedrooms, other microphones, other placement locations, etc.). In an embodiment, the data augmentation may include at least one of pitch shifting, Gaussian noise, loudness control, dynamic range control, and spec augmentation.

[0473] According to one embodiment, the reception control unit 416 may perform data enhancement related to pitch shifting based on the sleep sound information. For example, the reception control unit 416 may perform data enhancement by adjusting the pitch of the sound, such as by raising or lowering the pitch of the sound at predetermined intervals.

[0474] The reception control unit 416 can perform not only pitch shifting but also Gaussian noise, which performs data enhancement through noise-related correction, loudness control, which performs data enhancement by correcting the audio so that the sound quality is maintained even when the volume is changed, dynamic range control, which performs data enhancement by adjusting the dynamic range, which is the logarithmic ratio measured in dB between the maximum and minimum amplitudes of the audio, and spec augmentation, which is related to the increase in audio specifications.

[0475] That is, the reception control unit 416 can enhance the accuracy of sleep stage prediction by enabling the sleep analysis model to perform robust recognition in response to sleep sounds acquired from various environments through data enhancement of the acoustic information (i.e., sleep acoustic information) that is the basis for the analysis of the present invention.

[0476] According to an embodiment of the present invention, the reception control unit 416 may acquire fourth environment creation information based on the third sleeping state information. The fourth environment creation information is the same as that described in relation to the operation of the processor 110 of the embodiment of FIG. 1f, and therefore, a repeated description will be omitted.

[0477] According to an embodiment of the present invention, the reception control unit 416 may determine to transmit the environment creation information to the environment creation unit 415. Specifically, the reception control unit 416 may generate environment creation information related to illuminance adjustment, and may control the illuminance adjustment operation of the environment creation unit 415 by determining to transmit the environment creation information to the environment creation unit 415.

[0478] According to an embodiment, the quality of light and air may be one of the major factors that can affect sleep quality. For example, the illuminance, color, and degree of exposure of light can have a positive or negative effect on sleep quality. Furthermore, sleep quality is also significantly affected by the type / concentration of fine dust, the type / concentration of harmful gases, the presence or absence of allergens, air temperature, and humidity. Therefore, the reception control unit 416 can adjust the illuminance and air quality to improve the user's sleep quality. For example, the reception control unit 416 can monitor the user's sleep status before and after falling asleep, and thereby adjust the illuminance to effectively wake the user up. That is, the reception control unit 416 can grasp the sleep state (e.g., sleep stage) and automatically adjust the illuminance and air quality to maximize sleep quality.

[0479] In one embodiment, the reception control unit 416 may receive sleep plan information from the user terminal 300. The reception control unit 416 may generate external environment creation information based on the received sleep plan information.

[0480] In addition, the reception control unit 416 can receive sleep plan information from the user terminal 300 and, based on the information, generate first environment creation information for controlling the air purifier from the time when the user is predicted to prepare for sleep (e.g., the sleep induction time) to the time when the user falls asleep (i.e., the time when the second sleep state information is acquired).

[0481] In addition, for example, the reception control unit 416 can grasp the time when the user falls asleep, i.e., the time of falling asleep, through the second sleep state information, and can generate second environment creation information based on the second sleep state information.

[0482] In an embodiment, the reception control unit 416 may generate environment creation information based on the sleep stage information. In an embodiment, the sleep stage information may include information regarding changes in the user's sleep stages acquired over time through analysis of sleep acoustic information.

[0483] For example, when the reception control unit 416 determines from the user's sleep stage information that the user has entered a sleep stage (e.g., light sleep), it can generate external environment creation information that minimizes illuminance to create a dark room environment without light. It can also generate environment creation information that blinks the LED of the air purifier to minimize driving noise and adjusts the airflow volume and strength to create a preset airflow. In other words, by creating optimal illuminance for each user's sleep stage, i.e., an optimal sleep environment, it is possible to improve the user's sleep efficiency.

[0484] In addition, the reception control unit 416 may generate environment creation information for providing appropriate illumination according to changes in the user's sleep stage during sleep. For example, the reception control unit 416 may generate more diverse external environment creation information according to changes in the sleep stage, such as providing subtle red light when the user changes from light sleep to deep sleep, or reducing illumination or providing blue light when the user changes from REM sleep to light sleep.

[0485] This can have the effect of allowing the user to maximize the quality of their sleep by automatically taking into account situations during sleep, not just before sleep or immediately after waking up, and considering the entire sleep experience rather than just a part of it.

[0486] Also, for example, the reception control unit 416 can identify the user's desired wake-up time through the sleep plan information, generate a predicted wake-up time based on the desired wake-up time, and generate environment creation information accordingly.

[0487] In addition, the reception control unit 416 may determine to transmit the environment creation information to the environment creation unit 415. That is, the reception control unit 416 may generate environment creation information that allows the user to easily fall asleep or wake up naturally when going to bed or waking up based on the sleep plan information, and may control the environment creation operation of the environment creation unit 415 through the environment creation information, thereby improving the quality of the user's sleep.

[0488] In a further embodiment, the reception control unit 416 may generate recommended sleep plan information based on the sleep stage information. Specifically, the reception control unit 416 may obtain information regarding changes in the user's sleep stages (e.g., sleep cycles) through the sleep stage information and may set an expected wake-up time based on such information.

[0489] In addition, the reception control unit 416 may generate environment creation information according to the recommended sleep plan information and determine to transmit the generated information to the environment creation unit 415. Therefore, the user can wake up naturally according to the recommended sleep plan information recommended by the reception control unit 416. This has the advantage of improving the user's sleep efficiency because the reception control unit 416 recommends the time to wake up for the user according to changes in the user's sleep stage, which may be the time when the user's fatigue level is minimized.

[0490] According to one embodiment, the reception control unit 416 may compare the user's actual wake-up time with the desired wake-up time information and update the environment creation information. Specifically, the reception control unit 416 may use the second sensor unit to generate actual wake-up time information related to the user's actual wake-up time. For example, when the user wakes up and leaves the bed area (e.g., a previously set area), the wireless link that was changed by the user's body is restored, and the second sensor unit detects this change in signal level to accurately detect the time when the user actually got out of bed after waking up (i.e., the actual wake-up time). That is, the second sensor unit may record the time when the user leaves the previously set area and generate actual wake-up time information.

[0491] According to an embodiment of the present invention, the reception control unit 416 compares the desired wake-up time information with the actual wake-up time information, and if the comparison results in discrepancies, updates the environment creation information. Here, the actual wake-up time information compared with the desired wake-up time information may include information about actual wake-up times accumulated over a certain number of times. For example, the actual wake-up time information may include information about the times when the user actually woke up within a week.

[0492] In an embodiment, the reception control unit 416 may analyze the difference between the desired wake-up time and the accumulated actual wake-up time to update the environment creation information. Specifically, if the actual wake-up time is later than the desired wake-up time, the reception control unit 416 may gradually increase the maximum brightness of the white light provided at the wake-up time to manipulate the user's circadian rhythm. For example, the next day, if the actual wake-up time is later than the desired wake-up time, the reception control unit 416 may update the environment creation information so that the maximum brightness of the white light provided at the wake-up time is higher than the previous day, corresponding to the user's wake-up time. Conversely, if the actual wake-up time is earlier than the desired wake-up time, the reception control unit 416 may decrease the maximum brightness of the white light provided at the wake-up time to delay the user's wake-up time. For example, the next day, if the actual wake-up time is earlier than the desired wake-up time, the reception control unit 416 may update the environment creation information so that the maximum brightness of the white light provided at the wake-up time is lower than the previous day, corresponding to the user's wake-up time. That is, the reception control unit 416 can compare the actual wake-up time of the user with the desired wake-up time, and update the environment creation information to change the user's circadian rhythm according to the comparison result, thereby creating a sleep environment optimized for the user and further improving sleep efficiency.

[0493] According to one embodiment of the present invention, the reception control unit 416 can drive the acoustic collection unit through at least one measurement mode of a manual sleep measurement mode and an automatic sleep measurement mode to collect acoustic information, and calculate sleep state information based on the collected acoustic information.

[0494] In an embodiment, the manual sleep measurement mode may mean that the measurement mode is started manually by the user generating a sleep input signal. For example, the user may generate the sleep input signal by applying physical pressure to a sleep input button formed on the outer surface of the sleep environment adjusting device 400, or may generate the sleep input signal using a user terminal. When the sleep input signal is generated, the sleep environment adjusting device 400 (i.e., the receiving module) may acquire acoustic information related to a space based on the time point and acquire the user's sleep state information based on the acoustic information. That is, through the manual sleep measurement mode, the user can directly determine the time point at which to start measuring their own sleep state.

[0495] According to an embodiment, the automatic sleep measurement mode may mean that sleep measurement is automatically started without a separate user action for generating a sleep input signal. The automatic sleep measurement mode may be characterized in that after detecting user movement in a space through the first sensor unit, the measurement mode is automatically started when the user is identified as being located in a previously set area through the second sensor unit. The automatic sleep measurement mode will be described in detail below with reference to FIG. 13.

[0496] 13 is a flowchart illustrating an example of a process of acquiring sleep state information through a sleep measurement mode of an environment creating apparatus according to an embodiment of the present invention. The steps illustrated in FIG. 13 may be reordered, and at least one step may be omitted or added, as necessary. That is, the above steps are merely an embodiment of the present invention, and the scope of the present invention is not limited thereto.

[0497] According to one embodiment, the reception control unit 416 may detect the occurrence of user movement within a space through a first sensor unit (S1100). The first sensor unit may include at least one of a PIR sensor and an ultrasonic sensor.

[0498] According to one embodiment, the reception control unit 416 may identify that the user is located in a previously set area through the second sensor unit (S1200). The second sensor unit may receive a wireless signal transmitted from the transmission module 420 and may detect whether the user is located in a previously set area based on the received wireless signal.

[0499] In the embodiment, the second sensor unit may be provided at a position facing the transmitting module 420 based on the preset area. For example, the transmitting module 420 and the second sensor unit may be provided on both sides of the bed where the user sleeps. In this case, the sleep environment controlling device 400 of the present invention may acquire information on whether the user is located in the preset area and object state information, which is information on the user's movement or breathing, based on the Wi-Fi based OFDM signals transmitted and received via the transmitting module 420 and the receiving module 410.

[0500] According to one embodiment, the reception control unit 416 may drive the sound collection unit 414 to collect sound information related to a space (S1300).

[0501] That is, the reception control unit 416 can detect user movement occurring in a space through the first sensor unit, and when the user movement is identified in a pre-set area through the second sensor unit, automatically collect sound information related to the space through the sound collection unit 414.

[0502] According to one embodiment, the reception control unit 416 may calculate sleep state information based on the collected acoustic information (S1400). The reception control unit 416 may acquire sleep state information related to whether the user is asleep or asleep based on a singular point identified from the acoustic information. Specifically, the reception control unit 416 may determine that the user is asleep if no singular point is identified, and may determine that the user is asleep after the singular point if a singular point is identified. Furthermore, the reception control unit 416 may identify a time point (e.g., a wake-up time) at which a previously established pattern is not observed after the singular point is identified, and may determine that the user has fallen asleep, i.e., woken up, if the time point is identified.

[0503] 14 is a flowchart illustrating an example of a process for creating an environment that induces a user to fall asleep, according to an embodiment of the present invention. The steps shown in FIG. 14 may be reordered, and at least one step may be omitted or added, as necessary. That is, the above steps are merely an embodiment of the present invention, and the scope of the present invention is not limited thereto.

[0504] According to one embodiment, when the user's sleep state is before sleep, the receiving module 410 may identify a sleep induction point based on desired bedtime information (S2100). As a specific example, the user may generate sleep plan information by setting the time the user intends to go to sleep and the time the user intends to wake up via the user terminal 300, and may transmit the generated sleep plan information to the receiving module 410. In this case, the sleep plan information may include desired bedtime information and desired wake-up time information. The receiving module 410 may identify a sleep induction point based on the desired bedtime information.

[0505] In addition, the receiving module 410 can detect whether the user is located in a previously set area at the time of sleep induction through the second sensor unit (S2200). The second sensor unit receives the wireless signal transmitted from the transmitting module 420 and can detect whether the user is located in a previously set area based on the received wireless signal.

[0506] In an embodiment, if it is detected that the user is not located in a previously set area, the receiving module 410 may transmit a notification to the user terminal (S2300). Specifically, if the sleep induction time is approaching but the user is not located in a previously set area, the receiving module 410 may transmit a notification to the user terminal to prepare for sleep.

[0507] In addition, in an embodiment, when detecting that the user is located in a pre-set area, the receiving module 410 may generate first environment creation information for supplying the pre-set white light from the sleep induction time to the sleep time (S2400). That is, the first environment creation information may be generated only when the user is located in the pre-set area corresponding to the sleep induction time. In other words, the receiving module 410 may control the operation of the environment creation unit 415, which performs an environment adjustment operation, by generating the first environment creation information only when the user is located in the pre-set area. As a result, the environment creation unit 415 may not perform an operation to change the sleep environment if the user is not located in a specific position.

[0508] 15 is a flowchart illustrating an exemplary process of changing a user's sleep environment during sleep and immediately before waking up, according to an embodiment of the present invention. The order of the steps illustrated in FIG. 15 may be changed as needed, and at least one step may be omitted or added. In other words, the above steps are merely an embodiment of the present invention, and the scope of the present invention is not limited thereto.

[0509] According to one embodiment, the receiving module 410 may generate second environment creation information for minimizing illuminance to create a dark room environment without light when the user is asleep (S3100). For example, if there is light interference during sleep, the probability of fragmented sleep increases, making it difficult to get a good, deep sleep.

[0510] That is, when the receiving module 410 detects that the user has entered sleep (or a sleep stage) (when the second sleep state information is acquired), it can generate control information, i.e., second environment creation information, to prevent light from being supplied, thereby increasing the probability that the user will fall into deep sleep and improving the quality of sleep.

[0511] According to one embodiment, the receiving module 410 may identify a wake-up induction time based on the user's desired wake-up time information, and generate third environment creation information that gradually increases the illuminance of white light from the wake-up induction time to the desired wake-up time (S3200).

[0512] [Air Purifier 500]

[0513] Hereinafter, an example in which an environment-controlling device is embodied as an air purifier according to one embodiment of the present invention will be described in detail. Figure 11 is a conceptual diagram illustrating the operation of the environment-creating device according to the present invention. Specifically, Figure 11(a) is a schematic diagram in which the environment-creating device 30 of Figure 1f is embodied as an air purifier 500, and Figure 11(b) is a schematic diagram in which the air purifier 500 operates in conjunction with a user terminal 300.

[0514] As shown in FIG. 11( a ), the air purifier 500 according to the present invention can operate in conjunction with the user terminal 300 and the computing device 100 .

[0515] The computing device 100 may include a network unit 180, a memory 120, and a processor 110 (see FIG. 2c). The network unit 180 transmits and receives data to and from the user terminal 300, the external server 20, and the air purifier 500. The network unit 180 may transmit and receive data, etc., for performing the method for creating a sleep environment based on sleep state information according to an embodiment of the present invention, to and from other computing devices, servers, etc.

[0516] That is, the network unit 180 may provide a communication function between the computing device 100, the user terminal 300, the external server 20, and the air purifier 500. For example, the network unit 180 may receive sleep screening records and electronic health records for multiple users from a hospital server. As another example, the network unit 180 may receive environmental sensing information related to the space where the user is active from the user terminal 300. As another example, the network unit 180 may transmit environmental creation information related to air quality for adjusting the environment of the space where the user is located to the air purifier 500. Additionally, the network unit 180 may allow information transmission between the computing device 100, the user terminal 300, and the external server 20 by calling a procedure in the computing device 100.

[0517] The memory 120 may store a computer program for performing a method for creating a sleep environment based on sleep state information according to an embodiment of the present invention, and the stored computer program may be read and driven by the processor 110. The memory 120 may also store any type of information generated or determined by the processor 110 and any type of information received by the network unit 180. The memory 120 may also store data related to the user's sleep. For example, the memory 120 may temporarily or permanently store input / output data (e.g., environmental sensing information related to the user's sleep environment (especially related to air quality), sleep state information corresponding to the environmental sensing information, or environment creation information based on the sleep state information). The computer program, when loaded into the memory 120, may include one or more instructions that cause the processor 110 to perform methods / operations according to various embodiments of the present invention. In one embodiment, the computer program may include one or more instructions for performing a method for creating a sleep environment based on sleep state information, including acquiring sleep state information of a user, generating environment creation information based on the sleep state information, and transmitting the environment creation information to an environment creation device.

[0518] The operation method, hardware configuration, and software configuration of the network unit 180 and memory 120 are the same as those described above.

[0519] The processor 110 may read a computer program stored in the memory 120 to provide a sleep analysis model according to an embodiment of the present invention. According to an embodiment of the present invention, the processor 110 may perform calculations to calculate environment creation information based on sleep state information. According to an embodiment of the present invention, the processor 110 may perform calculations to train the sleep analysis model. Specific details of the sleep analysis model are the same as those described above.

[0520] The processor 110 may acquire the user's sleep state information and environmental sensing information, as described above. The processor 110 may generate first through n-th environment creation information. Specifically, when the user is in a pre-sleep state, the processor 110 may generate first environment creation information for controlling an air purifier from a time when the user is predicted to prepare for sleep (e.g., a sleep induction time) to a time when the user falls asleep (i.e., a time when the second sleep state information is acquired). Specifically, the processor 110 may generate first environment creation information for controlling the air purifier to remove fine dust and harmful gases in advance until a predetermined time (e.g., 20 minutes) before the user falls asleep. The first environment creation information may include information for controlling the air purifier to generate noise (white noise) sufficient to induce sleep just before sleep, adjusting the airflow intensity to a level lower than a preset intensity, or lowering the intensity of an LED. In addition, the first environment creation information may include information for controlling the air purifier to perform dehumidification / humidification based on temperature and humidity information in the sleeping space.

[0521] The processor 110 may generate second environment creation information for controlling the air purifier to turn off the LED of the air purifier based on the second sleep state information, operate the air purifier at a noise level below a pre-set level, adjust the airflow intensity below a pre-set intensity, adjust the airflow temperature within a pre-set range, or maintain the humidity in the sleep space at a predetermined temperature.

[0522] In addition, the processor 110 may generate third environment creation information and fourth environment creation information based on the third sleeping state information and the fourth sleeping state information.

[0523] The processor 110 may determine to transmit the environment creation information to the air purifier 500. That is, the processor 110 may improve the quality of the user's sleep by generating external environment creation information that allows the user to easily fall asleep or wake up naturally when going to bed or waking up.

[0524] As shown in Fig. 11(b), the air purifier 500 according to the present invention can operate in conjunction with a user terminal 300. That is, the system according to the embodiment of Fig. 11(b) may include the air purifier 500, the user terminal 300, the external server 20, and a network. In this embodiment, the air purifier 500 according to the present invention includes the configuration of the computing device 100 of Fig. 11(a) and additional configuration for operating as an air purifier.

[0525] 12 is a block diagram showing the configuration of an air purifier 500 according to an embodiment of the present invention. As shown in FIG. 12, an air purifier 500, which is an example of an air purifier according to the present invention, may include a network unit 510, a memory 520, a processor 530, a driving unit 540, and a measuring unit 550.

[0526] The air purifier 500 may be implemented as an air purifying device embedded in the ceiling or exterior wall of a building, apartment, or house, as a fixed air purifier fixed to one side of an indoor space, as a portable air purifier that is easy to carry and move, as an in-vehicle air purifying device installed in a vehicle, or as a wearable air purifier that is worn on the body to purify the air around the user.

[0527] The air purifier 500 may be implemented as various types of air purifiers, such as a dust collection filter type air purifier that removes dust using pretreatment and a HEPA filter, an adsorption filter type that adsorbs harmful gases using activated carbon, a wet type that removes dust and harmful gases using water, an electrostatic precipitator type that removes dust using high voltage, an anion type that removes dust by generating negative ions using high voltage and supplying them into the air, a plasma type that removes harmful gases by generating positive / negative ions using plasma, and a UV photocatalyst type that removes odors and harmful gases by oxidizing / reducing OH radicals and active oxygen generated by irradiating TiO with ultraviolet light, or a combination air purifier that combines two or more types.

[0528] The functions, operations, hardware configurations, and software configurations of the network unit 510, memory 520, and processor 530 of the air purifier 500 are the same as those described above. The first through nth environment creation information generated by the processor 530 may be transmitted to the driving unit 540. The driving unit 540 operates various hardware elements provided in the air purifier 500.

[0529] The measuring unit 550 may include one or more sensors for sensing air components in the space, illuminance, and the state of components of the air purifier, etc. Specifically, the measuring unit may include a dust sensor for detecting invisible airborne particles such as PM1.0, PM2.5, and PM10, a gas sensor for detecting harmful gases and odors in the room, an illuminance sensor for detecting indoor illuminance, a TVOC sensor for measuring the total concentration of over 300 types of volatile organic compounds contained in the indoor air, a CO2 sensor for measuring the concentration of carbon dioxide in the indoor air, a radon sensor for measuring the concentration of radon, a pressure sensor for measuring the filter differential pressure depending on the lifespan of the filter unit to indicate when to replace the filter, a temperature sensor for measuring the indoor temperature, etc.

[0530] Although not shown in the drawings, the air purifier 500 may include a housing having an outlet and an inlet, a filter unit, a blower fan, a sterilizer unit, a humidifier unit, a heater unit, a cooler unit, and a measuring unit. The housing may be designed in various ways depending on the type of the air purifier 500, such as an embedded type, a fixed type, a mobile type, a vehicle type, or a wearable type. The filter unit may be selected according to the air purification method, such as a dust collection filter type, an adsorption filter type, a wet type, an electrostatic precipitator type, an anion type, a plasma type, or a UV photocatalyst type. The blower fan may be connected to a motor that rotates using power supplied from a power supply unit. The sterilizer unit sterilizes the inhaled air using chemical or electrical methods. The humidifier unit humidifies the inhaled air before discharging it, and the heater unit and cooler unit heat or cool the inhaled air to a predetermined temperature.

[0531] The hardware elements of the air purifier 500 described above are merely one embodiment, and some of them may be integrated into a single configuration, some components may be omitted, and various components for performing air purification functions not described above may be added.

[0532] Meanwhile, the environmental sensing information may be acquired via the user terminal 300. The environmental sensing information may be sleep acoustic information acquired in a bedroom where the user sleeps.

[0533] Furthermore, the environmental sensing information may be information about the quality of air in the sleeping space acquired from the measurement unit 550 provided in the air purifier 500. The environmental sensing information acquired through the user terminal 300 or the measurement unit 550 may be information that serves as a basis for acquiring information about the user's sleeping state in the present invention.

[0534] For example, sleep state information related to whether the user is before, during, or after sleep may be obtained through environmental sensing information obtained in relation to the user's activity. Also, information related to the quality of the air around the user before, during, and after sleep may be obtained.

[0535] The processor 530 may acquire sleep state information based on environmental sensing information acquired through the user terminal 300 and / or the measurement unit 550 .

[0536] Specifically, the processor 530 may identify a singular point at which pre-defined pattern information is detected in the environmental sensing information. Here, the pre-defined pattern information may be related to breathing and movement patterns associated with sleep. For example, in a wakeful state, the entire nervous system is activated, resulting in irregular breathing patterns and frequent body movements. Furthermore, the throat muscles may not relax, resulting in very little breathing noise. On the other hand, when the user sleeps, the autonomic nervous system stabilizes, resulting in regular breathing, less body movements, and louder breathing noise. That is, the processor 530 may identify a time point at which pre-defined pattern sound information associated with regular breathing, less body movements, or less breathing noise is detected in the environmental sensing information as a singular point. Furthermore, the processor 530 may acquire sleep audio information based on the identified singular point. The processor 530 may identify a singular point associated with the user's sleep time point in the chronologically acquired environmental sensing information and acquire sleep audio information based on the singular point.

[0537] Furthermore, the air quality measured by the measuring unit 550 has a significant impact on a user's sleep. A paper analyzing the relationship between air quality and sleep confirmed that sleep disorders show a statistically significant correlation with air pollution. For example, exposure to PM10 can cause difficulty maintaining sleep, and it was found that men, in particular, are most likely to experience sleep disorders when exposed to PM1. It was also found that women are most likely to experience sleep disorders when exposed to PM1 or PM2.5. It was also found that high levels of SO2 and O3 are most likely to cause sleep disturbances related to wheezing. Furthermore, it was also found that if pregnant women are exposed to PM2.5 during the 31st to 35th weeks of pregnancy, their children are most likely to have shorter sleep duration. Various studies have been conducted on the correlation between AHI and air quality measurements, and while the results vary slightly across studies, they all consistently show a strong correlation between air quality and sleep.

[0538] The air purifier 500 according to the present invention can obtain sleep state information based on environmental sensing information, generate environment creation information, and perform an operation appropriate for the sleep stage using the environment creation information.

[0539] Specifically, when the processor 530 of the air purifier 500 determines that the user is in a pre-sleep state, the processor 530 may generate first environment creation information for controlling the air purifier from the time when the user is predicted to prepare for sleep (e.g., the sleep induction time) to the time when the user falls asleep (i.e., the time when the second sleep state information is acquired). The first environment creation information may be generated reflecting the PM concentration, harmful gas concentration, CO2 concentration, SO2 concentration, O3 concentration, humidity, temperature, etc. measured by the measurement unit 550.

[0540] The first environment creation information may include information for controlling the air purifier to remove fine dust particles and harmful gases in advance until a predetermined time (e.g., 20 minutes) before the user goes to sleep, information for controlling the air purifier to induce noise (white noise) sufficient to induce sleep just before sleep, information for adjusting the airflow strength to a level lower than a preset strength, information for lowering the LED strength, and information for controlling the air purifier to dehumidify / humidify based on temperature and humidity information in the sleep space.

[0541] In addition, the processor 530 may generate second environment creation information for controlling the air purifier to turn off the LED of the air purifier based on the second sleep state information, operate the air purifier at a noise level below a pre-set level, adjust the airflow intensity below a pre-set intensity, adjust the airflow temperature within a pre-set range, or maintain the humidity in the sleep space at a predetermined temperature.

[0542] The second environment creation information may be control information for controlling the air purifier to turn off the LED of the air purifier, operate the air purifier at a noise level below a preset level, adjust the airflow intensity below a preset level, set the airflow temperature within a preset range, or maintain the humidity in the sleep space at a predetermined temperature, based on the second sleep state information. The user may be induced to sleep by airflow and white noise in a sleep space that is free of fine dust and harmful gases just before falling asleep, and after falling asleep, the user can have a deep sleep in an environment where the optimal temperature, humidity, etc. are controlled.

[0543] [Device 100a for generating imagery-guiding information / Device 200a for providing imagery-guiding information]

[0544] According to one embodiment of the present invention, as shown in FIG. 1h, the device 100a for generating imagery-guided information or the device 200a for providing imagery-guided information may be a terminal or a server, and may include any type of device.

[0545] In addition, the device 100a for generating imagery-guided information or the device 200a for providing imagery-guided information can generate a sleep analysis model for acquiring sleep state information corresponding to environmental sensing information by performing learning on one or more network functions through a learning dataset.

[0546] According to an embodiment of the present invention, the device 100a for generating image-guiding information or the device 200a for providing image-guiding information may be a server providing a cloud computing service.

[0547] More specifically, it may be a server that provides a cloud computing service that processes information on other computers connected to the Internet, not the user's computer.

[0548] A cloud computing service is a service that stores data on the Internet and allows users to access the necessary data and programs anytime and anywhere via an Internet connection without having to install them on their own computers, and allows users to easily share and transmit data stored on the Internet with simple operations and clicks.

[0549] Within the electronic device shown in FIG. 1h, steps may be performed: acquiring environmental sensing information; performing preprocessing on the acquired environmental sensing information; converting acoustic information contained in the preprocessed environmental sensing information into a spectrogram; generating sleep state information based on the converted spectrogram; and providing and feeding back image guidance information based on the generated sleep state information.

[0550] Alternatively, according to one embodiment of the present invention, the steps of acquiring environmental sensing information, performing preprocessing on the acquired environmental sensing information, converting acoustic information included in the preprocessed environmental sensing information into a spectrogram, and transmitting the converted spectrogram to a server may be performed within the electronic device, and when the server generates sleep state information through learning or inference based on the transmitted spectrogram, the electronic device may perform a step of receiving the sleep state information.

[0551] Alternatively, according to one embodiment of the present invention, if there is an electronic device and another electronic device acquires environmental sensing information, converts acoustic information included in the acquired environmental sensing information into a spectrogram, and generates sleep state information based on the converted spectrogram, a step may be performed in which the electronic device having environmental sensing and mood guidance information provision and feedback functions receives sleep state information from the other electronic device.

[0552] Here, the other electronic device may correspond to one or more other electronic devices other than the electronic device in which the environment sensing and image-guiding information generating and providing functions are implemented.

[0553] In the case where there are a plurality of other electronic devices, the steps of acquiring environmental sensing information, converting acoustic information contained in the environmental sensing information into a spectrogram, and generating sleep state information may be performed independently.

[0554] For example, according to one embodiment of the present invention, when there is an electronic device equipped with a function for providing imagery guidance information and feedback, another electronic device may acquire environmental sensing information, convert acoustic information included in the acquired environmental sensing information into a spectrogram, and transmit the converted spectrogram to a server. The server may then generate sleep state information based on the transmitted spectrogram, and the electronic device equipped with the function for providing imagery guidance information may receive the sleep state information generated by the server.

[0555] The various embodiments of the present invention described above are examples to illustrate that various operations such as acquiring environmental sensing information, preprocessing the environmental sensing information, converting spectrograms, and generating sleep state information do not necessarily occur within the same electronic device, but can occur in different devices, and that these operations can occur in chronological order, simultaneously, or independently and individually. Therefore, the present invention is not limited to the various embodiments described above.

[0556] [Electronic equipment 600]

[0557] FIG. 2b is a block diagram illustrating the configuration of an electronic device 600 according to the present invention.

[0558] The electronic device 600 shown in Fig. 2b may correspond to the device 100a for generating imagery-guiding information or the device 200a for providing imagery-guiding information, or may correspond to other devices. For example, the electronic device 600 shown in Fig. 2b may correspond to a user terminal, a device for generating and / or providing sleep images, or a device for generating and / or providing sleep content based on other user sleep information.

[0559] According to one embodiment of the present invention, as shown in FIG. 2b, the electronic device 600 may include, but is not limited to, a memory 610, an output unit 620, a processor 630, and an acquisition unit 640.

[0560] According to one embodiment of the present invention, an electronic device may be provided that includes a memory 610 in which mind-guiding information is recorded, an output unit 620 that outputs the recorded mind-guiding information, an acquisition unit 640 that acquires sleep state information from a user, means for transmitting the output mind-guiding information and the acquired sleep state information to a server, means for receiving the extracted user features if the server extracts user features based on the transmitted mind-guiding information and the transmitted sleep state information, and means for generating feature-based mind-guiding information based on the received user features.

[0561] According to one embodiment of the present invention, an electronic device may be provided that includes a memory 610 in which mind-guiding information is recorded, an output unit 620 that outputs the recorded mind-guiding information, an acquisition unit 640 that acquires sleep state information from a user, means for transmitting the output mind-guiding information and the sleep state information to a server, and means for the server to extract user features based on the transmitted mind-guiding information and the transmitted sleep state information, and, if the server generates feature-based mind-guiding information based on the extracted user features, receiving the generated feature-based mind-guiding information.

[0562] According to one embodiment of the present invention, an electronic device may be provided that includes a memory 610 in which mind-guiding information is recorded, an output unit 620 that outputs the recorded mind-guiding information, an acquisition unit 640 that acquires sleep state information from a user, a processor 630 that extracts user features based on the output mind-guiding information and the acquired sleep state information, means for transmitting the extracted user features to a server, and, if the server generates feature-based mind-guiding information based on the transmitted user features, means for receiving the generated feature-based mind-guiding information.

[0563] According to one embodiment of the present invention, a server device may be provided in which the model for generating and providing imagery guidance information is implemented, which extracts user features based on user sleep state information acquired through an acquisition unit of the electronic device and imagery guidance information output through an output unit of the electronic device, and generates feature-based imagery guidance information based on the extracted user features.

[0564] [Memory 610]

[0565] According to one embodiment of the present invention, the memory 610 may store a computer program having imagery guidance information based on a lookup table according to one embodiment of the present invention, imagery guidance information based on feature-based imagery guidance information, and user-related information input from the user, and the stored computer program may be read and driven by the processor 630.

[0566] Additionally, the memory 610 can store any type of information generated or determined by the processor 630 and any type of information received from a network.

[0567] The memory 610 may also store data related to the user's sleep.

[0568] For example, memory 610 may also provide temporary or permanent storage of input / output data.

[0569] Specifically, the memory 610 can temporarily or permanently store feature-based imagery guidance information generated or determined by the processor 630, but is not limited to this.

[0570] According to one embodiment of the present invention, memory 610 may store imagery guidance information.

[0571] The imagery guidance information stored in the memory 610 may be imagery guidance information based on a lookup table, or may be imagery guidance information based on feature-based imagery guidance information.

[0572] In addition, a step of preparing imagery induction information may be performed in memory 610, and the step of preparing imagery induction information may prepare imagery induction information based on a lookup table, or may prepare imagery induction information based on feature-based imagery induction information.

[0573] [Output section 620]

[0574] According to an embodiment of the present invention, the output unit 620 can output the recorded imagery guidance information.

[0575] For example, the output unit 620 may output the recorded imagery-guiding information as one or more of recorded imagery-guiding audio information, recorded imagery-guiding visual information, recorded imagery-guiding text information, and recorded imagery-guiding text audio information, or a combination of two or more of these.

[0576] According to an embodiment of the present invention, the output unit 620 may output feature-based image guidance information generated from the processor 630 based on the user's sleep state information.

[0577] For example, the feature-based imagery induction information output from the output unit 620 may be one or more of feature-based imagery induction audio information, feature-based imagery induction visual information, feature-based imagery induction text information, and feature-based imagery induction text audio information, or a combination of two or more of these, but is not limited to these.

[0578] In another example, the feature-based imagery induction information output from the output unit 620 may be one or more of feature-based time-series imagery induction audio information having an imagery induction scenario, feature-based time-series imagery induction visual information, feature-based time-series imagery induction text audio information, and feature-based time-series imagery induction text information, or a combination of two or more of these, but is not limited to these.

[0579] [Processor 630]

[0580] 2b, the processor 630 may read a computer program stored in the memory 610 to perform data processing for machine learning according to an embodiment of the present invention. According to an embodiment of the present invention, the processor 630 may perform calculations for neural network training.

[0581] The processor 630 can perform calculations for neural network training, such as processing input data for training using deep learning (DL), extracting features from the input data, calculating errors, and updating the weights of the neural network using backpropagation.

[0582] In addition, at least one of the CPU, GPGPU, and TPU of the processor 630 can process the learning of the network function.

[0583] For example, both the CPU and GPGPU can handle network function training and data classification using network functions.

[0584] In addition, in one embodiment of the present invention, the processors of multiple electronic devices 600 can be used together to process the learning of network functions and data classification using the network functions.

[0585] Furthermore, the computer program executed by the electronic device 600 according to an embodiment of the present invention may be a CPU, GPGPU, or TPU executable program.

[0586] According to an embodiment of the present invention, the processor 630 may read a computer program stored in the memory 610 to provide a sleep analysis model according to an embodiment of the present invention.

[0587] According to an embodiment of the present invention, the processor 630 may perform calculations to calculate feature-based imagery guidance information, which is information on the sequence of imagery guidance information, based on sleep state information.

[0588] Specifically, when the output unit 620 outputs imagery induction information based on a lookup table or feature-based imagery induction information, the user's features can be extracted based on the sleep state information acquired from the user through the imagery induction information.

[0589] According to an embodiment of the present invention, the processor 630 may perform calculations to train a sleep analysis model, thereby inferring sleep information related to the user's sleep quality based on the sleep analysis model.

[0590] According to an embodiment of the present invention, environmental sensing information acquired from a user in real time or periodically is input as an input value to the sleep analysis model, and data related to the user's sleep is output.

[0591] Such training of the sleep analysis model and inference based thereon may be performed by the apparatus 100a for generating image-guiding information or the apparatus 200a for providing image-guiding information.

[0592] That is, both learning and inference can be designed to be performed by the imagery guidance information generating device 100a or the imagery guidance information providing device 200a.

[0593] However, in other embodiments, learning may be performed by the device 100a for generating image-guiding information or the device 200a for providing image-guiding information, but inference may be performed by the user terminal 300.

[0594] According to one embodiment of the present invention, processor 630 may generally handle the overall operation of electronic device 600 .

[0595] The processor 630 processes signals, data, information, etc. input or output via the components detailed above, and can run applications stored in the memory 610 to provide or process appropriate information or functions to the user terminal.

[0596] According to one embodiment of the present invention, the processor 630 may obtain sleep state information of the user.

[0597] Acquiring sleep state information, according to one embodiment of the present invention, may involve acquiring or loading sleep state information stored in memory 610 .

[0598] In addition, sleep acoustic information can be acquired by receiving or loading data into another storage medium based on wired / wireless communication means from another electronic device or a separate processing module within the same electronic device.

[0599] According to one embodiment of the present invention, the processor 630 can extract features of the user based on the image-guiding information output from the output unit 620 and the user's sleep state information acquired from the acquisition unit 640.

[0600] The processor 630 can also generate feature-based image guidance information based on the extracted user features.

[0601] In addition, if information related to the user is recorded in the memory 610, the user's features can be extracted based on the recorded information.

[0602] [Acquisition part 640]

[0603] As shown in FIG. 2b, according to an embodiment of the present invention, an acquisition unit 640 of an electronic device 600 may acquire sleep state information from a user.

[0604] According to an embodiment of the present invention, if the acquiring unit 640 acquires sleep state information from a user in another electronic device, it may also perform a function of receiving the acquired sleep state information from the other electronic device.

[0605] [Sleep information]

[0606] According to an embodiment of the present invention, sleep information can be acquired from one or more sleep information sensor devices to achieve the objectives of the present invention. The sleep information may include user sleep acoustic information acquired in a non-invasive manner during the user's activity or sleep. The sleep information may also include user lifestyle information and user log data.

[0607] Meanwhile, in the present invention, sleep information may include environmental sensing information and user lifestyle information. The user lifestyle information may include information that affects the user's sleep. Specifically, the information that affects the user's sleep may include the user's age, gender, presence or absence of illness, occupation, sleep onset time, wake-up time, heart rate, electrocardiogram, and sleep duration. For example, if the user's sleep duration is shorter than the reference duration, it may affect the user's need for more sleep the next day. Conversely, if the user's sleep duration is sufficient than the reference duration, it may affect the user's need for even less sleep the next day.

[0608] [One or more sleep information sensor devices]

[0609] According to an embodiment of the present invention, the one or more sleep sensor devices may include a microphone module, a camera, and an illuminance sensor provided in the user terminal 300 .

[0610] For example, information related to the user's activities in a space may be acquired through a microphone module provided in the user terminal 300.

[0611] Furthermore, since the microphone module must be provided in the user terminal 300, which is relatively small in size, it may be configured as a micro-electromechanical system (MEMC).

[0612] [Environmental sensing information]

[0613] In an embodiment, environmental sensing information of the present invention may be acquired via the user terminal 300. The environmental sensing information may refer to sensing information acquired in a space where a user is located. The environmental sensing information may be sensing information acquired in relation to the user's activity or sleep in a non-contact manner.

[0614] According to one embodiment of the present invention, as shown in FIG. 1h, it may refer to, but is not limited to, sensing information acquired in the sleep sensing area 11a.

[0615] For example, the environmental sensing information may be sleep acoustic information acquired in a bedroom where the user sleeps. According to an embodiment, the environmental sensing information acquired through the user terminal 300 may be information that serves as a basis for acquiring the user's sleep state information in the present invention. For a specific example, sleep state information related to whether the user is before sleep, during sleep, or after sleep may be acquired through the environmental sensing information acquired in relation to the user's activity.

[0616] For another example, the environmental sensing information may include sounds generated by the user turning over in their sleep, sounds related to muscle movements, or sounds related to the user's breathing during sleep. The sleep sound information may refer to sound information related to the movement patterns and breathing patterns generated during the user's sleep. The environmental sensing information related to the user's activities in a space may be acquired via a microphone provided in the user terminal 300.

[0617] Alternatively, the environmental sensing information may include information about the user's breathing and movement. The user terminal 300 may include a radar sensor as a motion sensor. The user terminal 300 may generate a discrete waveform (respiratory information) corresponding to the user's breathing by signal processing the user's movement and distance measured through the radar sensor. Quantitative indicators related to sleep can be obtained based on the discrete waveform and movement.

[0618] The environmental sensing information may include measurements obtained through sensors that measure the temperature, humidity, and lighting level of the space the user is sleeping in. To this end, the user terminal 300 may be equipped with sensors that measure the temperature, humidity, and lighting level of the bedroom.

[0619] According to one embodiment of the present invention, the device 100a for generating imagery-guided information or the device 200a for providing imagery-guided information may acquire sleep state information based on environmental sensing information acquired through a microphone module configured with MEMS.

[0620] Specifically, the device 100a for generating imagery induction information or the device 200a for providing imagery induction information can convert unclearly acquired environmental sensing information containing a lot of noise into analyzable data, and can perform learning on an artificial neural network using the converted data.

[0621] According to one embodiment of the present invention, when pre-training of an artificial neural network is completed, the trained neural network can acquire sleep state information of a user based on a spectrogram acquired in response to sleep acoustic information.

[0622] Specifically, the trained neural network may be, but is not limited to, an artificial intelligence acoustic analysis model.

[0623] That is, when the device 100a for generating imagery-guiding information, the device 200a for providing imagery-guiding information, or the user terminal 300 acquires sleep acoustic information having a low signal-to-noise ratio, the device 100a can process the acquired sleep acoustic information into data suitable for analysis and process the processed data to provide sleep state information.

[0624] This eliminates the need for a microphone that contacts the user's body to capture clear sound, and allows sleep status to be monitored in a typical home environment simply by updating the software without having to purchase a separate additional device with a high signal-to-noise ratio, thereby providing increased convenience.

[0625] In FIG. 1d, the device 100a for generating image-guiding information is shown as a separate entity from the user terminal 300. However, according to an embodiment of the present invention, as shown in FIG. 1c, the device 100a for generating image-guiding information is included within the user terminal 300, and the functions of measuring sleep state and providing image-guiding information can be performed in a single integrated device.

[0626] Similarly, in FIG. 1e, the device 200a for providing image-guiding information is depicted as a separate entity from the user terminal 300, but according to an embodiment of the present invention, as shown in FIG. 1c, the device 200a for providing image-guiding information is included within the user terminal 300, and the functions of measuring sleep state and feeding back image-guiding information can be performed in a single integrated device.

[0627] The user terminal 300 may refer to any type of entity in a system having a mechanism for communicating with the computing device 100. For example, the user terminal 300 may include a personal computer (PC), a notebook computer, a mobile terminal, a smartphone, a tablet PC, an AI speaker, an AI TV, a wearable device, etc., and may include all types of terminals that can be connected to a wired / wireless network. The user terminal 300 may also include any server implemented by at least one of an agent, an application programming interface (API), and a plug-in. The user terminal 300 may also include an application source and / or a client application.

[0628] According to an embodiment of the present invention, the external server 20 may be a server that stores information on a plurality of training data for training a neural network. The plurality of training data may include, for example, health checkup information or sleep screening information. For example, the external server 20 may be at least one of a hospital server and an information server, and may be a server that stores information on a plurality of sleep multidimensional test records, electronic health records, electronic medical records, etc. For example, the sleep multidimensional test records may include information on the breathing and movement of a sleep screening subject during sleep and information on corresponding sleep diagnosis results (e.g., sleep stages, etc.). The information stored in the external server 20 may be used as training data, verification data, and test data for training the neural network of the present invention.

[0629] The computing device 100 of the present invention can receive health checkup in...

Claims

1. In a method for generating and providing sleep content based on user sleep information, providing a text input window on a display screen of the user terminal; a text transmission step of transmitting the input text to an external terminal when the text relating to the user's sleep mood, feeling, or memory of a dream is input through the text input window; receiving a sleep image or a sleep video corresponding to the text from the external device; providing the received sleep image or sleep video on the display screen; Including, A method for generating and providing sleep content based on user sleep information.

2. In a method for generating and providing sleep content based on user sleep information, a candidate group providing step of providing a candidate group of keywords related to the user's sleep mood, feeling, or memory of dreams on a display screen of the user terminal; a text transmitting step of transmitting text of the selected keyword candidate group to an external terminal when at least one of the keyword candidate group is selected; receiving a sleep image or a sleep video corresponding to the text from the external device; a sleep image or sleep video providing step of providing the received sleep image or sleep video on the display screen; Including, A method for generating and providing sleep content based on user sleep information.

3. In a method for generating and providing sleep content based on user sleep information, a receiving step of receiving text from a user terminal relating to the user's sleep mood, feelings, or memories of dreams; a sleep image or sleep video output step of inputting the text into a learning model stored in a memory and outputting a sleep image or sleep video corresponding to the text from the learning model; a sleep image or sleep video transmitting step of transmitting the output sleep image or sleep video to the user terminal or computing device; Including, A method for generating and providing sleep content based on user sleep information.

4. In a method for generating and providing sleep content based on user sleep information, A preparation stage in which imagery-guiding information is prepared; a preparation information providing step of providing the prepared image-guiding information to a user; acquiring sleep state information from a user; extracting features of the user based on the image-guiding information provided to the user and the sleep state information acquired from the user; generating feature-based image guidance information based on the extracted user features; Including, A method for generating and providing sleep content based on user sleep information.

5. The preparation step comprises: preparing the imagery-guiding information based on a look-up table; Including, The method of generating and providing sleep content based on user sleep information according to claim 4.

6. The preparation step comprises: preparing the imagery guidance information based on the feature-based imagery guidance information; Including, The method of generating and providing sleep content based on user sleep information according to claim 5.

7. The preparatory information providing step includes: providing one or more of prepared imagery-guiding audio information, prepared imagery-guiding visual information, prepared imagery-guiding text information, and prepared imagery-guiding text audio information, or providing a combination of two or more of these; Including, The method of generating and providing sleep content based on user sleep information according to any one of claims 4 to 6.

8. a generated information providing step of providing the generated feature-based image guidance information to a user; further comprising: The method of generating and providing sleep content based on user sleep information according to claim 4.

9. In a method for generating and providing sleep content based on user sleep information, an information preparation step of preparing information related to a user; an extraction step of extracting a user's feature based on the prepared information; generating feature-based image guidance information based on the extracted user features; Including, A method for generating and providing sleep content based on user sleep information.

10. The information preparation step includes: an input step of receiving information related to the user from the user; Including, The method of generating and providing sleep content based on user sleep information according to claim 9.

11. The information related to the user inputted from the user in the input step is: The keyword is one or more of the content selected by the swipe method, the text entered by the user, and the keyword selected by the user from the presented keywords, or a combination of two or more of these. The method of generating and providing sleep content based on user sleep information according to claim 10.

12. a generated information providing step of providing the generated feature-based image guidance information to a user; further comprising: The method of generating and providing sleep content based on user sleep information according to any one of claims 9 to 11.

13. The feature-based image guidance information provided in the generating information providing step is The information is one or more of feature-based imagery-guiding audio information, feature-based imagery-guiding visual information, feature-based imagery-guiding text information, and feature-based imagery-guiding text audio information, or a combination of two or more of these information. The method of generating and providing sleep content based on user sleep information according to claim 12.

14. In an electronic device, a memory in which mental imagery guidance information is recorded; an output unit that outputs the recorded imagery-guiding information; an acquisition unit that acquires sleep state information from a user; a processor for extracting features of a user based on the output image guidance information and the acquired sleep state information; Including, the processor generates feature-based imagery guidance information based on the extracted user features. electronic equipment.

15. In a method for generating and providing sleep content based on user sleep information, a sleep information acquiring stage of acquiring sleep information from one or more sleep information sensor devices (the sleep information includes sleep acoustic information of the user); generating one or more data arrays relating to the user's sleep based on the acquired sleep information; inputting the generated features related to the user's sleep into a content generating artificial intelligence; generating user sleep content based on the output of the content-generating artificial intelligence; Including, A method for generating and providing sleep content based on user sleep information.

16. The sleep information acquisition stage includes: a sleep information inferring step of inferring information about sleep using the user's sleep acoustic information as an input of a sleep information inference deep learning model; Including, The method of generating and providing sleep content based on user sleep information according to claim 15.

17. generating one or more data arrays relating to the user's sleep, generating one or more data arrays regarding the user's sleep based on the inferred sleep information; Including, The method of generating and providing sleep content based on user sleep information according to claim 16.

18. generating one or more data arrays relating to the user's sleep, generating one or more data arrays regarding the user's sleep by inputting the inferred sleep information into a large language model to generate one or more data arrays regarding the user's sleep; Including, The method of generating and providing sleep content based on user sleep information according to claim 17.

19. In a method for generating and providing sleep content based on user sleep information, A user keyword input step; generating base sentences using the input user keywords as inputs to a large-scale language model; a sleep sentence keyword refining step of selecting sleep sentence keywords based on the generated basic sentences; selecting a sleep content theme based on the selected text keywords; generating sleep content based on the selected sleep content theme; Including, A method for generating and providing sleep content based on user sleep information.

20. The sleep sentence keyword refining step includes: extracting sleep sentence keywords using the generated base sentences as inputs to a large-scale language model; Including, The method of claim 19, wherein the sleep content is generated and provided based on the user's sleep information.

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