Sleep environment control system using artificial intelligence sleep analysis in apartment building and method of the same

Abstract

The sleep environment control system and method according to the present invention have the advantage of creating a customized sleep environment by analyzing a user's sleep pattern using artificial intelligence in the bedroom of a resident of a multi-unit dwelling and controlling the operation of sleep environment facilities that affect sleep environment factors, including temperature, humidity, illuminance, and sound in the bedroom, differently according to the user's sleep pattern.

Description

Technology Field

[0001] The present invention relates to a sleep environment control system and method for multi-unit housing utilizing artificial intelligence sleep analysis. More specifically, it relates to a sleep environment control system and method for multi-unit housing utilizing artificial intelligence sleep analysis that analyzes a user's sleep pattern using artificial intelligence and controls the operation of indoor environmental facilities according to the user's sleep pattern to provide a user-customized deep sleep environment. Background Technology

[0002] Sleeponomics is a portmanteau of "sleep" and "economics," referring to a growing industry as modern people begin spending large sums of money on quality sleep. As the amount of sleep modern people get has decreased significantly compared to the past and interest in health has increased, interest in Sleeponomics is growing as social spending on achieving quality sleep—even if it is short—is rising.

[0003] Recently, there has been active technological development regarding bedding and applications for analyzing user sleep, but there are limitations in providing customized sleep solutions. Prior art literature

[0004] Korean Registered Patent No. 10-2658000 The problem to be solved

[0005] The objective of the present invention is to provide a sleep environment control system and method for multi-unit housing utilizing artificial intelligence sleep analysis that can further improve the quality of sleep for users of multi-unit housing. means of solving the problem

[0006] A sleep environment control system for a multi-unit dwelling utilizing artificial intelligence sleep analysis according to the present invention comprises: a plurality of sleep environment facilities based on the Internet of Things (IoT) that are installed in a bedroom of the multi-unit dwelling and control sleep environment factors including temperature, humidity, illuminance, and sound of the bedroom; a sleep analysis module that recognizes a user lying in a pre-designated position in the bedroom during a pre-set sleep test period, periodically collects biosignals regarding the user's sleep state, and analyzes sleep patterns including sleep duration, sleep depth, and periodic changes according to the user and the time of sleep; and a sleep environment control module that controls each of the sleep environment facilities according to the sleep pattern during the sleep test period using a plurality of operating conditions, evaluates a sleep score for each of the operating conditions, sets an operating condition in which the sleep score is greater than or equal to a pre-set deep sleep score as a deep sleep condition, and controls the sleep environment facilities to operate according to the deep sleep condition when the sleep test period ends.

[0007] The above sleeping environment facilities may include at least some of a heating and cooling facility for controlling the temperature of the bedroom, a humidity control facility for controlling the humidity of the bedroom, a lighting facility for controlling the lighting of the bedroom, and an acoustic facility for controlling the sound of the bedroom.

[0008] The sleep analysis module may include a biosignal measurement unit that measures a user's biosignal and an artificial intelligence unit that analyzes the sleep pattern through an artificial intelligence algorithm according to changes in the biosignal measured by the biosignal measurement unit.

[0009] The sleep analysis module divides the time from the user's sleep onset to the time of waking into multiple sleep stages according to the sleep pattern, and the sleep environment control module can control the operating conditions of the sleep environment facilities differently for each sleep stage.

[0010] The sleep analysis module determines the time for sleep based on the outdoor temperature, analyzes the sleep pattern based on the time for sleep, and the sleep environment control module can derive multiple different deep sleep conditions based on the time for sleep.

[0011] The above biosignals may include at least some of the user's heart rate, respiratory rate, body temperature, sound, and movement.

[0012] The sleep environment control module sets the operating conditions of the sleep environment facilities to a preset default value for each sleep stage during the sleep test period, evaluates the sleep score when operating at the default value, and if the sleep score is less than the deep sleep score, can re-evaluate the sleep score while increasing or decreasing the operating conditions from the default value.

[0013] It may further include a user interface configured to communicate with the sleep environment control module, and configured to display the deep sleep conditions set by the sleep environment control module or to receive the deep sleep conditions from the user.

[0014] The sleep analysis module and the sleep environment control module can distinguish and recognize users based on user information received from the user.

[0015] The above sleep analysis module can collect the user's biometric information to distinguish and recognize the user.

[0016] A sleep environment control system for a multi-unit dwelling utilizing artificial intelligence sleep analysis according to another aspect of the present invention comprises: a plurality of sleep environment facilities based on the Internet of Things (IoT) that are installed in a bedroom of the multi-unit dwelling to control sleep environment factors including temperature, humidity, illuminance, and sound of the bedroom; and a sleep analysis module that recognizes a user lying in a pre-designated position in the bedroom during a pre-set sleep test period, periodically collects biosignals regarding the user's sleep state, and analyzes sleep patterns including sleep duration, sleep depth, and periodic changes according to the user and the time of sleep. The sleep environment control module includes a plurality of operating conditions for each of the sleep environment facilities according to the sleep pattern during the sleep test period, evaluates a sleep score for each of the operating conditions, sets an operating condition in which the sleep score is greater than or equal to a preset deep sleep score as a deep sleep condition, and controls the sleep environment facilities to operate according to the deep sleep condition when the sleep test period ends; the sleep environment facilities include at least some of a heating and cooling facility for controlling the temperature of the bedroom, a humidity control facility for controlling the humidity of the bedroom, an illuminance facility for controlling the illuminance of the bedroom, and an acoustic facility for controlling the sound of the bedroom; the sleep analysis module includes a biosignal measurement unit for measuring a user's biosignal and an artificial intelligence unit that analyzes the sleep pattern through an artificial intelligence algorithm according to changes in the biosignal measured by the biosignal measurement unit; the sleep environment control module sets the operating conditions of the sleep environment facilities to a preset default value for each sleep stage during the sleep test period, evaluates the sleep score when operating at the default value, and if the sleep score is less than the deep sleep score, can re-evaluate the sleep score while increasing or decreasing the operating conditions from the default value.

[0017] A method for controlling a sleep environment in a multi-unit dwelling using artificial intelligence sleep analysis according to the present invention comprises: a sleep analysis step in which a sleep analysis module periodically collects biosignals regarding the sleep state of a user using a bedroom during a preset sleep test period, analyzes the user's sleep pattern, and stores it; a sleep condition setting step in which a sleep environment control module controls the operating conditions of a plurality of sleep environment facilities that regulate sleep environment factors including temperature, humidity, illuminance, and sound of the bedroom during the sleep test period differently, evaluates a sleep score according to the sleep pattern for each operating condition, derives an operating condition in which the sleep score is greater than or equal to a preset deep sleep score, and sets it as a deep sleep condition for each user; and a sleep environment control step in which, after the sleep test period ends, the sleep environment control module controls the sleep environment facilities to operate according to the deep sleep condition during the user's sleep.

[0018] It may further include a user recognition step that recognizes the user by measuring the user's biometric information.

[0019] The above-mentioned deep sleep condition setting step sets the operating conditions of the sleep environment facilities to a preset default value for each sleep stage during the sleep test period, evaluates the sleep score when operating at the default value, and if the sleep score is less than the deep sleep score, can re-evaluate the sleep score while increasing or decreasing the operating conditions from the default value. Effects of the invention

[0020] The sleep environment control system and method according to the present invention have the advantage of creating a customized sleep environment by analyzing a user's sleep pattern using artificial intelligence in the bedroom of a resident of a multi-unit dwelling and controlling the operation of sleep environment facilities that affect sleep environment factors, including temperature, humidity, illuminance, and sound in the bedroom, differently according to the user's sleep pattern. Brief explanation of the drawing

[0021] FIG. 1 is a schematic diagram showing a sleep environment control system for a multi-unit dwelling utilizing artificial intelligence sleep analysis according to an embodiment of the present invention. FIG. 2 is a block diagram showing the control configuration of a sleep environment control system for a multi-unit dwelling utilizing artificial intelligence sleep analysis according to an embodiment of the present invention. FIG. 3 is a flowchart illustrating a method for controlling the sleep environment of a multi-unit dwelling using artificial intelligence sleep analysis according to an embodiment of the present invention. Figure 4 shows an example of sleep conditions regarding temperature. Figure 5 shows an example of sleep conditions regarding illuminance. Specific details for implementing the invention

[0022] Hereinafter, embodiments of the present invention will be described with reference to the attached drawings.

[0023] FIG. 1 is a schematic diagram showing a sleep environment control system for a multi-unit dwelling utilizing artificial intelligence sleep analysis according to an embodiment of the present invention. FIG. 2 is a block diagram showing the control configuration of a sleep environment control system for a multi-unit dwelling utilizing artificial intelligence sleep analysis according to an embodiment of the present invention.

[0024] Referring to FIGS. 1 and 2, a sleep environment control system for a multi-unit dwelling utilizing artificial intelligence sleep analysis according to an embodiment of the present invention includes a plurality of sleep environment facilities (10), a sleep analysis module (20), a sleep environment control module (30), and a user interface (40).

[0025] The above sleep environment equipment (10) is installed in a bedroom of a multi-unit dwelling and is equipment for creating a sleep environment by controlling sleep environment factors that may affect sleep. The above sleep environment factors are described as including the temperature, humidity, illuminance, and sound of the bedroom, but are not limited thereto and can be varied and applied as long as there are other factors that may affect sleep.

[0026] The above sleep environment facilities (10) include facilities that can communicate based on the Internet of Things (IoT) and whose operation can be controlled by the sleep environment control module (30).

[0027] In this embodiment, the sleep environment equipment (10) is described by example as including a heating and cooling system (11) for controlling the temperature of the bedroom, a humidity control system (12) for controlling the humidity of the bedroom, an illuminance system (13) for controlling the illuminance of the bedroom, and an acoustic system (14) for controlling the sound of the bedroom. The heating and cooling system (11) may include a boiler, an air conditioner, etc. The humidity control system (12) may include a humidifier, a dehumidifier, etc. The illuminance system (13) may include lighting provided in the bedroom and an electric curtain installed in the bedroom. The acoustic system (14) may include a speaker, etc., capable of providing noise levels, brainwave-inducing sounds, natural sounds, music, etc. Although the sleep environment equipment (10) is described by example as being installed in a built-in manner in the apartment building, it is not limited thereto and can be applied if the user installs it individually and connects it for communication. In addition, the heating and cooling equipment (11) and the humidity control equipment (12) can, of course, be provided as a single unit. Furthermore, it is also possible to include an air purifier (not shown) for controlling the comfort level of the bedroom.

[0028] The sleep analysis module (20) is a module for periodically measuring and collecting the user's biosignals while the user is sleeping, and for monitoring and analyzing the sleep patterns of each user. The biosignals may include heart rate, respiratory rate, body temperature, movement, posture, and sound.

[0029] The above sleep pattern may include sleep duration, sleep depth, and periodic changes. The above sleep pattern is measured differently depending on the user, the time of sleep, and the operating conditions of the sleep environment equipment. The above time of sleep is described by example as spring, summer, autumn, seasons, weekdays, weekends, day, night, etc.

[0030] The sleep analysis module (20) can analyze sleep patterns according to the user and the time of sleep during a pre-set sleep test period, and can also periodically analyze sleep patterns while the sleep environment control facilities (10) are controlled according to the deep sleep conditions described below after the end of the sleep test period.

[0031] The above sleep analysis module (20) includes a biosignal measurement unit (21) and an artificial intelligence unit (22).

[0032] The above biosignal measuring unit (21) may include smart bedding such as a smart mattress and smart pillow provided in the bedroom, and wearable devices such as a smart watch and health band worn by the user. However, it is not limited to these, and any sensor capable of measuring the user's biosignal can be applied in various ways.

[0033] The artificial intelligence unit (22) analyzes the sleep patterns of each user through a preset artificial intelligence algorithm based on changes in the biosignal measured by the biosignal measuring unit (21).

[0034] The artificial intelligence unit (22) divides the time from the time the user falls asleep until the time they wake up into a plurality of sleep stages according to the sleep pattern.

[0035] In this embodiment, the sleep stages are described by example as being divided into a sleep onset stage, an intermediate sleep stage, a deep sleep stage, and an awakening stage. The artificial intelligence unit (22) can divide the sleep stages into the user's total sleep time. For example, if the user sleeps for a total of 7 hours from 11 PM to 6 AM, the total sleep time of 7 hours can be divided into a sleep onset stage, in which the user enters sleep from 11 PM until a first time point after a first set time has elapsed; an intermediate sleep stage, in which sleep is maintained from the first time point until a second time point after a second set time has elapsed; a deep sleep stage, in which sleep continues from the second time point until a third time point after a third set time has elapsed; and an awakening stage, in which the user wakes up from sleep from the third time point until a fourth time point after a fourth set time has elapsed. The first, second, third, and fourth set times may be set differently depending on the user, the time of sleep, and the temperature, humidity, light intensity, and sound of the bedroom. However, this is not limited thereto, and the number or duration of the sleep stages can be varied and applied.

[0036] For each of the above sleep stages, the operation of the sleep environment control facilities is controlled differently for the temperature, humidity, illumination, and sound of the bedroom.

[0037] In addition, the sleep analysis module (20) can also collect the user's biometric information to distinguish and recognize multiple users. The biometric information may include the user's height, weight, body shape, etc., and when the user lies down on the smart bedding, the user's biometric information can be collected to identify the user.

[0038] The sleep environment control module (30) may be provided in the bedroom, and of course, may also be provided in a server or terminal that is capable of communicating with the sleep analysis module (20) and the sleep environment equipment (10). The sleep environment control module (30) may also provide a sleep environment control app to a user terminal or wall pad, etc., for displaying the user's sleep pattern and controlling the sleep environment equipment (10).

[0039] The above sleep environment control module (30) controls the operating conditions of the sleep environment facilities (10) differently during the sleep test period to evaluate the sleep score for each operating condition, and derives the operating condition in which the sleep score is greater than or equal to a preset deep sleep score as the optimal condition for deep sleep and sets it as the deep sleep condition for the user.

[0040] The sleep environment control module (30) can, of course, derive different deep sleep conditions for the same user depending on the time of sleep, and set and store the deep sleep conditions according to the time of sleep as multiple sleep modes. For example, deep sleep conditions when the time of sleep is spring, weekday, and daytime nap can be set as the first sleep mode, and deep sleep conditions when it is spring, weekend, and nighttime sleep can be set as the second sleep mode, etc. The multiple sleep modes can be manually selected by the user through the user interface (40).

[0041] In addition, the sleep environment control module (30) controls the sleep environment facilities (10) to operate according to the deep sleep conditions when the user sleeps after the sleep test period has ended.

[0042] The above user interface (40) is configured to communicate with the sleep environment control module (30) and can display the sleep conditions set by the sleep environment control module (30) through the sleep environment control app, receive input from the user to modify the sleep conditions, receive user information from the user, receive manual input of the sleep conditions desired by the user, or receive input from the user to select one of the plurality of sleep modes.

[0043] The above user interface (40) may include a wall pad, smartphone, smart watch, etc. provided in the bedroom.

[0045] The method for controlling the sleep environment of a multi-unit dwelling using artificial intelligence sleep analysis according to the embodiment of the present invention configured as described above is as follows.

[0046] FIG. 3 is a flowchart illustrating a method for controlling the sleep environment of a multi-unit dwelling using artificial intelligence sleep analysis according to an embodiment of the present invention.

[0047] Referring to FIG. 3, the sleep environment control method of a multi-unit dwelling utilizing artificial intelligence sleep analysis according to the present invention includes a user recognition step (S1), a sleep analysis step (S2), a deep sleep condition setting step (S3), and a sleep environment control step (S4).

[0048] The above user recognition step (S1) is a step of determining whether the user using the sleep environment control system is a new user or a previously registered user.

[0049] First, in the case of a new user who is using the sleep environment control system for the first time, the biosignal measurement unit (21) measures the new user's biosignal information, assigns an ID based on the biosignal information, and can register the user as new user information. However, this is not limited thereto, and it is also possible for the new user to directly input user information through the user interface (40) to be assigned an identification number or ID.

[0050] Meanwhile, when a registered user who has previously registered with the sleep environment control system uses the sleep environment control system, the biometric information of the registered user is measured, and the measured biometric information is compared with user information previously stored in the database (not shown) to distinguish and recognize which of the registered users it is. However, this is not limited thereto, and it is also possible for the registered user to directly input their ID and sleep mode using the user interface (40). The ID is pre-assigned, and the sleep mode is a mode stored as a deep sleep condition derived from pre-analyzing the sleep pattern of the registered user.

[0051] The above bio information is explained as being measured using the above bio signal measuring unit (21).

[0052] For example, if the above biosignal measuring unit (21) is a smart bedding, when a user lies down on the smart bedding, biosignal information including at least some of the user's height, weight, body shape, and posture can be measured to determine whether the user is a new user or a registered user. If the user's biosignal information measured by the above biosignal measuring unit (21) is not stored in the database, the user can be registered as a new user.

[0053] As described above, when a user is recognized, the sleep analysis step (S2) is performed.

[0054] The following is an example explaining the analysis of a new user's sleep patterns.

[0055] The sleep analysis step (S2) described above is a step of periodically measuring and collecting biosignals regarding the sleep state of a user lying in a predetermined location in the bedroom, and analyzing and storing the user's sleep pattern based on the biosignals. Here, the designated location refers to a location equipped with the biosignal measuring unit (21) capable of measuring the user's biosignals.

[0056] In the above sleep analysis step (S2), the sleep time is determined based on the outdoor environment, such as the outdoor temperature, and sleep patterns that vary according to the sleep time can be analyzed separately for the user as well. Here, the sleep time can be classified into spring, summer, autumn, seasons, weekdays, weekends, day, night, etc.

[0057] The above sleep analysis step (S2) includes a biosignal collection process (S2-1) and a sleep pattern analysis process (S2-2).

[0058] The above biosignal collection process (S2-1) is a process in which the biosignal measurement unit (21) periodically measures and collects the user's biosignals during the sleep test period. Here, the biosignals may include heart rate, respiratory rate, body temperature, movement, posture, and sound.

[0059] The above sleep pattern analysis process (S2-2) is a process in which the artificial intelligence unit (22) analyzes the sleep pattern of each user using the artificial intelligence algorithm according to the change in the biosignal measured by the biosignal measurement unit (21).

[0060] The artificial intelligence unit (22) divides the user's sleep pattern into multiple sleep stages from the time of falling asleep to the time of waking up.

[0061] In this embodiment, the sleep stages are described by example as being divided into a sleep onset stage, a mid-sleep stage, a deep sleep stage, and an awakening stage. Here, the number or duration of the sleep stages may vary depending on the user or the time of sleep.

[0062] Meanwhile, during the above sleep test period, the sleep environment control module (30) performs the above deep sleep condition setting step (S3).

[0063] The above-mentioned deep sleep condition setting step (S3) includes a sleep score evaluation process (S3-1) and a deep sleep condition derivation process (S3-2).

[0064] The above sleep score evaluation process (S3-1) is a process in which the sleep environment control module (30) controls the operating conditions of the sleep environment equipment (10), which controls sleep environment factors including temperature, humidity, light intensity, and sound of the bedroom for each sleep stage during the sleep test period, differently, and evaluates the sleep score for each operating condition.

[0065] For example, the sleep environment control module (30) sets the operating conditions of the sleep environment facilities (10) to a preset default value for each sleep stage, and evaluates the user's sleep score while the sleep environment facilities (10) are operating at the default value. The default value is set differently for each sleep stage and is set differently for each sleep environment facility (10).

[0066] That is, if the default value of the bedroom illumination is set to 150 lux during the sleep onset stage among the above sleep stages, the user's sleep score can be evaluated while gradually decreasing the bedroom illumination to 40 lux during the sleep onset stage. Additionally, if the default value of the bedroom sound is set to 40 dB during the sleep onset stage, the user's sleep score can be evaluated while gradually decreasing or maintaining the bedroom sound during the sleep onset stage. Furthermore, it is also possible to evaluate the user's sleep score by playing brainwave-inducing sounds, including beta, alpha, theta, and delta waves, while varying the sound, or by playing a mixture of brainwave-inducing sounds and natural sounds. Similarly, among the above sleep stages, default values ​​are set for stages other than the sleep onset stage, and changes in the sleep score can be evaluated while increasing or decreasing the default values ​​for each sleep stage.

[0067] The above-mentioned deep sleep condition derivation process (S3-2) is a process of deriving and setting an operating condition as the deep sleep condition of the user such that the sleep score measured in the above-mentioned sleep score evaluation process (S3-1) is greater than or equal to the above-mentioned deep sleep score.

[0068] The sleep environment control module (30) can derive different deep sleep conditions for the same user according to the sleep periods and set and store the deep sleep conditions according to the sleep periods as multiple sleep modes. That is, the deep sleep conditions can be set differently depending on the user, the sleep period, and the temperature, illumination, humidity, sound, etc. of the bedroom. For example, the deep sleep conditions may be derived as deep sleep conditions for the temperature of the bedroom, deep sleep conditions for the humidity of the bedroom, deep sleep conditions for the illumination of the bedroom, and deep sleep conditions for the sound of the bedroom, and each deep sleep condition may be derived differently depending on spring, summer, autumn, winter, daytime sleep, nighttime sleep, etc. For example, when the sleep period is spring, weekday, and daytime, the sleep conditions regarding temperature, illuminance, humidity, and sound can be integrated and stored as a first sleep mode, and when the sleep period is spring, weekend, and nighttime, the sleep conditions regarding temperature, illuminance, humidity, and sound can be integrated and set as a second sleep mode, etc. The above multiple sleep modes can be manually selected by the user through the user interface (40). In addition, the sleep conditions regarding illuminance of the bedroom include illuminance, color temperature, dimming value, etc. The sleep conditions regarding sound include noise level, brainwave-inducing sound, other sounds, etc.

[0069] When the user's deep sleep condition is derived in the above deep sleep condition derivation process (S3-2), the sleep modes for the user's deep sleep condition are stored in the above database (not shown).

[0070] As described above, sleep patterns for each user are analyzed during a pre-set sleep test period, and the user's deep sleep conditions can be derived based on the sleep patterns.

[0071] When a deep sleep condition is derived for each user, the sleep environment control step (S4) can be performed in which the operation of the sleep environment facilities (10) is controlled according to the deep sleep condition during the user's sleep.

[0072] Figure 4a shows an example of sleep conditions regarding temperature during weekday night sleep in spring, and Figure 4b shows an example of sleep conditions regarding temperature during night sleep in summer.

[0073] Figure 5a shows an example of sleep conditions for summer light intensity, and Figure 5b shows an example of sleep conditions for winter light intensity.

[0074] Comparing Figure 4 and Figure 5, it can be seen that the sleep stages for temperature and illuminance are set differently.

[0075] The above sleep environment control step (S4) is a step of controlling the sleep environment facilities (10) to operate according to the derived deep sleep conditions when the user sleeps, after the above sleep test period has ended and the above deep sleep conditions have been derived.

[0076] The above sleep environment control step (S4) may be automatically performed by detecting when the user wants to sleep lying down in a pre-designated position in the bedroom, or it may be performed when the user directly inputs the desired sleep mode into the user interface (40).

[0077] Meanwhile, the sleep mode including the above-mentioned deep sleep conditions can be displayed through the user interface (40) so that the user can check it. In addition, it is also possible for the user to manually input and adjust some of the deep sleep conditions displayed on the user interface (40).

[0078] In addition, even after the above sleep test period has ended, the user's sleep patterns can be periodically analyzed to adjust the conditions for deep sleep according to the user's frequently changing sleep patterns.

[0079] As described above, the sleep environment control system according to the present invention has the advantage of creating a customized sleep environment for the user by using artificial intelligence to monitor and analyze the user's sleep pattern in the bedroom of a resident of a multi-unit dwelling, and by controlling the operation of the sleep environment equipment (10), including the heating and cooling equipment (11), humidity control equipment (12), lighting equipment (13), and sound equipment (14), which are built into the bedroom or other room according to the user's sleep pattern.

[0080] Accordingly, in the present invention, since the sleep environment facilities (10) can be controlled to suit different sleep patterns for each user, the user can sleep in an optimal sleep environment.

[0082] The present invention has been described with reference to the embodiments illustrated in the drawings, but this is merely illustrative, and those skilled in the art will understand that various modifications and equivalent alternative embodiments are possible therefrom. Accordingly, the true technical scope of protection of the present invention should be determined by the technical spirit of the appended claims. Explanation of the symbols

[0083] 10: Sleep Environment Equipment 20: Sleep Analysis Module 30: Sleep environment control module 40: User interface

Claims

Claim 1 It includes a plurality of sleep environment facilities based on the Internet of Things (IoT) that are installed in a bedroom of a multi-unit dwelling and regulate sleep environment factors including temperature, humidity, illuminance, and sound of the bedroom; a sleep analysis module that recognizes a user lying in a pre-designated position in the bedroom during a pre-set sleep test period, periodically collects biosignals regarding the user's sleep state, and analyzes sleep patterns including sleep duration, sleep depth, and periodic changes according to the user and the time of sleep; and a sleep environment control module that controls each of the sleep environment facilities according to the sleep pattern during the sleep test period using multiple operating conditions, evaluates a sleep score for each operating condition, sets an operating condition where the sleep score is greater than or equal to a pre-set deep sleep score as a deep sleep condition, and controls the sleep environment facilities to operate according to the deep sleep condition when the sleep test period ends. The sleep analysis module includes a biosignal measurement unit that measures the user's biosignals and an artificial intelligence unit that analyzes the sleep pattern through an artificial intelligence algorithm according to changes in the biosignals measured by the biosignal measurement unit. The sleep analysis module determines the time of sleep based on the outdoor temperature, analyzes the sleep pattern according to the time of sleep, and the sleep environment control The module is a sleep environment control system for multi-unit housing utilizing artificial intelligence sleep analysis, which derives multiple different deep sleep conditions according to the sleep period. Claim 2 A sleep environment control system for a multi-unit dwelling utilizing artificial intelligence sleep analysis, wherein the sleep environment facilities include at least some of a heating and cooling facility for controlling the temperature of the bedroom, a humidity control facility for controlling the humidity of the bedroom, an illuminance facility for controlling the illuminance of the bedroom, and an acoustic facility for controlling the sound of the bedroom. Claim 3 delete Claim 4 A sleep environment control system for an apartment building utilizing artificial intelligence sleep analysis, wherein, in claim 1, the sleep analysis module divides the time from the user's falling asleep to the time of waking up into a plurality of sleep stages according to the sleep pattern, and the sleep environment control module controls the operating conditions of the sleep environment facilities differently for each sleep stage. Claim 5 delete Claim 6 A sleep environment control system for an apartment building utilizing artificial intelligence sleep analysis, wherein the biosignal includes at least some of the user's heart rate, respiratory rate, body temperature, sound, and movement. Claim 7 A sleep environment control system for a multi-unit dwelling utilizing artificial intelligence sleep analysis according to claim 4, wherein the sleep environment control module sets the operating conditions of the sleep environment facilities to a preset default value for each sleep stage during the sleep test period, evaluates the sleep score when operating with the default value, and if the sleep score is less than the deep sleep score, re-evaluates the sleep score while increasing or decreasing the operating conditions from the default value. Claim 8 A sleep environment control system for an apartment building utilizing artificial intelligence sleep analysis, wherein, in claim 4, the system further comprises a user interface configured to communicate with the sleep environment control module, and configured to display the deep sleep conditions set by the sleep environment control module or to receive the deep sleep conditions from a user. Claim 9 A sleep environment control system for a multi-unit dwelling utilizing artificial intelligence sleep analysis, wherein the sleep analysis module and the sleep environment control module distinguish and recognize users according to user information received from a user. Claim 10 In claim 1, the sleep analysis module collects biometric information of a user and distinguishes and recognizes the user, thereby forming a sleep environment control system for an apartment building utilizing artificial intelligence sleep analysis. Claim 11 delete Claim 12 A sleep analysis module periodically collects biosignals regarding the sleep state of a user using a bedroom during a preset sleep test period, analyzes and stores the user's sleep pattern, and divides the sleep into multiple sleep stages from the time of falling asleep to the time of waking up according to the sleep pattern; a sleep environment control module controls the operating conditions of multiple sleep environment facilities that regulate sleep environment factors including temperature, humidity, illuminance, and sound of the bedroom during the sleep test period differently, evaluates a sleep score according to the sleep pattern for each operating condition, derives an operating condition in which the sleep score is greater than or equal to a preset deep sleep score, and sets it as a deep sleep condition for each user; and a sleep environment control module controls the sleep environment facilities to operate according to the deep sleep condition when the user sleeps after the sleep test period ends, wherein the sleep analysis module includes a biosignal measurement unit that measures the user's biosignals and an artificial intelligence unit that analyzes the sleep pattern through an artificial intelligence algorithm according to changes in the biosignals measured by the biosignal measurement unit, and wherein the sleep analysis module determines the time of sleep based on the outdoor temperature, analyzes the sleep pattern according to the time of sleep, and the sleep An environment control module is a method for controlling the sleep environment of an apartment building using artificial intelligence sleep analysis, which derives multiple different deep sleep conditions according to the sleep period. Claim 13 delete Claim 14 A method for controlling a sleep environment in a multi-unit dwelling using artificial intelligence sleep analysis, wherein the step of setting deep sleep conditions involves setting the operating conditions of the sleep environment facilities to a preset default value for each of the sleep stages during the sleep test period, evaluating a sleep score when operating at the default value, and, if the sleep score is less than the deep sleep score, re-evaluating the sleep score while increasing or decreasing the operating conditions from the default value.

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