Intelligent comprehensive environment regulation and control method based on sleep aiding

Abstract

The invention belongs to the field of intelligent environment comprehensive regulation and control, and particularly discloses and provides an intelligent environment comprehensive regulation and control method based on sleep aiding, which comprises the following steps: firstly, according to the heart rate and skin resistance of a user, evaluating the stability of a sleep state, automatically adjusting the brightness and color temperature of light, and creating a suitable sleep atmosphere; secondly, determining the temperature and humidity of the preference environment by analyzing the longest sleep time, the sleep time and the number of times of waking up at night in the historical sleep data of the user, and intelligently regulating and controlling the environment to match the temperature and humidity of the preference environment of the user. And finally, the system recommends a suitable music type according to the environmental noise type, and accurately recommends sleep music based on preference feedback of the user for each piece of music. Meanwhile, environmental noise decibel is monitored in real time, music volume is dynamically adjusted, harmonious coexistence of music and environmental noise is ensured, a more comfortable and quiet sleep environment is created for the user, and the sleep quality of the user is improved in multiple dimensions.

Description

Technical Field

[0001] The present invention belongs to the field of intelligent environment comprehensive regulation and control, and relates to an intelligent environment comprehensive regulation and control method based on sleep aid. Background Art

[0002] In modern society, with the accelerated pace of life and the increase in work pressure, good sleep quality has become the focus of more and more people. However, many factors such as environmental noise, light, temperature, humidity and personal psychological state will affect people's sleep quality. In order to deal with these problems, traditional sleep aids such as drugs and natural therapies have certain effects, but they often have side effects, inconvenient operation or short-lasting effects.

[0003] For example, a Chinese patent with publication number CN112107771A discloses a sleep-aid control method, system and device based on photoelectric detection, including obtaining the user's photoelectric volumetric pulse wave signal; the photoelectric volumetric pulse wave signal is measured by a photoelectric sensor set on a sleep pillow through contact with the user's neck; the user's heart rate is calculated by the photoelectric volumetric pulse wave signal; the set heart rate range of the heart rate is determined according to the user's height and weight; the music in the corresponding type of music library is called and played based on the heart rate setting range; one heart rate setting range corresponds to one type of music library; the user's sleep state is determined by the heart rate; the sleep state includes wakefulness, light sleep and deep sleep; the music is played and stopped by the sleep state. The present invention can realize the automatic and accurate selection of sleep-aid music and the automatic stop of music playback.

[0004] The above existing technologies have the following problems: 1. The existing technologies mainly focus on regulating the environment according to the real-time environment and user needs when the user is sleeping, thereby helping the user to fall asleep faster, but fail to combine the user's historical sleep data, and thus cannot use historical data to understand the changes in the user's sleep quality under different sleep data (sleep time, sleep duration and number of awakenings at night), resulting in the inability to accurately adjust environmental parameters to promote better sleep, and thus cannot provide users with more accurate and personalized sleep support, thereby reducing the user's sleep quality and quality of life.

[0005] 2. Failure to match ambient noise with the type of music and adjust the volume of music according to the decibel of ambient noise. When the ambient noise does not match the type of music, users may feel uncomfortable or irritated. For example, strong noise accompanied by soft music may not have the desired soothing effect, but instead increase the user's anxiety. If the music volume cannot be adjusted in real time according to the decibel of ambient noise, a volume that is too low may not effectively cover up the noise, while a volume that is too high may become a new source of interference and even damage the user's hearing health. Summary of the invention

[0006] In view of this, in order to solve the problems raised in the above background technology, a comprehensive intelligent environment control method based on sleep aid is proposed.

[0007] The purpose of the present invention can be achieved through the following technical solutions: The present invention provides a comprehensive intelligent environment control method based on sleep aid, including: S1, user sleep state level judgment: collecting the heart rate and skin resistance of each user at each set monitoring time point, and analyzing the sleep state stability index of each user.

[0008] S2. Determine the sleep state level: Determine the sleep state level of each user according to the sleep state stability index of each user, and adjust the brightness and color temperature of the light in the environment corresponding to the user based on the sleep state level.

[0009] S3. Environmental temperature and humidity control: Extract the waking time, number of waking up at night, duration of falling asleep and time of sleeping of each user on each set historical day from the historical sleep data of each user, obtain the temperature and humidity of the sleeping environment on the historical days corresponding to the actual longest sleep time, shortest duration of falling asleep and least number of waking up at night of each user, determine the preferred temperature and humidity of the sleeping environment of each user, and then control the temperature and humidity of the sleeping environment of each user.

[0010] The preferred sleeping environment temperature and humidity of each user is determined, including: recording the temperature of the sleeping environment of each user on the historical day corresponding to the actual longest sleeping time, the shortest sleeping time, and the least number of night awakenings as , and , Indicates The number corresponding to each user, .

[0011] Determine the temperature of each user's preferred sleeping environment , ,in , and The weights of the temperature of the sleeping environment on the historical days corresponding to the user's actual longest sleep time, shortest sleep time, and least number of nighttime awakenings are respectively represented, and .

[0012] Based on the analysis method of the temperature of each user's preferred sleeping environment, the humidity of each user's preferred sleeping environment is obtained in the same way.

[0013] S4. Music type recommendation: Collect the ambient noise of each user's environment at each set monitoring time point, analyze and obtain the similarity between the ambient noise of each user's environment at each set monitoring time point and the frequency spectrum feature vector corresponding to each ambient noise type, and then analyze the ambient noise type of each user's environment at the set monitoring time point, and then recommend music types to each user according to the preset music type matching rules.

[0014] S5. Music recommendation: Obtain the percentage of clicks on each music in the recommended music type of each user, and recommend music that each user listens to while sleeping.

[0015] S6. Music volume adjustment: collect the ambient noise decibels of each user's environment in real time and adjust the music volume of each user during sleep.

[0016] Preferably, analyzing the sleep state stability index of each user includes: collecting the heart rate of each user at each set monitoring time point, recorded as , the skin resistance of each user at each set monitoring time point is collected by the skin resistance meter and recorded as ,in Indicates The number corresponding to each user, , Indicates The number corresponding to each monitoring time point, .

[0017] The average heart rate of users of different age groups during the sleep stage is extracted from the database, and according to the age of each user, the average heart rate of the corresponding age group during the sleep stage of each user is screened and recorded as the reference heart rate of each user.

[0018] Analyze each user's sleep stability index ,

[0019] ,in and Respectively represent The reference heart rate and skin resistance of each user, represents the total number of monitoring time points, and Represent the weights corresponding to the user's heart rate and skin resistance, respectively, and .

[0020] Preferably, the determining of the sleep state level of each user includes: comparing the sleep state stability index of each user with the preset sleep state stability index range corresponding to each sleep state level, and corresponding the preset sleep state level to which the sleep state stability index of a certain user belongs to the sleep state stability index range as the sleep state level of the user, thereby obtaining the sleep state level of each user.

[0021] Preferably, the adjusting the brightness and color temperature of the light in the environment corresponding to the user includes: extracting suitable brightness and color temperature of the ambient light in each sleep state level of the user from a database, screening the brightness and color temperature of the light corresponding to each user's sleep state level, and adjusting the brightness and color temperature of the light in the environment of each user.

[0022] Preferably, the method of obtaining the temperature and humidity of the sleeping environment of the historical days corresponding to the actual longest sleeping time, the shortest sleeping time and the least number of nighttime awakenings of each user includes: extracting the historical sleep data of each user, and extracting the awakening time, the number of nighttime awakenings, the sleeping time and the sleeping time of each user on each set historical day from the historical sleep data of each user.

[0023] Subtract the sleeping time from the waking time of each user on each set historical day to obtain the actual sleeping time of each user on each set historical day;

[0024] The temperature and humidity of the sleeping environment of each user at each monitoring time point on each set historical day are collected.

[0025] The temperature of the sleeping environment of each user at each monitoring time point on each set historical day is substituted into the average calculation formula to obtain the temperature of the sleeping environment of each user on each set historical day.

[0026] Based on the analysis method of the temperature of the sleeping environment of each user on each set historical day, the humidity of the sleeping environment of each user on each set historical day is obtained in the same way.

[0027] The actual longest sleeping time of each user is screened out from the actual sleeping time of each user on each set historical day, and then the temperature and humidity of the sleeping environment on the historical day corresponding to the actual longest sleeping time of each user are obtained.

[0028] The shortest sleeping time of each user is selected from the sleeping time of each user on each set historical day, and then the temperature and humidity of the sleeping environment of the historical day corresponding to the shortest sleeping time of each user are obtained.

[0029] The minimum number of nighttime awakenings of each user on each set historical day is screened out, and then the temperature and humidity of the sleeping environment on the historical day corresponding to the minimum number of nighttime awakenings of each user is obtained.

[0030] Preferably, the regulating the temperature and humidity of each user's sleeping environment includes: collecting the temperature and humidity of each user's sleeping environment in real time, comparing the temperature of each user's sleeping environment with the temperature of the corresponding user's preferred sleeping environment, if the temperature of a user's sleeping environment is different from the temperature of the corresponding user's preferred sleeping environment, adjusting the temperature of the user's sleeping environment to the temperature of the corresponding user's preferred sleeping environment, and then adjusting the temperature of each user's sleeping environment.

[0031] Based on the temperature control method of each user's sleeping environment, the humidity of each user's sleeping environment is similarly controlled.

[0032] Preferably, the analysis of the type of environmental noise in the environment of each user includes: collecting the environmental noise in the environment of each user at each set monitoring time point, and then obtaining the spectrum characteristics of the environmental noise in the environment of each user at each set monitoring time point through spectrum analysis software, and then obtaining the spectrum characteristic vector of the environmental noise in the environment of each user at each set monitoring time point.

[0033] The spectrum feature vector corresponding to each environmental noise type is extracted from the database.

[0034] The frequency spectrum feature vectors of the ambient noise in the environment of each user at each set monitoring time point and the frequency spectrum feature vectors corresponding to each ambient noise type are substituted into the cosine similarity calculation formula to obtain the similarity between the frequency spectrum feature vectors of the ambient noise in the environment of each user at each set monitoring time point and each ambient noise type.

[0035] The similarities between the ambient noise of each user's environment at each set monitoring time point and the spectrum feature vectors corresponding to each ambient noise type are sorted to obtain the ambient noise type with the highest similarity, which is used as the ambient noise type of each user's environment at each set monitoring time point.

[0036] The ambient noise type of each user's environment at each set monitoring time point is associated with the preset music type matching rules, and then the music type is recommended for each user.

[0037] Preferably, the recommending music for each user to listen to while sleeping comprises: extracting historical data of each user listening to music from a database, extracting the number of clicks on each music in the recommended music type for each user from the historical data of each user listening to music, dividing the number of clicks on each music in the recommended music type for each user by the total number of clicks on the corresponding music type, to obtain the proportion of the number of clicks on each music in the recommended music type for each user.

[0038] The music with the largest percentage of clicks is selected from the percentage of clicks of each music in the recommended music types of each user, and is used as the music recommended for each user to listen to while sleeping.

[0039] Preferably, the analysis of the music volume of each user while sleeping includes: real-time collection of the ambient noise decibels of each user's environment, and adjusting the music volume listened to by the corresponding user while sleeping based on a preset adjustment ratio of the ambient noise decibels to the music volume.

[0040] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) By real-time monitoring of physiological indicators such as heart rate and skin resistance, the system can accurately evaluate the user's sleep state, thereby better adjusting environmental factors to promote good sleep. By timely adjusting the brightness and color temperature of the light, it helps the user fall asleep faster, increase the proportion of deep sleep, improve the mental state during the day, and improve work efficiency and quality of life.

[0041] (2) The present invention determines the preferred sleeping environment temperature and humidity of each user by obtaining the actual longest sleeping time, shortest sleeping time and least number of nighttime awakenings of each user on historical days, and then regulates the temperature and humidity of each user's sleeping environment. Optimizing the temperature and humidity conditions helps reduce the number of nighttime awakenings, shortens the sleeping time, and may extend the deep sleep time, thereby being able to accurately adjust environmental parameters to promote better sleep, providing users with more accurate and personalized sleep support, significantly improving the users' sleep quality and quality of life, improving the users' overall health, and reducing health problems caused by insufficient or poor sleep quality. In addition, temperature and humidity regulation based on the users' actual needs can avoid unnecessary energy consumption.

[0042] (3) The present invention can create a more peaceful and comfortable sleeping environment for users by analyzing the type of ambient noise and monitoring the decibel of ambient noise in real time, recommending corresponding music and automatically adjusting the music volume to cover up or neutralize the bad noise. This helps to reduce noise interference, improve the user's sleep quality and promote deep sleep. Different users have different preferences and reactions to music. Based on the proportion of clicks on each music in each user's music type, the present invention can more accurately recommend the music that the user likes. This personalized recommendation not only improves user satisfaction, but also helps users relax and fall asleep more effectively. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0044] Figure 1 It is a schematic diagram for implementing the method steps of the present invention. DETAILED DESCRIPTION

[0045] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0046] See also Figure 1 As shown, the present invention provides a comprehensive intelligent environment control method based on sleep aid, the method comprising: S1, user sleep state level judgment: collecting the heart rate and skin resistance of each user at each set monitoring time point, and analyzing the sleep state stability index of each user.

[0047] Further, the sleep state stability index of each user is analyzed, including: collecting the heart rate of each user at each set monitoring time point, recorded as , the skin resistance of each user at each set monitoring time point is collected by the skin resistance meter and recorded as ,in Indicates The number corresponding to each user, , Indicates The number corresponding to each monitoring time point, .

[0048] The average heart rate of users of different age groups during the sleep stage is extracted from the database, and according to the age of each user, the average heart rate of the corresponding age group during the sleep stage of each user is screened and recorded as the reference heart rate of each user.

[0049] Analyze each user's sleep stability index ,

[0050] ,in and Respectively represent The reference heart rate and skin resistance of each user, represents the total number of monitoring time points, and Represent the weights corresponding to the user's heart rate and skin resistance, respectively, and .

[0051] As a preferred embodiment, the and They can be set to 0.6 and 0.4 respectively. Heart rate, as an important indicator of the cardiovascular system, is generally considered to be a key factor in evaluating sleep quality and stability. Skin resistance is usually related to an individual's emotional state and physiological arousal level. During sleep, changes in skin resistance can reflect stress reactions or emotional fluctuations, but compared to heart rate, its role in directly reflecting sleep depth and quality may be slightly weaker. Therefore, the weight corresponding to the user's heart rate is greater than the weight corresponding to skin resistance.

[0052] S2. Determine the sleep state level: Determine the sleep state level of each user according to the sleep state stability index of each user, and adjust the brightness and color temperature of the light in the environment corresponding to the user based on the sleep state level.

[0053] Furthermore, the determination of the sleep state level of each user includes: comparing the sleep state stability index of each user with the preset sleep state stability index range corresponding to each sleep state level, and corresponding the preset sleep state level to which the sleep state stability index of a certain user belongs to the sleep state stability index range as the sleep state level of the user, thereby obtaining the sleep state level of each user.

[0054] Furthermore, the adjusting the brightness and color temperature of the light in the environment corresponding to the user includes: extracting suitable brightness and color temperature of the ambient light in each sleep state level of the user from a database, screening the brightness and color temperature of the light corresponding to each user's sleep state level, and adjusting the brightness and color temperature of the light in the environment of each user.

[0055] By real-time monitoring of physiological indicators such as heart rate and skin resistance, the system can accurately evaluate the user's sleep state, thereby better adjusting environmental factors to promote good sleep. By timely adjusting the brightness and color temperature of the light, it helps the user fall asleep faster, increase the proportion of deep sleep, improve the daytime mental state, and improve work efficiency and quality of life.

[0056] S3. Environmental temperature and humidity control: Extract the waking time, number of waking up at night, duration of falling asleep and time of sleeping of each user on each set historical day from the historical sleep data of each user, obtain the temperature and humidity of the sleeping environment on the historical days corresponding to the actual longest sleep time, shortest duration of falling asleep and least number of waking up at night of each user, determine the preferred temperature and humidity of the sleeping environment of each user, and then control the temperature and humidity of the sleeping environment of each user.

[0057] Furthermore, the method of obtaining the temperature and humidity of the sleeping environment of the historical days corresponding to the actual longest sleeping time, shortest sleeping time and least number of nighttime awakenings of each user includes: extracting the historical sleep data of each user, and extracting the awakening time, number of nighttime awakenings, sleeping time and sleeping time of each user on each set historical day from the historical sleep data of each user.

[0058] As a preferred embodiment, the waking time, number of waking up at night, duration of falling asleep and time to fall asleep are specifically: the time point when the user no longer enters the sleep state, the number of times the user wakes up at night, the time required for the user to go to bed and enter the sleep state, and the time point when the user enters the sleep state.

[0059] The historical sleep data of each user is collected through smart watches, smart bracelets, smart mattresses, etc.

[0060] The actual sleeping time of each user on each set historical day is obtained by subtracting the sleeping time from the waking time of each user on each set historical day.

[0061] The temperature and humidity of the sleeping environment of each user at each monitoring time point on each set historical day are collected.

[0062] As a preferred embodiment, the temperature and humidity of the sleeping environment of each user at each monitoring time point on each set historical day are collected by a temperature and humidity sensor.

[0063] The temperature of the sleeping environment of each user at each monitoring time point on each set historical day is substituted into the average calculation formula to obtain the temperature of the sleeping environment of each user on each set historical day.

[0064] Based on the analysis method of the temperature of the sleeping environment of each user on each set historical day, the humidity of the sleeping environment of each user on each set historical day is obtained in the same way.

[0065] The actual longest sleeping time of each user is screened out from the actual sleeping time of each user on each set historical day, and then the temperature and humidity of the sleeping environment on the historical day corresponding to the actual longest sleeping time of each user are obtained.

[0066] The shortest sleeping time of each user is selected from the sleeping time of each user on each set historical day, and then the temperature and humidity of the sleeping environment of the historical day corresponding to the shortest sleeping time of each user are obtained.

[0067] The minimum number of nighttime awakenings of each user on each set historical day is screened out, and then the temperature and humidity of the sleeping environment on the historical day corresponding to the minimum number of nighttime awakenings of each user is obtained.

[0068] Furthermore, the determination of the preferred sleeping environment temperature and humidity of each user includes: recording the temperature of the sleeping environment of each user on the historical day corresponding to the actual longest sleeping time, the shortest sleeping time, and the least number of nighttime awakenings as , and .

[0069] Determine the temperature of each user's preferred sleeping environment , ,in , and The weights of the temperature of the sleeping environment on the historical days corresponding to the user's actual longest sleep time, shortest sleep time, and least number of nighttime awakenings are respectively represented, and .

[0070] As a preferred embodiment, the , and They can be set to 0.4, 0.3 and 0.3 respectively. On the days with the longest actual sleep time, the user is often in a deeper and more comfortable sleep state. The temperature preference in this state reflects the user's most comfortable temperature demand for a full night's sleep. The user is more likely to fall asleep on the days with the shortest sleep time. On the days with the least number of nighttime awakenings, it usually means higher sleep quality. Therefore, the weight corresponding to the temperature of the historical day corresponding to the user's actual longest sleep time is greater than the weight corresponding to the temperature of the historical day corresponding to the shortest sleep time and the least number of nighttime awakenings.

[0071] Based on the analysis method of the temperature of each user's preferred sleeping environment, the humidity of each user's preferred sleeping environment is obtained in the same way.

[0072] Furthermore, the temperature and humidity of each user's sleeping environment are controlled, including: real-time collection of the temperature and humidity of each user's sleeping environment, comparing the temperature of each user's sleeping environment with the temperature of the corresponding user's preferred sleeping environment, if the temperature of a user's sleeping environment is different from the temperature of the corresponding user's preferred sleeping environment, adjusting the temperature of the user's sleeping environment to the temperature of the corresponding user's preferred sleeping environment, and thereby adjusting the temperature of each user's sleeping environment.

[0073] Based on the temperature control method of each user's sleeping environment, the humidity of each user's sleeping environment is similarly controlled.

[0074] The present invention determines the preferred sleeping environment temperature and humidity of each user by obtaining the temperature and humidity of the sleeping environment of the historical days corresponding to the actual longest sleeping time, the shortest sleeping time and the least number of awakenings at night of each user, and then regulates the temperature and humidity of the sleeping environment of each user. Optimizing the temperature and humidity conditions helps to reduce the number of awakenings at night, shorten the sleeping time, and possibly prolong the deep sleep time, so that the environmental parameters can be accurately adjusted to promote better sleep, providing users with more accurate and personalized sleep support, significantly improving the users' sleep quality and quality of life, improving the users' overall health status, and reducing health problems caused by lack of sleep or poor sleep quality. In addition, the temperature and humidity regulation based on the actual needs of the users can avoid unnecessary energy consumption.

[0075] S4. Music type recommendation: Collect the ambient noise of each user's environment at each set monitoring time point, analyze and obtain the similarity between the ambient noise of each user's environment at each set monitoring time point and the frequency spectrum feature vector corresponding to each ambient noise type, and then analyze the ambient noise type of each user's environment at the set monitoring time point, and then recommend music types to each user according to the preset music type matching rules.

[0076] Furthermore, the analysis of the type of environmental noise in the environment of each user includes: collecting the environmental noise in the environment of each user at each set monitoring time point, and then obtaining each spectrum feature of the environmental noise in the environment of each user at each set monitoring time point through spectrum analysis software, and then obtaining the spectrum feature vector of the environmental noise in the environment of each user at each set monitoring time point.

[0077] The spectrum feature vector corresponding to each environmental noise type is extracted from the database.

[0078] The frequency spectrum feature vectors of the ambient noise in the environment of each user at each set monitoring time point and the frequency spectrum feature vectors corresponding to each ambient noise type are substituted into the cosine similarity calculation formula to obtain the similarity between the frequency spectrum feature vectors of the ambient noise in the environment of each user at each set monitoring time point and each ambient noise type.

[0079] The similarities between the ambient noise of each user's environment at each set monitoring time point and the spectrum feature vectors corresponding to each ambient noise type are sorted to obtain the ambient noise type with the highest similarity, which is used as the ambient noise type of each user's environment at each set monitoring time point.

[0080] The ambient noise type of each user's environment at each set monitoring time point is associated with the preset music type matching rules, and then the music type is recommended for each user.

[0081] As a preferred embodiment, the specific process of recommending music types for each user is as follows: substituting the environmental noise type of each user's environment at each set monitoring time point into a preset music type matching rule, obtaining the music type corresponding to the environmental noise type of each user's environment at each set monitoring time point, summarizing them to obtain the number of each music type, and selecting the music type with the largest number as the recommended music type for each user.

[0082] The types of environmental noise include: traffic noise, social life noise and mechanical noise.

[0083] The preset music types include: relaxing jazz, classical music and natural sounds.

[0084] The specific process of associating the preset music type matching rule is: extracting the frequency of each environmental noise type and each music type from the database.

[0085] The frequencies of each environmental noise type and each music type are matched to obtain the frequency similarity between each environmental noise type and each music type, and the frequency similarity is compared with a preset similarity threshold. If the frequency similarity between a certain environmental noise type and a certain music type is greater than the preset similarity threshold, the environmental noise type is matched with the music type.

[0086] For example, when social life noise is detected, natural sounds are recommended.

[0087] S5. Music recommendation: Obtain the percentage of clicks on each music in the recommended music type of each user, and recommend music that each user listens to while sleeping.

[0088] Furthermore, the recommending of music for each user to listen to while sleeping includes: extracting historical data of each user listening to music from a database, extracting the number of clicks on each music in the recommended music type for each user from the historical data of each user listening to music, dividing the number of clicks on each music in the recommended music type for each user by the total number of clicks on the corresponding music type, to obtain a proportion of the number of clicks on each music in the recommended music type for each user.

[0089] The music with the largest percentage of clicks is selected from the percentage of clicks of each music in the recommended music types of each user, and is used as the music recommended for each user to listen to while sleeping.

[0090] S6. Music volume adjustment: collect the ambient noise decibels of each user's environment in real time and adjust the music volume of each user during sleep.

[0091] Furthermore, the analysis of the music volume of each user while sleeping includes: real-time collection of the ambient noise decibels of the environment in which each user is located, and adjusting the music volume listened to by the corresponding user while sleeping based on a preset adjustment ratio of the ambient noise decibels to the music volume.

[0092] As a preferred embodiment, the preset adjustment ratio of the ambient noise decibel to the music volume can be specifically set to 3:4. For example, whenever the ambient noise decibel increases by 3 units, the music volume will automatically increase by 4 units.

[0093] The present invention can create a more peaceful and comfortable sleeping environment for users by analyzing the type of environmental noise and monitoring the decibels of environmental noise in real time, recommending corresponding music and automatically adjusting the music volume to cover up or neutralize adverse noise. This helps to reduce noise interference, improve the user's sleep quality, and promote deep sleep. Different users have different preferences and reactions to music. Based on the proportion of the number of clicks on each music in each user's music type, the present invention can more accurately recommend the music that the user likes. This personalized recommendation not only improves user satisfaction, but also more effectively helps users relax and fall asleep.

[0094] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they shall all fall within the protection scope of the present invention.

Claims

1. A comprehensive intelligent environment control method based on sleep aid, characterized by: The method includes: S1. User sleep status level judgment: collect the heart rate and skin resistance of each user at each set monitoring time point, and analyze the sleep status stability index of each user; S2. Sleep state level determination: Determine the sleep state level of each user according to the sleep state stability index of each user, and adjust the brightness and color temperature of the light in the environment corresponding to the user based on the sleep state level; S3, environmental temperature and humidity control: extract the wake-up time, number of wake-ups at night, sleep duration and sleep time of each user on each set historical day from the historical sleep data of each user, obtain the temperature and humidity of the sleeping environment on the historical day corresponding to the actual longest sleep time, shortest sleep duration and least number of wake-ups at night of each user, determine the preferred temperature and humidity of the sleeping environment of each user, and then control the temperature and humidity of the sleeping environment of each user; The preferred sleeping environment temperature and humidity of each user is determined, including: recording the temperature of the sleeping environment of each user on the historical day corresponding to the actual longest sleeping time, the shortest sleeping time, and the least number of night awakenings as , and , Indicates The number corresponding to each user, ; Determine the temperature of each user's preferred sleeping environment , ,in , and The weights of the temperature of the sleeping environment on the historical days corresponding to the user's actual longest sleep time, shortest sleep time, and least number of nighttime awakenings are respectively represented, and ; Based on the analysis method of the temperature of each user's preferred sleeping environment, the humidity of each user's preferred sleeping environment is obtained in the same way; S4, music type recommendation: collect the environmental noise of each user's environment at each set monitoring time point, analyze and obtain the similarity of the environmental noise of each user's environment at each set monitoring time point and the frequency spectrum feature vector corresponding to each environmental noise type, and then analyze the environmental noise type of each user's environment at the set monitoring time point, and then recommend music types to each user according to the preset music type matching rules; S5. Music recommendation: obtaining the percentage of clicks on each music in the recommended music type of each user, and recommending music that each user listens to while sleeping; S6. Music volume adjustment: collect the ambient noise decibels of each user's environment in real time and adjust the music volume of each user during sleep.

2. A sleep-aiding intelligent environment comprehensive control method according to claim 1, characterized in that: Analyze each user's sleep stability index, including: Collect the heart rate of each user at each set monitoring time point, recorded as , the skin resistance of each user at each set monitoring time point is collected by the skin resistance meter and recorded as ,in Indicates The number corresponding to each user, , Indicates The number corresponding to each monitoring time point, ; Extract the average heart rate of users of different age groups during the sleep stage from the database, and select the average heart rate of the corresponding age group of each user during the sleep stage according to the age of each user, and record it as the reference heart rate of each user; Analyze each user's sleep stability index , ,in and Respectively represent The reference heart rate and skin resistance of each user, represents the total number of monitoring time points, and Represent the weights corresponding to the user's heart rate and skin resistance, respectively, and .

3. A sleep-aiding intelligent environment comprehensive control method according to claim 1, characterized in that: The step of determining the sleep status level of each user includes: The sleep state stability index of each user is compared with the sleep state stability index range corresponding to each preset sleep state level, and the sleep state stability index range to which the sleep state stability index of a user belongs corresponds to the preset sleep state level as the sleep state level of the user, thereby obtaining the sleep state level of each user.

4. A sleep-aiding intelligent environment comprehensive control method according to claim 1, characterized in that: The step of adjusting the brightness and color temperature of the light corresponding to the environment where the user is located includes: The appropriate brightness and color temperature of the ambient light for each user at each sleep state level are extracted from the database, the brightness and color temperature of the light corresponding to each user's sleep state level are screened, and the brightness and color temperature of the light in each user's environment are adjusted.

5. A sleep-aiding intelligent environment comprehensive control method according to claim 2, characterized in that: The method of obtaining the temperature and humidity of the sleeping environment of each user on the historical day corresponding to the actual longest sleeping time, the shortest sleeping time, and the least number of awakenings at night includes: Extracting the historical sleep data of each user, and extracting the wake-up time, number of wake-ups at night, sleep duration and sleep time of each user on each set historical day from the historical sleep data of each user; Subtract the sleeping time from the waking time of each user on each set historical day to obtain the actual sleeping time of each user on each set historical day; Collect the temperature and humidity of the sleeping environment of each user at each monitoring time point on each set historical day; Substituting the temperature of the sleeping environment of each user at each monitoring time point on each set historical day into the average calculation formula to obtain the temperature of the sleeping environment of each user on each set historical day; Based on the analysis method of the temperature of the sleeping environment of each user on each set historical day, the humidity of the sleeping environment of each user on each set historical day is obtained in the same way; Filtering out the actual longest sleep time of each user from the actual sleep time of each user on each set historical day, and then obtaining the temperature and humidity of the sleeping environment on the historical day corresponding to the actual longest sleep time of each user; The shortest sleeping time of each user is selected from the sleeping time of each user on each set historical day, and then the temperature and humidity of the sleeping environment of the historical day corresponding to the shortest sleeping time of each user are obtained; The minimum number of nighttime awakenings of each user on each set historical day is screened out, and then the temperature and humidity of the sleeping environment on the historical day corresponding to the minimum number of nighttime awakenings of each user is obtained.

6. A sleep-aiding intelligent environment comprehensive control method according to claim 1, characterized in that: The controlling of the temperature and humidity of the sleeping environment of each user includes: The temperature and humidity of each user's sleeping environment are collected in real time, and the temperature of each user's sleeping environment is compared with the temperature of the preferred sleeping environment of the corresponding user. If the temperature of a user's sleeping environment is different from the temperature of the preferred sleeping environment of the corresponding user, the temperature of the user's sleeping environment is adjusted to the temperature of the preferred sleeping environment of the corresponding user, thereby adjusting the temperature of each user's sleeping environment; Based on the temperature control method of each user's sleeping environment, the humidity of each user's sleeping environment is similarly controlled.

7. A sleep-aiding intelligent environment comprehensive control method according to claim 1, characterized in that: The analyzing the type of environmental noise in the environment of each user includes: Collect the environmental noise of each user's environment at each set monitoring time point, and then obtain the spectrum characteristics of the environmental noise of each user's environment at each set monitoring time point through spectrum analysis software, and then obtain the spectrum feature vector of the environmental noise of each user's environment at each set monitoring time point; Extract the spectral feature vector corresponding to each environmental noise type from the database; Substitute the frequency spectrum feature vector of the ambient noise of each user's environment at each set monitoring time point and the frequency spectrum feature vector corresponding to each ambient noise type into the cosine similarity calculation formula to obtain the similarity between the frequency spectrum feature vector of the ambient noise of each user's environment at each set monitoring time point and each ambient noise type; The similarities between the ambient noise of each user's environment at each set monitoring time point and the spectrum feature vectors corresponding to each ambient noise type are sorted to obtain the ambient noise type with the highest similarity, and the type is used as the ambient noise type of each user's environment at each set monitoring time point; The ambient noise type of each user's environment at each set monitoring time point is associated with the preset music type matching rules, and then the music type is recommended for each user.

8. The method for comprehensive control of an intelligent environment based on sleep aid according to claim 1, characterized in that: The recommendation of music for each user to listen to while sleeping includes: Extracting the historical data of each user listening to music from the database, extracting the number of clicks on each piece of music in the recommended music type of each user from the historical data of each user listening to music, dividing the number of clicks on each piece of music in the recommended music type of each user by the total number of clicks on the corresponding music type, and obtaining the percentage of the number of clicks on each piece of music in the recommended music type of each user; The music with the largest percentage of clicks is selected from the percentage of clicks of each music in the recommended music types of each user, and is used as the music recommended for each user to listen to while sleeping.

9. The method for comprehensive control of intelligent environment based on sleep aid according to claim 1, characterized in that: The analyzing the music volume of each user during sleep includes: The ambient noise decibel of each user's environment is collected in real time, and based on the pre-set adjustment ratio of ambient noise decibel to music volume, the volume of music listened to by the corresponding user while sleeping is adjusted.

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