Intelligent alarm clock and control method thereof

Abstract

The invention relates to the technical field of alarm clocks, in particular to an intelligent alarm clock and a control method thereof. The control method of the intelligent alarm clock comprises the following steps: monitoring and acquiring sleep quality data of a user in a sleep area in real time; outputting a sleep quality report and a corresponding sleep suggestion according to the acquired sleep quality data; before the preset alarm time, starting an awakening mode according to the sleep state of the user; adjusting preset schedule reminding time and preset schedule reminding content according to the weather condition and the real-time traffic condition of the position where the user is located; and controlling to output the adjusted preset schedule reminding content at the adjusted preset schedule reminding time. According to the intelligent alarm clock and the control method thereof, the functions of sleep monitoring and sleep suggestion providing are achieved, the user can be awakened in the appropriate sleep time, the awakening discomfort is reduced, schedule arrangement can be optimized, multiple functions are achieved, and better user experience is provided.

Description

Technical Field

[0001] The invention relates to the technical field of alarm clocks, in particular to an intelligent alarm clock and a control method thereof. Background Art

[0002] The traditional alarm clock is a clock with an alarm device. It can not only indicate the time, but also send out sound signals or other signals at the time people set. The alarm clock has a loud sound and a strong reminder sound. It is generally used as a sleep reminder in the bedroom. It can help people develop good work and rest habits and refuse laziness. It is deeply loved by people.

[0003] However, with the development of society, people have higher and higher requirements for alarm clocks. The existing alarm clocks have relatively simple overall functions and poor user experience. Summary of the invention

[0004] The technical problem to be solved by the embodiments of the present invention is to provide a smart alarm clock and a control method thereof, so as to solve the problem that the overall functions of the alarm clock in the prior art are relatively simple and the user experience is poor.

[0005] The present invention discloses a control method for an intelligent alarm clock, and the control method for the intelligent alarm clock comprises:

[0006] Real-time monitoring to obtain the sleep quality data of the user in the sleeping area;

[0007] Output a sleep quality report and corresponding sleep suggestions based on the acquired sleep quality data;

[0008] Before the preset alarm time, the wake-up mode is activated according to the user's sleep state;

[0009] Adjust the preset schedule reminder time and preset schedule reminder content according to the weather conditions and real-time traffic conditions at the user's location;

[0010] The adjusted preset schedule reminder content is outputted at the adjusted preset schedule reminder time.

[0011] Optionally, the step of starting the wake-up mode according to the user's sleeping state includes:

[0012] Analyze the user's sleeping state and determine the user's sleep cycle;

[0013] Determine whether the time difference between the current time and the preset alarm time is less than a preset value, and determine whether the user is in the light sleep stage of the sleep cycle. If the time difference is less than the preset value and the user is in the light sleep stage of the sleep cycle, the wake-up mode is started in combination with the user's sleep quality data and user portrait.

[0014] Optionally, the step of starting the wake-up mode in combination with the user's sleep quality data and the user portrait includes:

[0015] Based on the pre-built user profile, obtain the type of multimedia content preferred by the user;

[0016] Generate multimedia content that meets the user's preferences as target multimedia content using an artificial intelligence model based on the user's sleep quality data;

[0017] The target multimedia content is played.

[0018] Optionally, the step of starting the wake-up mode in combination with the user's sleep quality data and the user portrait further includes:

[0019] The brightness of the light is controlled to be gradually increased, or the brightness and color of the light are controlled to change as the target multimedia content changes.

[0020] Optionally, the step of analyzing the user's sleep state and determining the user's sleep cycle includes:

[0021] Obtain the user's original physiological data;

[0022] extracting features related to sleep stages from the raw physiological data;

[0023] Using deep learning models, the extracted features are analyzed to identify different sleep stages;

[0024] Analyzes consecutive sleep stages to determine the user's sleep cycle.

[0025] Optionally, the step of acquiring the sleep quality data of the user in the sleeping area through real-time monitoring by the microwave radar module includes:

[0026] The microwave radar module continuously sends microwave signals to the sleeping area and receives reflected microwave signals, and converts the reflected microwave signals into digital signals to obtain Doppler frequency shift information and the distance between the user and the smart alarm clock;

[0027] Extracting original physiological data of the user from the Doppler frequency shift information;

[0028] Extracting the user's location and the user's location change characteristics from the distance information;

[0029] Get the time corresponding to the position change feature;

[0030] The original physiological data, the position change characteristics and the time corresponding to the position change characteristics are processed to obtain sleep quality data.

[0031] Optionally, the control method of the smart alarm clock further includes:

[0032] Collect users’ daily behavior data;

[0033] Based on the daily behavior data, a user behavior pattern model is established to predict the items that the user needs to carry in a specific scenario;

[0034] monitoring whether the user carries the item;

[0035] When it is detected that the user is in the exit area and is not carrying the predicted items, a reminder notification is automatically issued.

[0036] Optionally, the control method of the smart alarm clock further includes:

[0037] Control and display solar term information, wherein the solar term information includes solar term introduction, traditional customs of solar terms, and health management suggestions for solar terms.

[0038] Optionally, the control method of the smart alarm clock further includes:

[0039] Detecting the user's posture in the sleeping area through a microwave radar module;

[0040] If the microwave radar module detects that the user stands up and moves, the light will be turned on;

[0041] If the microwave radar module detects that the user is lying down, the light will be turned off.

[0042] The present invention also discloses a control method for a smart alarm clock using any one of the above-mentioned control methods, wherein the smart alarm clock comprises a microwave radar module, a main control module, a sound module and a display module, wherein the main control module is connected to the microwave radar module, the display module and the sound module, wherein:

[0043] The microwave radar module is used to monitor and obtain the sleep quality data of the user in the sleeping area in real time;

[0044] The main control module is used to control the display module and / or the generating module to output a sleep quality report and corresponding sleep suggestions based on the acquired sleep quality data; it is also used to start the wake-up mode according to the user's sleep status before the preset alarm time; it is also used to adjust the preset schedule reminder time and the preset schedule reminder content according to the weather conditions and real-time traffic conditions at the user's location, and control the sound module to output the adjusted preset schedule reminder content at the adjusted preset schedule reminder time.

[0045] Compared with the prior art, the beneficial effects of the smart alarm clock and its control method provided by the embodiments of the present invention are: obtaining the sleep quality data of the user in the sleeping area through real-time monitoring, analyzing the obtained sleep quality data, outputting a sleep quality report and corresponding sleep suggestions, and having the functions of sleep monitoring and providing sleep suggestions, which helps the user to have a more comprehensive understanding of his or her sleep situation and thus take corresponding measures to improve the sleep quality; the smart alarm clock can also start the wake-up mode according to the user's sleep state, so as to wake the user up at a suitable sleep time and reduce the discomfort caused by the wake-up; and the present application can also intelligently adjust the preset schedule reminder time and the preset schedule reminder content according to the weather conditions and real-time traffic conditions to help the user optimize the schedule. Therefore, the smart alarm clock of the present application has multiple functions and provides a better user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The scheme of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments, in which:

[0047] Figure 1 It is a flowchart of an embodiment of the control method of the smart alarm clock provided by the present application;

[0048] Figure 2 This is a flowchart of an embodiment of monitoring and obtaining sleep quality data provided by the present application;

[0049] Figure 3 This is a flowchart of an embodiment of starting a wake-up mode according to a user's sleep state provided by the present application;

[0050] Figure 4 is a flowchart of an embodiment of determining a user's sleep cycle provided by the present application;

[0051] Figure 5 This is a flowchart of an embodiment of initiating a wake-up mode by combining the user's sleep quality data and user portrait provided by the present application;

[0052] Figure 6 It is a structural block diagram of an embodiment of the smart alarm clock provided by the present application;

[0053] Figure 7 It is a structural schematic diagram of an embodiment of the smart alarm clock provided by the present application;

[0054] Figure 8 It is a schematic diagram of the exploded structure of an embodiment of the smart alarm clock provided by the present application;

[0055] Fig. 9 is a structural block diagram of another embodiment of the smart alarm clock provided by the present application;

[0056] Fig.10It is a structural block diagram of an embodiment of the computer-readable storage medium provided by the present application.

[0057] The reference numerals in the figures are:

[0058] 110, main control module; 120, microwave radar module; 130, display module; 140, sound module; 150, light emitting module; 160, camera module; 170, housing; 180, circuit board;

[0059] 210, processor; 220, memory;

[0060] 310. Computer program. DETAILED DESCRIPTION

[0061] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. Now, in conjunction with the accompanying drawings, the preferred embodiments of the present invention are described in detail.

[0062] The embodiment of the present invention provides a method for controlling an intelligent alarm clock. Figure 1 As shown, the control method of the intelligent alarm clock includes:

[0063] S110, real-time monitoring to obtain sleep quality data of the user in the sleeping area;

[0064] S120, outputting a sleep quality report and corresponding sleep suggestions according to the acquired sleep quality data;

[0065] S130, before the preset alarm time, starting the wake-up mode according to the user's sleeping state;

[0066] S140, adjusting the preset schedule reminder time and preset schedule reminder content according to the weather conditions and real-time traffic conditions at the user's location;

[0067] S150: Controlling output of adjusted preset schedule reminder content at the adjusted preset schedule reminder time.

[0068] In the embodiment of the present application, the sleep quality data of the user in the sleeping area is acquired through real-time monitoring, and the acquired sleep quality data is analyzed to output a sleep quality report and corresponding sleep suggestions. The smart alarm clock has the functions of sleep monitoring and providing sleep suggestions, which helps the user to have a more comprehensive understanding of his or her sleep situation and thus take corresponding measures to improve the sleep quality. The smart alarm clock can also start the wake-up mode according to the user's sleep status so as to wake the user up at a suitable sleep time and reduce the discomfort caused by the wake-up. The present application can also intelligently adjust the preset schedule reminder time and the preset schedule reminder content according to the weather conditions and real-time traffic conditions to help the user optimize the schedule. Therefore, the smart alarm clock of the present application has multiple functions and provides a better user experience.

[0069] In an optional embodiment of the present application, refer to Figure 1 and Figure 2 In step S110, the step of real-time monitoring and obtaining the sleep quality data of the user in the sleeping area includes:

[0070] S210, continuously sending and receiving reflected microwave signals to the sleeping area through the microwave radar module, and converting the reflected microwave signals into digital signals to obtain Doppler frequency shift information and distance information between the user and the smart alarm clock;

[0071] S220, analyzing the Doppler frequency shift information to obtain the original physiological data of the user;

[0072] S230, analyzing the distance information to obtain the user's location and the user's location change characteristics;

[0073] S240: Process the original physiological data and position change characteristics to obtain sleep quality data.

[0074] The original physiological data includes breathing rate and heart rate. The user's position change characteristics include lying down, turning over, and standing up. The original physiological data and position change characteristics have corresponding occurrence time points.

[0075] The microwave radar module transmits and receives microwave signals. When the user's body in the sleeping area makes slight movements (such as breathing, heartbeat, etc.) or changes position (such as lying down, standing up, turning over), the frequency of the reflected microwave signal will change, thereby generating a Doppler frequency shift and obtaining Doppler frequency shift information. By analyzing the Doppler frequency shift information, the user's breathing rate and heart rate can be obtained.

[0076] Specifically, a filter can be used to filter the converted digital signal received by the microwave radar module to remove environmental noise and clutter and improve the signal quality. The Doppler frequency shift information obtained by the microwave radar module is essentially a time domain signal. By performing frequency domain analysis on the filtered signal, the time domain signal is converted into a frequency domain signal using fast Fourier transform. Through fast Fourier transform, the main frequency components of heart rate and breathing can be extracted from the frequency domain, and the main frequency can be determined by identifying the peak in the spectrum, and then the breathing frequency and heart rate can be calculated.

[0077] The microwave radar module can also calculate the distance between the user and the microwave radar module by measuring parameters such as the propagation time of the signal. Since the distance between the user and the microwave radar module will be different when the user turns over or stands up, the distance information can be analyzed to determine the user's position and the characteristics of the user's position change.

[0078] Sleep quality data includes bedtime, sleep time, wake-up time, sleep duration, sleep cycle, sleep depth, number of turns, respiratory rate and heart rate changes. Sleep quality data can be obtained by processing the original physiological data and position change characteristics. For example, the time corresponding to the user lying down is determined as the user's bedtime, and the time corresponding to the user getting up is determined as the wake-up time. The number of times the user turns over is counted as the number of turns, and the difference between the time when the user initially lies down and the time when he finally gets up is calculated to get the sleep duration, and the depth of sleep is determined according to the time and number of turning over actions.

[0079] According to the obtained sleep quality data, a sleep quality report and corresponding sleep suggestions can be output. Specifically, after obtaining the above sleep quality data, the sleep quality report and corresponding sleep suggestions can be output through the pre-trained CNN-LSTM hybrid model recognition and processing. The sleep quality report includes a visual presentation of various data indicators (bedtime, sleep time, wake-up time, sleep duration, sleep cycle, sleep depth, number of tossing, breathing frequency and heart rate changes) as well as a comprehensive sleep quality score and evaluation.

[0080] Specifically, the sleep quality data is normalized using the following formula and mapped to [0, 1]:

[0081]

[0082] In the formula, X i For each data in the data set; X min is the minimum data in the data set; X max The maximum value in the data set.

[0083] Since sleep quality data is time series data, the sliding window algorithm can be used to divide the sleep quality data into multiple sequence segments. Each window can contain several minutes of data. The data is input into the trained CNN-LSTM hybrid model, and the input sleep quality data is identified by the CNN-LSTM hybrid model. For example, the input user's heart rate is [60, 62, 65, 68, 70, 72, 75, 78, 80, 82], and the breathing rate is [16, 17, 18, 19, 20, 21, 22, 23, 24, 25]. The corresponding output sleep stage label of the CNN-LSTM hybrid model is [light sleep, light sleep, deep sleep, deep sleep, light sleep, REM sleep, light sleep, awake, awake]. This result shows that the user is in light sleep for the first two minutes, deep sleep for the next three minutes, then back to light sleep for one minute, then in REM sleep for one minute, and awake for the last three minutes. Through this identification, a detailed sleep quality report can be generated, and corresponding sleep suggestions can be provided for the corresponding sleep quality report.

[0084] The sleep quality report can be in the form of a chart, video report, audio report, etc. The sleep quality report can include a visual presentation of various data indicators as well as a comprehensive sleep quality score and evaluation. Sleep suggestions can be displayed through smart push or directly on the display interface of the smart alarm clock. For example, the smart alarm clock can regularly push personalized sleep suggestions to users through its supporting mobile phone application; or the sleep suggestions can be directly displayed on the user interface of the smart alarm clock, and users can see the corresponding improvement suggestions when viewing the sleep quality report.

[0085] Furthermore, the user can directly provide feedback on the received suggestions in the supporting application of the smart alarm clock, express the effectiveness of the suggestions or provide other feedback, or the user can directly click on the feedback on the user interface.

[0086] Sleep suggestions can be targeted at different sleep problems, such as insomnia, risk of sleep apnea, lack of sleep, etc., and provide corresponding improvement suggestions, such as adjusting the sleeping environment, establishing a regular schedule, and performing relaxation exercises. Specifically, for users who have difficulty falling asleep, it is recommended to establish fixed bedtime and wake-up times, avoid excessive sleep or staying up late, perform relaxation exercises before bedtime, and limit caffeine and alcohol; for users at risk of sleep apnea, it is recommended to sleep on your side to reduce the risk of sleep apnea; for users who lack sleep, it is recommended to try to increase sleep time and optimize the sleeping environment; for users with many sleep interruptions, it is recommended to limit fluid intake within two hours before bedtime and establish fixed bedtime habits, such as reading or listening to light music.

[0087] In an optional embodiment of the present application, refer to Figure 1 and Figure 3 In step S130, the step of starting the wake-up mode according to the user's sleep state includes:

[0088] S310, analyzing the user's sleep state and determining the user's sleep cycle;

[0089] S320, determining whether the time difference between the current time and the preset alarm time is less than a preset value, and determining whether the user is in a light sleep stage of the sleep cycle; if the time difference is less than the preset value and the user is in a light sleep stage of the sleep cycle, starting the wake-up mode in combination with the user's sleep quality data and user portrait.

[0090] By analyzing the user's sleeping state, the user's sleep cycle can be determined. A complete sleep cycle includes light sleep, deep sleep, and rapid eye movement. The light sleep stage is the period when the user is most likely to wake up. Therefore, choosing to wake up the user in the light sleep stage can reduce the discomfort caused by wakeup. Among them, the user's entire sleep process usually includes multiple sleep cycles. The user is in the light sleep stage but the current time is not necessarily close to the preset alarm time. Therefore, by judging the current time, if the time difference between the current time and the preset alarm time is less than the preset value, it means that the current time is close to the preset alarm time. If the user happens to be in the light sleep stage, the wake-up mode is activated to reduce the discomfort of waking up the user and provide the user with a better user experience.

[0091] By combining the user's sleep quality data and user portrait to start the wake-up mode, the music that matches the user's preferences and sleep quality can be intelligently selected to wake the user up, providing the user with a better experience. For example, for users with poor sleep quality, soothing and gentle music is recommended to help them wake up peacefully.

[0092] In an optional embodiment of the present application, refer to Figure 3 and Figure 4 In step S310, the step of analyzing the user's sleep state and determining the user's sleep cycle includes:

[0093] S410, obtaining original physiological data of the user;

[0094] S420, extracting features related to sleep stages from the original physiological data;

[0095] S430, using a deep learning model to analyze the extracted features and identify different sleep stages;

[0096] S440: Analyze consecutive sleep stages to determine the user's sleep cycle.

[0097] The original physiological data includes respiratory rate and heart rate. The acquired original physiological data is preprocessed, including normalization, to eliminate the influence of different dimensions and magnitudes, so that the data is at the same standard, which is convenient for subsequent analysis. Features related to sleep stages are extracted from the preprocessed data, such as heart rate variability, changes in breathing patterns, etc. These features help to identify different sleep stages. By analyzing the heart rate data, such as analyzing the degree of fluctuation of the heart rate data, the heart rate variability can be obtained; analyzing the periodic changes in the breathing frequency in a short period of time can reflect whether the breathing pattern is regular and help identify the user's sleep stage. For example, in the stable stage of non-rapid eye movement sleep, the breathing amplitude and frequency are relatively regular, while in the unstable stage of non-rapid eye movement sleep, the breathing frequency shows irregularity, and even periodic breathing may occur. Therefore, by analyzing the features related to the sleep stage, different sleep stages can be identified.

[0098] By analyzing the extracted features through a deep learning model, the light sleep stage, deep sleep stage, and rapid eye movement stage can be identified. By analyzing continuous sleep stages, the user's sleep cycle can be identified. During the user's sleep cycle, if the user is in the light sleep stage when it is easiest to wake up, the wake-up mode is activated to reduce the discomfort caused by wake-up. The deep learning model can achieve high-precision sleep stage identification. This technology not only improves the accuracy of monitoring, but also improves the user experience.

[0099] In an optional embodiment of the present application, in step S320, the step of starting the wake-up mode in combination with the user's sleep quality data and the user portrait includes:

[0100] S510, obtaining the type of multimedia content preferred by the user according to the pre-built user portrait;

[0101] S520, generating multimedia content that meets the user's preferences as target multimedia content using a pre-trained artificial intelligence model according to the user's sleep quality data;

[0102] S530: Play the target multimedia content.

[0103] By obtaining the type of multimedia content preferred by the user, multimedia content that meets the user's preferences can be intelligently generated, such as music, sound effects or animations to wake up the user. Different users have different preferences. Therefore, this application has a personalized wake-up mode to provide a better user experience.

[0104] In a specific implementation scenario, the construction of user portraits can be achieved by analyzing the user's listening behavior on the music platform (such as playlists, favorite songs, etc.) to obtain the user's listening habits, music type preferences, and listening time, and analyzing the viewing behavior on the video playback platform (such as the most played videos, favorite videos, etc.) to obtain the animations that the user may like, etc., all of which can be used as content recorded in the user portrait. Based on the user portrait, the type of multimedia content preferred by the user can be obtained, such as soothing music, energetic music, natural sound effects, science fiction sound effects, game music, cartoon animations, or educational animations.

[0105] The user's sleep quality data represents the user's sleep quality, such as sleep duration, sleep depth, number of tossing and turning, breathing frequency, etc. which are related to sleep quality. Based on these sleep quality data, the user's sleep quality can be identified. For example, if the number of tossing and turning exceeds a preset value, it is identified that the user's sleep quality is poor.

[0106] The artificial intelligence model is trained by collecting a large amount of sleep quality data and labeled multimedia content. The trained artificial intelligence model can push and output personalized multimedia content based on the user's sleep quality data. For example, during sleep, it is detected that the user's deep sleep stage lasts for a short time and frequently enters the light sleep stage. This may indicate poor sleep quality. The artificial intelligence model is used to identify that the deep sleep stage lasts for a short time and frequent entry into the light sleep stage are poor sleep quality, and outputs music with a poor sleep quality label that meets the user's preferences. For example, a light music can be pushed or soft natural sound effects can be generated to help users transition from sleep to a natural wakeful state, providing a better user experience.

[0107] Among them, music that meets user preferences can be recommended based on the similarity between users of the smart alarm clock. If two users show high consistency in past interactions, the smart alarm clock will recommend music that is liked by at least one similar user to the other user.

[0108] In an optional embodiment of the present application, the step of starting the wake-up mode in combination with the user's sleep quality data and the user portrait further includes:

[0109] S540: Control the brightness of the light to gradually increase, or control the brightness and color of the light to change as the music or sound effects of the target multimedia content change.

[0110] By controlling the lights and multimedia content to wake up users, the personalized experience is enhanced, a positive and comfortable atmosphere is created, and a better user experience is provided.

[0111] In a specific implementation scenario, the morning sunlight can be simulated and the light can be controlled to gradually become stronger. This can be achieved using a breathing light. By outputting a PWM signal and adjusting the duty cycle of the PWM signal, the brightness change of the breathing light can be controlled. For example, a periodically changing PWM signal is set, in which the duty cycle gradually increases from 0% to 100%, and then gradually decreases to 0%, to simulate the effect of breathing. This cycle can be set to a few seconds to match the transition of the human body from sleep to wakefulness.

[0112] For color change, a three-color light-emitting diode integrating three colors can be used, which can be achieved by adjusting the PWM duty cycle of the red, green and blue channels of the three-color light-emitting diode. For example, when simulating the sunrise effect, the duty cycle of red and green can be gradually increased, and the duty cycle of blue can be reduced to produce changes from dark to bright and from cold colors to warm colors.

[0113] For the brightness and color of lights to change with the music or sound effects of multimedia content, the rhythm of the music can be extracted to control the color change and brightness of the lights in synchronization with the rhythm of the music, the rhythm information of the music can be matched with the control signal of the lights in time, or a timer can be used to control the changes of the lights to achieve consistency between the lighting effects and the rhythm of the music.

[0114] In step S140, regarding the weather conditions at the user's location, the smart alarm clock may be integrated with a weather API to obtain the weather conditions at the user's location. The smart alarm clock may adjust the preset schedule reminder time and preset schedule reminder content according to the weather conditions, such as reminding the user to bring an umbrella on rainy days and reminding the user to keep warm when the temperature is low. The smart alarm clock also integrates a map API to obtain real-time traffic conditions and provide travel suggestions to users, such as suggesting to go out early during peak traffic hours to ensure that the user has enough time to prepare.

[0115] The preset schedule reminder content can be manually input by the user in advance through the mobile phone application, or voice input, etc. The reminder method of the preset schedule reminder content can be voice broadcast, vibration, a pop-up reminder window on the display, etc.

[0116] In an optional embodiment of the present application, the control method of the smart alarm clock further includes:

[0117] Collect users’ daily behavior data;

[0118] Based on behavioral data, establish a user behavior pattern model to predict what items users need to carry in specific scenarios;

[0119] Monitor whether the user is carrying items;

[0120] When it is detected that the user is in the exit area and does not carry the predicted items, a reminder notification is automatically issued to prompt the user to carry the predicted items.

[0121] Specifically, a camera can be built into the smart alarm clock to capture and collect the user's daily behavior data, such as the items they often carry. The user behavior pattern model established by the machine learning algorithm can be used to analyze the user's behavior pattern and identify the user's fixed habits and items they often carry when going out. For example, it can be learned that the user usually carries a mobile phone, keys, and wallet when going out every morning. Therefore, by learning the user's daily behavior data, when the user is in the going-out area and does not carry the predicted items, the user is reminded to carry the corresponding items, which has the function of reminding forgotten items.

[0122] In an optional embodiment of the present application, the control method of the smart alarm clock further includes:

[0123] Detecting users in sleeping areas through a microwave radar module;

[0124] If the user is detected lying down after the preset alarm time, multimedia content that meets the user's preferences is played.

[0125] The multimedia content preferred by the user can increase the attractiveness of the wake-up call and reduce the possibility of staying in bed. The multimedia content preferred by the user can be synchronized with the user's favorite animations and sounds to the smart alarm clock through the mobile phone application, such as playing the user's favorite game music or special reminders of animation characters, playing the user's favorite animations, and playing corresponding music at the same time, etc., to achieve personalized wake-up.

[0126] In an optional embodiment of the present application, the control method of the smart alarm clock further includes:

[0127] Controls the display of solar term information, which includes solar term introductions, traditional customs of solar terms, and health management suggestions for solar terms.

[0128] By displaying solar term information, we can promote traditional culture and provide people with guidance on how to take care of their bodies, diet and daily life in different seasons. Adjusting lifestyles and eating habits according to changes in solar terms will help maintain good health and adapt to changes in the natural environment.

[0129] In an optional embodiment of the present application, the control method of the smart alarm clock further includes:

[0130] Detecting the user's posture in the sleeping area through a microwave radar module;

[0131] If the microwave radar module detects that the user stands up and moves, the light will be turned on;

[0132] If the microwave radar module detects that the user is lying down, the light will be turned off.

[0133] The user's posture is detected by the microwave radar module, and the light is then turned on or off. This helps the user avoid groping in the dark when getting up at night and improves the convenience of getting up. The light can be turned off after the user lies down, without manual operation. It is easy to operate, energy-saving and environmentally friendly.

[0134] In an optional embodiment of the present application, the control method of the smart alarm clock further includes:

[0135] Control the playback of interesting photo albums, interesting music and / or interesting stories.

[0136] Specifically, the smart alarm clock can classify and identify themes based on personal photos uploaded by users, automatically generate personalized albums, and display the user's fun albums as dynamic backgrounds, which are automatically updated with time and seasons to increase the fun of life.

[0137] Fun music can be automatically played according to the user's music preferences, which can not only wake up the user but also have a soothing psychological effect; users can use AI music creation products such as Sponge Music to input a sentence of inspiration or lyrics to quickly generate personalized music.

[0138] Interesting stories can be generated based on the user's interests and preferences to provide users with a personalized auditory experience, or the smart alarm clock can integrate all teaching materials from the first grade of elementary school to high school, providing services for listening to stories and teaching materials.

[0139] Smart alarm clocks can also learn users' daily behavior patterns through machine learning algorithms, predict users' needs, and provide personalized wake-up services; smart alarm clocks can communicate with users in simple ways, such as asking about weather conditions, news information, etc. when the alarm rings, and give corresponding answers immediately.

[0140] refer to Figures 6 to 8 The embodiment of the present application also provides a smart alarm clock, which is controlled by the above-mentioned control method of the smart alarm clock. The smart alarm clock includes a main control module 110, a microwave radar module 120, a sound module 140 and a display module 130. The main control module 110 is connected to the microwave radar module 120, the display module 130, and the sound module 140.

[0141] The microwave radar module 120 is used to monitor and obtain the sleep quality data of the user in the sleeping area in real time;

[0142] The main control module 110 is used to control the display module 130 and / or the generating module to output a sleep quality report and corresponding sleep suggestions based on the acquired sleep quality data; it is also used to start the wake-up mode according to the user's sleep status before the preset alarm time; it is also used to adjust the preset schedule reminder time and the preset schedule reminder content according to the weather conditions and real-time traffic conditions at the user's location, and control the sound module 140 to output the adjusted preset schedule reminder content at the adjusted preset schedule reminder time.

[0143] The main control module 110 is specifically used to analyze the user's sleep state, determine the user's sleep cycle, determine whether the time difference between the current time and the preset alarm time is less than a preset value, and determine whether the user is in the light sleep stage of the sleep cycle. If the time difference is less than the preset value and the user is in the light sleep stage of the sleep cycle, the wake-up mode is started in combination with the user's sleep quality data and user portrait.

[0144] The main control module 110 is also specifically used to obtain the type of multimedia content preferred by the user from a pre-built user portrait, the multimedia content including music, sound effects and / or animation, and use an artificial intelligence model to generate multimedia content that meets the user's preferences as target multimedia content based on the user's sleep quality data; and control the display module 130 and / or the sound module 140 to play the target multimedia content.

[0145] The main control module 110 is also specifically used to obtain the user's original physiological data, extract features related to the sleep stages from the original physiological data, use a deep learning model to analyze the extracted features, identify different sleep stages, analyze continuous sleep stages, and determine the user's sleep cycle.

[0146] The main control is also specifically used to extract the user's original physiological data from the Doppler frequency shift information; extract the user's position and the user's position change characteristics from the distance information; obtain the time corresponding to the position change characteristics; and process the original physiological data, position change characteristics, and the time corresponding to the position change characteristics to obtain sleep quality data.

[0147] The smart alarm clock also includes a camera module 160 for capturing the user's daily behavior data. The main control module 110 is also used to establish a user behavior pattern model based on the user's daily behavior data to predict the items that the user needs to carry in a specific scenario. When it is detected that the user is in the exit area and does not carry the predicted items, the sound module 140 is controlled to automatically issue a reminder notification to prompt the user to carry the predicted items.

[0148] The main control module 110 is also used to control the display module 130 to display solar term information, which includes solar term introductions, traditional customs of solar terms, and health management suggestions for solar terms.

[0149] The smart alarm clock also includes a light emitting module 150, and the main control module 110 is also used to control the light emitting module 150 to turn on or off, so as to turn on or off the light.

[0150] refer to Figures 6 to 8 The smart alarm clock also includes a shell 170 and a circuit board 180. The circuit board 180 is arranged in the shell 170. The microwave radar module 120, the main control module 110, the display module 130, the sound module 140, the light emitting module 150 and the camera module 160 are all arranged on the circuit board 180. The display module 130 is located on the front side of the shell 170 and is exposed to the shell 170. The microwave radar module 120, the light emitting module 150 and the camera module 160 are all located on the front side of the shell 170.

[0151] In actual applications, the light emitting module 150 may be disposed around the display module 130 .

[0152] The smart alarm clock has the same technical effect as the control method of the smart alarm clock mentioned above, which will not be described in detail here.

[0153] See also Fig. 9 , Fig. 9 2 is a block diagram of an embodiment of the smart alarm clock provided by the present invention. The smart alarm clock includes a processor 210 and a memory 220. The processor 210 is coupled to the memory 220. The memory 220 stores a computer program 310, and the processor 210 executes the computer program 310 to implement the above method when working. The detailed steps can be referred to above, and will not be repeated here.

[0154] See also Fig.10 , Fig.10 3 is a block diagram of an embodiment of a computer-readable storage medium provided by the present invention. The computer-readable storage medium stores at least one computer program 310, which is used to be executed by the processor 210 to implement the above method. The detailed steps can be referred to above and will not be repeated here. In one embodiment, the computer-readable storage medium can be a storage chip, a hard disk, or a mobile hard disk or a USB flash drive, a CD, or other readable and writable storage tools in the terminal, or a server, etc.

[0155] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be completed by instructing the relevant hardware through a computer program, and the program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in the present application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0156] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0157] It should be understood that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. For those skilled in the art, the technical solutions described in the above embodiments can be modified, or some of the technical features therein can be replaced by equivalents; and all these modifications and replacements should fall within the protection scope of the claims attached to the present invention.

Claims

1. A method for controlling an intelligent alarm clock, characterized in that: The control method of the intelligent alarm clock comprises: Real-time monitoring to obtain the sleep quality data of the user in the sleeping area; Output a sleep quality report and corresponding sleep suggestions based on the acquired sleep quality data; Before the preset alarm time, the wake-up mode is activated according to the user's sleep state; Adjust the preset schedule reminder time and preset schedule reminder content according to the weather conditions and real-time traffic conditions at the user's location; The adjusted preset schedule reminder content is outputted at the adjusted preset schedule reminder time.

2. The control method of the smart alarm clock according to claim 1, characterized in that: The step of starting the wake-up mode according to the user's sleeping state includes: Analyze the user's sleeping state and determine the user's sleep cycle; Determine whether the time difference between the current time and the preset alarm time is less than a preset value, and determine whether the user is in the light sleep stage of the sleep cycle. If the time difference is less than the preset value and the user is in the light sleep stage of the sleep cycle, the wake-up mode is started in combination with the user's sleep quality data and user portrait.

3. The control method of the smart alarm clock according to claim 2, characterized in that: The step of starting the wake-up mode in combination with the user's sleep quality data and the user portrait includes: Based on the pre-built user profile, obtain the type of multimedia content preferred by the user; Generate multimedia content that meets the user's preferences as target multimedia content using an artificial intelligence model based on the user's sleep quality data; The target multimedia content is played.

4. The control method of the smart alarm clock according to claim 3, characterized in that: The step of starting the wake-up mode in combination with the user's sleep quality data and the user portrait also includes: The brightness of the light is controlled to be gradually increased, or the brightness and color of the light are controlled to change as the target multimedia content changes.

5. The control method of the smart alarm clock according to claim 2, characterized in that: The step of analyzing the user's sleep state and determining the user's sleep cycle includes: Obtain the user's original physiological data; extracting features related to sleep stages from the raw physiological data; Using deep learning models, the extracted features are analyzed to identify different sleep stages; Analyzes consecutive sleep stages to determine the user's sleep cycle.

6. The control method of the smart alarm clock according to claim 1, characterized in that: The step of acquiring the sleep quality data of the user in the sleeping area through real-time monitoring by the microwave radar module includes: The microwave radar module continuously sends microwave signals to the sleeping area and receives reflected microwave signals, and converts the reflected microwave signals into digital signals to obtain Doppler frequency shift information and the distance between the user and the smart alarm clock; Extracting original physiological data of the user from the Doppler frequency shift information; Extracting the user's location and the user's location change characteristics from the distance information; Get the time corresponding to the position change feature; The original physiological data, the position change characteristics and the time corresponding to the position change characteristics are processed to obtain sleep quality data.

7. The control method of the smart alarm clock according to claim 1, characterized in that: The control method of the intelligent alarm clock also includes: Collect users’ daily behavior data; Based on the daily behavior data, a user behavior pattern model is established to predict the items that the user needs to carry in a specific scenario; monitoring whether the user carries the item; When it is detected that the user is in the exit area and is not carrying the predicted items, a reminder notification is automatically issued.

8. The control method of the smart alarm clock according to claim 1, characterized in that: The control method of the intelligent alarm clock also includes: Control and display solar term information, wherein the solar term information includes solar term introduction, traditional customs of solar terms, and health management suggestions for solar terms.

9. The control method of the smart alarm clock according to claim 1, characterized in that: The control method of the intelligent alarm clock also includes: Detecting the user's posture in the sleeping area through a microwave radar module; If the microwave radar module detects that the user stands up and moves, the light will be turned on; If the microwave radar module detects that the user is lying down, the light will be turned off.

10. A smart alarm clock, characterized in that: The control method of the smart alarm clock according to any one of claims 1 to 9 is applied for control, wherein the smart alarm clock comprises a microwave radar module, a main control module, a sound module and a display module, wherein the main control module is connected to the microwave radar module, the display module and the sound module, wherein: The microwave radar module is used to monitor and obtain the sleep quality data of the user in the sleeping area in real time; The main control module is used to control the display module and / or the generating module to output a sleep quality report and corresponding sleep suggestions based on the acquired sleep quality data; it is also used to start the wake-up mode according to the user's sleep status before the preset alarm time; it is also used to adjust the preset schedule reminder time and the preset schedule reminder content according to the weather conditions and real-time traffic conditions at the user's location, and control the sound module to output the adjusted preset schedule reminder content at the adjusted preset schedule reminder time.

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