1. A method for controlling ambience based on sleep parameters, comprising the steps of: receiving input sleep parameters including sleep stage, heart rate, and respiratory rate; processing the input sleep parameters using an artificial intelligence model to determine an appropriate ambience control setting; controlling one or more ambience control devices based on the determined setting; and adjusting the ambience control setting as the sleep parameters change.

2. The method of claim 1, wherein the ambience control devices include lighting, temperature control, and audio playback.

3. The method of claim 1, wherein the artificial intelligence model is trained using a machine learning algorithm.

4. The method of claim 1, wherein the input sleep parameters are received from a wearable device.

5. The method of claim 1, wherein the ambience control setting is adjusted in real-time based on the detected changes in the sleep parameters.

6. A system for controlling ambience based on sleep parameters, comprising: one or more ambience control devices; a computer processor is configured to: receive input sleep parameters; process the input sleep parameters using an artificial intelligence model to determine an appropriate ambience control setting; control the one or more ambience control devices based on the determined setting; and adjusting the ambience control setting as the sleep parameters change; and a user interface for displaying the current ambience control setting and providing an option for the user to adjust the settings manually.

7. The system of claim 6, wherein the ambience control devices include lighting, temperature control, and audio playback.

8. The system of claim 6, wherein the artificial intelligence model is trained using a machine learning algorithm.

9. The system of claim 6, wherein the ambience control setting is adjusted in real-time based on the detected changes in the sleep parameters.

10. The system of claim 6, further comprising a feedback mechanism to improve the accuracy of the artificial intelligence model by receiving user feedback on the effectiveness of the ambience control settings and adjusting the model based on the feedback. AI BASED AMBIENCE CONTROL AS PER SLEEP PARAMETERS Abstract Adjusting the environment to fit a person's sleep needs may be included in the methods disclosed below. Input sleep metric collection may be a part of this method, which might include things like sleep stage, heart rate, and breathing rate. Other sleep input settings may be provided if needed. Embodiments may also make use of a model developed utilising artificial intelligence to analyse the input sleep parameters and find the optimal setting for the ambiance controller. Instead, the invention might be implemented by controlling a set of devices that modify the environment in accordance with the selected configuration. Embodiments may also have the ability to vary the ambiance control setting based on the user's current quality of sleep. , Claims:Claims :

1. A method for controlling ambience based on sleep parameters, comprising the steps of: receiving input sleep parameters including sleep stage, heart rate, and respiratory rate; processing the input sleep parameters using an artificial intelligence model to determine an appropriate ambience control setting; controlling one or more ambience control devices based on the determined setting; and adjusting the ambience control setting as the sleep parameters change.

2. The method of claim 1, wherein the ambience control devices include lighting, temperature control, and audio playback.

3. The method of claim 1, wherein the artificial intelligence model is trained using a machine learning algorithm.

4. The method of claim 1, wherein the input sleep parameters are received from a wearable device.

5. The method of claim 1, wherein the ambience control setting is adjusted in real-time based on the detected changes in the sleep parameters.

6. A system for controlling ambience based on sleep parameters, comprising: one or more ambience control devices; a computer processor is configured to: receive input sleep parameters; process the input sleep parameters using an artificial intelligence model to determine an appropriate ambience control setting; control the one or more ambience control devices based on the determined setting; and adjusting the ambience control setting as the sleep parameters change; and a user interface for displaying the current ambience control setting and providing an option for the user to adjust the settings manually.

7. The system of claim 6, wherein the ambience control devices include lighting, temperature control, and audio playback.

8. The system of claim 6, wherein the artificial intelligence model is trained using a machine learning algorithm.

9. The system of claim 6, wherein the ambience control setting is adjusted in real-time based on the detected changes in the sleep parameters.

10. The system of claim 6, further comprising a feedback mechanism to improve the accuracy of the artificial intelligence model by receiving user feedback on the effectiveness of the ambience control settings and adjusting the model based on the feedback.

Description:AI BASED AMBIENCE CONTROL AS PER SLEEP PARAMETERS
Field of the Invention
[0001] The invention relates to the field of sleep technology, particularly to the use of artificial intelligence (AI) algorithms to control the ambience of a sleep environment based on individual sleep parameters. The technology involves analyzing various sleep parameters, such as heart rate, respiratory rate, and body temperature, to determine the ideal ambient conditions for an individual's sleep.
Background
[0002] The background description includes information that may be useful in understanding the present invention. It is not an admission that any of the information provided herein is prior art or relevant to the presently claimed invention, or that any publication specifically or implicitly referenced is prior art.
[0003] AI-based ambience control as per sleep parameters is a technology that utilizes artificial intelligence algorithms to automatically adjust the ambient conditions in a room based on the sleep parameters of the user. The ambient conditions include factors such as temperature, lighting, and sound, which can have a significant impact on the quality of sleep. Conventionally, adjusting the ambient conditions for optimal sleep requires manual adjustment by the user or the use of pre-set programs. However, with the advancement of AI and machine learning, it is now possible to automatically adjust the ambient conditions based on the sleep parameters of the user.
[0004] AI-based ambience control involves using sensors and data analysis to collect information on the sleep parameters of the user, such as heart rate, body temperature, and sleep cycle. The AI algorithm analyses this data and adjusts the ambient conditions in the room accordingly. For example, if the user's body temperature is high, the AI algorithm may adjust the temperature of the room to a cooler setting to promote better sleep.
[0005] One example of AI-based ambience control is the "Sleep Smart" system developed by researchers at the Massachusetts Institute of Technology (MIT). The system uses a combination of sensors and machine learning algorithms to monitor the sleep parameters of the user and adjust the ambient conditions in the room accordingly. The system can adjust the lighting, temperature, and sound levels in the room to create an optimal sleeping environment. Another example is the "Nokia Sleep" system, which is a sleep monitoring system that utilizes sensors and AI algorithms to monitor the sleep parameters of the user and adjust the ambient conditions in the room. The system can also integrate with other smart home devices to provide a more comprehensive sleep experience.
[0006] AI-based ambience control as per sleep parameters has several advantages over traditional methods of adjusting ambient conditions for sleep. It provides a more personalized and customized experience for the user, as the ambient conditions can be adjusted based on the user's specific sleep parameters. It also eliminates the need for manual adjustment, making it a more convenient and effortless way to achieve optimal sleep. Overall, AI-based ambience control as per sleep parameters is an exciting development in the field of sleep technology. It has the potential to revolutionize the way we approach sleep and create a more personalized and optimized sleeping environment for everyone. Few of the associated prior arts are listed below.
[0007] CN112283884A (By: GUANGDONG MIDEA REFRIGERATION EQUIPMENT, MIDEA GROUP) The invention discloses an atmosphere lamp control method and device of an air conditioner, the air conditioner and a readable storage medium. The method comprises the steps of determining the stage of current sleep operation control in a sleep curve when the air conditioner carries out the sleep operation control according to the sleep curve; generating a corresponding driving curve according tothe current stage; controlling an atmosphere lamp on the air conditioner according to the corresponding driving curve. Therefore, the atmosphere lamp is arranged on the air conditioner, the corresponding driving curve is generated based on the sleep curve, and the atmosphere lamp is controlled according to the corresponding driving curve so that the sleep of a user can be facilitated, and the sleep pressure of the user is relieved. CN113310194B (By: QINGDAO HAIER AIR CONDITIONER GENERAL, HAIER SMART HOME) The invention provides a sleep environment intelligent adjusting method and a sleep environment adjusting system. The sleep environment intelligent adjusting method comprises the steps that a sleep trend curve of a target user is obtained, and the sleep trend curve stipulates time points and duration of all sleep stages; acquiring initial target parameters of a sleep environment; setting a stage target parameter of each sleep stage according to the initial target parameters; after a sleep mode is started, environment adjusting equipment in the sleep environment is controlled to operate according to the stage target parameters of all the sleep stages. According to the Sleep environment intelligent adjusting method and sleep environment adjusting system, after the sleep mode is started, environment adjusting equipment in the sleep environment is controlled to operate according to the stage target parameters of all the sleep stages, all the environment parameters correspondingly change along with a sleep trend of a user and are not limited to a temperature and humidity adjustment, the comfort requirement of the user in the sleep process is comprehensively met, and the intelligent level of an intelligent household electrical appliance is improved. US9993195B2 (By: PHILIPS) The invention relates to a sleep disturbance monitoring apparatus (1) for monitoring a sleep disturbance of a person. An ambience disturbance profile, which describes which levels and/or changes of an ambient signal, which is, for example, a temperature signal or a noise signal, are related to disturbed sleep, is amended depending on a correlation between the ambience signal and a sleep signal which is indicative of the quality of the sleep of the person. After the ambience disturbance profile has been amended, an environmental disturbance factor, which disturbs the sleep, is determined based on a comparison of an actual ambient signal with the amended ambience disturbance profile, wherein information regarding the determined environmental disturbance factor is output to the person on an output unit. This allows providing personalized information regarding environmental sleep disturbance factors, i.e. the information considers the individual susceptibility of a person for environmental disturbances during sleep.
[0008] Even though, AI based ambience control has contributed a lot, the AI-based ambience control is the potential for bias in the data sets used to train the machine learning models. AI systems rely on large data sets to learn patterns and make decisions, but if these data sets are biased, the system may make inaccurate or unfair decisions. For example, if the data set used to train an AI-based ambience control system is biased towards a certain demographic or location, the system may not be able to accurately control the environment for a more diverse population.
[0009] Another potential limitation is the ethical considerations surrounding the use of AI-based ambience control systems. As these systems become more sophisticated, they may have access to sensitive data such as personal preferences, health information, and behavior patterns. This raises concerns about privacy, security, and the potential for misuse of this data. Additionally, there may be ethical considerations around the use of AI-based ambience control systems in certain environments, such as healthcare facilities or prisons.

Lastly, the integration of AI-based ambience control systems with existing infrastructure and technology can also present a limitation. Many buildings and environments were not designed with AI-based systems in mind, and retrofitting them with the necessary hardware and software can be complex and costly. Additionally, integrating these systems with other technologies such as smart home devices or Internet of Things (IoT) devices may present compatibility and security challenges.Thus a further advancement in this field of technology is required.
[00010] All references, including publications, patent applications, and patents, cited herein are hereby incorporated by reference to the same extent as if each reference were individually and specifically indicated to be incorporated by reference and were set forth in its entirety herein.
[00011] It also shall be noted that as used herein and in the appended claims, the singular forms “a”, “an”, and “the” include plural referents unless the context clearly dictates otherwise. This invention can be achieved by means of hardware including several different elements or by means of a suitably programmed computer. In the unit claims that list several means, several ones among these means can be specifically embodied in the same hardware item. The use of such words as first, second, third does not represent any order, which can be simply explained as names.
Summary
[00012] The following presents a simplified summary of various aspects of this disclosure in order to provide a basic understanding of such aspects. This summary is not an extensive overview of all contemplated aspects, and is intended to neither identify key or critical elements nor delineate the scope of such aspects. Its purpose is to present some concepts of this disclosure in a simplified form as a prelude to the more detailed description that is presented later.
[00013] The following paragraphs provide additional support for the claims of the subject application.
[00014] The invention relates to the field of sleep technology, particularly to the use of artificial intelligence (AI) algorithms to control the ambience of a sleep environment based on individual sleep parameters. The technology involves analyzing various sleep parameters, such as heart rate, respiratory rate, and body temperature, to determine the ideal ambient conditions for an individual's sleep.
[00015] Embodiments of the present disclosure may include a method for controlling ambience based on sleep parameters, including the steps of receiving input sleep parameters including sleep stage, heart rate, and respiratory rate. Embodiments may also include processing the input sleep parameters using an artificial intelligence model to determine an appropriate ambience control setting. Embodiments may also include controlling one or more ambience control devices based on the determined setting. Embodiments may also include adjusting the ambience control setting as the sleep parameters change.
[00016] In some embodiments, the ambience control devices include lighting, temperature control, and audio playback. In some embodiments, the artificial intelligence model may be trained using a machine learning algorithm. In some embodiments, the input sleep parameters may be received from a wearable device. In some embodiments, the ambience control setting may be adjusted in real-time based on the detected changes in the sleep parameters.
[00017] Embodiments of the present disclosure may also include a system for controlling ambience based on sleep parameters, wherein the system including one or more ambience control devices. Embodiments may also include a computer processor that may be configured to receive input sleep parameters. Embodiments may also include processing of the input sleep parameters using an artificial intelligence model to determine an appropriate ambience control setting.
[00018] Embodiments may also include controlling of the one or more ambience control devices based on the determined setting. Embodiments may also include adjusting the ambience control setting as the sleep parameters change. Embodiments may also include a user interface for displaying the current ambience control setting and providing an option for the user to adjust the settings manually.
[00019] In some embodiments, the artificial intelligence model may be trained using a machine learning algorithm. In some embodiments, the ambience control setting may be adjusted in real-time based on the detected changes in the sleep parameters. In some embodiments, the system may include a feedback mechanism to improve the accuracy of the artificial intelligence model by receiving user feedback on the effectiveness of the ambience control settings and adjusting the model based on the feedback. In some embodiments, the ambience control setting may be automatically adjusted based on a predetermined schedule or the user's sleep pattern.
Brief Description of the Drawings
[00020] The features and advantages of the present disclosure would be more clearly understood from the following description taken in conjunction with the accompanying drawings in which:
[00021] FIG. 1 is a flowchart illustrating a method for controlling ambience, according to some embodiments of the present disclosure.
[00022] FIG. 2 is a block diagram illustrating a system for controlling ambience based on sleep parameters, according to some embodiments of the present disclosure.
Detailed Description
[00023] In the following detailed description of the invention, reference is made to the accompanying drawings that form a part hereof, and in which is shown, by way of illustration, specific embodiments in which the invention may be practiced. In the drawings, like numerals describe substantially similar components throughout the several views. These embodiments are described in sufficient detail to claim those skilled in the art to practice the invention. Other embodiments may be utilized and structural, logical, and electrical changes may be made without departing from the scope of the present invention. The following detailed description is, therefore, not to be taken in a limiting sense, and the scope of the present invention is defined only by the appended claims and equivalents thereof.
[00024] The use of the terms “a” and “an” and “the” and “at least one” and similar referents in the context of describing the invention (especially in the context of the following claims) are to be construed to cover both the singular and the plural, unless otherwise indicated herein or clearly contradicted by context. The use of the term “at least one” followed by a list of one or more items (for example, “at least one of A and B”) is to be construed to mean one item selected from the listed items (A or B) or any combination of two or more of the listed items (A and B), unless otherwise indicated herein or clearly contradicted by context. The terms “comprising,” “having,” “including,” and “containing” are to be construed as open-ended terms (i.e., meaning “including, but not limited to,”) unless otherwise noted. Recitation of ranges of values herein are merely intended to serve as a shorthand method of referring individually to each separate value falling within the range, unless otherwise indicated herein, and each separate value is incorporated into the specification as if it were individually recited herein. All methods described herein can be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The use of any and all examples, or exemplary language (e.g., “such as”) provided herein, is intended merely to better illuminate the invention and does not pose a limitation on the scope of the invention unless otherwise claimed. No language in the specification should be construed as indicating any non-claimed element as essential to the practice of the invention.
[00025] The invention relates to the field of sleep technology, particularly to the use of artificial intelligence (AI) algorithms to control the ambience of a sleep environment based on individual sleep parameters. The technology involves analyzing various sleep parameters, such as heart rate, respiratory rate, and body temperature, to determine the ideal ambient conditions for an individual's sleep.
[00026] A flowchart representation of the method for controlling ambience is shown in FIG. 1, which also contains a description of the method in accordance with different illustrative examples included in the current disclosure. Receiving input sleep metrics such as the stage of sleep, the heart rate, and the respiration rate are examples of what the method may consist of when it gets to step 110 of the technique in certain implementations of the method. During the 120th step of the process, the method may entail analysing the input sleep parameters using an artificial intelligence model in order to select an appropriate ambience control setting. The approach may entail controlling one or more devices that alter the atmosphere based on the setting that has been determined at step 130. In the event that the sleep settings are changed, it is possible that step 140 of the method will need an adjustment to be made to the ambience control setting.
[00027] The devices that regulate the environment could include things like lighting, temperature adjustment, and the playing of music in certain implementations. Other implementations might not contain any of these features. One of the many ways that the artificial intelligence model may be implemented is by training it with the assistance of a machine learning algorithm. Nevertheless, this is only one of the many possible approaches. If a wearable device is available, it may be used in certain implementations to collect the input sleep parameters. If this is the case, the phrase "input sleep parameters" will be used. In some implementations of the technology, adjustments to the configuration of the ambience control may be done in real time, based on the changes that have been observed in the characteristics of the user's sleep.
[00028] As a block diagram, the system 200 for controlling ambience based on sleep parameters is shown in FIG. 2, which also offers a description of the system 200 in line with different features of the present disclosure. In different configurations of the system 200, which may or may not include the presence of one or more ambience control devices 210, a computer processor 220 has the potential to be configured to carry out the following activities. There is a possibility that the user interface 222 will be located inside the computer processor 220. The current setting for the ambience control will be shown on this user interface 222, and the user will have the opportunity to manually adjust the settings. Using a model based on artificial intelligence, perform processing on the provided sleep parameters in order to determine the optimal setting for the ambience control. Operate the one or more devices utilised for ambience control based on the setting that has been decided. Adjusting the ambience control setting accordingly is recommended in light of the fact that the sleep characteristics are subject to change.
[00029] One of the many ways that the artificial intelligence model may be implemented is by training it with the assistance of a machine learning algorithm. Nevertheless, this is only one of the many possible approaches. In some implementations of the technology, adjustments to the configuration of the ambience control may be done in real time, based on the changes that have been observed in the characteristics of the user's sleep. A feedback mechanism for the aim of enhancing the precision of the artificial intelligence model may be included in some implementations of the system 200. This is because the system's primary goal is to learn from its past mistakes. This is performed by first requesting user input on the effectiveness of the ambiance control settings, and then updating the model in line with that feedback after it has been received. In some implementations, the ambience control setting may be updated in such a manner that it is changed automatically in response to the user's sleep pattern or a predetermined schedule.
[00030] The present invention relates to a system for controlling ambience based on sleep parameters is designed to provide a comfortable and relaxing sleep environment for users. It includes one or more ambience control devices, such as smart lights, smart speakers, or air conditioners, that can adjust the lighting, sound, temperature, and other environmental factors that can affect sleep quality. The system is designed to provide users with a comfortable and relaxing sleep environment that adapts to their individual sleep needs. By employing artificial intelligence to process sleep parameters and modify ambience control settings, the system can help users achieve better sleep quality and improve their overall health and well-being.
[00031] In an embodiment, the system is controlled by a computer processor that is configured to receive input sleep parameters from the user, such as bedtime, wake-up time, and desired sleep duration. The computer processor then processes these input sleep parameters using an artificial intelligence model to determine an appropriate ambience control setting. The artificial intelligence model may consider a variety of factors, including the time of day, the user's past sleep patterns, and environmental factors such as weather conditions and noise levels. The computer processor in the system for controlling ambience based on sleep parameters can use various input sleep parameters to determine an appropriate ambience control setting. For example, the processor can receive the user's bedtime, wake-up time, and desired sleep duration. Based on these parameters, the artificial intelligence model can determine an appropriate time to begin adjusting the ambience settings, such as gradually dimming the lights and lowering the volume of ambient noise.
[00032] Referring to the preceding embodiment, in addition to these sleep parameters, the system can also consider other factors that may affect the user's sleep quality. For example, the system may monitor the user's heart rate and respiratory rate during sleep and use this information to adjust the ambience settings accordingly. The system may also consider the user's sleep history, such as how long it takes them to fall asleep and how often they wake up during the night. Environmental factors can also be considered by the artificial intelligence model in determining an appropriate ambience control setting. For instance, if the weather is expected to be hot and humid, the system can adjust the temperature and humidity levels in the user's bedroom to optimize their sleep quality.
[00033] Referring to the preceding embodiment, similarly, if there are high levels of noise outside, the system can adjust the ambient noise levels in the user's bedroom to mask the external noise and create a more peaceful sleep environment. By considering all these factors and processing the input sleep parameters using an artificial intelligence model, the system can determine an appropriate ambience control setting that is tailored to the user's specific needs and preferences.
[00034] In an embodiment, based on the determined ambience control setting, the computer processor controls the one or more ambience control devices to create a comfortable and relaxing sleep environment for the user. For example, if the user has indicated that they have trouble falling asleep, the system may dim the lights, play soothing music, or white noise, and adjust the temperature to a cooler setting to create a more comfortable sleep environment. As the user's sleep parameters change, such as when they enter different stages of sleep, the system adjusts the ambience control setting to maintain an optimal sleep environment. For instance, if the user has a bedtime of 10 PM and a wake-up time of 6 AM, the system may gradually dim the lights in the bedroom starting at 9 PM to help the user wind down and prepare for sleep. In the morning, the system may gradually increase the brightness of the lights to mimic a sunrise and help the user wake up more naturally.
[00035] Referring to the preceding embodiment, if the user has indicated that they prefer a cooler sleep environment, the system may adjust the temperature in the bedroom to a cooler setting before bedtime and maintain that temperature throughout the night. Similarly, if the user has trouble falling asleep, the system may play soothing music or white noise to help the user relax and fall asleep more easily. If the user has a history of snoring or sleep apnoea, the system may adjust the bed position or elevation to help alleviate these issues. Further, if the user is sensitive to noise, the system may use noise-cancelling technology or adjust the sound environment to minimize external noises that may disrupt their sleep.
[00036] Referring to the preceding embodiment, the ambience control setting is adjusted in real-time based on the detected changes in the sleep parameters. For instance, if the user's heart rate increases during sleep, indicating that they are becoming more restless, the system may adjust the ambience control setting to increase the volume of the white noise or soothing music to help the user relax and fall back asleep. Similarly, if the user's body temperature drops during the night, the system may adjust the temperature setting to keep the user warm and comfortable without disrupting their sleep.
[00037] Referring to the preceding embodiment, another example could be if the user wakes up during the night and reports feeling anxious or stressed, the system may detect this change in sleep parameters and adjust the ambience control settings to provide calming music or scents to help the user relax and fall back asleep. By adjusting the ambience control setting in real-time based on changes in the user's sleep parameters, the system can create an optimal sleep environment and improve the user's overall sleep quality.
[00038] In an embodiment, the system also includes a user interface that displays the current ambience control setting and provides an option for the user to adjust the settings manually. The user interface may be a mobile application, a web application, or a physical control panel that allows the user to adjust the lighting, sound, temperature, and other environmental factors manually. The user interface may also provide feedback on the user's sleep quality, such as the number of hours slept and the quality of sleep, which can help the user adjust their sleep habits over time.
[00039] Referring to the preceding embodiment, the user interface of the system can display various types of feedback to the user regarding their sleep quality. For example, the user interface may display the number of hours the user slept the previous night, as well as the quality of their sleep based on metrics such as deep sleep, light sleep, and REM sleep. This information can help the user understand how well they are sleeping and adjust their sleep habits if necessary.
[00040] Referring to the preceding embodiment, additionally, the user interface may display trends in the user's sleep quality over time, allowing them to track their progress and make informed decisions about their sleep habits. For example, if the user notices that their sleep quality tends to be better on nights when they use a particular ambience control setting, they may choose to adjust their settings accordingly in the future. The user interface may also provide recommendations for improving sleep quality based on the user's sleep parameters and historical data. For example, if the user consistently wakes up feeling groggy, the system may recommend adjusting their bedtime or sleep duration to improve their overall sleep quality.
[00041]
[00042] The current disclosure may comprise a method for regulating ambiance based on sleep parameters. This method may include the steps of receiving input sleep parameters such as sleep stage, heart rate, and respiration rate. Other input sleep parameters may also be included. Processing the input sleep parameters using an artificial intelligence model to identify an optimal ambiance control setting is another possibility that may be included in embodiments. Controlling one or more devices that affect the atmosphere depending on the setting that has been selected may likewise be considered an embodiment. Altering the ambiance control setting in response to changes in the sleep characteristics is another possibility for embodiments.
[00043] The lighting, the temperature control, and the music playback are all examples of ambiance control devices that may be found in certain embodiments. There are a few different ways that the artificial intelligence model may be implemented, but one of them involves training it using a machine learning algorithm. In some implementations, the input sleep parameters may be obtained via a wearable device if it's available. Adjustments to the setting of the ambiance control may be made in real time, according on the identified changes in the sleep characteristics, in some embodiments of the technology.
[00044] A system for managing the ambiance based on sleep characteristics, wherein the ambiance may comprise one or more ambience control devices, is another component that may be included in embodiments of the current disclosure. A computer processor may also be included in certain embodiments, and this computer processor may be designed to take in user-supplied sleep settings. Processing the input sleep parameters using an artificial intelligence model to find an optimal ambiance control setting.
[00045] Controlling one or more ambiance control devices depending on the determined setting is another possibility that may be included in embodiments. Altering the ambiance control setting in response to changes in the sleep characteristics is another possibility for embodiments. In certain embodiments, there is also an option for there to be a user interface that displays the current setting for the ambiance control and gives the user the ability to manually modify the settings themselves.
[00046] There are a few different ways that the artificial intelligence model may be implemented, but one of them involves training it using a machine learning algorithm. Adjustments to the setting of the ambiance control may be made in real time, according on the identified changes in the sleep characteristics, in some embodiments of the technology. The system may, in some implementations, include a feedback mechanism for the purpose of improving the accuracy of the artificial intelligence model. This is accomplished by soliciting feedback from the user regarding the efficiency of the ambience control settings and then modifying the model in accordance with that feedback. In some implementations, the user's sleep pattern or a specified schedule may cause the ambiance control setting to be modified in such a way that it is automatically changed.
[00047] Example embodiments herein have been described above with reference to block diagrams and flowchart illustrations of methods and apparatuses. It will be understood that each block of the block diagrams and flowchart illustrations, and combinations of blocks in the block diagrams and flowchart illustrations, respectively, can be implemented by various means including hardware, software, firmware, and a combination thereof. For example, in one embodiment, each block of the block diagrams and flowchart illustrations, and combinations of blocks in the block diagrams and flowchart illustrations can be implemented by computer program instructions. These computer program instructions may be loaded onto a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions which execute on the computer or other programmable data processing apparatus create means for implementing the functions specified in the flowchart block or blocks.

[00048] Throughout the present disclosure, the term ‘Artificial intelligence (AI)’ as used herein relates to any mechanism or computationally intelligent system that combines knowledge, techniques, and methodologies for controlling a bot or other element within a computing environment. Furthermore, the artificial intelligence (AI) is configured to apply knowledge and that can adapt it-self and learn to do better in changing environments. Additionally, employing any computationally intelligent technique, the artificial intelligence (AI) is operable to adapt to unknown or changing environment for better performance. The artificial intelligence (AI) includes fuzzy logic engines, decision-making engines, preset targeting accuracy levels, and/or programmatically intelligent software.
[00049] Throughout the present disclosure, the term ‘processing means’ or ‘microprocessor’ or ‘processor’ or ‘processors’ includes, but is not limited to, a general purpose processor (such as, for example, a complex instruction set computing (CISC) microprocessor, a reduced instruction set computing (RISC) microprocessor, a very long instruction word (VLIW) microprocessor, a microprocessor implementing other types of instruction sets, or a microprocessor implementing a combination of types of instruction sets) or a specialized processor (such as, for example, an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), a digital signal processor (DSP), or a network processor).
[00050] The term “non-transitory storage device” or “storage” or “memory,” as used herein relates to a random access memory, read only memory and variants thereof, in which a computer can store data or software for any duration.
[00051] Operations in accordance with a variety of aspects of the disclosure is described above would not have to be performed in the precise order described. Rather, various steps can be handled in reverse order or simultaneously or not at all.
While several implementations have been described and illustrated herein, a variety of other means and/or structures for performing the function and/or obtaining the results and/or one or more of the advantages described herein may be utilized, and each of such variations and/or modifications is deemed to be within the scope of the implementations described herein. More generally, all parameters, dimensions, materials, and configurations described herein are meant to be exemplary and that the actual parameters, dimensions, materials, and/or configurations will depend upon the specific application or applications for which the teachings is/are used. Those skilled in the art will recognize, or be able to ascertain using no more than routine experimentation, many equivalents to the specific implementations described herein. It is, therefore, to be understood that the foregoing implementations are presented by way of example only and that, within the scope of the appended claims and equivalents thereto, implementations may be practiced otherwise than as specifically described and claimed. Implementations of the present disclosure are directed to each individual feature, system, article, material, kit, and/or method described herein. In addition, any combination of two or more such features, systems, articles, materials, kits, and/or methods, if such features, systems, articles, materials, kits, and/or methods are not mutually inconsistent, is included within the scope of the present disclosure.

Claims
I/We Claim:
1. A method for controlling ambience based on sleep parameters, comprising the steps of: receiving input sleep parameters including sleep stage, heart rate, and respiratory rate; processing the input sleep parameters using an artificial intelligence model to determine an appropriate ambience control setting; controlling one or more ambience control devices based on the determined setting; and adjusting the ambience control setting as the sleep parameters change.
2. The method of claim 1, wherein the ambience control devices include lighting, temperature control, and audio playback.
3. The method of claim 1, wherein the artificial intelligence model is trained using a machine learning algorithm.
4. The method of claim 1, wherein the input sleep parameters are received from a wearable device.
5. The method of claim 1, wherein the ambience control setting is adjusted in real-time based on the detected changes in the sleep parameters.
6. A system for controlling ambience based on sleep parameters, comprising: one or more ambience control devices; a computer processor is configured to: receive input sleep parameters; process the input sleep parameters using an artificial intelligence model to determine an appropriate ambience control setting; control the one or more ambience control devices based on the determined setting; and adjusting the ambience control setting as the sleep parameters change; and a user interface for displaying the current ambience control setting and providing an option for the user to adjust the settings manually.
7. The system of claim 6, wherein the ambience control devices include lighting, temperature control, and audio playback.
8. The system of claim 6, wherein the artificial intelligence model is trained using a machine learning algorithm.
9. The system of claim 6, wherein the ambience control setting is adjusted in real-time based on the detected changes in the sleep parameters.
10. The system of claim 6, further comprising a feedback mechanism to improve the accuracy of the artificial intelligence model by receiving user feedback on the effectiveness of the ambience control settings and adjusting the model based on the feedback.

AI BASED AMBIENCE CONTROL AS PER SLEEP PARAMETERS
Abstract
Adjusting the environment to fit a person's sleep needs may be included in the methods disclosed below. Input sleep metric collection may be a part of this method, which might include things like sleep stage, heart rate, and breathing rate. Other sleep input settings may be provided if needed. Embodiments may also make use of a model developed utilising artificial intelligence to analyse the input sleep parameters and find the optimal setting for the ambiance controller. Instead, the invention might be implemented by controlling a set of devices that modify the environment in accordance with the selected configuration. Embodiments may also have the ability to vary the ambiance control setting based on the user's current quality of sleep. , Claims:Claims
I/We Claim:
1. A method for controlling ambience based on sleep parameters, comprising the steps of: receiving input sleep parameters including sleep stage, heart rate, and respiratory rate; processing the input sleep parameters using an artificial intelligence model to determine an appropriate ambience control setting; controlling one or more ambience control devices based on the determined setting; and adjusting the ambience control setting as the sleep parameters change.
2. The method of claim 1, wherein the ambience control devices include lighting, temperature control, and audio playback.
3. The method of claim 1, wherein the artificial intelligence model is trained using a machine learning algorithm.
4. The method of claim 1, wherein the input sleep parameters are received from a wearable device.
5. The method of claim 1, wherein the ambience control setting is adjusted in real-time based on the detected changes in the sleep parameters.
6. A system for controlling ambience based on sleep parameters, comprising: one or more ambience control devices; a computer processor is configured to: receive input sleep parameters; process the input sleep parameters using an artificial intelligence model to determine an appropriate ambience control setting; control the one or more ambience control devices based on the determined setting; and adjusting the ambience control setting as the sleep parameters change; and a user interface for displaying the current ambience control setting and providing an option for the user to adjust the settings manually.
7. The system of claim 6, wherein the ambience control devices include lighting, temperature control, and audio playback.
8. The system of claim 6, wherein the artificial intelligence model is trained using a machine learning algorithm.
9. The system of claim 6, wherein the ambience control setting is adjusted in real-time based on the detected changes in the sleep parameters.
10. The system of claim 6, further comprising a feedback mechanism to improve the accuracy of the artificial intelligence model by receiving user feedback on the effectiveness of the ambience control settings and adjusting the model based on the feedback.