This invention relates to a cloud server and machine learning based system for snore monitoring.
Background of the Invention
Snore monitoring is the primary requirement for the users who suffer with snoring. As snoring affects the quality and quantity of sleep, for both snorers and co-sleepers. The real-time analysis of snoring assists the user to find the reason behind it. Moreover, a cloud server-based visualization and machine learning based analysis have significant impact of real-time snore monitoring.
US20170361044A1 discloses Methods and apparatus for treating a respiratory disorder, in one aspect, include an apparatus that delivers backup breaths at a sustained timed backup rate that is a function of the patient's spontaneous respiratory rate. Other aspects include apparatus that delivers backup breaths at a rate that gradually increases from a spontaneous backup rate to a sustained timed backup rate or, alternatively, apparatus that oscillates a treatment pressure in antiphase with the patient's spontaneous respiratory efforts when a measure indicative of ventilation is greater than a threshold. Other aspects include apparatus configured to treat Cheyne-Stokes respiration by computing the treatment pressure so as to bring a measure indicative of ventilation of the patient towards a target ventilation that is dependent on the measure indicative of ventilation or, alternatively, by periodically elevating the treatment pressure to a high level for a short time, the high level being high enough and the short time being long enough to induce a central apnea in a patient. Depending on functionality, the foregoing apparatus may comprise an adaptive servo-ventilator or CPAP therapy device.
Research Gap:
? Real-time monitoring and detection of snoring is required to be explored.
? Communication based system is lacking for further analysis
US7246619B2 discloses Method and apparatus for detecting disordered breathing in a patient and, in particular, to a method and apparatus for detecting patient snoring and/or for dynamically determining a snore detection threshold, and to a pressure support system and method of providing pressure support that uses this unique snore detection and/or snore detection dynamic adjustment technique to control the pressure provided to at patient.
Research Gap:
• Wireless communication powered system is not covered in this invention.
• Sensor based mechanism is unavailable in this invention.
None of the prior art indicate above either alone or in combination with one another disclose what the present invention has disclosed. Present invention is < >
SUMMARY OF THE INVENTION
This summary is provided to introduce a selection of concepts, in a simplified format, that are further described in the detailed description of the invention.
This summary is neither intended to identify key or essential inventive concepts of the invention and nor is it intended for determining the scope of the invention.
In this invention, a system is implemented for monitoring and analyzing the snore of a user during sleep. The proposed system i.e., snore monitoring mote (90) is embedded to the table near by the bed as shown in the figure.1. Here the snore monitoring mote is primary unit that senses the snoring of the user through microphone (13). The microphone module (13) it is able to sense the snoring sounds of the user clearly. The computing unit (10) in the snore monitoring mote is trained with machine learning model to recognize the snoring and type of snoring of the user. The pretrained machine learning (ML) model (12) connected to computing unit smoothly process the identification of exact snoring and type of snoring with the help of co-processor (11). If the snoring monitoring mote detects that the user is extremely snoring, the computing unit requests the portable device connected to the user to wake up the user by triggering via Bluetooth 5.0 communication provided by the ESP32 module (14). Here user is wake up with the help of vibrating motor (22) connect to it. ESP 32 (14) is hybrid module as it is inbuilt with multiple communication protocol like Bluetooth and Wi-Fi module. This module provides the snoring monitoring mote to transmit data on both communication protocols. The Wi-Fi module communicates the information on the cloud server and the complete analysis of snoring will be observed through cloud server (30). This indeed assists the user to overcome the snoring problem quickly by analyzing it in real time. Snore monitoring mote (90) is provided with dual power supply like battery and external power source (15) and wearable device (91) is powered with battery power supply (24).
To further clarify advantages and features of the present invention, a more particular description of the invention will be rendered by reference to specific embodiments thereof, which is illustrated in the appended drawings. It is appreciated that these drawings depict only typical embodiments of the invention and are therefore not to be considered limiting of its scope. The invention will be described and explained with additional specificity and detail with the accompanying drawings.
BRIEF DESCRIPTION OF THE DRAWINGS
The illustrated embodiments of the subject matter will be understood by reference to the drawings, wherein like parts are designated by like numerals throughout. The following description is intended only by way of example, and simply illustrates certain selected embodiments of devices, systems, and methods that are consistent with the subject matter as claimed herein, wherein:
Figure 1. Architecture of real-time system for monitoring the snoring
The figures depict embodiments of the present subject matter for the purposes of illustration only. A person skilled in the art will easily recognize from the following description that alternative embodiments of the structures and methods illustrated herein may be employed without departing from the principles of the disclosure described herein.
DETAILED DESCRIPTION OF THE INVENTION
The detailed description of various exemplary embodiments of the disclosure is described herein with reference to the accompanying drawings. It should be noted that the embodiments are described herein in such details as to clearly communicate the disclosure. However, the amount of details provided herein is not intended to limit the anticipated variations of embodiments; on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the scope of the present disclosure as defined by the appended claims.
It is also to be understood that various arrangements may be devised that, although not explicitly described or shown herein, embody the principles of the present disclosure. Moreover, all statements herein reciting principles, aspects, and embodiments of the present disclosure, as well as specific examples, are intended to encompass equivalents thereof.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments. As used herein, the singular forms “a",” “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises,” “comprising,” “includes” and/or “including,” when used herein, specify the presence of stated features, integers, steps, operations, elements and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and/or groups thereof.
It should also be noted that in some alternative implementations, the functions/acts noted may occur out of the order noted in the figures. For example, two figures shown in succession may, in fact, be executed concurrently or may sometimes be executed in the reverse order, depending upon the functionality/acts involved.
In addition, the descriptions of "first", "second", “third”, and the like in the present invention are used for the purpose of description only, and are not to be construed as indicating or implying their relative importance or implicitly indicating the number of technical features indicated. Thus, features defining "first" and "second" may include at least one of the features, either explicitly or implicitly.
Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which example embodiments belong. It will be further understood that terms, e.g., those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
These and other advantages of the present subject matter would be described in greater detail with reference to the following figures. It should be noted that the description merely illustrates the principles of the present subject matter. It will thus be appreciated that those skilled in the art will be able to devise various arrangements that, although not explicitly described herein, embody the principles of the present subject matter and are included within its scope.
Best Method of working:
Disclosed herein a cloud server and machine learning based system for snore monitoring comprises snore monitoring mote (90), microphone (13), computing unit (10), machine learning (ML) model (12), co-processor (11), ESP32 module (14), vibrating motor (22), cloud server (30), power source (15) and wearable device (91) is powered with battery power supply (24).
In another embodiment, snore monitoring mote (90) is embedded to the table near by the bed and the snore monitoring mote is primary unit that senses the snoring of the user through microphone (13).
In further embodiment, the microphone module (13) it is able to sense the snoring sounds of the user clearly; and the computing unit (10) in the snore monitoring mote is trained with machine learning model to recognize the snoring and type of snoring of the user.
In another embodiment, the pretrained machine learning (ML) model (12) connected to computing unit smoothly process the identification of exact snoring and type of snoring with the help of co-processor (11).
In another embodiment, If the snoring monitoring mote detects that the user is extremely snoring, the computing unit requests the portable device connected to the user to wake up the user by triggering via Bluetooth 5.0 communication provided by the ESP32 module (14).
In another embodiment, user is wake up with the help of vibrating motor (22) connect to it; and ESP 32 (14) is hybrid module as it is inbuilt with multiple communication protocol like Bluetooth and Wi-Fi module.
In another embodiment, this module provides the snoring monitoring mote to transmit data on both communication protocols; and the Wi-Fi module communicates the information on the cloud server and the complete analysis of snoring is observed through cloud server (30).
In another embodiment, this indeed assists the user to overcome the snoring problem quickly by analyzing it in real time; and Snore monitoring mote (90) is provided with dual power supply like battery and external power source (15) and wearable device (91) is powered with battery power supply (24).
ADVANTAGES OF THE INVENTION:
a. The proposed system assists to monitor the snoring during sleep.
b. The system is able to provide the real-time snoring status on cloud server.
c. The system also provides complete sleep pattern of the user and in addition it provides the levels of snoring clearly.
Novel Features of the Invention:
? Real-time based system for snore monitoring with ESP 32 module
? Machine learning and ESP 32 module-based computing unit for monitoring of snore in real-time.
? Cloud server based real-time analysis of snoring and sleeping of an individual.

We Claim:

1. A cloud server and machine learning based system for snore monitoring comprises snore monitoring mote (90), microphone (13), computing unit (10), machine learning (ML) model (12), co-processor (11), ESP32 module (14), vibrating motor (22), cloud server (30), power source (15) and wearable device (91) is powered with battery power supply (24).
2.The system as claimed in claim 1, wherein snore monitoring mote (90) is embedded to the table near by the bed and the snore monitoring mote is primary unit that senses the snoring of the user through microphone (13).
3. The system as claimed in claim 1, wherein the microphone module (13) it is able to sense the snoring sounds of the user clearly; and the computing unit (10) in the snore monitoring mote is trained with machine learning model to recognize the snoring and type of snoring of the user.
4. The system as claimed in claim 1, wherein the pretrained machine learning (ML) model (12) connected to computing unit smoothly process the identification of exact snoring and type of snoring with the help of co-processor (11).
5. The system as claimed in claim 1, wherein If the snoring monitoring mote detects that the user is extremely snoring, the computing unit requests the portable device connected to the user to wake up the user by triggering via Bluetooth 5.0 communication provided by the ESP32 module (14).
6. The system as claimed in claim 1, wherein user is wake up with the help of vibrating motor (22) connect to it; and ESP 32 (14) is hybrid module as it is inbuilt with multiple communication protocol like Bluetooth and Wi-Fi module.
7. The system as claimed in claim 1, wherein this module provides the snoring monitoring mote to transmit data on both communication protocols; and the Wi-Fi module communicates the information on the cloud server and the complete analysis of snoring is observed through cloud server (30).
8. The system as claimed in claim 1, wherein this indeed assists the user to overcome the snoring problem quickly by analyzing it in real time; and Snore monitoring mote (90) is provided with dual power supply like battery and external power source (15) and wearable device (91) is powered with battery power supply (24).