A system and a method for real-time environment monitoring and health tracking

Abstract

A system (100) for real-time environment monitoring and health tracking is provided. The system includes a wearable mask (110) adapted to fit on a user's face. A sensor unit (120) obtains a plurality of parameters from the user and surrounding environment. A receiving module (150) receives data from a plurality of sensors. A processing module (160) processes the data received from the plurality of sensors by utilizing an artificial intelligence model. A notification module (170) triggers an alert to a user device (270) if the fall detection sensor detects a sudden fall of the user, generates the alert to the user device if abnormal cough patterns are detected. A feedback module (180) transmits a health report of the user to the user device. A tracking module (185) enables the user to locate the wearable mask if misplaced by activating a buzzer positioned in the wearable mask via the user device.

Description

[0001] A SYSTEM AND A METHOD FOR REAL-TIME ENVIRONMENT MONITORING AND HEALTH TRACKING

[0002] EARLIEST PRIORITY DATE:

[0003] This Application claims priority from a Complete patent application filed in India having Patent Application No. 202421100144, filed on 17th day of December 2024, and titled “A SYSTEM AND A METHOD FOR REAL-TIME ENVIRONMENT MONITORING AND HEALTH TRACKING”.

[0004] FIELD OF INVENTION

[0005] Embodiments of the present disclosure relate to the field of face mask, and more particularly, a system and a method for real-time environment monitoring and health tracking.

[0006] BACKGROUND

[0007] Face mask is essential when there is an increase in airborne contaminants and virus in a surrounding environment to safeguard user’s health and wellbeing. Typically, primary purpose of the face mask acts as a barrier preventing transmission of respiratory droplets from the virus.

[0008] Traditional face mask (such as N95 or cloth masks) only filter particles but do not provide real-time feedback on surrounding air quality and the user is unaware of pollution levels or harmful particles in the surrounding environment, limiting the user ability to take timely protective action. Further, the face mask does not monitor the user’s health in real-time such as body temperature, heart rate, respiratory patterns, or hydration levels, leaving the user without critical health data during extended mask use. Typically, the face mask is a passive device that do not integrate with a user device and the user lack a convenient way to receive health alerts, track data, or manage mask- related functions like filter changes and air quality notifications.

[0009] Further, wearing the face mask often muffles speech, making it difficult to communicate effectively with peers. Furthermore, current face masks do not allow the user to take calls, listen to music, or engage with media without removing the face mask.

[0010] Furthermore, the user often misplaces their face mask, and current face masks do not offer any method for easily locating them. Additionally, existing face mask lack emergency location-sharing features that could be vital in case of accidents. Further, the face mask does not provide any form of fall detection or emergency response, leaving vulnerable populations such as elderly without immediate help in case of accidents.

[0011] Moreover, usage of the traditional face mask has no indication of when air filter is no longer effective or needs to be replaced, which can lead to reduced protection over time. Existing face masks do not address buildup of carbon dioxide inside the face mask during extended wear, which can cause discomfort and reduced cognitive function. They also tend to trap heat, making the face mask uncomfortable to wear for long periods.

[0012] Additionally, the face mask cannot filter out foul odors in the surrounding environment with strong, unpleasant smells, leading to discomfort for the user.

[0013] Existing masks do not utilize artificial intelligence to track and interpret health data, leaving gaps in detecting early symptoms of illnesses such as respiratory infections or cardiovascular issues. Hence, there is a need for an improved system to monitor and track the user’s health and the surrounding environment which addresses the aforementioned issue(s).

[0014] OBJECTIVE OF THE INVENTION

[0015] An objective of the present invention is to integrate a sensor unit in a wearable mask to obtain parameters from a user and surrounding environment to ensure user protection.

[0016] Another objective of the present invention is to integrate an artificial intelligence into the wearable mask, thereby allowing for real-time health tracking and early detection of respiratory and cardiovascular issues.

[0017] Yet, another objective of the present invention is to connect the wearable mask with a user device via Bluetooth, thereby allowing the user to monitor the user’s health data, receive alerts, and control features like fall detection, wearable mask location.

[0018] Another objective of the present invention is to include a dynamic ventilation, a perfume diffuser, hydration monitoring, and a speech amplification to make the wearable mask suitable for prolonged wear in various environments.

[0019] BRIEF DESCRIPTION

[0020] In accordance with an embodiment of the present disclosure, a system for real-time environment monitoring and health tracking is provided. The system includes a wearable mask adapted to fit on a user’s face. The system also includes a sensor unit operatively coupled to the wearable mask, wherein the sensor unit is configured to obtain a plurality of parameters from the user and surrounding environment, wherein the sensor unit comprises a plurality of sensors, wherein the plurality of sensors comprises an air pollution sensor, a touch sensor, a temperature sensor, a breath analysis sensor, a fall detection sensor, a biosensor, a carbon dioxide sensor, volatile organic compound sensor, an electroencephalogram sensor and a pollen sensor. The system also includes a processing subsystem hosted on a server wherein the processing subsystem is configured to execute on a network to control bidirectional communications among a plurality of modules. The processing subsystem includes a receiving module configured to receive data from the plurality of sensors. The processing subsystem also includes a processing module operatively coupled to the receiving module, wherein the processing module is configured to process the data received from the plurality of sensors by utilizing an artificial intelligence model. The processing module is also configured to identify one or more abnormalities in the breath, wherein the one or more abnormalities comprises alcohol content, digestive issues, and respiratory problems. Further, the processing module is configured to monitor the user’s brainwave activity to detect stress and fatigue in real-time. Further, the processing module is also configured to identify presence of pollen in air in the surrounding environment. Furthermore, the processing module is configured to analyze cough patterns to assess respiratory health of the user via a microphone positioned in the wearable mask, wherein the microphone captures sound from the cough, frequency and intensity of the sound from the cough. The processing subsystem includes a notification module operatively coupled to the processing module, wherein the notification module is configured to trigger an alert to a user device if the fall detection sensor detects a sudden fall of the user upon monitoring movements of the user. The notification module is configured to trigger the alert to the user via the user device when stress indicators are significantly high. The notification module is also configured to trigger the alert to the user device when high level of pollen is detected, enabling the user to adopt preventive measures, wherein the preventive measures includes antihistamines and avoiding outdoor exposure. Further, the notification module is also configured to generate the alert to the user device if abnormal cough patterns are detected to flag early signs of respiratory illnesses of the user. The processing subsystem includes a feedback module operatively coupled to the notification module, wherein the feedback module is configured to provide a feedback to the user if unusual compounds are detected in the breath. The feedback module is also configured to transmit a health report comprising a physiological data of the user via an interface to the user device, wherein the physiological data comprises a data skin temperature, heart rate, hydration levels, and overall health indicators. A tracking module operatively coupled to the feedback module, wherein the tracking module is configured to enable the user to locate the wearable mask if misplaced by activating a built-in buzzer positioned in the wearable mask via the user device to emit a sound.

[0021] In accordance with another embodiment of the present disclosure, a method for realtime environment monitoring and health tracking is provided. The method includes obtaining, by a sensor unit of a wearable mask, a plurality of parameters from the user and surrounding environment, wherein the sensor unit comprises a plurality of sensors, wherein the plurality of sensors comprises an air pollution sensor, a touch sensor, a temperature sensor, a breath analysis sensor, a fall detection sensor, a biosensor, a carbon dioxide sensor, volatile organic compound sensor, an electroencephalogram sensor and a pollen sensor. The method also includes receiving, by a receiving module, data from the plurality of sensors. Further, the method includes processing, by a processing module, the data received from the plurality of sensors by utilizing an artificial intelligence model. Further, the method also includes identifying, by the processing module, one or more abnormalities in the breath, wherein the one or more abnormalities comprises alcohol content, digestive issues, and respiratory problems. Furthermore, the method includes monitoring, by the processing module, the user’s brainwave activity to detect stress and fatigue in real-time. Moreover, the method includes identifying, by the processing module, presence of pollen in air in the surrounding environment. Additionally, the method includes analyzing, by the processing module, cough patterns to assess respiratory health of the user via a microphone positioned in the wearable mask, wherein the microphone captures sound from the cough, frequency and intensity of the sound from the cough. Further, the method includes triggering, by a notification module, an alert to a user device if the fall detection sensor detects a sudden fall of the user upon monitoring movements of the user. Further, the method also includes triggering, by the notification module, the alert to the user via the user device when stress indicators are significantly high. Furthermore, the method includes triggering, by the notification module, the alert to the user device when high level of pollen is detected, enabling the user to adopt preventive measures, wherein the preventive measures comprises antihistamines and avoiding outdoor exposure. Moreover, the method includes generating, by the notification module, the alert to the user device if abnormal cough patterns are detected to flag early signs of respiratory illnesses of the user. Additionally, the method includes providing, by a feedback module, a feedback to the user if unusual compounds are detected in the breath. Further, the method includes transmitting, by the feedback module, a health report comprising a physiological data of the user via an interface to the user device, wherein the physiological data comprises a data skin temperature, heart rate, hydration levels, and overall health indicators. The method includes enabling, by a tracking module, the user to locate the wearable mask if misplaced by activating a built-in buzzer positioned in the wearable mask via the user device to emit a sound.

[0022] To further clarify the advantages and features of the present disclosure, a more particular description of the disclosure will follow by reference to specific embodiments thereof, which are illustrated in the appended figures. It is to be appreciated that these figures depict only typical embodiments of the disclosure and are therefore not to be considered limiting in scope. The disclosure will be described and explained with additional specificity and detail with the appended figures.

[0023] BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The disclosure will be described and explained with additional specificity and detail with the accompanying figures in which: FIG. 1 is a block diagram representation of a system for real-time environment monitoring and health tracking in accordance with an embodiment of the present disclosure;

[0025] FIG. 2 is a block diagram of an exemplary embodiment of a system for real-time environment monitoring and health tracking of FIG. 1 in accordance with an embodiment of the present disclosure;

[0026] FIG. 3 is a schematic representation of a wearable mask of FIG. 1 in accordance with an embodiment of the present disclosure;

[0027] FIG. 4 is a block diagram of a computer or a server in accordance with an embodiment of the present disclosure;

[0028] FIG. 5 (a) illustrates a flow chart representing the steps involved in a method for realtime environment monitoring and health tracking in accordance with an embodiment of the present disclosure; and

[0029] FIG. 5(b) illustrates continued steps of the method of FIG. 5(a) in accordance with an embodiment of the present disclosure.

[0030] Further, those skilled in the art will appreciate that elements in the figures are illustrated for simplicity and may not have necessarily been drawn to scale. Furthermore, in terms of the construction of the device, one or more components of the device may have been represented in the figures by conventional symbols, and the figures may show only those specific details that are pertinent to understanding the embodiments of the present disclosure so as not to obscure the figures with details that will be readily apparent to those skilled in the art having the benefit of the description herein.

[0031] DETAILED DESCRIPTION For the purpose of promoting an understanding of the principles of the disclosure, reference will now be made to the embodiment illustrated in the figures and specific language will be used to describe them. It will nevertheless be understood that no limitation of the scope of the disclosure is thereby intended. Such alterations and further modifications in the illustrated system, and such further applications of the principles of the disclosure as would normally occur to those skilled in the art are to be construed as being within the scope of the present disclosure.

[0032] The terms “comprises”, “comprising”, or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process or method that comprises a list of steps does not include only those steps but may include other steps not expressly listed or inherent to such a process or method. Similarly, one or more devices or subsystems or elements or structures or components preceded by "comprises... a" does not, without more constraints, preclude the existence of other devices, sub-systems, elements, structures, components, additional devices, additional sub-systems, additional elements, additional structures or additional components. Appearances of the phrase "in an embodiment", "in another embodiment" and similar language throughout this specification may, but not necessarily do, all refer to the same embodiment.

[0033] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this disclosure belongs. The system, methods, and examples provided herein are only illustrative and not intended to be limiting.

[0034] In the following specification and the claims, reference will be made to a number of terms, which shall be defined to have the following meanings. The singular forms “a”, “an”, and “the” include plural references unless the context clearly dictates otherwise.

[0035] Embodiments of the present disclosure relate to a system for real-time environment monitoring and health tracking is provided. The system includes a wearable mask adapted to fit on a user’s face. The system also includes a sensor unit operatively coupled to the wearable mask, wherein the sensor unit is configured to obtain a plurality of parameters from the user and surrounding environment, wherein the sensor unit comprises a plurality of sensors, wherein the plurality of sensors comprises an air pollution sensor, a touch sensor, a temperature sensor, a breath analysis sensor, a fall detection sensor, a biosensor, a carbon dioxide sensor, volatile organic compound sensor, an electroencephalogram sensor and a pollen sensor. The system also includes a processing subsystem hosted on a server wherein the processing subsystem is configured to execute on a network to control bidirectional communications among a plurality of modules. The processing subsystem includes a receiving module configured to receive data from the plurality of sensors. The processing subsystem also includes a processing module operatively coupled to the receiving module, wherein the processing module is configured to process the data received from the plurality of sensors by utilizing an artificial intelligence model. The processing module is also configured to identify one or more abnormalities in the breath, wherein the one or more abnormalities comprises alcohol content, digestive issues, and respiratory problems. Further, the processing module is configured to monitor the user’s brainwave activity to detect stress and fatigue in real-time. Further, the processing module is also configured to identify presence of pollen in air in the surrounding environment. Furthermore, the processing module is configured to analyze cough patterns to assess respiratory health of the user via a microphone positioned in the wearable mask, wherein the microphone captures sound from the cough, frequency and intensity of the sound from the cough. The processing subsystem includes a notification module operatively coupled to the processing module, wherein the notification module is configured to trigger an alert to a user device if the fall detection sensor detects a sudden fall of the user upon monitoring movements of the user. The notification module is configured to trigger the alert to the user via the user device when stress indicators are significantly high. The notification module is also configured to trigger the alert to the user device when high level of pollen is detected, enabling the user to adopt preventive measures, wherein the preventive measures comprises antihistamines and avoiding outdoor exposure. Further, the notification module is also configured to generate the alert to the user device if abnormal cough patterns are detected to flag early signs of respiratory illnesses of the user. The processing subsystem includes a feedback module operatively coupled to the notification module, wherein the feedback module is configured to provide a feedback to the user if unusual compounds are detected in the breath. The feedback module is also configured to transmit a health report comprising a physiological data of the user via an interface to the user device, wherein the physiological data comprises a data skin temperature, heart rate, hydration levels, and overall health indicators. A tracking module is operatively coupled to the feedback module, wherein the tracking module is configured to enable the user to locate the wearable mask if misplaced by activating a built-in buzzer positioned in the wearable mask via the user device to emit a sound.

[0036] FIG. 1 is a block diagram representation of a system for real-time environment monitoring and health tracking in accordance with an embodiment of the present disclosure. The system (100) includes a processing subsystem (130) hosted on a server (140). In one embodiment, the server (140) may include a cloud-based server. In another embodiment, parts of the server (140) may be a local server coupled to a first user device. The processing subsystem (130) is configured to execute on a network (145) to control bidirectional communications among a plurality of modules. In one example, the network (145) may be a private or public local area network (LAN) or Wide Area Network (WAN), such as the Internet. In another embodiment, the network ( 160) may include both wired and wireless communications according to one or more standards and / or via one or more transport mediums. In one example, the network (145) may include wireless communications according to one of the 802.11 or Bluetooth specification sets, or another standard or proprietary wireless communication protocol. In yet another embodiment, the network (145) may also include communications over a terrestrial cellular network, including, a global system for mobile communications (GSM), code division multiple access (CDMA), and / or enhanced data for global evolution (EDGE) network.

[0037] The system (100) includes a wearable mask (110) adapted to fit on a user’s face. Typically, the wearable mask (110) is an artificial intelligence -powered face mask for real-time monitoring of a surrounding environment and health tracking of the user.

[0038] The system (100) also includes a sensor unit (120) operatively coupled to the wearable mask (110). The sensor unit (120) is configured to obtain a plurality of parameters from the user and the surrounding environment. Examples of the plurality of parameters includes, but is not limited to an air quality of the surrounding environment, temperature of the user’s body, cough patterns of the user, breath composition of the user, fall detection of the user, skin temperature, hydration levels, and overall health indicators of the user, carbon dioxide in the wearable mask (110).

[0039] The sensor unit (120) includes a plurality of sensors. The plurality of sensors includes an air pollution sensor (340, FIG. 3), a touch sensor (310, FIG. 3), a temperature sensor (300, FIG. 3), a breath analysis sensor (380, FIG. 3), a fall detection sensor (350, FIG. 3), a biosensor (370, FIG. 3), a carbon dioxide sensor (375, FIG. 3), a volatile organic compound sensor (385, FIG. 3), an electroencephalogram sensor (390, FIG. 3) and a pollen sensor (395, FIG. 3).

[0040] The air pollution sensor (340, FIG. 3) is configured to measure air quality index in the user’s surrounding environment in real-time to assess pollution level in the surrounding environment. Typically, the pollution level in the surrounding environment is amount of harmful substances (pollutants) present in an atmosphere. Examples of the pollutants in the atmosphere includes ozone, nitrogen dioxide, sulphur dioxide, and carbon monoxide and concentration of the pollutants in the atmosphere is measured by the air quality index. Simultaneously, a feedback is generated on status of the air quality index via one or more light emitting diode indicators positioned on the wearable mask (110) to the user. For example, the one or more light emitting diode indicators includes red (worst pollution), orange (bad pollution), yellow (moderate pollution), and green (clean air), thereby providing instant feedback on the air quality, allowing the user to make quick decisions regarding safety. Further, the notification is generated on status of the air quality index to the user device (270, FIG. 2).

[0041] The touch sensor (310, FIG. 3) is configured to detect presence of the wearable mask (110) to activate the plurality of sensors.

[0042] The temperature sensor (300, FIG. 3) is configured to monitor temperature of the user’s body in real-time. The temperature sensor (300, FIG. 3) is positioned at a location where the wearable mask (110) contacts the user’s skin. Simultaneously, an alert is generated to the user device (270, FIG. 2) in response to detection of abnormalities in the temperature. For example, the abnormalities refer to a deviation in the temperature of the user. In one embodiment, the temperature sensor (300, FIG. 3) also detects ambient temperature when the wearable mask (110) is not being worn by the user.

[0043] The breath analysis sensor (380, FIG. 3) is configured to identify one or more abnormalities in the breath. The one or more abnormalities includes alcohol content, digestive issues, and respiratory problems. Simultaneously, the feedback is transmitted to the user device (270, FIG. 2) upon detection of the one or more abnormalities.

[0044] Further, the breath analyzer sensor (380, FIG. 3) also detects potential illness based on the abnormalities in the user's breathing pattern. If any irregularity is detected, an alert is transmitted to the user, advising them to visit a healthcare provider for further evaluation.

[0045] The fall detection sensor (350, FIG. 3) is configured to detect a sudden fall of the user upon monitoring movements of the user. Simultaneously, the alert is triggered to the user device (270, FIG. 2) if the fall detection sensor (350, FIG. 3) detects a sudden fall of the user upon monitoring movements of the user. The biosensor (370, FIG. 3) is configured to collect a physiological data from the user. The physiological data includes skin temperature, hydration levels, and overall health indicators of the user. Simultaneously, the notification is sent to the user device (270, FIG. 2), if abnormalities are detected in the physiological data.

[0046] The carbon dioxide sensor (375, FIG. 3) is configured to monitor amount of carbon dioxide exhaled by the user in the wearable mask (110). Further, the carbon dioxide sensor (375, FIG. 3) is also configured to track the amount of the carbon dioxide rebreathed by the user. Simultaneously, the alert is sent to the user device (270, FIG. 2) when level of the carbon dioxide is high, ensuring that the user adjust environment or ventilation.

[0047] The volatile organic compound sensor (385, FIG. 3) is configured to monitor air to identify harmful gases. The harmful gases include benzene, formaldehyde, and other organic compounds. Simultaneously, the alert is generated through the one or more light emitting diode indicators positioned on the wearable mask (110) and the user device (270, FIG. 2) when high levels of the harmful gases are detected, enabling the user to move to a safe environment.

[0048] The electroencephalogram sensor (390, FIG. 3) is configured to monitor the user’s brainwave activity to detect stress and fatigue in real-time. Simultaneously, the alert is triggered to the user via the user device (270, FIG. 2) when stress indicators are significantly high. Typically, the user device (270, FIG. 2) is operated by the user.

[0049] The pollen sensor (395, FIG. 3) is configured to identify presence of pollen in air in the surrounding environment. Typically, the pollen in the air is a modest, powdery grain released from plants during reproductive process. Typically, wind, insects, or animals carry powdery grains to fertilize other plants of same species. However, when the pollen becomes airborne, it leads to seasonal allergies and other respiratory issues for the user with low immunity. Upon detecting the pollen, the alert is triggered to the user device (270, FIG. 2) when a high level of pollen is detected, enabling the user to adopt preventive measures. The preventive measures include antihistamines and avoiding outdoor exposure.

[0050] The system (100) also includes a processing subsystem (130). The processing subsystem (130) includes a receiving module (150), a processing module (160), notification module (170), a feedback module (180), and a tracking module (185).

[0051] The receiving module (150) is configured to receive data from the plurality of sensors. Typically, the data received from the plurality of sensors are stored for an extended period to analyse the user’s health and abnormalities in future stage.

[0052] The processing module (160) is operatively coupled to the receiving module (150). The processing module ( 160) is configured to process the data received from the plurality of sensors by utilizing an artificial intelligence model. Typically, the artificial intelligence model captures raw data from the plurality of sensors, analyze, and generate meaningful insights or actions. Further, the artificial intelligence model is configured to process the data received from the sensor unit (120) through one or more techniques such as machine learning or deep learning, to identify patterns, detect anomalies, predict outcomes, or make decisions from the raw data.

[0053] The processing module ( 160) is also configured to identify one or more abnormalities in the breath. The one or more abnormalities includes, but is not limited to, alcohol content, digestive issues, and respiratory problems. Typically, the one or more abnormalities are detected by the breath analyzer sensor.

[0054] Further, the processing module (160) is configured to monitor the user’s brainwave activity to detect stress and fatigue in real-time. Typically, an Electroencephalogram sensor (390, FIG. 3) measures and records electrical activities of a brain of the user. Further, the processing module ( 160) is also configured to identify presence of pollen in air in the surrounding environment. Typically, the pollen in the air is detected by the pollen sensor (395, FIG. 3).

[0055] The processing module (160) is configured to analyze cough patterns to assess respiratory health of the user via a microphone (320, FIG. 3) positioned in the wearable mask (110). The microphone (320, FIG. 3) captures sound from the cough, frequency and intensity of the sound from the cough. Simultaneously, the alert is generated to the user device (270, FIG. 2) if abnormal cough patterns are detected to flag early signs of respiratory illnesses of the user.

[0056] The notification module (170) is operatively coupled to the processing module (160). The notification module (170) is configured to trigger the alert to the user device (270, FIG. 2) if the fall detection sensor (350, FIG. 3) detects a sudden fall of the user upon monitoring movements of the user. Typically, the fall detection sensor (350, FIG. 3) analyzes motion, orientation, and impact of the movements of the user.

[0057] The notification module (170) is also configured to trigger the alert to the user via the user device (270, FIG. 2) when stress indicators are significantly high. Typically, the user device (270, FIG. 2) is operated by the user.

[0058] Further, the notification module (170) is configured to trigger the alert to the user device (270, FIG. 2) when a high level of pollen is detected, enabling the user to adopt preventive measures. The preventive measures include antihistamines and avoiding outdoor exposure.

[0059] The notification module (170) is configured to generate the alert to the user device (270, FIG. 2) if abnormal cough patterns are detected to flag early signs of respiratory illnesses of the user. Typically, examples of the early signs of respiratory illness of the user includes irritation and inflammation of airways, increases mucus production, damage to respiratory tissues. The feedback module (180) is operatively coupled to the notification module (170). The feedback module ( 180) is configured to provide a feedback to the user if unusual compounds are detected in the breath. The unusual compounds includes, but is not limited to alcohol or specific respiratory markers.

[0060] The feedback module ( 180) is also configured to transmit a health report including the physiological data of the user via an interface to the user device (270, FIG. 2). Typically, the interface may be a wired or wireless communication protocol to transmit the physiological data to the user device (270, FIG. 2). The physiological data includes a data skin temperature, heart rate, hydration levels, and overall health indicators.

[0061] The tracking module (185) is operatively coupled to the feedback module (180). The tracking module (185) is configured to enable the user to locate the wearable mask (110) if misplaced by activating a built-in buzzer (360, FIG. 3) positioned in the wearable mask (110) via the user device (270, FIG. 2) to emit a sound.

[0062] It must be noted that, microcontroller serves as a brain of the wearable mask (110), processing the data received from the plurality of sensors, controlling features, and coordinating communication with the user device (270, FIG. 2). Further, the microcontroller integrates the plurality of sensors, the artificial intelligence module, and a mobile connectivity into a cohesive system, managing real-time data processing, triggering alerts, and ensuring efficient functionality.

[0063] FIG. 2 is a block diagram of an exemplary embodiment of a system for real-time environment monitoring and health tracking of FIG. 1 in accordance with an embodiment of the present disclosure. The wearable mask (110) further includes a filter replacement unit (190). The filter replacement unit (190) includes a sensor configured to measure the wearable mask’s (110) filter wear and tear over time. Simultaneously, a notification is transmitted to the user device (270) when the filter is no longer effective, ensuring continuous protection. Further, the wearable mask (110) includes an earpiece (195, FIG. 3) adapted to enable the user to engage with the user device (270) through the microphone (320, FIG. 3) via the Bluetooth.

[0064] Further, the user device (270) is connected to the wearable mask (110) via the Bluetooth.

[0065] Furthermore, the wearable mask (110) includes a perfume diffuser (200), a speech amplification module (210), a dynamic ventilation unit (220), and a location tracking module (230).

[0066] The perfume diffuser (200) is adapted to enable the user to activate a diffuser via the user device (270) to release a predetermined amount of fragrance to surrounding environment when exposed to unpleasant smells.

[0067] The speech amplification module (210) is configured to amplify voice of the user using a microphone (320, FIG.3) to enhance effective communication in a noisy environment. The dynamic ventilation unit (220) is configured to adjust airflow inside the wearable mask (110) based on the user’s activity level or environmental conditions to maintain comfort to the user and reduce the airflow during rest. Typically, the dynamic ventilation unit (220) includes one or more sensors to identify deviations in the user’s activity. For example, when the user is engaged in a physical activity, the one or more sensors triggers an increase in the airflow to facilitate breathing and cooling. In contrast, when the user is at rest, the dynamic ventilation unit (220) reduces airflow to conserve energy and maintain comfort. Additionally, environmental sensors monitor temperature, humidity, and air quality in the user surroundings to further adjust the airflow based on external conditions. For instance, if surrounding temperature rises or humidity increases, the dynamic ventilation unit (220) boosts the airflow to maintain the user cool. Typically, the dynamic ventilation unit (220) is powered by an energyefficient fan system, which adjusts speed in real-time to optimize performance while extending battery life. This automatic adjustment ensures that the user experiences consistent comfort and breathability, regardless the physical activity or environmental changes.

[0068] The location tracking module (230) is configured to track and transmit the user’s global positioning system location through the user device (270) to emergency responders, thereby enabling the emergency responders to locate the user.

[0069] Consider a non-limiting example, wherein a User X is wearing the wearable mask (110) during daily routine in a polluted city. As the user X step out, the air pollution sensor (340, FIG. 3) immediately detects a rise in the AQI, signaling that the air quality is poor. Simultaneously, the receiving module (150) receives data from the air pollution sensor (340, FIG. 3). The processing module (160) processes the data received from the air pollution sensor (340, FIG. 3), triggering the mask's LED indicators to glow orange, indicating bad pollution, and an alert is sent to the user device (270). Simultaneously, the user X receives a notification on the user device (270), prompting to consider take a different route or activating the perfume diffuser (200) to mask unpleasant smell. As the user X continues walking, the temperature sensor (300, FIG. 3) keeps track of the user’s temperature, ensuring it's within the normal range. However, the touch sensor (310, FIG. 3) detects that the wearable mask (110) is securely in place and activates sensor unit (120). Suddenly, User X feels a slight dizziness due to the air quality index and starts coughing. The cough pattern detection picks up early signs of irritation in the User X’s respiratory system, analyzing coughing frequency and intensity. The notification module (170) transmits the alert to the user X user device (270), advising the user to take rest or to drink water. Meanwhile, the CO2 sensor inside the wearable mask (110) tracks the carbon dioxide in the wearable mask (110) and ensures it remains at safe levels, avoiding discomfort and the user X falls due to discomfort. As soon as the user X falls the fall detection sensor (350, FIG. 3) triggers an SOS alert to a nearby responders or family and friends (predefined emergency contacts with GPS (global positioning system) location, while location tracking module (230) feature ensures emergency responders can easily locate them. The wearable mask (110) is also embedded with earpiece (195, FIG. 3) and microphone (320, FIG. 3) and a speech amplification module (210). Further, a feedback module (180) transmits a health report including a physiological data of the user via an interface to the user device (270), thereby providing a real-time health and environmental monitoring, ensuring that User X stays safe and informed during their journey.

[0070] FIG. 3 is a schematic representation of a wearable mask of FIG. 1 in accordance with an embodiment of the present disclosure. The wearable mask (110) includes a temperature sensor (300), touch sensor (310), light emitting diode indicators (315), earpiece (195), microphone (320), perfume diffuser (200), microcontroller (330), air pollution sensor (340), fall detection sensor (350), built-in-buzzer (360), biosensor (370), a carbon dioxide sensor (375), a volatile organic compound sensor (385), an electroencephalogram sensor (390), a pollen sensor (395), and breath analyzer sensor (380).

[0071] Typically, the microcontroller (330) is integrated with a plurality of sensors. The microcontroller (330) coordinates operation of the plurality of sensors within the wearable mask (110). The microcontroller (330) processes the data from each of the plurality of sensors in real-time, using an artificial intelligence model to analyze health of the user and environmental conditions. Further, the Bluetooth connection allows for seamless communication between the wearable mask (110) and the user device (270, FIG. 2), where the user receives notifications, alerts, health metrics, and can control additional features like the buzzer (360) or perfume diffuser (200) from the user device (270, FIG. 2).

[0072] For example, when the air pollution sensor (340) detects high AQI levels, the microcontroller (330) processes this data and triggers LED notifications on the wearable mask (110) while also alerting the user via the user device (270, FIG. 2). Similarly, if the temperature or EEG sensor detect abnormal readings, the microcontroller activates alerts through the user device (270, FIG. 2), allowing the user X to take preventive action. The sensor unit (120) and all other components (perfume diffuser (200), buzzer (360)) are powered and synchronized by the microcontroller (330), ensuring that the wearable mask (110) functions as an integrated whole, combining health monitoring, safety features, and comfort enhancements.

[0073] FIG. 4 is a block diagram of a computer or a server in accordance with an embodiment of the present disclosure. The server (140) includes processor(s) (430), and memory (410) operatively coupled to the bus (420). The processor(s) (430), as used herein, means any type of computational circuit, such as, but not limited to, a microprocessor, a microcontroller, a complex instruction set computing microprocessor, a reduced instruction set computing microprocessor, a very long instruction word microprocessor, an explicitly parallel instruction computing microprocessor, a digital signal processor, or any other type of processing circuit, or a combination thereof.

[0074] The memory (410) includes several subsystems stored in the form of executable program which instructs the processor (430) to perform the method steps illustrated in FIG. 1. The memory (410) includes a processing subsystem (130) of FIG.l. The processing subsystem (130) includes a plurality of modules a receiving module (150), a processing module (160), notification module (170), and a feedback module (180).

[0075] The receiving module (150) is configured to receive data from the plurality of sensors. The processing subsystem (130) also includes a processing module (160) operatively coupled to the receiving module (150), wherein the processing module (160) is configured to process the data received from the plurality of sensors by utilizing an artificial intelligence model. The processing module ( 160) is also configured to identify one or more abnormalities in the breath, wherein the one or more abnormalities includes alcohol content, digestive issues, and respiratory problems. Further, the processing module (160) is configured to monitor the user’s brainwave activity to detect stress and fatigue in real-time. Further, the processing module (160) is also configured to identify presence of pollen in air in the surrounding environment. Furthermore, the processing module (160) is configured to analyze cough patterns to assess respiratory health of the user via a microphone (320, FIG. 3) positioned in the wearable mask (110), wherein the microphone (320, FIG. 3) captures sound from the cough, frequency and intensity of the sound from the cough. The processing subsystem (130) includes a notification module (170) operatively coupled to the processing module (160), wherein the notification module (170) is configured to trigger an alert to a user device (270, FIG. 2) if the fall detection sensor (350, FIG. 3) detects a sudden fall of the user upon monitoring movements of the user. The notification module (170) is configured to trigger the alert to the user via the user device (270, FIG. 2) when stress indicators are significantly high. The notification module (170) is also configured to trigger the alert to the user device (270, FIG. 2) when high level of pollen is detected, enabling the user to adopt preventive measures, wherein the preventive measures includes antihistamines and avoiding outdoor exposure. Further, the notification module (170) is also configured to generate the alert to the user device (270, FIG. 2) if abnormal cough patterns are detected to flag early signs of respiratory illnesses of the user. The processing subsystem (130) includes a feedback module (180) operatively coupled to the notification module (170), wherein the feedback module (180) is configured to provide a feedback to the user if unusual compounds are detected in the breath. The feedback module ( 180) is also configured to transmit a health report comprising a physiological data of the user via an interface to the user device (270, FIG. 2), wherein the physiological data includes a data skin temperature, heart rate, hydration levels, and overall health indicators. A tracking module (185) is operatively coupled to the feedback module (180), wherein the tracking module (185) is configured to enable the user to locate the wearable mask (110) if misplaced by activating the built- in buzzer (360) positioned in the wearable mask (110) via the user device (270, FIG. 2) to emit a sound. The bus (420) as used herein refers to be internal memory channels or computer network that is used to connect computer components and transfer data between them. The bus (420) includes a serial bus or a parallel bus, wherein the serial bus transmits data in bit-serial format and the parallel bus transmits data across multiple wires. The bus (420) as used herein, may include but not limited to, a system bus, an internal bus, an external bus, an expansion bus, a frontside bus, a backside bus and the like.

[0076] FIG. 5 (a) illustrates a flow chart representing the steps involved in a method for realtime environment monitoring and health tracking in accordance with an embodiment of the present disclosure. FIG. 5 (b) illustrates continued steps of the method of FIG. 5(a) in accordance with an embodiment of the present disclosure.

[0077] The method (600) includes obtaining, by a sensor unit of a wearable mask, a plurality of parameters from the user and surrounding environment, wherein the sensor unit includes a plurality of sensors, wherein the plurality of sensors includes an air pollution sensor, a touch sensor, a temperature sensor, a breath analysis sensor, a fall detection sensor, a biosensor, a carbon dioxide sensor, volatile organic compound sensor, an electroencephalogram sensor and a pollen sensor in step 610.

[0078] Typically, the touch sensor is configured to detect presence of the wearable mask to activate the plurality of sensors.

[0079] The biosensor is configured to collect the physiological data from the user.

[0080] The air pollution sensor is configured to measure air quality index in the user’s surrounding environment in real-time to assess pollution level in the surrounding environment. Examples of the pollutants includes in the air quality index, but is not limited to nitrogen dioxide, sulfur dioxide, particulate matter and ammonia. The temperature sensor is configured to monitor temperature of the user’s body in realtime, wherein the temperature sensor is positioned at a location where the wearable mask contacts the user’s skin.

[0081] The carbon dioxide sensor is configured to monitor amount of carbon dioxide exhaled by the user in the wearable mask. The carbon dioxide sensor is configured to track the amount of the carbon dioxide re-breathed by the user.

[0082] The volatile organic compound sensor is configured to monitor air to identify harmful gases, wherein the harmful gases includes benzene, formaldehyde, and other organic compounds.

[0083] The method (600) also includes receiving, by a receiving module, data from the plurality of sensors in step 620.

[0084] Further, the method (600) includes processing, by a processing module, the data received from the plurality of sensors by utilizing an artificial intelligence model in step 630.

[0085] Further, the method (600) also includes identifying, by the processing module, one or more abnormalities in the breath, wherein the one or more abnormalities includes alcohol content, digestive issues, and respiratory problems in step 640.

[0086] Furthermore, the method (600) includes monitoring, by the processing module, the user’s brainwave activity to detect stress and fatigue in real-time in step 650.

[0087] Moreover, the method (600) includes identifying, by the processing module, presence of pollen in air in the surrounding environment in step 660.

[0088] Further, the method (600) includes analyzing, by the processing module, cough patterns to assess respiratory health of the user via a microphone positioned in the wearable mask, wherein the microphone captures sound from the cough, frequency and intensity of the sound from the cough in step 670.

[0089] Further, the method (600) also includes triggering, by a notification module, an alert to a user device if the fall detection sensor detects a sudden fall of the user upon monitoring movements of the user in step 680.

[0090] The method (600) includes triggering, by the notification module, the alert to the user via the user device when stress indicators are significantly high in step 690.

[0091] Typically, the notification module is configured to generate feedback on status of the air quality index via one or more light emitting diode indicators positioned on the wearable mask to the user. The notification module is also configured to generate a notification on the status of the air quality index to the user device. Further, the notification module is configured to generate the alert to the user device in response to detection of abnormalities in the temperature. Further, the notification module is configured to transmit the alert to the user device upon detection of a critical rise or high level of carbon dioxide in the wearable mask. Further, the notification module is configured to notify the user when the wearable mask’s filter replacement is required to ensure the user protection generate the alert through one or more light emitting diode indicators positioned on the wearable mask and the user device when high levels of the harmful gases are detected, enabling the user to move to a safe environment.

[0092] The wearable mask is equipped with a charging module, allowing for efficient and fast charging. The charging module ensures that the wearable mask can be easily recharged through a standardized USB Type-C port, offering compatibility with a wide range of charging accessories. In addition to charging functionality, the wearable mask monitor’s battery level. When the battery level reaches a low threshold, the wearable mask triggers an alert, notifying the user that charging is required. Further, the method (600) includes triggering, by the notification module, the alert to the user device when high level of pollen is detected, enabling the user to adopt preventive measures, wherein the preventive measures includes antihistamines and avoiding outdoor exposure in step 700.

[0093] Furthermore, the method (600) includes generating, by the notification module, the alert to the user device if abnormal cough patterns are detected to flag early signs of respiratory illnesses of the user in step 710.

[0094] Moreover, the method (600) includes providing, by a feedback module, a feedback to the user if unusual compounds are detected in the breath in step 720.

[0095] Additionally, the method (600) includes transmitting, by the feedback module, a health report comprising a physiological data of the user via an interface to the user device, wherein the physiological data includes a data skin temperature, heart rate, hydration levels, and overall health indicators in step 730.

[0096] Further, the method (600) includes enabling, by a tracking module, the user to locate the wearable mask if misplaced by activating a built-in buzzer positioned in the wearable mask via the user device to emit a sound in step 740.

[0097] V arious embodiments of the system for real-time environment monitoring and health tracking above provides various benefits upon integration of the artificial intelligence model into the wearable mask, thereby allowing for real-time health tracking and early detection of respiratory and cardiovascular issues and provide proactive health insights. Further, the wearable mask integrates a plurality of sensors to provide a holistic view of the user’s environment and health. Further, the wearable mask’s ability to connect with the user device via Bluetooth, thereby allowing the user to monitor their health data, receive alerts, and control features like fall detection or mask location, providing convenience and usability to the user. Furthermore, inclusion of dynamic ventilation unit, a perfume diffuser, hydration monitoring, and speech amplification module makes the wearable mask suitable for prolonged wear in various environments, from daily commutes to high-risk settings.

[0098] The techniques described in this disclosure may be implemented, at least in part, in hardware, software, firmware, or any combination thereof. For example, various aspects of the described techniques may be implemented within one or more processors, including one or more microprocessors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or any other equivalent integrated or discrete logic circuitry, as well as any combinations of such components. The term “processor” or “processing subsystem” may generally refer to any of the foregoing logic circuitry, alone or in combination with other logic circuitry, or any other equivalent circuitry. A electronic control unit including hardware may also perform one or more of the techniques of this disclosure.

[0099] Such hardware, software, and firmware may be implemented within the same device or within separate devices to support the various techniques described in this disclosure. In addition, any of the described units, modules, or components may be implemented together or separately as discrete but interoperable logic devices. Depiction of different features as modules or units is intended to highlight different functional aspects and does not necessarily imply that such modules or units must be realized by separate hardware, firmware, or software components. Rather, functionality associated with one or more modules or units may be performed by separate hardware, firmware, or software components, or integrated within common or separate hardware, firmware, or software components.

[0100] It will be understood by those skilled in the art that the foregoing general description and the following detailed description are exemplary and explanatory of the disclosure and are not intended to be restrictive thereof. While specific language has been used to describe the disclosure, any limitations arising on account of the same are not intended. As would be apparent to a person skilled in the art, various working modifications may be made to the method in order to implement the inventive concept as taught herein. The figures and the foregoing description give examples of embodiments. Those skilled in the art will appreciate that one or more of the described elements may well be combined into a single functional element. Alternatively, certain elements may be split into multiple functional elements. Elements from one embodiment may be added to another embodiment. For example, the order of processes described herein may be changed and are not limited to the manner described herein. Moreover, the actions of any flow diagram need not be implemented in the order shown; nor do all of the acts need to be necessarily performed. Also, those acts that are not dependent on other acts may be performed in parallel with the other acts. The scope of embodiments is by no means limited by these specific examples.

Claims

I CLAIM:

1. A system (100) for real-time environment monitoring and health tracking comprising: a wearable mask (110) adapted to fit on a user’s face; characterized in that, a sensor unit (120) operatively coupled to the wearable mask (110), wherein the sensor unit (120) is configured to obtain a plurality of parameters from the user and surrounding environment, wherein the sensor unit (120) comprises a plurality of sensors, wherein the plurality of sensors comprises an air pollution sensor, a touch sensor, a temperature sensor, a breath analysis sensor, a fall detection sensor, a biosensor, a carbon dioxide sensor, volatile organic compound sensor, an electroencephalogram sensor and a pollen sensor; a processing subsystem (130) hosted on a server (140) wherein the processing subsystem (130) is configured to execute on a network (145) to control bidirectional communications among a plurality of modules comprising: a receiving module (150) configured to receive data from the plurality of sensors; a processing module (160) operatively coupled to the receiving module (150), wherein the processing module (160) is configured to: process the data received from the plurality of sensors by utilizing an artificial intelligence model; identify one or more abnormalities in the breath, wherein the one or more abnormalities comprises alcohol content, digestive issues, and respiratory problems;monitor the user’s brainwave activity to detect stress and fatigue in real-time; identify presence of pollen in air in the surrounding environment; and analyze cough patterns to assess respiratory health of the user via a microphone (320) positioned in the wearable mask (110), wherein the microphone (320) captures sound from the cough, frequency and intensity of the sound from the cough; a notification module (170) operatively coupled to the processing module (160), wherein the notification module (170) is configured to: trigger an alert to a user device (270) if the fall detection sensor detects a sudden fall of the user upon monitoring movements of the user; trigger the alert to the user via the user device (270) when stress indicators are significantly high; trigger the alert to the user device (270) when high level of pollen is detected, enabling the user to adopt preventive measures, wherein the preventive measures comprises antihistamines and avoiding outdoor exposure; and generate the alert to the user device (270) if abnormal cough patterns are detected to flag early signs of respiratory illnesses of the user; a feedback module ( 180) operatively coupled to the notification module (170), wherein the feedback module (180) is configured to: provide feedback to the user if unusual compounds are detected in the breath; andtransmit a health report comprising a physiological data of the user via an interface to the user device (270), wherein the physiological data comprises a data skin temperature, heart rate, hydration levels, and overall health indicators; and a tracking module (185) operatively coupled to the feedback module (180), wherein the tracking module (185) is configured to enable the user to locate the wearable mask (110) if misplaced by activating a built-in buzzer (360) positioned in the wearable mask (110) via the user device (270) to emit a sound.

2. The system (100) as claimed in claim 1, wherein the touch sensor is configured to detect presence of the wearable mask (110) to activate the plurality of sensors.

3. The system (100) as claimed in claim 1, wherein the biosensor is configured to collect the physiological data from the user.

4. The system (100) as claimed in claim 1, wherein the air pollution sensor is configured to measure air quality index in the user’s surrounding environment in realtime to assess pollution level in the surrounding environment.

5. The system (100) as claimed in claim 1, wherein the temperature sensor is configured to monitor temperature of the user’s body in real-time, wherein the temperature sensor is positioned at a location where the wearable mask (110) contacts the user’s skin.

6. The system (100) as claimed in claim 1, wherein the carbon dioxide sensor configured to: monitor amount of carbon dioxide exhaled by the user in the wearable mask (110); andtrack amount of the carbon dioxide re-breathed by the user.

7. The system (100) as claimed in claim 1, wherein the volatile organic compound sensor is configured to monitor air to identify harmful gases, wherein the harmful gases comprises benzene, formaldehyde, and other organic compounds.

8. The system (100) as claimed in claim 1, wherein the wearable mask (110) comprises a filter replacement unit (190), wherein the filter replacement unit (190) comprises a sensor configured to measure the wearable mask’s (110) filter wear and tear over time.

9. The system (100) as claimed in claim 1, wherein the notification module (170) is configured to: generate feedback on status of the air quality index via one or more light emitting diode indicators positioned on the wearable mask ( 110) to the user; generate a notification on the status of the air quality index to the user device (270); generate the alert to the user device (270) in response to detection of abnormalities in the temperature; transmit the alert to the user device (270) upon detection of a critical rise or high level of carbon dioxide in the wearable mask (110); notify the user when the wearable mask’s (110) filter replacement is required to ensure the user protection; and generate the alert through the one or more light emitting diode indicators positioned on the wearable mask (110) and the user device (270) when high levels of the harmful gases are detected, enabling the user to move to a safe environment.

10. The system (100) as claimed in claim 1, wherein the wearable mask (110) comprises an earpiece (195) adapted to enable the user to engage with the user device (270) through the microphone (320) via the Bluetooth.

11. The system (100) as claimed in claim 1, wherein the wearable mask (110) comprises: a perfume diffuser (200) adapted to enable the user to activate a diffuser via the user device (270) to release a predetermined amount of fragrance to the surrounding environment when exposed to unpleasant smells; a speech amplification module (210) configured to amplify voice of the user using the microphone (320) to enhance effective communication in a noisy environment; a dynamic ventilation unit (220) configured to adjust airflow inside the wearable mask (110) based on the user’s activity level or environmental conditions to maintain comfort to the user and reduce the airflow during rest; and a location tracking module (230) configured to track and transmit the user’s global positioning system location through the user device (270) to emergency responders, thereby enabling the emergency responders to locate the user.

12. A method (600) for real-time environment monitoring and health tracking comprising: characterized in that, obtaining, by a sensor unit of a wearable mask, a plurality of parameters from the user and surrounding environment, wherein the sensor unit comprises a plurality of sensors, wherein the plurality of sensors comprises an air pollution sensor, a touch sensor, a temperature sensor, a breath analysis sensor, a fall detection sensor, abiosensor, a carbon dioxide sensor, volatile organic compound sensor, an electroencephalogram sensor and a pollen sensor; (610) receiving, by a receiving module, data from the plurality of sensors; (620) processing, by a processing module, the data received from the plurality of sensors by utilizing an artificial intelligence model; (630) identifying, by the processing module, one or more abnormalities in the breath, wherein the one or more abnormalities comprises alcohol content, digestive issues, and respiratory problems; (640) monitoring, by the processing module, the user’s brainwave activity to detect stress and fatigue in real-time; (650) identifying, by the processing module, presence of pollen in air in the surrounding environment; (660) analyzing, by the processing module, cough patterns to assess respiratory health of the user via a microphone positioned in the wearable mask, wherein the microphone captures sound from the cough, frequency and intensity of the sound from the cough; (670) triggering, by a notification module, an alert to a user device if the fall detection sensor detects a sudden fall of the user upon monitoring movements of the user; (680) triggering, by the notification module, the alert to the user via the user device when stress indicators are significantly high; (690)triggering, by the notification module, the alert to the user device when high level of pollen is detected, enabling the user to adopt preventive measures, wherein the preventive measures comprises antihistamines and avoiding outdoor exposure; (700) generating, by the notification module, the alert to the user device if abnormal cough patterns are detected to flag early signs of respiratory illnesses of the user; (710) providing, by a feedback module, a feedback to the user if unusual compounds are detected in the breath; (720) transmitting, by the feedback module, a health report comprising a physiological data of the user via an interface to the user device, wherein the physiological data comprises a data skin temperature, heart rate, hydration levels, and overall health indicators; (730) and enabling, by a tracking module, the user to locate the wearable mask if misplaced by activating a built-in buzzer via the user device to emit a sound. (740)

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