DESC:EARLIEST PRIORITY DATE:
This Application claims priority from a Provisional patent application filed in India having Patent Application No. 202141047957, filed on October 21, 2021, and titled “SYSTEM AND METHOD FOR AIR PURIFICATION AND LOCALIZED AIR QUALITY MONITORING”.
FIELD OF INVENTION
[0001] Embodiments of the present disclosure relate to the field of face masks, and more particularly, a system for purifying and monitoring localized air and a method thereof.
BACKGROUND
[0002] Nowadays, people pay much attention to the devices and methods of monitoring the air quality in the environment. It is important to monitor carbon monoxide, carbon dioxide, volatile organic compounds (VOC), PM2.5, and so on. The exposure of these substances in the environment will cause human health problems or even harm the life. According to the World Health Organization (WHO), air pollution may be linked to 7 million premature deaths. Specifically, outdoor air pollution may several health diseases such as, heart disease, stroke, chronic obstructive pulmonary disease, lung cancer and acute lower respiratory infections in children. Further, multiple diseases are spread through respiratory droplets. Therefore, it is essential that the air surrounding a person be purified.
[0003] In one example, portable electronic devices are widely used and applied in the modern lives. If the portable electronic device is capable of immediately providing people with the monitored information relating to the environment for caution, it may help people escape or prevent from the injury and influence on human health caused by the exposure of the substances described above in the environment. However, there is a need of providing a driving and information transmitting system for an air-filtering protection device, which is capable of combining with an actuating and sensing device for monitoring the environment and enabling a protection mechanism immediately when the air quality is poor.
[0004] In another example, a mask may be used to manage health of the user from the toxic environment. Specifically in recent years, various attempts have been made to protect human respiratory health in such an environment, and one example is the development of the mask. Since the main respiratory system of a person is the nose and mouth, the nose and mouth are protected by a mask to prevent direct inhalation of air pollutants. The mask body is implemented in a dual structure having a filter body for effective blocking of foreign substances and pathogens. However, the conventional mask blocks the inflow of foreign substances or pathogens to the user's respiratory system and prevents the discomfort of the surrounding people due to the bad breath of the user or to prevent the pathogen from being transmitted to the surrounding people when the user is infected.
[0005] Hence, there is a need for an improved system and method for air purification and localized air quality monitoring which addresses the aforementioned issue(s).
BRIEF DESCRIPTION
[0006] In accordance with an embodiment of the present disclosure, a smart mask to purify and monitor localized air is provided. The smart mask includes a processing subsystem hosted on a server. The processing subsystem is configured to execute on a network to control bidirectional communications among a plurality of modules. The processing subsystem includes an identifying module operatively coupled to the processing subsystem and includes a capacitance sensor wherein the capacitance sensor is configured to detect a wearable position of the smart mask on the face of a user. The processing subsystem also includes an integrated sensor module operatively coupled to the identifying module wherein the integrated sensor module is configured to measure the air quality within an interior zone and exterior zone of the smart mask by a plurality of sensor nodes. The integrated sensor module further includes a first CO2 sensor positioned on an outer layer of the smart mask wherein the first CO2 sensor is configured to detect the carbon dioxide level of the surrounding air, a second CO2 sensor embedded inside the smart mask wherein the second CO2 sensor is configured to detect the carbon dioxide level inside the smart mask, a CO sensor positioned on the outer layer of the smart mask wherein the CO Sensor is configured to detect the carbon monoxide level of the air surrounding the smart mask and an air quality sensor positioned on the outer layer of the smart mask wherein the air quality sensor module is configured to detect the quality of the air surrounding the smart mask. Further, the processing subsystem also includes an Artificial Intelligence module operatively coupled to the integrated sensor module wherein the Artificial Intelligence module is configured to receive the measurements of the air quality. The Artificial Intelligence module further includes an analysis module configured to analyze the concentration of oxygen present in the air during the natural process of respiration of the user based on the carbon dioxide level detected by the second CO2 sensor, an air quality index module configured to compute the air quality index of the air surrounding the smart mask based on the carbon dioxide level, carbon monoxide level, and air quality detected by the first CO2 sensor, the CO sensor and the air quality sensor respectively and an alert module configured to alert the user to change a filter disposed in the smart mask based on the frequency of the smart mask worn by the user. Furthermore, the processing subsystem includes a predication module operatively coupled to the Artificial Intelligence module wherein the prediction module is configured to predict the air quality corresponding to a user location based on previously recorded air quality data of different users in the location. Moreover, the processing subsystem includes a hybrid filter module configured to filter out solid particles and gaseous particles from the air during the natural process of respiration of the user. The hybrid filter module further includes a HEPA filter module configured to removes solid particles from the air wherein the solid particles include dust, pollen, mold spores, dust mites, most bacteria and other allergens and an activated carbon filter module configured to remove gaseous particle from the air wherein the gaseous particle includes odours, smoke and fumes.
[0007] In accordance with another embodiment of the present disclosure, a method for operating the smart mask to purify and monitor localized air is provided. The method includes identifying, by a capacitance sensor of an identifying module, a wearable position of the smart mask on a face of a user. The method also includes detecting, by an integrated sensor module, the air quality within an interior zone and exterior zone of the smart mask wherein the detecting the air quality comprises detecting the carbon dioxide level surrounding the air, the carbon dioxide level inside the smart mask, the carbon monoxide level of the air surrounding the smart mask, the quality of the air surrounding the smart mask. Further, the method includes analyzing, by an analyzing module of an Artificial Intelligence module, the concentration of oxygen present in the air during the natural process of respiration of the user based on the carbon dioxide level detected by the second CO2 sensor. Furthermore, the method includes computing, by an air quality index module of an Artificial Intelligence module, the air quality index of the air surrounding the smart mask based on the carbon dioxide level, carbon monoxide level, toxic gas and air quality detected by the first CO2 sensor, the CO sensor and the air quality senor respectively. Moreover, the method includes alerting, by an alert module of an Artificial Intelligence module, the user to change a filter disposed in the smart mask based on the frequency of the smart mask worn by the user. The method includes predicting, by a predication module, the air quality corresponding to a user location based on previously recorded air quality data of different users in the location. The method includes removing, by a HEPA filter of a hybrid filter module, solid particles from the air wherein the solid particles include dust, pollen, mold spores, dust mites, most bacteria and other allergens. The method also includes removing, by an activated carbon filter of a hybrid filter module, gaseous particle from the air wherein the gaseous particle includes odours, smoke and fumes.
[0008] 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.
BRIEF DESCRIPTION OF THE DRAWINGS
[0009] The disclosure will be described and explained with additional specificity and detail with the accompanying figures in which:
[0010] FIG. 1 is a schematic representation of a smart mask to purify and monitor localized air in accordance with an embodiment of the present disclosure;
[0011] FIG. 2 is a block diagram of a processing subsystem in a smart mask in accordance with an embodiment of the present disclosure;
[0012] FIG. 3 is a block diagram of an Integrated Sensor Module of FIG. 2 in accordance with an embodiment of the present disclosure;
[0013] FIG. 4 is a block diagram of an Artificial Intelligence Module of FIG. 2 in accordance with an embodiment of the present disclosure;
[0014] FIG. 5 is a block diagram of a Hybrid Filter Module of FIG. 2 in accordance with an embodiment of the present disclosure;
[0015] FIG. 6 is a block diagram of a computer or a server in accordance with an embodiment of the present disclosure; and
[0016] FIG. 7 illustrates a flow chart representing the steps involved in a method for purifying and monitoring localized air using a smart mask in accordance with an embodiment of the present disclosure.
[0017] 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.
DETAILED DESCRIPTION
[0018] 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.
[0019] 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.
[0020] 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.
[0021] 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.
[0022] Embodiments of the present disclosure relate to a smart mask for purifying and monitoring localized air of a user. The smart mask includes a processing subsystem hosted on a server. The processing subsystem is configured to execute on a network to control bidirectional communications among a plurality of modules. The processing subsystem includes an identifying module operatively coupled to the processing subsystem and includes a capacitance sensor wherein the capacitance sensor is configured to detect a wearable position of the smart mask on the face of a user. The processing subsystem also includes an integrated sensor module operatively coupled to the identifying module wherein the integrated sensor module is configured to measure the air quality within an interior zone and exterior zone of the smart mask by a plurality of sensor nodes. The integrated sensor module further includes a first CO2 sensor positioned on an outer layer of the smart mask wherein the first CO2 sensor is configured to detect the carbon dioxide level of the surrounding air, a second CO2 sensor embedded inside the smart mask wherein the second CO2 sensor is configured to detect the carbon dioxide level inside the smart mask, a CO sensor positioned on the outer layer of the smart mask wherein the CO Sensor is configured to detect the carbon monoxide level of the air surrounding the smart mask and an air quality sensor positioned on the outer layer of the smart mask wherein the air quality sensor module is configured to detect the quality of the air surrounding the smart mask. Further, the processing subsystem also includes an Artificial Intelligence module operatively coupled to the integrated sensor module wherein the Artificial Intelligence module is configured to receive the measurements of the air quality. The Artificial Intelligence module further includes an analysis module configured to analyze the concentration of oxygen present in the air during the natural process of respiration of the user based on the carbon dioxide level detected by the second CO2 sensor, an air quality index module configured to compute the air quality index of the air surrounding the smart mask based on the carbon dioxide level, carbon monoxide level, and air quality detected by the first CO2 sensor, the CO sensor and the air quality sensor respectively and an alert module configured to alert the user to change a filter disposed in the smart mask based on the frequency of the smart mask worn by the user. Furthermore, the processing subsystem includes a predication module operatively coupled to the Artificial Intelligence module wherein the prediction module is configured to predict the air quality corresponding to a user location based on previously recorded air quality data of different users in the location. Moreover, the processing subsystem includes a hybrid filter module configured to filter out solid particles and gaseous particles from the air during the natural process of respiration of the user. The hybrid filter module further includes a HEPA filter module configured to removes solid particles from the air wherein the solid particles include dust, pollen, mold spores, dust mites, most bacteria and other allergens and an activated carbon filter module configured to remove gaseous particle from the air wherein the gaseous particle includes odours, smoke and fumes.
[0023] FIG. 1 is a schematic representation of a smart mask (104) to purify and monitor localized air in accordance with an embodiment of the present disclosure. The smart mask (104) is worn by the user (102) on his/ her face by griping the ear loops (108) around his/her ears. As a result, the smart mask (104) comes is close contact with the user’s skin. The smart mask (104) typically covers the nose and mouth regions of the user (as these regions form the main respiratory system) to form a constant internal space for breathing. Typically, the user (102) may wear the smart mask (104) in a closed environment or in an open environment at a specific geographical location.
[0024] In one embodiment, the material of the smart mask (104) may be formed of a relatively soft and soft silicon or plastic material.
[0025] Further, the smart mask (104) is adapted with an identifying module (106) and a processing subsystem (110). The identifying module (106) is positioned on any one of the ear loops (108) of the smart mask (104). In one embodiment, the identifying module (106) may be positioned on an inner layer of the smart mask (104) that meets a chin area of the user (102). Typically, the identifying module (106) is configured with a capacitance sensor (not shown in FIG. 1) and adapted to detect whether the user has worn the mask. In one embodiment, the detection may be completed within a specific time period, for instance 50 seconds and the like. Upon detection, the processing subsystem (110) gets activated.
[0026] It must be noted that the identifying module (106) may be positioned at any suitable position on the smart mask (104) such that the capacitance sensor of the identifying module (106) is capable to sense the user wearing the smart mask (104).
[0027] The processing subsystem (110) is further explained in conjunction with FIG. 2.
[0028] FIG. 2 is a block diagram of a processing subsystem (110) in a smart mask (104) in accordance with an embodiment of the present disclosure. The processing subsystem (110) is hosted on a server (112). In one embodiment, the server (112) may include a cloud-based server. In another embodiment, parts of the server (112) may be a local server coupled to a user device (116). The processing subsystem (105) is configured to execute on a network (114) to control bidirectional communications among a plurality of modules. In one example, the network (114) may be a private or public local area network (LAN) or Wide Area Network (WAN), such as the Internet. In another embodiment, the network (114) 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 (114) 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 (114) 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.
[0029] The smart mask (104) includes an identifying module (106) operatively coupled to the processing subsystem (110) and comprises a capacitance sensor (not shown in FIG.2). The capacitance sensor is configured to detect a wearable position of the smart mask (104) on the face of a user by sensing the skin of the user. In one embodiment, the identifying module (106) may be disposed at any suitable position on an inner layer of the smart mask (104) such that the capacitance sensor detects the skin of the user.
[0030] The smart mask (104) also includes an integrated sensor module (118) operatively coupled to the identifying module (106) of the processing subsystem (110). The integrated sensor module (118) is configured to measure the air quality within an interior zone and exterior zone of the smart mask. The interior zone corresponds to the air inside the smart mask in response to the user wearing the smart mask and the exterior zone corresponds to the air outside the smart mask. The integrated sensor module (118) module comprises a plurality of sensor nodes that is accountable to measure the air quality. The plurality of sensor nodes is further explained in conjunction with FIG. 3.
[0031] The plurality of sensor nodes include a first CO2 sensor (134) positioned on an outer layer of the smart mask (104). The first CO2 sensor (134) is configured to detect the carbon dioxide level of the surrounding air. Further, the plurality of sensor nodes include a second CO2 sensor (136) embedded inside the smart mask (104). The second CO2 sensor (136) is configured to detect the carbon dioxide level inside the smart mask (104) after the user (102) wears it. Furthermore, the plurality of sensor nodes comprises a CO sensor (138) positioned on the outer layer of the smart mask (104). The CO Sensor (138) is configured to detect the toxic carbon monoxide level of the air surrounding the smart mask (104). The plurality of sensor nodes also comprises an air quality sensor (140) positioned on the outer layer of the smart mask (104). The air quality sensor (140) is configured to detect the quality of the air surrounding the smart mask (104).
[0032] It must be noted that the smart mark (104) may be configured with any other suitable sensor node that is accountable to purify and monitor the air and must be limited to the said plurality of sensor nodes mentioned above.
[0033] The smart mask (100) includes an Artificial Intelligence module (120) operatively coupled to the integrated sensor module (118) of the processing subsystem (110). The Artificial Intelligence module (120) is configured to receive the measurements of the air quality from the integrated sensor module (118) using Artificial Intelligence algorithms. In other words, the Artificial Intelligence module (120) is accountable to analyze the breath of the user (102). Typically, the Artificial Intelligence module (120) is accountable to perform an analysis of the measurements of the air quality. The Artificial Intelligence module (120) is also configured to analyze the breath of the user (102). The result of the analysis monitors the quality of the air surrounding the smart mark (104). The Artificial Intelligence module (230) is further explained in conjunction with FIG. 4.
[0034] The smart mask (100) includes a prediction module (122) operatively coupled to the Artificial Intelligence module (120) of the processing subsystem (110). The prediction module (122) is configured to predict the air quality corresponding to a user location based on previously recorded air quality data of different users in the location. The prediction is performed by an artificial intelligence algorithm. Examples of the artificial intelligence algorithm includes, but are not limited to, a Deep Neural Network (DNN), Convolutional Neural Network (CNN), Restricted Boltzmann Machine (RBM), Deep Belief Network (DBN) and Deep Q-Networks.
[0035] The smart mask (100) includes a hybrid filter module (124) operatively coupled to the prediction module (122) of the processing subsystem (110) and configured to filter out solid particles and gaseous particles from the air during the natural process of respiration of the user. It is an essential feature of the hybrid filter module (124) that the filtration process is equipped with a unique filter configured with a combination of High Efficiency Particulate Air (HEPA) filter and activated carbon filtration technology. The HEPA filter can theoretically remove at least 99.97 percentage of dust, pollen, mold, bacteria and any other airborne particles. In one embodiment, the hybrid filter module (124) may include any other suitable filtration technologies such as, but not limited to, an Ultra-Low Penetration Air Filter (ULPA), Nano fiber filter (nano-fiber filter), electrostatic filter (electret filter), gas filter, catalyst filter, or anti-microbial filter. In addition, specific chemicals may be added to help remove specific gases or aerosols. The hybrid filter module (124) is further explained in conjunction with FIG. 5.
[0036] The smart mask (100) includes a report generation module (126) operatively coupled to the hybrid filer module (124) of the processing subsystem (110). The report generation module (126) is configured to display air quality index, carbon dioxide level, carbon monoxide level, and presence of toxic gasses that have been detected on a user device (116). Examples of the user device includes, but is not limited to, a personal computer (PC), a mobile phone, a tablet device, a personal digital assistant (PDA), a smart phone, a laptop, and pagers. In one embodiment, the report generation module (126) displays the air quality index, carbon dioxide level, carbon monoxide level, and presence of toxic gasses through graphical representations, pictorial representations and the like.
[0037] The smart mask (100) includes a wireless communication module (128) operatively coupled to the report generation module (126) of the processing subsystem (110). The wireless communication module (128) is configured to communicate the concentration of oxygen upon analysis and the air quality index of the air surrounding the smart mask (104) from the smart mask (104) to the user device (116). In one embodiment, the wireless communication is via Bluetooth low energy (BLE) technology that is intended to provide considerably reduced power consumption and cost while maintaining a suitable communication range.
[0038] The smart mask (100) also includes a wireless charging module (130) operatively coupled to the processing subsystem (110). The wireless charging module (130) is electrically connected to a rechargeable battery and is configured to wirelessly collect external energy to charge the rechargeable battery. The rechargeable battery is configured to power the integrated sensor module (118) of the smart mask (100). In one embodiment, a lithium-ion battery, a lithium polymer battery, and the like are suitable. The user can check the current battery state. Of course, the state of the battery can be checked via the user device (116) in cooperation with the application of the user device (116), and a warning can be issued when the remaining amount of the battery is low.
[0039] The processing subsystem (110) is operatively coupled to a database (132) configured to store the air quality measurements pertaining to the user location.
[0040] It is to be noted that the system may comprise, but is not limited to, a mobile phone, desktop computer, portable digital assistant (PDA), smart phone, tablet, ultra-book, netbook, laptop, multi-processor system, microprocessor-based or programmable consumer electronic system, or any other communication device that a user may use. In some embodiments, the system may comprise a display module (not shown) to display information (for example, in the form of user interfaces). In further embodiments, the system may comprise one or more of touch screens, accelerometers, gyroscopes, cameras, microphones, global positioning system (GPS) devices, and so forth.
[0041] In one embodiment, the various functional components of the system may reside on a single computer, or they may be distributed across several computers in various arrangements. The various components of the system may, furthermore, access one or more databases, and each of the various components of the system may be in communication with one another. Further, while the components of FIG. 1 are discussed in the singular sense, it will be appreciated that in other embodiments multiple instances of the components may be employed.
[0042] FIG. 3 is a block diagram of an Integrated Sensor Module of FIG. 2 in accordance with an embodiment of the present disclosure. The integrated sensor module (118) comprises a first CO2 sensor (134) positioned on an outer layer of the smart mask (104). The first CO2 sensor (134) is configured to detect the carbon dioxide level of the surrounding air. The integrated sensor module (118) also comprises a second CO2 sensor (136) embedded inside the smart mask (104). The second CO2 sensor (136) is configured to detect the carbon dioxide level inside the smart mask (104). Extreme levels of CO2 can lead to death, particularly in enclosed spaces. Examples of enclosed space are laboratories, some hospital rooms, breweries and the like. The integrated sensor module (118) further comprises a CO sensor (138) positioned on the outer layer of the smart mask (104). The CO sensor (138) is configured to detect the toxic carbon monoxide level of the air surrounding the smart mask (104). A very high level of carbon monoxide can also cause serious illness and death. The integrated sensor module (118) furthermore comprises an air quality sensor (140) positioned on the outer layer of the smart mask (104). The air quality sensor (140) is configured to detect the quality of the air surrounding the smart mask (104) by detecting the contaminants in the surrounding air. Examples of contaminants include pollutants and noxious gases that may be harmful to human health.
[0043] FIG. 4 is a block diagram of an Artificial Intelligence Module of FIG. 2 in accordance with an embodiment of the present disclosure. The Artificial Intelligence module (120) includes an analysis module (142), an air quality index module (144) and an alert module (146). The analysis module (142) is configured to analyze the concentration of oxygen present in the air during the natural process of respiration of the user based on the carbon dioxide level detected by the second CO2 sensor (136). The air quality index module (144) is configured to compute the air quality index of the air surrounding the smart mask based on the carbon dioxide level, carbon monoxide level, toxic gas and air quality detected by the first CO2 sensor (134), the CO sensor (138) and the air quality senor (140) respectively. The alert module (146) is configured to alert the user (102) to change a filter disposed in the smart mask based on the frequency of the smart mask (104) worn by the user (102). In other words, after frequent utilization of the smart mask (104), the filter may need to be replace due to the accumulation of dust, contaminants and the like. In one embodiment, the alert may be via warnings or triggers displayed on the user device.
[0044] FIG. 5 is a block diagram of a Hybrid Filter Module of FIG. 2 in accordance with an embodiment of the present disclosure.
[0045] The hybrid filter module (124) comprises a HEPA filter module (148) configured to removes solid particles from the air. The solid particles include, but not limited to, dust, pollen, mold spores, dust mites, most bacteria, and other allergens. The hybrid filter module (124) also comprises an activated carbon filter module (150) configured to remove gaseous particles from the air. The gaseous particle includes, but is not limited to, odours, smoke, and fumes.
[0046] It must be noted that the hybrid filter module (124) purifies the air using the combination of HEPA filters and activated carbon filters. The said combination achieves a high effective rate of filtration.
[0047] FIG. 6 is a block diagram of a computer or a server in accordance with an embodiment of the present disclosure. The server (200) includes processor(s) (230), and memory (210) operatively coupled to the bus (220). The processor(s) (230), 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.
[0048] The memory (210) includes several subsystems stored in the form of executable program which instructs the processor (230) to perform the method steps illustrated in FIG. 1. The memory (210) includes a processing subsystem (110) of FIG.1. The processing subsystem (110) further has following modules: an identifying module (106), an integrated sensor module (118), an Artificial Intelligence module (120), a prediction module (122), a hybrid filter module (124), a report generation module (126), a wireless communication module (128) and a wireless charging module (130).
[0049] In accordance with an embodiment of the present disclosure, a smart mask (104) to purify and monitor localized air is provided. The smart mask includes a processing subsystem (110) hosted on a server (112). The processing subsystem (110) is configured to execute on a network (114) to control bidirectional communications among a plurality of modules. The processing subsystem (110) includes an identifying module (106) operatively coupled to the processing subsystem (110) and includes a capacitance sensor wherein the capacitance sensor is configured to detect a wearable position of the smart mask (104) on the face of a user (102). The processing subsystem (110) also includes an integrated sensor module (118) operatively coupled to the identifying module (106) wherein the integrated sensor module (118) is configured to measure the air quality within an interior zone and exterior zone of the smart mask (104) by a plurality of sensor nodes. The integrated sensor module further includes a first CO2 sensor (134) positioned on an outer layer of the smart mask wherein the first CO2 sensor (134) is configured to detect the carbon dioxide level of the surrounding air, a second CO2 sensor (136) embedded inside the smart mask wherein the second CO2 sensor (136) is configured to detect the carbon dioxide level inside the smart mask, a CO sensor (138) positioned on the outer layer of the smart mask wherein the CO Sensor (138) is configured to detect the carbon monoxide level of the air surrounding the smart mask and an air quality sensor (140) positioned on the outer layer of the smart mask wherein the air quality sensor (140) is configured to detect the quality of the air surrounding the smart mask. Further, the processing subsystem (110) also includes an Artificial Intelligence module (120) operatively coupled to the integrated sensor module (118) wherein the Artificial Intelligence module (120) is configured to receive the measurements of the air quality. The Artificial Intelligence module (120) further includes an analysis module (142) configured to analyze the concentration of oxygen present in the air during the natural process of respiration of the user based on the carbon dioxide level detected by the second CO2 sensor (136), an air quality index module (144) configured to compute the air quality index of the air surrounding the smart mask based on the carbon dioxide level, carbon monoxide level, and air quality detected by the first CO2 sensor, the CO sensor (138) and the air quality sensor (140) respectively and an alert module (146) configured to alert the user to change a filter disposed in the smart mask based on the frequency of the smart mask worn by the user. Furthermore, the processing subsystem (110) includes a predication module (122) operatively coupled to the Artificial Intelligence module (120) wherein the prediction module (122) is configured to predict the air quality corresponding to a user location based on previously recorded air quality data of different users in the location. Moreover, the processing subsystem (110) includes a hybrid filter module (124) configured to filter out solid particles and gaseous particles from the air during the natural process of respiration of the user. The hybrid filter module further includes a HEPA filter module (148) configured to removes solid particles from the air wherein the solid particles include dust, pollen, mold spores, dust mites, most bacteria and other allergens and an activated carbon filter module (150) configured to remove gaseous particle from the air wherein the gaseous particle includes odours, smoke and fumes.
[0050] The bus (220) 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 (220) 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 (220) 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.
[0051] FIG. 7 illustrates a flow chart representing the steps involved in a method for purifying and monitoring localized air using a smart mask in accordance with an embodiment of the present disclosure. The method includes identifying a wearable position of the smart mask on the face of a user in step (310). The user may be in an enclosed environment or in an open environment. It is potential that the air in any of the said environment may be impure. Therefore, it is essential for the user to wear the smart mask disclosed herein. The smart mask is activated upon identifying the wearable position of the smart mask. Typically, the identification may take some time to complete its task, for example, but not limited to, approximately 50 seconds after the user wears the smart mask.
[0052] Further, identifying the wearable position is performed by a capacitance sensor embedded within the inner layer of the smart mask. Typically, the capacitance sensor identifies the wearable position when it senses the skin of the user. It must be noted the capacitance sensor may be disposed in a suitable position on the smart mask. For example, the capacitance sensor may be disposed on the ear loop of the smart mask or at a region on the smart mask that covers the chin of the user and the like.
[0053] The method includes detecting the air quality within an interior zone and exterior zone of the smart mask in step (320). It is essential that the air quality is measured and monitored inside the smart mask and outside the smart mask. This step (320) is performed by a plurality of sensor nodes that collectively intend to measure the air quality. The plurality of sensor nodes includes the following:
1. A first CO2 sensor: Positioned on an outer layer of the smart mask and configured to detect the carbon dioxide level of the surrounding air.
2. A second CO2 sensor: Positioned on an inner layer of the smart mask and configured to detect the carbon dioxide level inside the smart mask.
3. A CO sensor: Positioned on the outer layer of the smart mask and configured to detect the carbon monoxide level of the air surrounding the smart mask.
4. An air quality sensor: Positioned on the outer layer of the smart mask and configured to detect the quality of the air surrounding the smart mask.
[0054] The method includes analyzing the concentration of oxygen present in the air during the natural process of respiration of the user based on the carbon dioxide level detected by the second CO2 sensor in step (330). As the user respirates, it is essential to identify the carbon dioxide level within the smart mask.
[0055] The method includes computing the air quality index of the air surrounding the smart mask based on the carbon dioxide level, carbon monoxide level, toxic gas and air quality detected by the first CO2 sensor, the CO sensor and the air quality senor respectively in step (340).
[0056] Carbon monoxide is a colorless and odorless toxic gas generated when carbon in fuel is incompletely burned. The sources of emissions are mainly automobiles, natural sources such as the burning of factory fuels and wildfires and indoor sources such as kitchens, cigarette smoke and indoor heating.
[0057] The method includes alerting the user to change a filter disposed in the smart mask based on the frequency of the smart mask worn by the user in step (350). At times, the filter may have to be replaced due to accumulation of dust, dirt and other impurities that cause air pollution. In such a scenario, the user is alerted through his/her mobile device.
[0058] The method includes predicting the air quality corresponding to a user location based on previously recorded air quality data of different users in the location in step (360).
[0059] It must be noted that step (330), step (340) and step (360) are performed by an artificial intelligence algorithm. Examples of the artificial intelligence algorithm includes, but are not limited to, a Deep Neural Network (DNN), Convolutional Neural Network (CNN), Restricted Boltzmann Machine (RBM), Deep Belief Network (DBN) and Deep Q-Networks.
[0060] The method includes removing solid particles from the air wherein the solid particles include dust, pollen, mold spores, dust mites, most bacteria and other allergens in step (370).
[0061] The method includes removing gaseous particle from the air wherein the gaseous particle includes odours, smoke and fumes in step (380).
[0062] Various embodiments of the smart mask for purifying and monitoring the surrounding air and a method thereof described above enable various advantages. The design of the hybrid filter module comprising the combination of HEPA filters and activated carbon filters provides a unique air filter mechanism with a highly efficient rate of filtration. Further, the air inside and outside the smart mask is analyzed such that the air is purified and monitored periodically. This allows a location-based pollution monitoring system. Furthermore, the wireless charging design provides a battery powered mask.
[0063] 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 control unit including hardware may also perform one or more of the techniques of this disclosure.
[0064] 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.
[0065] 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.
[0066] 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.
[0067] 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:1. A smart mask (104) for purifying and monitoring localized air comprising:
a processing subsystem (110) hosted on a server (112), wherein the processing subsystem (110) is configured to execute on a network (114) to control bidirectional communications among a plurality of modules comprising:
an identifying module (106) operatively coupled to the processing subsystem (110) and comprising a capacitance sensor wherein the capacitance sensor is configured to detect a wearable position of the smart mask (104) on the face of a user (102);
an integrated sensor module (118) operatively coupled to the identifying module (106) wherein the integrated sensor module (118) is configured to measure the air quality within an interior zone and exterior zone of the smart mask (104) comprising:
a first CO2 sensor (134) positioned on an outer layer of the smart mask (104) wherein the first CO2 sensor (134) is configured to detect the carbon dioxide level of the surrounding air;
a second CO2 sensor (136) embedded inside the smart mask (104) wherein the second CO2 sensor (136) is configured to detect the carbon dioxide level inside the smart mask (104);
a CO sensor (138) positioned on the outer layer of the smart mask (104) wherein the CO Sensor (138) is configured to detect the carbon monoxide level of the air surrounding the smart mask (104);
an air quality sensor (140) positioned on the outer layer of the smart mask (104) wherein the air quality sensor module (140) is configured to detect the quality of the air surrounding the smart mask (104);
an Artificial Intelligence module (120) operatively coupled to the integrated sensor module (118) wherein the Artificial Intelligence module (120) is configured to receive the measurements of the air quality and comprising:
an analysis module (142) configured to analyze the concentration of oxygen present in the air during the natural process of respiration of the user (102) based on the carbon dioxide level detected by the second CO2 sensor (136);
an air quality index module (144) configured to compute the air quality index of the air surrounding the smart mask (104) based on the carbon dioxide level, carbon monoxide level, and air quality detected by the first CO2 sensor (134), the CO sensor (138) and the air quality sensor (140) respectively;
an alert module (146) configured to alert the user (102) to change a filter disposed in the smart mask (104) based on the frequency of the smart mask (104) worn by the user (102);
a predication module (122) operatively coupled to the Artificial Intelligence module (120) wherein the prediction module (122) is configured to predict the air quality corresponding to a user location based on previously recorded air quality data of different users in the location;
a hybrid filter module (124) configured to filter out solid particles and gaseous particles from the air during the natural process of respiration of the user (102) comprising:
a HEPA filter module (148) configured to removes solid particles from the air wherein the solid particles include dust, pollen, mold spores, dust mites, most bacteria and other allergens;
an activated carbon filter module (150) configured to remove gaseous particle from the air wherein the gaseous particle includes odours, smoke and fumes.

2. The smart mask (104) as claimed in claim 1 comprising a report generation module (126) operatively coupled to the processing sub-system (110) wherein the report generation module (126) is configured to display air quality index, carbon dioxide level, carbon monoxide level, and presence of toxic gasses of the user location.

3. The smart mask (104) as claimed in claim 1 comprising a wireless communication module (128) operatively coupled to the processing sub-system (110) wherein the wireless communication module (128) configured to wirelessly communicate the concentration of oxygen upon analysis and the air quality index of the air surrounding the smart mask (104) from the smart mask (104) to the user device (116).
4. The smart mask (104) as claimed in claim 1 comprising a wireless charging module (130) is electrically connected to the rechargeable battery, wherein the wireless charging module (130) is configured to wirelessly collect external energy to charge the rechargeable battery wherein rechargeable battery is configured to power the integrated sensor module (118) of the smart mask (104).

5. The smart mask (104) as claimed in claim 3 wherein the data transmitted through the wireless communication module (128) is stored in a network (114).

6. The smart mask (104) as claimed in claim 1 comprising a database (132) operatively coupled to the processing sub-system (110) wherein the database (132) is operable to store data wherein the data includes air quality index of the air corresponding to the user location.

7. The smart mask (104) as claimed in claim 1 wherein the interior zone corresponds to the air inside the smart mask (104) in response to the user (102) wearing the smart mask (104) and the exterior zone corresponds to the air outside the smart mask (104).

8. The smart mask (104) as claimed in claim1 wherein the user (102) is located in at least one of an enclosed environment and an open environment at a specific geographical location.

9. A method (300) for purifying and monitoring localized air using a smart mask comprising:
identifying, by a capacitance sensor of an identifying module, a wearable position of the smart mask on a face of a user; (310)
detecting, by an integrated sensor module, the air quality within an interior zone and exterior zone of the smart mask wherein the detecting the air quality comprises detecting the carbon dioxide level surrounding the air, the carbon dioxide level inside the smart mask, the carbon monoxide level of the air surrounding the smart mask, the quality of the air surrounding the smart mask; (320)
analyzing, by an analysis module of an Artificial Intelligence module, the concentration of oxygen present in the air during the natural process of respiration of the user based on the carbon dioxide level detected by the second CO2 sensor; (330)
computing, by an air quality index module of an Artificial Intelligence module, the air quality index of the air surrounding the smart mask based on the carbon dioxide level, carbon monoxide level, toxic gas and air quality detected by the first CO2 sensor, the CO sensor and the air quality senor respectively; (340)
alerting, by an alert module of an Artificial Intelligence module, the user to change a filter disposed in the smart mask based on the frequency of the smart mask worn by the user; (350)
predicting, by a predication module, the air quality corresponding to a user location based on previously recorded air quality data of different users in the location; (360)
removing, by a HEPA filter of a hybrid filter module, solid particles from the air wherein the solid particles include dust, pollen, mold spores, dust mites, most bacteria and other allergens; (370)
removing, by an activated carbon filter of a hybrid filter module, gaseous particle from the air wherein the gaseous particle includes odours, smoke and fumes. (380)

Dated this 20th day of October 2022

Signature

Jinsu Abraham
Patent Agent (IN/PA-3267)
Agent for the Applicant