Description:TECHNICAL FIELD
[0001] The present disclosure relates to health monitoring. More particularly the present disclosure relates to a system and method for monitoring patients from remote location, and enables a patient to receive instructions of treatment at home.

BACKGROUND
[0002] Background description includes information that may be useful in understanding the present invention. It is not an admission that any of the information provided herein is prior art or relevant to the presently claimed invention, or that any publication specifically or implicitly referenced is prior art.
[0003] Throughout the human history, the mankind has experienced a number of pandemics of infectious diseases such as smallpox, tuberculosis, HIV/AIDS, SARS, COVID 19, and the likes, and killed thousands of people all over the world. These infectious diseases represent a significant threat to the society in spite of medical advancement over last centuries. Therefore, preventive measures are required to determine any risk in people health and take necessary action based on determined risk.
[0004] COVID-19 spreads mainly among people who are in close contact within about 6 feet for a prolonged period. The risk of exposure to a virus posed to uninfected people from an infected person either by direct contact or action such as sneezing, coughing, and the like or through contact of any surface touched by the infected person.
[0005] Recent studies indicate that people who are infected by this virus but do not have symptoms also play a role in the spread of COVID-19. Therefore, the infected person should isolate himself to prevent spreading of the virus, but it is not possible, as they have to visit hospitals for treatments. Moreover, the regular visits to hospitals for regular check-ups have become jeopardized due to risk of developing infection. It is not possible for doctors and nurses to attend all Covid-19 patients who are in quarantine at once when there is a shortage of medical officials. With the increase in COVID-19 cases, the hospitals have been facing burden regarding management of patients and providing them necessary facilities. People avoid visiting hospitals due to risk of infectious diseases. Therefore, it has become extremely important that health care facilities are accessible at home.
[0006] Furthermore, Covid-19 is might be get easily transmitted from patients to doctor and nurses as well as other health workers even when they wear PPE Kits and other accessories. Therefore, a system is required for monitoring of home isolation Covid-19 patient remotely.
[0007] There is, therefore, a need of a solution for monitoring health at home by identifying symptoms of Covid-19 and providing better treatment remotely and quickly.

OBJECTS OF THE PRESENT DISCLOSURE
[0008] Some of the objects of the present disclosure, which at least one embodiment herein satisfies are as listed herein below.
[0009] It is an object of the present disclosure to provide a system for monitoring health at home.
[0010] It is an object of the present disclosure to provide a system to identify Covid-19 symptoms in a user.
[0011] It is an object of the present disclosure to provide a system that notifies the users automatically when health condition is critical.
[0012] It is an object of the present disclosure to provide a system that reduces the chances of getting infected from transmission diseases while visiting to hospitals.
[0013] It is an object of the present disclosure to provide a system that is user-friendly.

SUMMARY
[0014] The present disclosure relates to health monitoring. More particularly the present disclosure relates to a system and method for monitoring patients from remote location, and enables a patient to receive instructions of treatment at home.
[0015] An aspect of the present disclosure pertains to system for health monitoring, the system may including an input device configured to receive a plurality of health attributes as input from one or more sensing devices by a user, and correspondingly generate a first set of signals, a processing unit operatively coupled with the input device.
[0016] In an aspect, the processing unit may include a processor configured to execute a set of instructions, stored in a memory, which, on execution, causes the system to receive, the first set of signals pertaining to health attributes of the user by a communication unit, extract values of each of the plurality of health attributes from the received first set of signals, compare extracted values of the health attributes with a set of pre-defined threshold values, and generate warning signals when the value of any of the health attributes found beyond the associated pre-defined threshold values, also transmit the warning signals to one or more mobile computing devices, where the warning signals may pertain information such as risk, precautions and medications associated to one or more diseases.
[0017] In an aspect, the processing unit may be further configured to transmit the extracted values of each of the plurality of health attributes of the user to a server, and the server is configured to store information associated with many users, which may enable an entity to access information using the associated mobile computing devices.
[0018] In an aspect, the input device may include one or more ports to facilitate operative coupling with the one or more sensing devices to transmit received input to the input device, and the input device may facilitate the user to enter input using an interface provided on the input device.
[0019] In an aspect, the one or more sensing devices may be selected from a group of thermometer, oximeter, heart rate monitor, and blood pressure sensor, and acoustic sensor.
[0020] In an aspect, the plurality of health attributes may include any or a combination of body temperature, oxygen level, heart rate, blood pressure, and cough sound.
[0021] In an aspect, the communication unit may include any or combination of Wireless Fidelity (Wi-Fi) Module, Bluetooth Module, Li-Fi Module, Wireless Local Area Network (WLAN), and ZigBee.
[0022] In an aspect, the one or more mobile computing devices may include any or a combination of mobile terminal, laptop and tablet.
[0023] In an aspect, the present disclosure provides a method for health monitoring of a user, the method may include receiving by an input device, a plurality of health attributes of a user, collected by one or more sensing devices, transmitting by the input device, the received health attributes to a mobile computing device, extracting at a processor of a processing unit, values of the received plurality of health attributes, comparing at the processor, the extracted values of the plurality of health attributes with a dataset having a set of pre-defined threshold values, generating at the processor, warning signals pertaining information such as risk, precautions and medications associated to one or more diseases, and transmitting the generated warning signals to the associated mobile computing devices, transmitting at the processor, extracted values of each of the plurality of health attributes of the user to a server, and enabling at the processor, entity to access information using the associated mobile computing device.
[0024] Various objects, features, aspects and advantages of the inventive subject matter will become more apparent from the following detailed description of preferred embodiments, along with the accompanying drawing figures in which like numerals represent like components.

BRIEF DESCRIPTION OF DRAWINGS
[0025] The accompanying drawings are included to provide a further understanding of the present disclosure, and are incorporated in and constitute a part of this specification. The drawings illustrate exemplary embodiments of the present disclosure and, together with the description, serve to explain the principles of the present disclosure. The diagrams are for illustration only, which thus is not a limitation of the present disclosure.
[0026] In the figures, similar components and/or features may have the same reference label. Further, various components of the same type may be distinguished by following the reference label with a second label that distinguishes among the similar components. If only the first reference label is used in the specification, the description is applicable to any one of the similar components having the same first reference label irrespective of the second reference label.
[0027] FIG. 1A illustrates an exemplary network architecture in which or with which proposed system for health monitoring can be implemented, in accordance with an embodiment of the present disclosure.
[0028] FIG 2A illustrates an exemplary block diagram of a device used with proposed system in accordance with an embodiment of the present disclosure.
[0029] FIG. 2B illustrates an exemplary block diagram for proposed system, in accordance with an embodiment of the present disclosure.
[0030] FIG. 3 illustrates an exemplary functional components of a processing unit of the proposed system, in accordance with an embodiment of the present disclosure.
[0031] FIG. 4 illustrates an exemplary flow diagram of the proposed system in accordance with an embodiment of the present disclosure.
[0032] FIG. 5 illustrates an exemplary flow chart of a method for health monitoring, in accordance with an embodiment of the present disclosure.

DETAILED DESCRIPTION
[0033] The following is a detailed description of embodiments of the disclosure depicted in the accompanying drawings. The embodiments are in such detail as to clearly communicate the disclosure. However, the amount of detail offered is not intended to limit the anticipated variations of embodiments; on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the scope of the present disclosure as defined by the appended claims.
[0034] In the following description, numerous specific details are set forth in order to provide a thorough understanding of embodiments of the present invention. It will be apparent to one skilled in the art that embodiments of the present invention may be practiced without some of these specific details.
[0035] The present disclosure relates to health monitoring. More particularly the present disclosure relates to a system and method for monitoring patients from remote location, and enables a patient to receive instructions of treatment at home.
[0036] The present disclosure elaborates upon a system for health monitoring of a user at home. The system can include an input device, which can be used easily by user to receive health attributes as input from one or more sensing devices. Received input can be analysed by a processing unit to identify symptoms of COVID, if symptoms is found and health condition is critical, user can be alerted to take action accordingly. Also, when symptoms are normal such as normal fever, and flu, the system can recommend medications, guidelines to be follow, and diet. Also, received input and processed information can be stored to a server, which enables user, healthcare professionals, and other concerned person to check health condition any time from the server.
[0037] As illustrated in FIG. 1, a network implementation 100, a system 102 for monitoring health of many users can be communicatively coupled with a plurality of input devices 114-1, 114-2…114-N (collectively referred to as input devices 114 and individually referred to as input device 114 hereinafter) through network 104. The system 102 can be implemented using any or a combination of hardware components and software components such as a server 106, a computing system, a computing device, a security device and the likes.
[0038] Further, the system 102 can interact with the users 110-1, 110-2…110-N (collectively referred to as users 110, and individually referred to as user 110 herein after), through the input devices 114. Also, mobile computing devices 108-1, 108-2….108-N (collectively referred to as mobile computing devices 108, and individually referred to as mobile computing device 108 herein after), can be configured to receive the input from the associated input device 114 through applications residing on mobile computing device 108. The mobile computing device 108 can include but not limited to a laptop, phone, tablet etc. In an implementation, the system 102 can be accessed by applications residing on any operating system, including but not limited to, AndroidTM, iOSTM, and the like.
[0039] In an embodiment, the system 102 can be configured to analyse the input received through the input device 114, and when health condition is not critical, the system 102 can recommend treatment based on found disease automatically.
[0040] In an embodiment, the system can be operatively configured with an entity 112 through the network 104. The entity 112 can include any or combination of a healthcare professionals, healthcare staffs, family member, pharmacist, and likes. The entity 112 can be configured to check the health attributes of the user, and accordingly can recommend medications, instructions, and the likes to the user remotely when health condition is critical.
[0041] In an embodiment, received attributes and analysed information can be transmitted to a server 106 through the network 104 where the server 106 can be configured to store received attributes and information, which can be accessed by the users 110 and the entity 112 in future.
[0042] As illustrated in FIG. 2A, an input device 114 can be used to receive information form one or more sensing devices 202 (collectively referred as sensing devices 202 and individually referred as sensing device 202). The input device 114 can include one or more ports to facilitate operative coupling with the sensing devices 202, and upon coupling a plurality of health attributes (collectively referred as health attributes and individually referred as health attribute) collected by the sensing device 202 can be transmitted to the input device 114.
[0043] In an embodiment, the sensing device 202 can be selected from, but not limited to thermometer, oximeter, heart rate monitor, blood pressure sensor, and acoustic sensor, where the acoustic sensors can include any or a combination of mic, microphone, sensors, and the likes. The health attributes can include body temperature, oxygen level, heart rate, blood pressure, and cough sound, but not limited to likes.
[0044] In an embodiment, the health attributes can be input by the user through an interface configure with the input device 114. For example, when the user check body temperature through a thermometer, there is no option available to connect the thermometer with the input device 114, the user can enter collected temperature value manually through the interface which is touchscreen. The interface can include any or a combination of light emitting diode (LED), liquid crystal display (LCD), organic light emitting diode (OLED), LED matrix, and the likes.
[0045] In an exemplary embodiment, when a user is not feeling well, the user itself or any other family person can collect temperature value through a thermometer and oxygen level through an oximeter, and the collected temperature value and the oxygen level can be provided to the input device 114 by coupling through the port or can enter value manually.
[0046] In an exemplary embodiment, many sensing devices 202 can include Bluetooth, Wi-Fi, which enables the user to transmit the collected health attributes wirelessly to the input device 114. Also, many sensing devices 202 can be coupled to the input device 114 by using a cable, where one end can be coupled to the sensing device 202 and another end can be coupled with the input device 114.
[0047] As illustrated in Fig. 2B, a system 102 is disclosed, where the system can include an input device 114 which can be used by a user 110 to receive health attributes collected from sensing devices 202. In an exemplary embodiment, firstly, the user 110 is required to get register into the system 102 through a mobile computing device 108, in order to register the user 110 provide details such as, but not limited to, name, age, sex, address, mobile number, and email through the mobile application installed on the mobile computing device 108, and are stored in a database.
[0048] In an embodiment, a fog layer can include various technologies ranging from Bluetooth to satellite links and can assist in communication in between cloud 106 (interchangeably referred as server 106) and the mobile computing device 108. In an exemplary embodiment, the fog layer can reduce bandwidth and reduces back-and-forth communication between the input device 114 and the cloud 106. In another embodiment, the fog layer can include a series of nodes (interchangeably referred as processing unit) to receive health attributes from mobile computing devices 108 in real time, and the nodes perform real-time analysis of the received health attributes, and can transmit analyzed information to the cloud 106.
[0049] In an embodiment, the sensing device 202 can collect many health attributes which can be fed to the input device 114, further the input device 114 can transmit the received health attributes to the associated mobile computing device 108. The mobile computing device 108 can include a mobile application which can works as the fog layer. The fog layer can include a processing unit 118 to receive health attributes form the mobile computing device 108 through a communication unit 104, upon receiving the health attributes the processing unit 118 can extract values of each of the health attributes and compare with a set of pre-defined threshold values. When any of health attributes found beyond the associated threshold value and one or more diseases detected, the user 104 can be alerted. In an exemplary embodiment, the communication unit can include any or combination of Wireless Fidelity (Wi-Fi), Bluetooth, and the likes.
[0050] In an exemplary embodiment, the system 102 can be configured to analyse stages of one or more diseases. When the system 102 found that the user is having coronavirus at a lower stage, the system 102 can suggest the user 110 to take medicines prescribed by World Health Organizations (WHO), and instructions to be followed such as isolation, diet, and the likes.
[0051] In an embodiment, the received health attributes can be transmitted to the mobile computing device 108, and further can be transmitted to a server to store the health attributes which can be accessed by the user 110 and entity 112 anytime. In an exemplary embodiment, the entity 112 can be doctor, healthcare taker, patient, and relative.
[0052] In an embodiment, the processing unit can be communicatively coupled with the mobile computing device 108, and risk or stages of one or more diseases can be transmitted to the mobile computing device 108, which can be further transferred to the cloud, also, the processing unit can directly transfer the analysed data to the server 106.
[0053] In an exemplary embodiment, when the system 102 found that the user is having coronavirus at a critical stage, the system 102 can recommend the user 110 to contact with a doctor or hospitals. The user can take appointment of the doctor and can provide credentials to the doctor to access user’s history from the server 106.
[0054] As illustrated in FIG. 3, a processing unit 108 can include one or more processor(s) 302. The one or more processor(s) 302 can be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, logic circuitries, and/or any devices that manipulate data based on operational instructions. Among other capabilities, the one or more processor(s) 302 can be configured to fetch and execute computer readable instructions stored in a memory 304 of the processing unit 118. The memory 304 can store one or more computer-readable instructions or routines, which may be fetched and executed to create or share the data units over a network service. The memory 304 can include any non-transitory storage device including, for example, volatile memory such as RAM, or non-volatile memory such as EPROM, flash memory, and the likes.
[0055] In an embodiment, the processing unit 118 can also include an interface(s) 306. The interface(s) 306 may comprise a variety of interfaces, for example, interfaces for data input and output devices, referred to as I/O devices, storage devices, and the like. The interface(s) 306 may facilitate communication of system 102. The interface(s) 306 may also provide a communication pathway for one or more components of the system 102. Examples of such components include, but are not limited to, processing engine(s) 308 and database 320.
[0056] In an embodiment, a processing engine(s) 308 can be implemented as a combination of hardware and programming (for example, programmable instructions) to implement one or more functionalities of the processing engine(s) 308. In examples described herein, such combinations of hardware and programming may be implemented in several different ways. For example, the programming for the processing engine(s) 308 may be processor executable instructions stored on a non-transitory machine-readable storage medium and the hardware for the processing engine(s) 308 may include a processing resource (for example, one or more processors), to execute such instructions. In the present examples, the machine-readable storage medium may store instructions that, when executed by the processing resource, implement the processing engine(s) 308. In such examples, the processing unit 118 can include the machine-readable storage medium storing the instructions and the processing resource to execute the instructions, or the machine-readable storage medium may be separate but accessible to processing unit 118 and the processing resource. In other examples, the processing engine(s) 308 may be implemented by electronic circuitry. A database 320 can include data that is either stored or generated as a result of functionalities implemented by any of the components of the processing engine(s) 308.
[0057] In an embodiment, the processing engine(s) 308 can include an extraction unit 310 a comparison unit 312, a classification and training unit 314, a signal generation unit 316, and other unit(s) 318. The other unit(s) 318 can implement functionalities that supplement applications or functions performed by the system 102 or the processing engine(s) 308.
[0058] In an embodiment, the database 320 can include data that is either stored or generated as a result of functionalities implemented by any of the components of the processing engine(s) 308.
[0059] It would be appreciated that units being described are only exemplary units and any other unit or sub-unit may be included as part of the system 102. These units too may be merged or divided into super- units or sub-units as may be configured.
[0060] In an embodiment, the processing unit 118 can be configured to receive a first set of signals from an input device 114 in electric form, where the first set of signals pertain health attribute of a user 110, and further transmits the first set of signals to the extraction unit 310. The extraction unit 310 can be configured to extract a second set of signals from the first set of signals, where the second set of signals pertain to value of health attributes of the user 110. The health attributes can include any or a combination of body temperature, oxygen level, heart rate, blood pressure, cough sound, and the likes.
[0061] In an embodiment, the extraction unit 310 can be configured to extract one or more characteristics from the received cough sounds, where the one or more cough sound characteristics can include but not limited to cough pattern, pattern severity, dry cough severity, and wet cough severity. In an exemplary embodiment, when the user is having fever and dry cough, there are chances that the user is suffering from respiratory disease such as coronavirus.
[0062] In an embodiment, the comparison unit 312 can be configured to compare the extracted values of the health attributes with pre-stored threshold values. In another embodiment, the signal generation unit 316 can be configured to transmit warning signals to the associated mobile computing device 114 when the compared value of any of health attribute is found beyond the pre-stored threshold values, where the warning signals can pertain information such as risk, precautions and medications associated to one or more diseases.
[0063] In an exemplary embodiment, normal body temperature can be in range of 36.5 degree Celsius to 37.2 degree Celsius, normal oxygen saturation in body can be in between 95 percent to 100 percent. When the system received temperature value 38.1 degree Celsius, oxygen level 65, and dry cough is detected by acoustic sensors, the comparison unit 312 can determine disease such as coronavirus, flu and the likes, and accordingly can alert the user to take precautions such as isolation, wearing mask, washing hands, and medications prescribed by WHO.
[0064] In an exemplary embodiment, when the system 102 found disease on high risk, the user can be alerted to take appointment with a doctor or to visit hospital at earliest.
[0065] In an embodiment, the classification and training unit 314 can be configured to receive the extracted values of health attributes, from the extraction unit (212) in machine readable form or binary form and update and train the classification and training unit 314 based on extracted values of health attributes. In another embodiment, the classification and training unit 314 can be trained and updated based on the received health attributes. A deep leaning model can be trained based on the received health attributes and analysed information where the deep leaning model can be stored in the database 320. In yet another embodiment, once the dataset is trained correctly, a deep learning algorithm can be configured to perform repetitive, and routine tasks within a shorter period of time.
[0066] In an embodiment, the classification and training unit 314 can be configured to store the many users health attributes recorded over a period of time such as for week, month etc., for trend analysis and prediction of future health risk. Also, the classification and training unit 314 can be configured to store a set of training datasets to train a machine learning model for determining cough severity for the received cough sounds based on the training. The plurality of training datasets can include historical information related to cough sounds, cough pattern, pattern severity, dry cough, wet cough and the likes of a group of healthy people and a group of people suffering from one or more diseases.
[0067] In an exemplary embodiment, the processing engine 308 can be further configured in the form of an Artificial Neural Network like the following, but not limited to Convolutional Neural Network (CNN) and Deep Neural Network (DNN). In an exemplary embodiment, the processing engine 318 can include deep learning based classifiers, where the deep learning based classifiers can include KNN classifiers, MLP neural networks and the likes.
[0068] As illustrated in FIG. 4, an exemplary flow diagram the proposed system is disclosed. Firstly health attributes can be collected from sensing device 202 and fed to an input device 114, which can be transmitted to a mobile computing device 108 associated with the user 110, where a mobile application can be installed on the mobile computing device 108 that acts a fog layer and initiate processing of the received health attributes.
[0069] In an exemplary embodiment, at fog layer learning techniques can be applied on the received health attributes for comparing values of the health attributes with a set of pre-stored threshold values, and upon analysis the user can be alerted about health condition. For example, when body temperature is found in between 36.5 to 37.2 degree Celsius, then health status can be determined normal and when body temperature is found beyond threshold value, the health status can be determined critical. The health status normal and critical can be transmitted and displayed on the associated mobile computing device 108. Similarly, when pulse rate is found in between 60 to 100 beats per minute, the health status can be determined normal and when the pulse rate is found beyond threshold value, the health status can be determined critical and accordingly user can be alerted.
[0070] As illustrated in FIG. 5, a method for health monitoring is disclosed, at step 502, the method 500 can include receiving, by an input device 114, health attributes of a user, collected by one or more sensing devices 202.
[0071] At step 504, the method 300 can include transmitting, by the input device 114, the received health attributes to a mobile computing device 108, and a mobile application installed on the mobile computing device 108 works as a fog layer.
[0072] At step 506, the method 300 can include extracting, at a processor of a processing unit 118, values of the received health attributes;
[0073] At step 508, the method 300 can include comparing, at the processor, the extracted values of the of the health attributes with a dataset having a set of pre-defined threshold values;
[0074] At step 510, the method 300 can include generating, at the processor, warning signals pertaining information such as risk, precautions and medications associated to one or more diseases, and transmitting the generated warning signals to the associated mobile computing device 108;
[0075] At step 512, the method 300 can include transmitting, at the processor, the plurality of health attributes and analyzed information of the user to a server 106.
[0076] At step 514, the method 300 can include enabling, at the processor, entity to access information using the associated mobile computing device 108.
[0077] Moreover, in interpreting the specification, all terms should be interpreted in the broadest possible manner consistent with the context. In particular, the terms “comprises” and “comprising” should be interpreted as referring to elements, components, or steps in a non-exclusive manner, indicating that the referenced elements, components, or steps may be present, or utilized, or combined with other elements, components, or steps that are not expressly referenced. Where the specification claims refer to at least one of something selected from the group consisting of A, B, C ….and N, the text should be interpreted as requiring only one element from the group, not A plus N, or B plus N, etc.
[0078] While the foregoing describes various embodiments of the invention, other and further embodiments of the invention may be devised without departing from the basic scope thereof. The scope of the invention is determined by the claims that follow. The invention is not limited to the described embodiments, versions or examples, which are included to enable a person having ordinary skill in the art to make and use the invention when combined with information and knowledge available to the person having ordinary skill in the art.

ADVANTAGES OF THE INVENTION
[0079] The proposed invention provides a system to monitoring health at home.
[0080] The proposed invention provides a system for identifying Covid-19 symptoms in a user.
[0081] The proposed invention provides a system to notify the user automatically when health condition is critical
[0082] The proposed invention provides a system to reduce chances of getting infected from transmission diseases while visiting to hospitals.
[0083] The proposed invention provides a system that is user-friendly.

We Claims:

1. A system 102 for health monitoring, the system 102 comprising:
an input device 114 configured to receive a plurality of health attributes as input from one or more sensing devices 202 by a user 110, and correspondingly generate a first set of signals;
a processing unit 118 operatively configured with the input device 114, the processing unit 118 comprises a processor configured to execute a set of instructions, stored in a memory, which, on execution, causes the system to:
receive, the first set of signals pertaining to a plurality of health attributes of the user by a communication unit 104;
extract, values of each of the plurality of health attributes from the received first set of signals;
compare, extracted values of the plurality of health attributes with a set of pre-defined threshold values; and
generate, warning signals when the value of any of the plurality of health attributes found beyond the associated pre-defined threshold values, and transmit the warning signals to one or more mobile computing devices 108, wherein the warning signals pertain information such as risk, precautions and medications associated to one or more diseases; and
the processing unit further configured to transmit the extracted values of each of the plurality of health attributes of the user 110 to a server 106, wherein the server 106 is configured to store information associated with a plurality of users, and enable an entity 112 to access information using the associated mobile computing devices 108.
2. The system as claimed in claim 1, wherein the input device 114 having one or more ports to facilitate operative coupling with the one or more sensing devices 202 to transmit received input to the input device 114, and wherein the input device 114 facilitates the user to enter input using an interface provided on the input device 114.
3. The system as claimed in claim 1, wherein the one or more sensing devices 202 are selected from a group of thermometer, oximeter, heart rate monitor, and blood pressure sensor, and acoustic sensor.
4. The system as claimed in claim 1, wherein the plurality of health attributes comprises any or a combination of body temperature, oxygen level, heart rate, blood pressure, and cough sound.
5. The system as claimed in claim 1, wherein the communication unit 104 comprises any or combination of Wireless Fidelity (Wi-Fi) Module, Bluetooth Module, Li-Fi Module, Wireless Local Area Network (WLAN), and ZigBee.
6. The system 102 as claimed in claim 1, wherein the one or more mobile computing devices 108 comprises any or a combination of mobile terminal, laptop and tablet.
7. A method for health monitoring of a user 110, the method comprising:
receiving 502, by an input device 114, a plurality of health attributes of a user, collected by one or more sensing devices;
transmitting 504, by the input device 114, the received health attributes to a mobile computing device 108;
extracting, at a processor of a processing unit 118, values of the received plurality of health attributes;
comparing, at the processor, the extracted values of the plurality of health attributes with a dataset having a set of pre-defined threshold values;
generating, at the processor, warning signals pertaining information such as risk, precautions and medications associated to one or more diseases, and transmitting the generated warning signals to the associated mobile computing devices 108;
transmitting, at the processor, extracted values of each of the plurality of health attributes of the user to a server 106;
enabling, at the processor, entity 112 to access information using the associated mobile computing devices 108.