Description:BACKGROUND
Field of Invention
[001] Embodiments of the present invention generally relate to a smart health monitoring system and particularly to an Artificial Intelligence (AI) driven personal healthcare system.
Description of Related Art
[002] The field of personal health technology has experienced rapid advancement through the emergence of smart consumer electronics. Devices such as smart mirrors, intelligent refrigerators, and wearable fitness monitors now offer users the ability to collect various forms of biometric and lifestyle data. Each device addresses specific aspects of personal well-being by tracking parameters such as skin condition, nutrition, activity, hydration, and sleep. Despite the availability of these devices, each system operates independently, limiting the scope of actionable insights.
[003] Current commercial practices depend heavily on siloed systems where data remains confined within individual platforms. For example, smart mirrors perform facial analysis and reflect surface-level skin health, but lack access to dietary or hydration data. Similarly, smart refrigerators manage food inventory and nutritional values, yet do not reference user-specific physiological data. Wearable devices monitor physical activity, sleep cycles, and hydration levels, but fail to incorporate dietary or skin data. Although applications such as Apple Health or Google Fit attempt to centralize some data, they require manual input or support limited third-party device integration, which restricts seamless health data convergence.
[004] The inability of existing solutions to correlate data from multiple sources hinders comprehensive health evaluations. Users must interpret fragmented insights from distinct platforms, often without clinical relevance or personalization. This disjointed experience prevents individuals from forming a cohesive understanding of their health.
[005] There is thus a need for an improved and advanced Artificial Intelligence (AI) driven personal healthcare system that can address the aforementioned limitations in a more efficient manner.
SUMMARY
[006] Embodiments in accordance with the present invention provide an Artificial Intelligence (AI) driven personal healthcare system. The system comprising a smart mirror adapted to capture facial health parameters of a user. The system further comprising a smart refrigerator adapted to capture nutritional information of accommodated edibles. The system further comprising a wearable device adapted to capture physiological parameters of the user. The system further comprising a local data collection unit adapted to encapsulate the facial health parameters, the nutritional information, and the physiological parameters received from the smart mirror, the smart refrigerator, and the smart wearable, in a data packet. The system further comprising a processing unit, established on a cloud server, communicatively connected to the local data collection unit. The processing unit is configured to receive the encapsulated data packet from the local data collection unit; analyze a pattern in the received data packet for generation of a health score using machine learning algorithms; compare the generated health score with a health benchmark score; generate improvement recommendations, when the generated health score is less than the health benchmark score; and generate personalized health insights, when the generated health score is greater than the health benchmark score.
[007] Embodiments in accordance with the present invention further provide a method for developing an Artificial Intelligence (AI) driven personal healthcare system. The method comprising steps of capturing facial health parameters, nutritional information, and physiological parameters, from a smart mirror, a smart refrigerator, and a wearable device; encapsulating the captured facial health parameters, the captured nutritional information, and the captured physiological parameters in a data packet; analyzing a pattern in the encapsulated data packet for generation of a health score using machine learning algorithms; comparing the generated score with a benchmark score; generating improvement recommendations, when generated health score is less than the health benchmark score; and generating personalized health insights, when the generated health score is greater than the health benchmark score.
[008] Embodiments of the present invention may provide a number of advantages depending on their particular configuration. First, embodiments of the present application may provide an Artificial Intelligence (AI) driven personal healthcare system.
[009] Next, embodiments of the present application may provide a personal healthcare system that consolidates data from multiple smart devices such as a mirror, a fridge, and wearables, into a single dashboard, eliminating fragmented information and enabling a complete view of the user’s health.
[0010] Next, embodiments of the present application may provide a personal healthcare system that provides real-time, individualized health recommendations based on holistic analysis rather than isolated readings.
[0011] Next, embodiments of the present application may provide a personal healthcare system that automatically collects and processes information, reducing user effort while increasing accuracy.
[0012] Next, embodiments of the present application may provide a personal healthcare system that enables meaningful correlations, such as linking dry skin detected by a mirror with hydration data from a wearable and diet tracked via the fridge, offering an actionable advice backed by multiple health indicators.
[0013] Next, embodiments of the present application may provide a personal healthcare system that supports voice interaction, mobile access, and blockchain-backed data privacy, the system ensures convenient, secure, and hands-free management of health-related information.
[0014] These and other advantages will be apparent from the present application of the embodiments described herein.
[0015] The preceding is a simplified summary to provide an understanding of some embodiments of the present invention. This summary is neither an extensive nor an exhaustive overview of the present invention and its various embodiments. The summary presents selected concepts of the embodiments of the present invention in a simplified form as an introduction to the more detailed description presented below. As will be appreciated, other embodiments of the present invention are possible utilizing, alone or in combination, one or more of the features set forth above or described in detail below.
BRIEF DESCRIPTION OF THE DRAWINGS
[0016] The above and still further features and advantages of embodiments of the present invention will become apparent upon consideration of the following detailed description of embodiments thereof, especially when taken in conjunction with the accompanying drawings, and wherein:
[0017] FIG. 1 illustrates a schematic block diagram of an Artificial Intelligence (AI) driven personal healthcare system, according to an embodiment of the present invention;
[0018] FIG. 2 illustrates a block diagram of a processing unit, according to an embodiment of the present invention; and
[0019] FIG. 3 depicts a flowchart of a method for developing an Artificial Intelligence (AI) driven personal healthcare system, according to an embodiment of the present invention.
[0020] The headings used herein are for organizational purposes only and are not meant to be used to limit the scope of the description or the claims. As used throughout this application, the word "may" is used in a permissive sense (i.e., meaning having the potential to), rather than the mandatory sense (i.e., meaning must). Similarly, the words “include”, “including”, and “includes” mean including but not limited to. To facilitate understanding, like reference numerals have been used, where possible, to designate like elements common to the figures. Optional portions of the figures may be illustrated using dashed or dotted lines, unless the context of usage indicates otherwise.
DETAILED DESCRIPTION
[0021] The following description includes the preferred best mode of one embodiment of the present invention. It will be clear from this description of the invention that the invention is not limited to these illustrated embodiments but that the invention also includes a variety of modifications and embodiments thereto. Therefore, the present description should be seen as illustrative and not limiting. While the invention is susceptible to various modifications and alternative constructions, it should be understood, that there is no intention to limit the invention to the specific form disclosed, but, on the contrary, the invention is to cover all modifications, alternative constructions, and equivalents falling within the scope of the invention as defined in the claims.
[0022] In any embodiment described herein, the open-ended terms "comprising", "comprises”, and the like (which are synonymous with "including", "having” and "characterized by") may be replaced by the respective partially closed phrases "consisting essentially of", “consists essentially of", and the like or the respective closed phrases "consisting of", "consists of”, the like.
[0023] As used herein, the singular forms “a”, “an”, and “the” designate both the singular and the plural, unless expressly stated to designate the singular only.
[0024] FIG. 1 illustrates a schematic block diagram of an Artificial Intelligence (AI) driven personal healthcare system 100 (hereinafter referred to as the system 100), according to an embodiment of the present invention. In an embodiment of the present invention, the system 100 may be adapted to monitor a visual health indication, a dietary health indication, and a physiological health indication of a user. Further, upon monitoring of the discrepancies, the system 100 may generate improvement recommendations and personalized health insights for ensuring a healthy well-being of the user. Moreover, the system 100 may set goals for the user.
[0025] According to the embodiments of the present invention, the system 100 may incorporate non-limiting hardware components to enhance the processing speed and efficiency such as the system 100 may comprise a smart mirror 102, a smart refrigerator 104, a wearable device 106, a local data collection unit 108, a processing unit 110, a cloud server 112, a computing device 114, a communication network 116, a blockchain ledger 118, and a dataset 120. In an embodiment of the present invention, the hardware components of the system 100 may be integrated with computer-executable instructions for overcoming the challenges and limitations of the existing systems.
[0026] In an embodiment of the present invention, the smart mirror 102 may be adapted to capture facial health parameters of the user. The facial health parameters may be, but not limited to, a presence of hair fall, a redness in eyes, an appearance of facial pimples, a presence of blisters on lips, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the facial health parameters, including known, related art, and/or later developed technologies.
[0027] In an embodiment of the present invention, the smart refrigerator 104 may be adapted to capture nutritional information of accommodated edibles. The nutritional information may be, but not limited to, an amount of protein rich food in the smart refrigerator 104, an amount of vegetables in the smart refrigerator 104, an amount of meat in the smart refrigerator 104, an amount of fruits in the smart refrigerator 104, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the nutritional information, including known, related art, and/or later developed technologies.
[0028] In an embodiment of the present invention, the wearable device 106 may be adapted to capture physiological parameters of the user. The physiological parameters may be, but not limited to, a heartbeat, a body temperature, a sleep duration, an Electrocardiogram (ECG), a blood-oxygen level, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the physiological parameters, including known, related art, and/or later developed technologies.
[0029] In an embodiment of the present invention, the local data collection unit 108 may be adapted to encapsulate the facial health parameters, the nutritional information, and the physiological parameters received from the smart mirror 102, the smart refrigerator 104, and the smart wearable, in a data packet.
[0030] In an embodiment of the present invention, the processing unit 110 may be established on the cloud server 112. The processing unit 110 may be connected to the local data collection unit 108. The processing unit 110 may be configured to generate the improvement recommendations and the personalized health insights.
[0031] The improvement recommendations may be, but not limited to, a workout set, a brisk walk, an avoidance of certain edibles from diet, an inculcation of certain edibles in diet, a regular consumption of water, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the improvement recommendations, including known, related art, and/or later developed technologies.
[0032] The personalized health insights may be, but not limited to, hydration, nutrition, fitness, sleep, and so forth. The personalized health insights may be encoded in a health report format that may be daily generated by the processing unit 110 and may further be transmitted to the computing device 114. Embodiments of the present invention are intended to include or otherwise cover any type of personalized health insights, including known, related art, and/or later developed technologies.
[0033] The processing unit 110 may further be configured to execute computer-executable instructions to generate an output relating to the system 100. The processing unit 110 may be, but not limited to, a Programmable Logic Control (PLC) unit, a microprocessor, a development board, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the processing unit 110, including known, related art, and/or later developed technologies. In an embodiment of the present invention, the processing unit 110 may further be explained in conjunction with FIG. 2.
[0034] In an embodiment of the present invention, the cloud server 112 may be remotely located. In an exemplary embodiment of the present invention, the cloud server 112 may be a public cloud server. In another exemplary embodiment of the present invention, the cloud server 112 may be a private cloud server. In yet another embodiment of the present invention, the cloud server 112 may be a dedicated cloud server. According to embodiments of the present invention, the cloud server 112 may be, but not limited to, a Microsoft Azure cloud server, an Amazon AWS cloud server, a Google Compute Engine (GCE) cloud server, an Amazon Elastic Compute Cloud (EC2) cloud server, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the cloud server 112, including known, related art, and/or later developed technologies.
[0035] In an embodiment of the present invention, the computing device 114 may be an electronic device used by the user. The computing device 114 may comprise a mobile application (not shown).
[0036] The mobile application of the computing device 114 may be configured to notify the user upon generation of the improvement recommendations and the personalized health insights. Further, the mobile application of the computing device 114 may enable the user to receive the improvement recommendations and the personalized health insights. The improvement recommendations and the personalized health insights may be visually displayed to the user, in an embodiment of the present invention. In another embodiment of the present invention, the improvement recommendations and the personalized health insights may be vocally announced to the user. The vocal announcement may enable a handsfree interaction of the user with the computing device 114.
[0037] The computing device 114 may be, but not limited to, a laptop, a smart phone, a desktop, a smart home assistant, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the computing device 114, including known, related art, and/or later developed technologies.
[0038] In an embodiment of the present invention, the communication network 116 may be configured to establish a communicative link among the processing unit 110, the cloud server 112, and the computing device 114. The established communicative link may enable a transmission of the improvement recommendations and the personalized health insights. The communication network 116 may be adapted to operate on Internet of Things (IoT) protocols. The communication network 116 may be, but not limited to, a wired communication network, a wireless communication network, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the communication network 116, including known, related art, and/or later developed technologies.
[0039] The wired communication network may be enabled by means such as, but not limited to, a twisted pair cable, a co-axial cable, an Ethernet cable, a modem, a router, a switch, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the means that may enable the wired communication network, including known, related art, and/or later developed technologies.
[0040] The wireless communication network may be enabled by means such as, but not limited to, a Wi-Fi communication module, a Bluetooth communication module, a millimeter waves communication module, an Ultra-High Frequency (UHF) communication module, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the means that may enable the wireless communication network, including known, related art, and/or later developed technologies.
[0041] In an embodiment of the present invention, the blockchain ledger 118 may be adapted to store the improvement recommendations and the personalized health insights. The blockchain ledger 118 may enable a tamper-proof data sharing of the improvement recommendations and the personalized health insights. In an embodiment of the present invention, the dataset 120 may be adapted to store the improvement recommendations and the personalized health insights. The dataset 120 may enable a refinement of machine learning algorithms.
[0042] FIG. 2 illustrates a block diagram of the processing unit 110, according to an embodiment of the present invention. The processing unit 110 may comprise the computer-executable instructions in form of programming modules such as a data receiving module 200, a data analysis module 202, a data comparison module 204, and a data generation module 206.
[0043] In an embodiment of the present invention, the data receiving module 200 may be configured to receive the encapsulated data packet from the local data collection unit 108. The data receiving module 200 may be configured to transmit the encapsulated data packet to the data analysis module 202.
[0044] The data analysis module 202 may be activated upon receipt of the encapsulated data packet from the data receiving module 200. In an embodiment of the present invention, the data analysis module 202 may be configured to analyze a pattern in the received data packet for generation of a health score using the machine learning algorithms. The machine learning algorithms generate the health score in a real time. Further, the machine learning algorithms may interpolate and identify patterns in the received data packet. The patterns may further enable the machine learning algorithms to generate the health score. The data analysis module 202 may transmit the health score to the data comparison module 204.
[0045] The data comparison module 204 may be activated upon receipt of the health score from the data analysis module 202. In an embodiment of the present invention, the data comparison module 204 may be configured to compare the generated health score with a health benchmark score. Upon comparison, if the generated health score is less than the health benchmark score, then the data comparison module 204 may transmit a first activation signal to the data generation module 206. Else, the data comparison module 204 may transmit a second activation signal to the data generation module 206.
[0046] The data generation module 206 may be activated upon receipt of the first activation signal from the data comparison module 204. When activated using the first activation signal, the data generation module 206 may be configured to generate the improvement recommendations. Further, the data generation module 206 may be configured to establish a goal for the user. The goal may be, but not limited to, consumption of a preset amount of water, intake of predefined nutrients, a walk for a predefined duration, a total sleep hours, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the goal, including known, related art, and/or later developed technologies.
[0047] The data generation module 206 may be activated upon receipt of the second activation signal from the data comparison module 204. When activated using the second activation signal, the data generation module 206 may be configured to generate the personalized health insights.
[0048] Further, the data generation module 206 may be configured to transmit the improvement recommendations and the personalized health insights to the computing device 114. Furthermore, the data generation module 206 may be configured to store the improvement recommendations and the personalized health insights on the blockchain ledger 118 for the tamper-proof data sharing, and in the dataset 120 for refinement of the machine learning algorithms. Along with the refinements of the machine learning algorithms, the data generation module 206 may be configured to provide a feedback for the system 100.
[0049] In an exemplary scenario, if the smart mirror 102 may recognize a dry skin on the user, then the system 100 may propose drinking more water based on hydration data captured from the wearable device 106 and a food consumption tracked from the smart refrigerator 104.
[0050] FIG. 3 depicts a flowchart of a method 300 for developing the system 100, according to an embodiment of the present invention.
[0051] At step 302, the system 100 may capture the facial health parameters, the nutritional information, and the physiological parameters from the smart mirror 102, the smart refrigerator 104, and the wearable device 106.
[0052] At step 304, the system 100 may encapsulate the captured facial health parameters, the captured nutritional information, and the captured physiological parameters in the data packet.
[0053] At step 306, the system 100 may analyze the pattern in the encapsulated data packet for generation of the health score using the machine learning algorithms.
[0054] At step 308, the system 100 may compare the generated score with the benchmark score. Upon comparison, if the generated health score is less than the health benchmark score, then the method 300 may proceed to a step 310. Else, the method 300 may proceed to a step 320.
[0055] At step 310, the system 100 may generate the improvement recommendations.
[0056] At step 312, the system 100 may establish the goal for the user.
[0057] At step 314, the system 100 may transmit the improvement recommendations and the established goals to the computing device 114.
[0058] At step 316, the system 100 may store the improvement recommendations on the blockchain ledger 118.
[0059] At step 318, the system 100 may store the improvement recommendations in the dataset 120.
[0060] At the step 320, the system 100 may generate the personalized health insights when the generated health score is greater than the health benchmark score.
[0061] At step 322, the system 100 may transmit the personalized health insights to the computing device 114.
[0062] At step 324, the system 100 may store the personalized health insights on the blockchain ledger 118.
[0063] At step 326, the system 100 may store the personalized health insights in the dataset 120.
[0064] While the invention has been described in connection with what is presently considered to be the most practical and various embodiments, it is to be understood that the invention is not to be limited to the disclosed embodiments, but on the contrary, is intended to cover various modifications and equivalent arrangements included within the scope of the appended claims.
[0065] This written description uses examples to disclose the invention, including the best mode, and also to enable any person skilled in the art to practice the invention, including making and using any devices or systems and performing any incorporated methods. The patentable scope of the invention is defined in the claims, and may include other examples that occur to those skilled in the art. Such other examples are intended to be within the scope of the claims if they have structural elements that do not differ from the literal language of the claims, or if they include equivalent structural elements within substantial differences from the literal languages of the claims. , Claims:CLAIMS
I/We Claim:
1. An Artificial Intelligence (AI) driven personal healthcare system (100), the system (100) comprising:
a smart mirror (102) adapted to capture facial health parameters of a user;
a smart refrigerator (104) adapted to capture nutritional information of accommodated edibles;
a wearable device (106) adapted to capture physiological parameters of the user;
a local data collection unit (108) adapted to encapsulate the facial health parameters, the nutritional information, and the physiological parameters received from the smart mirror (102), the smart refrigerator (104), and the smart wearable, in a data packet; and
a processing unit (110), established on a cloud server (112), communicatively connected to the local data collection unit (108), characterized in that the processing unit (110) is configured to:
receive the encapsulated data packet from the local data collection unit (108);
analyze a pattern in the received data packet for generation of a health score using machine learning algorithms;
compare the generated health score with a health benchmark score;
generate improvement recommendations, when the generated health score is less than the health benchmark score; and
generate personalized health insights, when the generated health score is greater than the health benchmark score.
2. The system (100) as claimed in claim 1, wherein the processing unit (110) is configured to establish a goal for the user, when the generated health score is less than the health benchmark score.
3. The system (100) as claimed in claim 1, wherein the improvement recommendations and the generated personalized health insights are transmitted to a computing device (114) using a communication network (116).
4. The system (100) as claimed in claim 1, wherein the improvement recommendations and the generated personalized health insights are stored on a blockchain ledger (118) for tamper-proof data sharing.
5. The system (100) as claimed in claim 1, wherein the processing unit (110) is configured to store the generated improvement recommendations and the personalized health insights in a dataset (120) for refinement of the machine learning algorithms.
6. A method (300) for developing an Artificial Intelligence (AI) driven personal healthcare system (100), the method (300) is characterized by steps of:
capturing facial health parameters, nutritional information, and physiological parameters, from a smart mirror (102), a smart refrigerator (104), and a wearable device (106);
encapsulating the captured facial health parameters, the captured nutritional information, and the captured physiological parameters in a data packet;
analyzing a pattern in the encapsulated data packet for generation of a health score using machine learning algorithms;
comparing the generated score with a benchmark score;
generating improvement recommendations, when the generated health score is less than the health benchmark score; and
generating personalized health insights, when the generated health score is greater than the health benchmark score.
7. The method (300) as claimed in claim 6, comprising a step of establishing a goal for the user when the generated health score is less than the health benchmark score.
8. The method (300) as claimed in claim 6, comprising a step of transmitting the improvement recommendations and the generated personalized health insights to a computing device (114) using a communication network (116).
9. The method (300) as claimed in claim 6, wherein the improvement recommendations and the generated personalized health insights are stored on a blockchain ledger (118) for tamper-proof data sharing.
10. The method (300) as claimed in claim 6, comprising a step of storing the generated improvement recommendations and the personalized health insights in a dataset (120) for refinement of the machine learning algorithms.
Date: May 15, 2025
Place: Noida

Nainsi Rastogi
Patent Agent (IN/PA-2372)
Agent for the Applicant