Description:FIELD OF DISCLOSURE
[0001] The present disclosure relates generally relates to personalized nutrition, more specifically, relates to smart diet guide system and method thereof.
BACKGROUND OF THE DISCLOSURE
[0002] This invention provides tailored dietary recommendations based on individual health conditions, food preferences, and cultural habits. Unlike generic diet plans, it ensures that users receive advice suited to their unique nutritional needs, making it more effective in addressing deficiencies such as iron and zinc.
[0003] By encouraging the use of locally available, nutrient-rich foods, this invention supports sustainable food choices. It helps reduce dependency on expensive fortified products and imported supplements, making healthy eating more affordable and accessible, especially in low-income and rural areas.
[0004] The system educates users on the importance of proper nutrition and how to improve nutrient absorption through interactive learning modules. By incorporating community support and expert guidance, it fosters long-term healthy eating habits, leading to better overall health and well-being.
[0005] Existing solutions often provide generic diet plans that do not consider an individual’s specific health conditions, food preferences, or cultural habits. This makes them less effective in addressing specific nutritional deficiencies, leading to lower user engagement and long-term adherence. Without a tailored approach, users may struggle to follow the recommendations, making it difficult to achieve lasting health benefits.
[0006] Many current nutritional solutions rely on expensive fortified products, imported supplements, or specialized foods that are not easily available in rural or low-income areas. This makes it difficult for the most vulnerable populations to access sustainable and effective dietary improvements. As a result, individuals who need proper nutrition the most are often left without viable options, further worsening health disparities.
[0007] Most existing dietary tracking apps or nutritional programs do not focus on educating users about nutrient absorption, food combinations, or sustainable eating practices. Without proper awareness, individuals may not fully benefit from the recommended dietary changes, reducing the overall impact of these solutions. The lack of educational support prevents people from making informed dietary choices, leading to continued reliance on unhealthy or nutritionally inadequate foods.
[0008] Thus, in light of the above-stated discussion, there exists a need for a smart diet guide system and method thereof.
SUMMARY OF THE DISCLOSURE
[0009] The following is a summary description of illustrative embodiments of the invention. It is provided as a preface to assist those skilled in the art to more rapidly assimilate the detailed design discussion which ensues and is not intended in any way to limit the scope of the claims which are appended hereto in order to particularly point out the invention.
[0010] According to illustrative embodiments, the present disclosure focuses on a smart diet guide system and method thereof which overcomes the above-mentioned disadvantages or provide the users with a useful or commercial choice.
[0011] An objective of the present disclosure is to provide a smart diet guide that offers personalized nutritional recommendations based on an individual’s dietary needs, cultural preferences, and locally available food sources, ensuring sustainable and practical dietary solutions.
[0012] An objective of the present disclosure is to promote long-term health and wellness by addressing micronutrient deficiencies such as iron and zinc in a natural and accessible manner, reducing dependence on artificial supplements and fortified foods.
[0013] An objective of the present disclosure is to enhance user awareness of nutrient-rich food choices by integrating interactive educational components, empowering individuals to make informed dietary decisions for improved health outcomes.
[0014] Another objective of the present disclosure is to improve accessibility to reliable dietary guidance by offering a solution that is cost-effective, easy to use, and adaptable to different economic backgrounds and geographical locations.
[0015] Another objective of the present disclosure is to support sustainable eating habits by encouraging the consumption of locally sourced, seasonally available, and environmentally friendly food options to promote long-term food security.
[0016] An objective of the present disclosure is to bridge the gap between nutritional science and practical application by providing tailored dietary suggestions that are scientifically backed yet simple to understand and implement in daily life.
[0017] Another objective of the present disclosure is to offer a holistic approach to nutrition by considering factors such as food preparation methods, bioavailability of nutrients, and lifestyle habits to ensure optimal nutrient absorption.
[0018] Another objective of the present disclosure is to foster community engagement by creating a platform where users can share experiences, exchange nutritional insights, and seek guidance from health professionals for better adherence to dietary recommendations.
[0019] Another objective of the present disclosure is to provide a reliable and scalable dietary solution that can be utilized by individuals, healthcare professionals, and policymakers to improve public health outcomes on a larger scale.
[0020] Yet another objective of the present disclosure is to integrate adaptability within the dietary guidance system, allowing users from diverse backgrounds, dietary restrictions, and health conditions to receive customized recommendations that align with their specific needs.
[0021] In light of the above, in one aspect of the present disclosure, a smart diet guide system is disclosed herein. The system comprises a processing unit, configured to analyse user-specific dietary data and generate customized dietary recommendations based on bioavailability optimization techniques, cultural food preferences, and sustainability parameters. The system includes a data acquisition module, operably coupled to the processing unit, configured to collect user-specific dietary data, including nutritional requirements, health conditions, food preferences, and lifestyle factors. The system also includes a recommendation module, operably coupled to the processing unit, configured to refine and personalize dietary guidance by integrating historical user interactions, scientific dietary principles, and adaptive learning techniques. The system also includes a storage unit, operably coupled to the processing unit, configured to store a database of nutrient-rich foods, dietary guidelines, and user engagement records to enable data-driven improvements in recommendations. The system also includes a communication network, operably coupled to the processing unit, configured to enable seamless data exchange between a plurality of system components. The system also includes a user device, operably connected to the processing unit through the communication network, configured to provide users with real-time access to dietary recommendations, progress tracking, and interactive feedback. The system also includes a user interface, embedded within the user device, configured to allow users to input dietary preferences, receive personalized meal plans, track nutritional intake, and access educational content on diet optimization.
[0022] In one embodiment, the data acquisition module further comprises a real-time health monitoring sub-module, configured to integrate with wearable health devices and retrieve biometric data including heart rate, blood sugar levels, and physical activity metrics to enhance dietary recommendations based on physiological responses.
[0023] In one embodiment, the recommendation module further comprises an adaptive learning sub-module, configured to refine dietary suggestions dynamically by analysing longitudinal user data and evolving health patterns to offer progressive and personalized nutritional advice.
[0024] In one embodiment, the storage unit further comprises a structured nutritional database, configured to store and retrieve region-specific, culturally relevant food options and align recommendations with locally available, seasonal ingredients for sustainability-focused diet planning.
[0025] In one embodiment, the user device further comprises an offline functionality module, configured to allow users to access stored dietary recommendations and educational materials without an active internet connection, ensuring continued guidance in low-connectivity environments.
[0026] In one embodiment, the user interface further comprises an interactive visual representation module, configured to provide graphical insights into nutrient intake, progress trends, and dietary adjustments, enhancing user engagement and adherence to dietary goals.
[0027] In one embodiment, the processing unit further comprises a multilingual adaptation module, configured to enable dietary recommendations and educational content delivery in multiple languages, ensuring accessibility for diverse user demographics.
[0028] In one embodiment, the recommendation module further comprises a dietary restriction compliance sub-module, configured to filter meal plans and ingredient suggestions based on user-specified dietary restrictions, including vegan, gluten-free, diabetic-friendly, and allergen-sensitive options.
[0029] In one embodiment, the user interface further comprises a community engagement module, configured to connect users with nutritionists, dieticians, and peer support groups, enabling collaborative learning and shared health insights.
[0030] In light of the above, in one aspect of the present disclosure, smart diet guide system is disclosed herein. The method comprises receiving via a data acquisition module, user-specific dietary data including nutritional requirements, health conditions, food preferences, and lifestyle factors. The method includes processing by a processing unit, the acquired dietary data to identify nutritional gaps and recommend optimized dietary solutions based on bioavailability enhancement, cultural food preferences, and sustainability parameters. The method also includes generating via a recommendation module, customized dietary guidance by integrating scientific dietary principles, adaptive learning algorithms, and historical user interactions to improve personalization. The method also includes storing within a storage unit, a structured database comprising nutrient-rich food options, validated dietary guidelines, and user engagement records for continuous optimization and refinement of dietary recommendations. The method also includes facilitating via a communication network, seamless real-time data exchange between the processing unit and a user device to ensure instant delivery of dietary recommendations. The method also includes displaying via a user interface embedded in the user device, interactive meal plans, progress tracking insights, and educational content to guide users toward sustainable and effective nutritional improvements.
[0031] These and other advantages will be apparent from the present application of the embodiments described herein.
[0032] The preceding is a simplified summary to provide an understanding of some embodiments of the present invention. This summary is neither an extensive nor 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.
[0033] These elements, together with the other aspects of the present disclosure and various features are pointed out with particularity in the claims annexed hereto and form a part of the present disclosure. For a better understanding of the present disclosure, its operating advantages, and the specified object attained by its uses, reference should be made to the accompanying drawings and descriptive matter in which there are illustrated exemplary embodiments of the present disclosure.
BRIEF DESCRIPTION OF THE DRAWINGS
[0034] To describe the technical solutions in the embodiments of the present disclosure or in the prior art more clearly, the following briefly describes the accompanying drawings required for describing the embodiments or the prior art. Apparently, the accompanying drawings in the following description merely show some embodiments of the present disclosure, and a person of ordinary skill in the art can derive other implementations from these accompanying drawings without creative efforts. All of the embodiments or the implementations shall fall within the protection scope of the present disclosure.
[0035] The advantages and features of the present disclosure will become better understood with reference to the following detailed description taken in conjunction with the accompanying drawing, in which:
[0036] FIG. 1 illustrates a block diagram of a smart diet guide system and method thereof, in accordance with an exemplary embodiment of the present disclosure;
[0037] FIG. 2 illustrates a flowchart of a smart diet guide system, in accordance with an exemplary embodiment of the present disclosure;
[0038] FIG. 3 illustrates a flowchart of a smart diet guide method, in accordance with an exemplary embodiment of the present disclosure;
[0039] Like reference, numerals refer to like parts throughout the description of several views of the drawing.
[0040] The smart diet guide system and method thereof is illustrated in the accompanying drawings, which like reference letters indicate corresponding parts in the various figures. It should be noted that the accompanying figure is intended to present illustrations of exemplary embodiments of the present disclosure. This figure is not intended to limit the scope of the present disclosure. It should also be noted that the accompanying figure is not necessarily drawn to scale.
DETAILED DESCRIPTION OF THE DISCLOSURE
[0041] The following is a detailed description of embodiments of the disclosure depicted in the accompanying drawings. The embodiments are in such detail as to 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 spirit and scope of the present disclosure.
[0042] In the following description, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the present disclosure. It may be apparent to one skilled in the art that embodiments of the present disclosure may be practiced without some of these specific details.
[0043] Various terms as used herein are shown below. To the extent a term is used, it should be given the broadest definition persons in the pertinent art have given that term as reflected in printed publications and issued patents at the time of filing.
[0044] The terms “a” and “an” herein do not denote a limitation of quantity, but rather denote the presence of at least one of the referenced items.
[0045] The terms “having”, “comprising”, “including”, and variations thereof signify the presence of a component.
[0046] Referring now to FIG. 1 to FIG. 3 to describe various exemplary embodiments of the present disclosure. FIG. 1 illustrates a block diagram of a smart diet guide system and method thereof, in accordance with an exemplary embodiment of the present disclosure.
[0047] The system 100 may include a processing unit 102, configured to analyse user-specific dietary data and generate customized dietary recommendations based on bioavailability optimization techniques, cultural food preferences, and sustainability parameters. The system 100 may also include a data acquisition module 104, operably coupled to the processing unit 102, configured to collect user-specific dietary data, including nutritional requirements, health conditions, food preferences, and lifestyle factors. The system 100 may also include a recommendation module 106, operably coupled to the processing unit 102, configured to refine and personalize dietary guidance by integrating historical user interactions, scientific dietary principles, and adaptive learning techniques. The system 100 may also include a storage unit 108, operably coupled to the processing unit 102, configured to store a database of nutrient-rich foods, dietary guidelines, and user engagement records to enable data-driven improvements in recommendations. The system 100 may also include a communication network 110, operably coupled to the processing unit 102, configured to enable seamless data exchange between a plurality of system components. The system 100 may also include a user device 112, operably connected to the processing unit 102, through the communication network 110, configured to provide users with real-time access to dietary recommendations, progress tracking, and interactive feedback. The system 100 may also include a user interface 114, embedded within the user device 112, configured to allow users to input dietary preferences receive personalized meal plans, track nutritional intake, and access educational content on diet optimization.
[0048] The data acquisition module 104 further comprises a real-time health monitoring sub-module, configured to integrate with wearable health devices and retrieve biometric data including heart rate, blood sugar levels, and physical activity metrics to enhance dietary recommendations based on physiological responses.
[0049] The recommendation module 106 further comprises an adaptive learning sub-module, configured to refine dietary suggestions dynamically by analysing longitudinal user data and evolving health patterns to offer progressive and personalized nutritional advice.
[0050] The storage unit 108 further comprises a structured nutritional database, configured to store and retrieve region-specific, culturally relevant food options and align recommendations with locally available, seasonal ingredients for sustainability-focused diet planning.
[0051] The user device 112 further comprises an offline functionality module, configured to allow users to access stored dietary recommendations and educational materials without an active internet connection, ensuring continued guidance in low-connectivity environments.
[0052] The user interface 114 further comprises an interactive visual representation module, configured to provide graphical insights into nutrient intake, progress trends, and dietary adjustments, enhancing user engagement and adherence to dietary goals.
[0053] The processing unit 102 further comprises a multilingual adaptation module, configured to enable dietary recommendations and educational content delivery in multiple languages, ensuring accessibility for diverse user demographics.
[0054] The recommendation module 106 further comprises a dietary restriction compliance sub-module, configured to filter meal plans and ingredient suggestions based on user-specified dietary restrictions, including vegan, gluten-free, diabetic-friendly, and allergen-sensitive options.
[0055] The user interface 114 further comprises a community engagement module, configured to connect users with nutritionists, dieticians, and peer support groups, enabling collaborative learning and shared health insights.
[0056] The method 100 may include a receiving via a data acquisition module 104 user-specific dietary data including nutritional requirements, health conditions, food preferences, and lifestyle factors. The method 100 may also include a processing by a processing unit 102 the acquired dietary data to identify nutritional gaps and recommend optimized dietary solutions based on bioavailability enhancement, cultural food preferences, and sustainability parameters. The method 100 may also include a generating via a recommendation module 106 customized dietary guidance by integrating scientific dietary principles, adaptive learning algorithms, and historical user interactions to improve personalization. The method 100 may also include a storing within a storage unit 108 a structured database comprising nutrient-rich food options, validated dietary guidelines, and user engagement records for continuous optimization and refinement of dietary recommendations. The method 100 may also include a facilitating via a communication network 110 seamless real-time data exchange between the processing unit 102 and a user device 112 to ensure instant delivery of dietary recommendations. The method 100 may also include a displaying via a user interface 114 embedded in the user device 112 interactive meal plans, progress tracking insights, and educational content to guide users toward sustainable and effective nutritional improvements.
[0057] The processing unit 102 functions as the core analytical component responsible for managing and processing user-specific dietary data. The processing unit 102 performs in-depth analysis of nutritional requirements, health conditions, food preferences, and lifestyle factors to generate optimized dietary recommendations. By implementing bioavailability optimization techniques, the processing unit 102 ensures that nutrient absorption is maximized for each user. The processing unit 102 incorporates cultural food preferences into the analysis, allowing for personalized recommendations that align with the user’s regional dietary habits. Sustainability parameters are also integrated within the processing unit 102, ensuring that suggested dietary choices promote environmental consciousness. The processing unit 102 continuously refines its recommendations using data-driven learning techniques, adapting to user-specific patterns over time. The processing unit 102 interacts seamlessly with other components to ensure efficient data processing and decision-making within the system. The processing unit 102 enables real-time computations that facilitate accurate and adaptive dietary guidance. The processing unit 102 executes rapid processing of large datasets to provide instantaneous recommendations to users. The processing unit 102 integrates historical dietary interactions and scientific principles to refine nutritional guidance. The processing unit 102 establishes connectivity with other system components through an integrated communication framework, facilitating seamless information flow.
[0058] The processing unit 102 continuously processes complex dietary data to generate precise and effective meal recommendations. The processing unit 102 ensures that each recommendation aligns with user-specific health goals by considering past dietary habits, current health conditions, and scientifically validated nutritional principles. The processing unit 102 employs bioavailability optimization to enhance nutrient absorption based on metabolic efficiency. The processing unit 102 evaluates energy balance requirements and adjusts dietary plans accordingly. The processing unit 102 integrates machine learning models that analyse evolving user preferences to improve long-term adherence. The processing unit 102 refines recommendations by incorporating physiological data received from health monitoring devices. The processing unit 102 enhances the adaptability of dietary recommendations by updating them in response to real-time biometric changes. The processing unit 102 interacts with the recommendation module 106 to ensure meal plans meet user expectations while aligning with dietary restrictions. The processing unit 102 ensures compliance with sustainable dietary practices by integrating regionally available food options into recommendations. The processing unit 102 minimizes processing delays by prioritizing essential dietary calculations in real time. The processing unit 102 enhances precision in nutritional guidance by filtering out inconsistent data from user inputs. The processing unit 102 enables seamless system operation by ensuring optimal resource allocation across components.
[0059] The data acquisition module 104 collects user-specific dietary data essential for generating customized recommendations. The data acquisition module 104 gathers input related to nutritional requirements, health conditions, food preferences, and lifestyle factors to enhance the accuracy of dietary guidance. The data acquisition module 104 supports various input methods, including manual entry through the user interface 114 and automated retrieval from external devices. The data acquisition module 104 integrates with wearable health monitoring devices to collect real-time biometric data such as heart rate, blood sugar levels, and physical activity metrics. The data acquisition module 104 ensures that dietary recommendations align with real-time physiological conditions. The data acquisition module 104 transmits the acquired data to the processing unit 102 for analysis and recommendation generation. The data acquisition module 104 continuously updates dietary data, allowing the system to track progress and refine guidance dynamically. The data acquisition module 104 supports multiple data formats to accommodate different dietary assessment techniques. The data acquisition module 104 ensures accurate and comprehensive data collection, eliminating gaps in dietary assessment. The data acquisition module 104 enhances user experience by minimizing manual input efforts through automated data retrieval.
[0060] The data acquisition module 104 ensures that user-specific dietary data remains accurate and comprehensive by continuously retrieving information from multiple sources. The data acquisition module 104 facilitates seamless input through manual user entries, wearable health devices, and integrated external databases. The data acquisition module 104 enhances data accuracy by validating health parameters before processing. The data acquisition module 104 enables dynamic dietary updates by ensuring real-time monitoring of changes in user preferences and health conditions. The data acquisition module 104 captures and transmits essential biometric data such as heart rate, blood sugar levels, and physical activity metrics to the processing unit 102 for detailed analysis. The data acquisition module 104 eliminates the need for redundant user inputs by automatically syncing data from verified sources. The data acquisition module 104 enhances the efficiency of data collection by ensuring that all retrieved information remains structured and relevant. The data acquisition module 104 prevents inaccuracies by cross-referencing data points from multiple sources before integrating them into the system. The data acquisition module 104 provides seamless communication with the recommendation module 106 to ensure that updated user information reflects in dietary suggestions. The data acquisition module 104 supports adaptive user engagement by learning from repeated interactions to refine data collection strategies.
[0061] The recommendation module 106 personalizes dietary guidance by incorporating adaptive learning techniques and scientific dietary principles. The recommendation module 106 refines dietary suggestions dynamically based on user interaction history and evolving health patterns. The recommendation module 106 integrates nutritional science and machine learning algorithms to optimize meal planning. The recommendation module 106 aligns dietary recommendations with cultural food preferences to ensure adherence and practicality. The recommendation module 106 ensures that dietary guidance remains relevant and effective by continuously updating recommendations based on longitudinal user data. The recommendation module 106 analyses nutrient intake patterns to provide real-time dietary corrections. The recommendation module 106 considers dietary restrictions such as vegan, gluten-free, and allergen-sensitive options when generating meal plans. The recommendation module 106 enhances user engagement by adapting to personal taste preferences over time. The recommendation module 106 provides detailed breakdowns of nutrient compositions in recommended meals. The recommendation module 106 works in synchronization with the storage unit 108 to retrieve validated dietary guidelines.
[0062] The recommendation module 106 dynamically adjusts dietary suggestions based on a combination of historical dietary behaviours, current health data, and evolving nutritional research. The recommendation module 106 ensures that meal plans maintain a balance between nutrient density and user-specific taste preferences. The recommendation module 106 enhances dietary adherence by integrating alternative food options for ingredients that users avoid or dislike. The recommendation module 106 continuously evaluates dietary patterns to provide real-time recommendations that align with daily activity levels and metabolic efficiency. The recommendation module 106 prevents nutritional deficiencies by ensuring that all recommended meals provide essential vitamins and minerals. The recommendation module 106 refines dietary guidance by incorporating adaptive learning techniques that assess the effectiveness of past recommendations. The recommendation module 106 enables immediate meal plan modifications based on real-time user feedback. The recommendation module 106 enhances the accuracy of meal planning by considering food availability and seasonal variations. The recommendation module 106 prevents conflicting dietary suggestions by cross-referencing user health conditions and previously established dietary restrictions. The recommendation module 106 ensures that users receive scientifically backed nutritional recommendations that align with established health guidelines. The recommendation module 106 optimizes personalized meal plans by maintaining an adaptive approach to user health goals.
[0063] The storage unit 108 maintains an extensive database of nutrient-rich foods, dietary guidelines, and user engagement records. The storage unit 108 ensures data-driven improvements in recommendation accuracy and efficiency. The storage unit 108 organizes dietary information based on food categories, nutritional content, and user-specific health requirements. The storage unit 108 supports retrieval of region-specific and culturally relevant food options to align dietary guidance with local availability. The storage unit 108 ensures that dietary recommendations incorporate seasonal food variations for sustainability. The storage unit 108 records user engagement patterns to track adherence and optimize future dietary suggestions. The storage unit 108 safeguards sensitive dietary information with secure access protocols. The storage unit 108 enables fast data retrieval to support real-time recommendation adjustments. The storage unit 108 maintains a structured repository of validated nutritional guidelines to ensure reliability. The storage unit 108 enhances system efficiency by storing historical dietary interactions for continuous improvement.
[0064] The storage unit 108 ensures that all collected dietary data remains securely stored and efficiently organized for future retrieval. The storage unit 108 categorizes user-specific nutritional records to enable seamless data processing by the processing unit 102. The storage unit 108 enhances accessibility by structuring food-related information based on dietary needs, regional preferences, and sustainability factors. The storage unit 108 facilitates quick data retrieval to support real-time dietary adjustments. The storage unit 108 prevents data loss by implementing backup protocols that safeguard critical dietary information. The storage unit 108 maintains detailed records of user interactions to refine dietary recommendations over time. The storage unit 108 enhances long-term dietary planning by storing meal history and tracking user progress. The storage unit 108 ensures that stored data remains protected by utilizing secure encryption measures. The storage unit 108 enables seamless integration with external nutritional databases to enhance the accuracy of stored food composition data. The storage unit 108 optimizes retrieval speeds by prioritizing frequently accessed dietary records. The storage unit 108 ensures that dietary suggestions remain relevant by continuously updating stored information with newly acquired health and nutritional data.
[0065] The communication network 110 facilitates seamless data exchange between system components. The communication network 110 enables real-time interaction between the processing unit 102, data acquisition module 104, recommendation module 106, storage unit 108, and user devices 112. The communication network 110 ensures uninterrupted transmission of dietary data and recommendations. The communication network 110 enhances accessibility by supporting multiple connectivity protocols. The communication network 110 synchronizes user-specific dietary data across multiple devices. The communication network 110 minimizes latency to ensure instant feedback and dietary adjustments. The communication network 110 enhances user experience by providing immediate access to dietary insights. The communication network 110 maintains a high-speed data transmission framework to prevent delays in dietary recommendation delivery. The communication network 110 supports encrypted data exchange to ensure privacy and security. The communication network 110 optimizes bandwidth usage to improve system efficiency.
[0066] The communication network 110 facilitates efficient data exchange between all system components, ensuring that dietary recommendations remain dynamically updated. The communication network 110 enables continuous synchronization between the user device 112, processing unit 102, and storage unit 108. The communication network 110 prevents transmission delays by optimizing bandwidth allocation for high-speed data transfer. The communication network 110 enhances the reliability of system interactions by ensuring real-time updates to dietary recommendations. The communication network 110 enables remote data access, allowing users to receive dietary updates from multiple devices. The communication network 110 prevents disruptions by maintaining a secure and stable connection across all integrated components. The communication network 110 ensures encrypted data transmission to protect user privacy and prevent unauthorized access. The communication network 110 enhances accessibility by supporting multiple communication protocols, including wireless, cloud-based, and direct device synchronization. The communication network 110 maintains efficient system performance by managing data flow between interconnected modules. The communication network 110 enables instant feedback from the processing unit 102 to the user device 112, ensuring prompt updates to dietary recommendations.
[0067] The user device 112 provides users with real-time access to dietary recommendations and progress tracking. The user device 112 serves as the primary interface for user interaction with the system. The user device 112 ensures that users receive dietary recommendations instantly through seamless connectivity with the processing unit 102. The user device 112 enhances accessibility by supporting multiple device types, including smartphones, tablets, and computers. The user device 112 allows users to track nutritional intake and monitor adherence to dietary plans. The user device 112 integrates with wearable health devices to display real-time biometric updates. The user device 112 ensures uninterrupted access to dietary recommendations through offline functionality. The user device 112 synchronizes with cloud-based storage to retrieve historical dietary data. The user device 112 supports multilingual dietary recommendations for user convenience. The user device 112 enhances engagement through interactive dietary insights.
[0068] The user device 112 serves as the primary point of interaction for users to access dietary recommendations and track progress. The user device 112 enhances accessibility by supporting various platforms, including mobile phones, tablets, and computers. The user device 112 ensures uninterrupted access to dietary recommendations by allowing offline storage and retrieval of stored data. The user device 112 enhances user engagement by providing an intuitive interface for seamless navigation. The user device 112 enables real-time synchronization with the communication network 110 to ensure up-to-date dietary guidance. The user device 112 supports biometric data integration by displaying real-time health updates retrieved from connected wearable devices. The user device 112 enhances dietary tracking by enabling users to log meals and monitor nutrient intake effortlessly. The user device 112 supports multilingual dietary recommendations, ensuring accessibility across diverse user demographics. The user device 112 prevents disruptions in dietary planning by providing instant access to stored meal plans. The user device 112 enhances the user experience by offering visual meal representations and interactive insights. The user device 112 ensures that dietary recommendations remain personalized by syncing with stored user preferences and dietary histories.
[0069] The user interface 114 enables users to input dietary preferences and receive personalized meal plans. The user interface 114 provides an intuitive design for seamless navigation and interaction. The user interface 114 supports interactive visual representations of nutrient intake and dietary trends. The user interface 114 ensures ease of use through customizable settings and adaptive features. The user interface 114 enhances user engagement by offering real-time feedback and meal plan adjustments. The user interface 114 integrates educational content to improve dietary awareness. The user interface 114 ensures accessibility through multilingual support. The user interface 114 connects users with dieticians and nutritionists for expert guidance. The user interface 114 facilitates seamless dietary tracking through an integrated meal logging feature.
[0070] The user interface 114 provides an interactive platform for users to manage dietary preferences and receive personalized nutritional guidance. The user interface 114 enhances accessibility by offering an intuitive and user-friendly design. The user interface 114 supports customizable dietary settings to accommodate individual health requirements. The user interface 114 enhances user engagement by offering graphical representations of dietary trends and progress tracking. The user interface 114 ensures that meal recommendations remain practical by allowing users to modify and personalize their dietary plans. The user interface 114 supports real-time alerts and notifications to ensure adherence to meal plans. The user interface 114 integrates educational resources to improve nutritional awareness and promote healthy eating habits. The user interface 114 provides users with direct access to dietitians and nutritionists for expert dietary guidance. The user interface 114 supports voice-assisted commands to enhance ease of use. The user interface 114 prevents errors in meal planning by allowing users to review and confirm dietary suggestions before implementation. The user interface 114 ensures a seamless dietary management experience by integrating with other system components to deliver accurate and timely recommendations.
[0071] FIG. 2 illustrates a flowchart of a smart diet guide system, in accordance with an exemplary embodiment of the present disclosure.
[0072] At 202, user inputs dietary preferences, health conditions, and lifestyle factors through the user interface on the user device.
[0073] At 204, the data acquisition module collects and transmits user-specific dietary data to the processing unit for analysis.
[0074] At 206, the processing unit analyses the data and integrates bioavailability optimization, cultural food preferences, and sustainability parameters.
[0075] At 208, the recommendation module refines and personalizes dietary guidance using adaptive learning and historical user interactions.
[0076] At 210, the storage unit retrieves relevant nutrient-rich food options and dietary guidelines for data-driven recommendations.
[0077] At 212, the communication network facilitates real-time data exchange between the processing unit and the user device.
[0078] At 214, the user device displays personalized dietary recommendations, progress tracking, and interactive feedback through the user interface.
[0079] FIG. 3 illustrates a flowchart of a smart diet guide method, in accordance with an exemplary embodiment of the present disclosure.
[0080] At 302, receiving via a data acquisition module user-specific dietary data including nutritional requirements, health conditions, food preferences, and lifestyle factors.
[0081] At 304, processing by a processing unit the acquired dietary data to identify nutritional gaps and recommend optimized dietary solutions based on bioavailability enhancement, cultural food preferences, and sustainability parameters.
[0082] At 306, generating via a recommendation module customized dietary guidance by integrating scientific dietary principles, adaptive learning algorithms, and historical user interactions to improve personalization.
[0083] At 308, storing within a storage unit a structured database comprising nutrient-rich food options validated dietary guidelines, and user engagement records for continuous optimization and refinement of dietary recommendations.
[0084] At 310, facilitating via a communication network seamless real-time data exchange between the processing unit and a user device to ensure instant delivery of dietary recommendations.
[0085] At 312, displaying via a user interface embedded in the user device interactive meal plans, progress tracking insights, and educational content to guide users toward sustainable and effective nutritional improvements.
[0086] While the invention has been described in connection with what is presently considered to be the most practical and various embodiments, it will 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.
[0087] A person of ordinary skill in the art may be aware that, in combination with the examples described in the embodiments disclosed in this specification, units and algorithm steps may be implemented by electronic hardware, computer software, or a combination thereof.
[0088] The foregoing descriptions of specific embodiments of the present disclosure have been presented for purposes of illustration and description. They are not intended to be exhaustive or to limit the present disclosure to the precise forms disclosed, and many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described to best explain the principles of the present disclosure and its practical application, and to thereby enable others skilled in the art to best utilize the present disclosure and various embodiments with various modifications as are suited to the particular use contemplated. It is understood that various omissions and substitutions of equivalents are contemplated as circumstances may suggest or render expedient, but such omissions and substitutions are intended to cover the application or implementation without departing from the scope of the present disclosure.
[0089] Disjunctive language such as the phrase “at least one of X, Y, Z,” unless specifically stated otherwise, is otherwise understood with the context as used in general to present that an item, term, etc., may be either X, Y, or Z, or any combination thereof (e.g., X, Y, and/or Z). Thus, such disjunctive language is not generally intended to, and should not, imply that certain embodiments require at least one of X, at least one of Y, or at least one of Z to each be present.
[0090] In a case that no conflict occurs, the embodiments in the present disclosure and the features in the embodiments may be mutually combined. The foregoing descriptions are merely specific implementations of the present disclosure, but are not intended to limit the protection scope of the present disclosure. Any variation or replacement readily figured out by a person skilled in the art within the technical scope disclosed in the present disclosure shall fall within the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure shall be subject to the protection scope of the claims.
, Claims:I/We Claim:
1. A smart diet guide system (100) comprising:
a processing unit (102), configured to analyse user-specific dietary data and generate customized dietary recommendations based on bioavailability optimization techniques, cultural food preferences, and sustainability parameters;
a data acquisition module (104), operably coupled to the processing unit (102), configured to collect user-specific dietary data, including nutritional requirements, health conditions, food preferences, and lifestyle factors;
a recommendation module (106), operably coupled to the processing unit (102), configured to refine and personalize dietary guidance by integrating historical user interactions, scientific dietary principles, and adaptive learning techniques;
a storage unit (108), operably coupled to the processing unit (102), configured to store a database of nutrient-rich foods, dietary guidelines, and user engagement records to enable data-driven improvements in recommendations;
a communication network (110), operably coupled to the processing unit (102), configured to enable seamless data exchange between a plurality of system components;
a user device (112), operably connected to the processing unit (102) through the communication network (110), configured to provide users with real-time access to dietary recommendations, progress tracking, and interactive feedback; and
a user interface (114), embedded within the user device (112), configured to allow users to input dietary preferences, receive personalized meal plans, track nutritional intake, and access educational content on diet optimization.
2. The system (100) as claimed in claim 1, wherein the data acquisition module (104) further comprises a real-time health monitoring sub-module, configured to integrate with wearable health devices and retrieve biometric data including heart rate, blood sugar levels, and physical activity metrics to enhance dietary recommendations based on physiological responses.
3. The system (100) as claimed in claim 1, wherein the recommendation module (106) further comprises an adaptive learning sub-module, configured to refine dietary suggestions dynamically by analysing longitudinal user data and evolving health patterns to offer progressive and personalized nutritional advice.
4. The system (100) as claimed in claim 1, wherein the storage unit (108) further comprises a structured nutritional database, configured to store and retrieve region-specific, culturally relevant food options and align recommendations with locally available, seasonal ingredients for sustainability-focused diet planning.
5. The system (100) as claimed in claim 1, wherein the user device (112) further comprises an offline functionality module, configured to allow users to access stored dietary recommendations and educational materials without an active internet connection, ensuring continued guidance in low-connectivity environments.
6. The system (100) as claimed in claim 1, wherein the user interface (114) further comprises an interactive visual representation module, configured to provide graphical insights into nutrient intake, progress trends, and dietary adjustments, enhancing user engagement and adherence to dietary goals.
7. The system (100) as claimed in claim 1, wherein the processing unit (102) further comprises a multilingual adaptation module, configured to enable dietary recommendations and educational content delivery in multiple languages, ensuring accessibility for diverse user demographics.
8. The system (100) claimed in claim 1, wherein the recommendation module (106) further comprises a dietary restriction compliance sub-module, configured to filter meal plans and ingredient suggestions based on user-specified dietary restrictions, including vegan, gluten-free, diabetic-friendly, and allergen-sensitive options.
9. The system (100) as claimed in claim 1, wherein the user interface (114) further comprises a community engagement module, configured to connect users with nutritionists, dieticians, and peer support groups, enabling collaborative learning and shared health insights.
10. A smart diet guide method (100) comprising:
receiving via a data acquisition module (104), user-specific dietary data including nutritional requirements, health conditions, food preferences, and lifestyle factors;
processing by a processing unit (102), the acquired dietary data to identify nutritional gaps and recommend optimized dietary solutions based on bioavailability enhancement, cultural food preferences, and sustainability parameters;
generating via a recommendation module (106), customized dietary guidance by integrating scientific dietary principles, adaptive learning algorithms, and historical user interactions to improve personalization;
storing within a storage unit (108), a structured database comprising nutrient-rich food options, validated dietary guidelines, and user engagement records for continuous optimization and refinement of dietary recommendations;
facilitating via a communication network (110), seamless real-time data exchange between the processing unit (102) and a user device (112) to ensure instant delivery of dietary recommendations;
displaying via a user interface (114), embedded in the user device (112), interactive meal plans, progress tracking insights, and educational content to guide users toward sustainable and effective nutritional improvements.