Description:BACKGROUND
Field of Invention
[001] Embodiments of the present invention generally relate to a food identification and balancing and particularly to a personalized food selection system for special diets.
Description of Related Art
[002] Consumers with dietary restrictions often encounter significant challenges when attempting to select appropriate food products. The primary issue arises from inconsistent labelling standards and limited accessibility to detailed ingredient information. Many individuals who require allergen-free, gluten-free, vegan, or other specialized diets must rely on their own scrutiny of product labels, which frequently contain ambiguous or incomplete data. This creates a potential risk to consumer health and contributes to overall dietary uncertainty.
[003] Current commercial practices utilize digital applications that depend on barcode scanning and static ingredient databases. While these applications provide general insights, they often lack the capacity to reflect real-time changes in food formulations. Furthermore, they do not allow for user-specific dietary filters beyond basic categories, which limits their usefulness to individuals with complex or multiple dietary constraints. Such systems remain reactive and rigid, offering minimal adaptability to evolving dietary needs or local food availability.
[004] Some platforms offer basic filtering options on e-commerce websites, but these filters function based on vendor-entered metadata rather than real ingredient lists. Consequently, users face difficulty in verifying product suitability at the point of selection. In addition, the absence of automated ingredient validation across languages, formats, and brands reduces the effectiveness of these systems.
[005] There is thus a need for an improved and advanced personalized food selection system for special diets that can administer the aforementioned limitations in a more efficient manner.
SUMMARY
[006] Embodiments in accordance with the present invention provide a personalized food selection system for special diets. The system comprising an input unit adapted to scan an edible product using an Optical Character Recognition (OCR) technique. The input unit is adapted to enable a user to create a dietary profile. The system further comprising a data acquisition unit adapted to receive the scanned ingredients in the edible product from the input unit. The system further comprising a processing unit communicatively connected to the data acquisition unit. The processing unit is configured to receive the ingredients from the data acquisition unit; analyze the received ingredients, using smart computing techniques, for identification of allergens, hidden ingredients, dietary compatibility, or a combination thereof. The smart computing techniques are selected from a Machine Learning (ML), a Natural Language Processing (NLP), or a combination thereof; correlate the analyzed ingredients with the dietary profile of the user; and transmit a ‘SAFE’ indication to the input unit, when the ingredients match with the dietary profile of the user.
[007] Embodiments in accordance with the present invention further provide a method for personalized food selection. The method comprising steps of receiving ingredients from an input unit; analyzing the received ingredients, using smart computing techniques, for identification of allergens, hidden ingredients, dietary compatibility, or a combination thereof. The smart computing techniques are selected from a Machine Learning (ML), a Natural Language Processing (NLP), or a combination thereof; correlating the analyzed ingredients with a dietary profile of a user, and transmitting a ‘SAFE’ indication to the input unit, when the ingredients match with the dietary profile of the user.
[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 a personalized food selection system for special diets.
[009] Next, embodiments of the present application may provide a personalized food selection system that extracts and analyzes ingredient lists directly from food labels using Optical Character Recognition (OCR) and Artificial Intelligence (AI), enabling instant identification of allergens and dietary incompatibilities without reliance on pre-existing databases.
[0010] Next, embodiments of the present application may provide a personalized food selection system that intelligently suggests suitable, locally available alternatives based on ingredient similarity and availability.
[0011] Next, embodiments of the present application may provide a personalized food selection system that improves its detection accuracy over time by learning from user interactions and label variations.
[0012] Next, embodiments of the present application may provide a personalized food selection system that functions across mobile and cloud environments, ensuring seamless updates, wide accessibility, and a consistent user experience across devices and locations.
[0013] Next, embodiments of the present application may provide a personalized food selection system that uses Natural Language Processing (NLP) to understand ingredient information across various languages and label formats, ensuring accurate dietary assessment regardless of regional packaging differences.
[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 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 personalized food selection system for special diets, 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 personalized food selection, 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 personalized food selection system 100 (hereinafter referred to as the system 100) for special diets, according to an embodiment of the present invention. The system 100 may be adapted to investigate ingredients of an edible product, and match the investigated ingredients with a user preferred meal plan. The system 100 further indicates a suitability for consumption of the edible product based upon a match making of the investigated ingredients with the user preferred meal plan.
[0025] The system 100 may be used by users such as, but not limited to, a sportsperson, a gym trainee, a soldier, a dietician, an actor, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the users and use case scenarios of the system 100.
[0026] 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 an input unit 102, a data acquisition unit 104, a processing unit 106, and smart computing techniques 108. 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 the limitations of the existing systems.
[0027] In an embodiment of the present invention, the input unit 102 may be adapted to scan the edible product for extraction of ingredients. In an embodiment of the present invention, the input unit 102 may be adapted to upload the extracted ingredients in the edible product to the system 100. The ingredients uploaded by the input unit 102 may enable the system 100 to analyze the ingredients for suitability for consumption. The input unit 102 may operate on an Optical Character Recognition (OCR) technique for reading the ingredients imprinted on the edible product, extracting the ingredients encoded in a bar code of the edible product, capturing an image of the edible product for interpolation of the ingredients in the edible product, and so forth. Embodiments of the present invention are intended to include or otherwise cover any technique, including known, related art, and/or later developed technologies, for extraction of the ingredients in the edible product.
[0028] In an embodiment of the present invention, the input unit 102 may be adapted to enable a user to create a dietary profile. The dietary profile may comprise dietary preferences, dietary avoidances, meal timings, fulfillment of nutrients, cheat meals, and so forth. Embodiments of the present invention are intended to include or otherwise cover any components, including known, related art, and/or later developed technologies, in the dietary profile. The input unit 102 may be, but not limited to, a laptop, a mobile, a bar code scanner, a camera, and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the input unit 102, including known, related art, and/or later developed technologies.
[0029] In an embodiment of the present invention, the data acquisition unit 104 may be adapted to receive the ingredients from the input unit 102.
[0030] In an embodiment of the present invention, the processing unit 106 may be in communication with the data acquisition unit 104. The processing unit 106 may further be configured to execute computer-executable instructions to generate an output relating to the system 100. According to embodiments of the present invention, the processing unit 106 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 106 including known, related art, and/or later developed technologies. In an embodiment of the present invention, the processing unit 106 may further be explained in conjunction with FIG. 2.
[0031] FIG. 2 illustrates a block diagram of the processing unit 106, according to an embodiment of the present invention. The processing unit 106 may comprise the computer-executable instructions in form of programming modules such as a data receiving module 200, a data assessment module 202, a data matchmaking module 204, a data transmission module 206.
[0032] In an embodiment of the present invention, the data receiving module 200 may be configured to receive the ingredients from the data acquisition unit 104. The data receiving module 200 may be configured to transmit the received ingredients to the data assessment module 202.
[0033] The data assessment module 202 may be activated upon receipt of the ingredients from the data receiving module 200. In an embodiment of the present invention, the data assessment module 202 may be configured to activate the smart computing techniques 108 for analysis of the received ingredients. The received ingredients may be analyzed for factors such as, but not limited to, identification of allergens, hidden ingredients, dietary compatibility, and so forth. Embodiments of the present invention are intended to include or otherwise cover any factors, including known, related art, and/or later developed technologies, that may be analyzed in the received ingredients. The smart computing techniques 108 may be, but not limited to, a Machine Learning (ML), a Natural Language Processing (NLP), and so forth. Embodiments of the present invention are intended to include or otherwise cover any type of the smart computing techniques 108, including known, related art, and/or later developed technologies. The data assessment module 202 may be configured to transmit the analyzed ingredients to the data matchmaking module 204.
[0034] The data matchmaking module 204 may be activated upon receipt of the analyzed ingredients from the data assessment module 202. In an embodiment of the present invention, the data matchmaking module 204 may be configured to correlate the analyzed ingredients with the dietary profile of the user. Upon correlation, if the analyzed ingredients match with the dietary profile of the user, then the data matchmaking module 204 may transmit a safe signal to the data transmission module 206. Else, the data matchmaking module 204 may transmit an unsafe signal to the data transmission module 206.
[0035] The data transmission module 206 may be activated upon receipt of the safe signal from the data matchmaking module 204. The data transmission module 206 may be configured to transmit a ‘SAFE’ indication to the input unit 102.
[0036] However, if the data transmission module 206 may be activated upon receipt of the unsafe signal from the data matchmaking module 204. Then, the data transmission module 206 may be configured to transmit an ‘UNSAFE’ indication to the input unit 102. Further, the data transmission module 206 may be configured to transmit an alternative of the corresponding edible product that may be in line with the dietary profile of the user. The alternative edible product may be locally sourced and may be nearby and readily available. Further, based on the recommendation of the alternative edible product, the data transmission module 206 may be configured to enable the user to provide a feedback to the system 100. Furthermore, the feedback may conduct continuous learning and updates leading to improvement in accuracy of recommendation of the alternative edible product and user experience over time.
[0037] In an exemplary scenario, if the dietary profile of the user may allow consumption of red meat up to 60 grams, and the user may choose a medium burger. Upon extraction of the ingredients in the medium burger, the system 100 may match the extracted ingredients with the dietary profile. Further, upon matching the extracted ingredients with the dietary profile the system 100 may conclude that the dietary profile of the user is allowing up to 60 grams of red meat. Thus, the system 100 may indicate the medium burger as safe for consumption.
[0038] In another exemplary scenario, if the dietary profile of the user may restrict consumption of carbonated sugar, and the user may choose a bottle of Coke using the input unit 102. Upon extraction of the ingredients in the bottle of Coke, the system 100 may match the extracted ingredients with the dietary profile. Further, upon matching the extracted ingredients with the dietary profile the system 100 may conclude that the dietary profile of the user is restricting consumption of carbonated sugar, however, the bottle of Coke which the user may be willing to consume contains carbonated sugar. Thus, the system 100 may indicate the bottle of Coke as unsafe for consumption. However, the system 100 may further recommend the user to consume sugarcane juice, black coffee, green tea, and so forth, as the recommendations do not consume carbonated sugar, thus aligning with the dietary profile of the user.
[0039] FIG. 3 depicts a flowchart of a method 300 for personalized food selection, according to an embodiment of the present invention.
[0040] At step 302, the system 100 may enable the input unit 102 to scan and extract the ingredients in the edible product.
[0041] At step 304, the system 100 may receive the ingredients in the edible product from the input unit 102.
[0042] At step 306, the system 100 may analyze the received ingredients for identification of the allergens, the hidden ingredients, the dietary compatibility, and so forth.
[0043] At step 308, the system 100 may correlate the analyzed ingredients with the dietary profile of the user.
[0044] At step 310, if the ingredients match with the dietary profile of the user, then the method 300 may proceed to a step 312. Else, the method 300 may proceed to a step 314.
[0045] At step 312, the system 100 may transmit the ‘SAFE’ indication to the input unit 102.
[0046] At step 314, the system 100 may transmit the ‘UNSAFE’ indication to the input unit 102.
[0047] At step 316, the system 100 may enable the user to provide the feedback.
[0048] 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. A personalized food selection system (100) for special diets, the system (100) comprising:
an input unit (102) adapted to scan an edible product using an Optical Character Recognition (OCR) technique, wherein the input unit (102) is adapted to enable a user to create a dietary profile
a data acquisition unit (104) adapted to receive the scanned ingredients in the edible product from the input unit (102); and
a processing unit (106) communicatively connected to the data acquisition unit (104), characterized in that the processing unit (106) is configured to:
receive the ingredients from the data acquisition unit (104);
analyze the received ingredients, using smart computing techniques (108), for identification of allergens, hidden ingredients, dietary compatibility, or a combination thereof, wherein the smart computing techniques (108) is selected from a Machine Learning (ML), a Natural Language Processing (NLP), or a combination thereof;
correlate the analyzed ingredients with the dietary profile of the user; and
transmit a ‘SAFE’ indication to the input unit (102), when the ingredients match with the dietary profile of the user.
2. The system (100) as claimed in claim 1, wherein the processing unit (106) is configured to transmit an ‘UNSAFE’ indication to the input unit (102) along with alternatives of the corresponding edible product, when the ingredients mismatch with the dietary profile of the user.
3. The system (100) as claimed in claim 1, wherein the input unit (102) is adapted to read the ingredients imprinted on the edible product, extract the ingredients encoded in a bar code of the edible product, capture an image of the edible product for interpolation of the ingredients in the edible product, or a combination thereof.
4. The system (100) as claimed in claim 1, wherein the dietary profile comprise dietary preferences, dietary avoidances, meal timings, fulfillment of nutrients, cheat meals, or a combination thereof.
5. The system (100) as claimed in claim 1, wherein the processing unit (106) is configured to conduct continuous learning and updates leading to improvement in accuracy and user experience over time.
6. The system (100) as claimed in claim 1, wherein the processing unit (106) is configured to enable a user to provide a feedback to the system (100).
7. A method (300) for personalized food selection, the method (300) is characterized by steps of:
receiving ingredients from an input unit (102);
analyzing the received ingredients, using smart computing techniques (108), for identification of allergens, hidden ingredients, dietary compatibility, or a combination thereof, wherein the smart computing techniques (108) is selected from a Machine Learning (ML), a Natural Language Processing (NLP), or a combination thereof;
correlating the analyzed ingredients with a dietary profile of a user; and
transmitting a ‘SAFE’ indication to the input unit (102), when the ingredients match with the dietary profile of the user.
8. The method (300) as claimed in claim 7, comprising a step of transmitting an ‘UNSAFE’ indication to the input unit (102) along with alternatives of the corresponding edible product, when the ingredients mismatch with the dietary profile of the user.
9. The method (300) as claimed in claim 7, wherein the input unit (102) operates on an Optical Character Recognition (OCR) technique for reading the ingredients imprinted on the edible product, extracting the ingredients encoded in a bar code of the edible product, capturing an image of the edible product for interpolation of the ingredients in the edible product, or a combination thereof.
10. The method (300) as claimed in claim 7, wherein the dietary profile comprise dietary preferences, dietary avoidances, meal timings, fulfillment of nutrients, cheat meals, or a combination thereof.
Date: June 03, 2025
Place: Noida

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