An artificial intelligence based system and method for nutrient estimation, and meal planning

Abstract

An artificial intelligence (AI) based system for nutrient estimation, and meal planning comprises a server processor coupled with a database in network communication with a plurality of users connected over the said network. The database stores characteristics that represent physical conditions about the users (e.g. DNA test results, family health history, BMI along with meal patterns, hunger, sleep patterns, and food habits). The database coupled with the said server processor includes a diet plan dataset, and an ingredient nutritional information dataset. The server processor is operable to generate a meal profile for each of the users, wherein each meal profile comprises a plurality of individual characteristics representative of the user's physical condition. The system analyses the stored characteristics, and recommended nutritional intake levels to generate at least one meal plan.

Description

[0001] This invention relates to the system and method for providing the diet plans to user. More particularly, it relates to the software application providing meal plans based on DNA structure of the particular user using Artificial Intelligence (AI). Background of the Invention

[0002] Often times, it is advantageous for consumers of food to design their diets to align with their wellness and / or health objectives. An individual may have one or more diseases that the individual wishes to prevent, and in some cases may also have genetic predisposition for a specific disease. Another individual may already be suffering from a disease, and may wish to alleviate or cure the disease. Another individual may be interested in improving physiological and psychological performance in areas such as visual acuity, cognitive functions, memory, and physical endurance.

[0003] Alternatively, the diet may have to consider groups as opposed to single individuals. There is a need for the individual meal planner based on his desires. The individual has his own reasons like allergies to specific things, not likely to take and certain reasons to avoid. It is not possible for every individual to have a personal dietician hired.

[0004] Therefore, the inventors find a need for an Artificial Intelligence (AI) based system and method for nutrient estimation, and meal planning. Brief Summary of the Invention

[0005] The following presents a simplified summary of the disclosure in order to provide a basic understanding to the reader. This summary is not an extensive overview of the disclosure and it does not identify key / critical elements of the invention or delineate the scope of the invention. Its sole purpose is to present some concepts disclosed herein in a simplified form as a prelude to the more detailed description that is presented later.

[0006] It is an object of the invention to provide the meal plans for the particular user based on his / her DNA structure and other attributes.

[0007] It is yet another object of the invention to provide recipes based on the user preferences, dislikes and allergies.

[0008] It is yet another object of the invention to determine the ideal body weight of the user taking all attributes into consideration.

[0009] According to an exemplary embodiment of present invention, an Artificial Intelligence (AI) based system for food and nutrient estimation, and meal planning is disclosed. The system comprises a server processor coupled with a database in network communication with a plurality of users connected over the said network.

[0010] In accordance with the aspect of the present invention, the database of the system stores characteristics that represent physical conditions about the users. The database coupled with the said server processor includes a diet plan dataset, and an ingredient nutritional information dataset.

[0011] In accordance with the aspect of the present invention, the server processor of the system is operable to generate a meal profile for each of the users, wherein each meal profile comprises a plurality of individual characteristics representative of the user's physical condition.

[0012] In accordance with the aspect of the present invention, the system analyses the stored characteristics, and recommended nutritional intake levels to generate at least one meal plan. The characteristics that represents physical conditions about the users stored by the said database of the said system includes diagnoses information related to a diagnoses including DNA test results, family health history, BMI along with meal patterns, hunger, sleep patterns, and food habits.

[0013] In accordance with the aspect of the present invention, the said system is associated with a mobile application that each user communicates, comprises a rule-based valuation to deploy a mean occurrence of nutritive components, leading to a method for regulating the diversity and synchronization of the menus by tracking all primary health parameters, ailments, and / or symptoms.

[0014] In accordance with the aspect of the present invention, the said system enables the users to input information and / or allow access to health history and all other vital information of current food intake, or any vital information, and details of the nutrition goal for a healthy lifestyle.

[0015] In accordance with the aspect of the present invention, the said system enables a plurality of healthcare advisors to have seamless access to an online consultation with ability to access a user’s primary health report in real-time ensuring designing of a meal plan based on the said rules-based engine using AI.

[0016] In accordance with the aspect of the present invention, the ingredient nutritional information dataset comprises a plurality of food ingredients and wherein each food ingredient of the plurality is assigned a nutritional value.

[0017] In accordance with the aspect of the present invention, the nutritional value includes at least one selected from the group consisting of a calorific value of the food ingredient, a protein content of the food ingredient, a carbohydrate content of the food ingredient, a fat content of the food ingredient, a mineral content of the food ingredient, a vitamin content of the food ingredient, a sugar content of the food ingredient, a salt content of the food ingredient, and a combination thereof.

[0018] In accordance with the aspect of the present invention, the user specific characteristics include food ingredients allergy information for the user, the food ingredients allergy information.

[0019] In accordance with the aspect of the present invention, the food ingredients allergy information comprises at least one selected from the group consisting of a food ingredient allergic for the user, a food ingredient non-allergic for the user and a combination thereof, and wherein the one or more food ingredients to be replaced in the selected diet plan are identified based on the food ingredients allergy information for the user.

[0020] In accordance with the aspect of the present invention, the user specific characteristics includes food desirability information for the user, the food desirability information for the user comprising at least one selected from the group consisting of: a food ingredient desirable by the user, a food ingredient undesirable by the user and a combination thereof, and wherein the one or more food ingredients to be replaced in the diet plan are identified based on the food desirability information for the user.

[0021] In accordance with the aspect of the present invention, Artificial Intelligence (AI) based method illustrates a flow of steps a semantic analysis model and a nutritional model undergoes and the nutritional ingredient analysis is done through fuzzy analysis.

[0022] In accordance with the aspect of the present invention, the operation of a rule-based valuation of precise nutritional analysis is done by inputting the dietary record.

[0023] In accordance with the aspect of the present invention, the user specific characteristics include health advisor recommendation for the user, the healthcare advisor recommendation for the user.

[0024] In accordance with the aspect of the present invention, the healthcare advisor recommendation for the user comprises at least one selected from the group consisting of a food ingredient recommended for the user by a healthcare advisor, a food ingredient rejected for the user by the healthcare advisor and a combination thereof, and wherein the one or more food ingredients to be replaced in the selected diet plan are identified based on the healthcare advisor recommendation information for the user.

[0025] Further objects, features, and advantages of the invention will be readily apparent from the following description of the preferred embodiments thereof, taken in conjunction with the accompanying drawings. Brief Description of the Drawings

[0026] The objectives as described above as well as the uniqueness of the proposed technology along with its advantages can be better appreciated by referring to the following illustrative and non-limiting detailed description of the present invention along with the following schematic diagrams, wherein:

[0027] Figure 1 illustrates the block diagram of the diet plan generation system, according to the embodiment of the invention;

[0028] Figure 2 illustrates the flow chart depicting the meal plans as per ideal body weight, according to the embodiment of the invention;

[0029] Figure 3 illustrates the process of flow of steps in the artificial intelligence semantic analysis model and nutritional model, according to the embodiment of the invention;

[0030] Figure 4 illustrates the nutritional ingredient analysis through fuzzy analysis, according to the embodiment of the invention;

[0031] Figure 5 illustrates the operation of a rule-based valuation of precise nutritional analysis, according to the embodiment of the invention;

[0032] Figure 6 illustrates example depicting nutritional knowledge by the software application, according to the embodiment of the invention. Detailed Description of the Invention

[0033] It is to be understood that the present disclosure is not limited in its application to the details of construction and the arrangement of components set forth in the following description or illustrated in the drawings. The present disclosure is capable of other embodiments and of being practiced or of being carried out in various ways. In addition, it is to be understood that the phraseology and terminology used herein is for the purpose of description and should not be regarded as limiting.

[0034] The use of “including”, “comprising” or “having” and variations thereof herein is meant to encompass the items listed thereafter and equivalents thereof as well as additional items. 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. Further, the use of terms “first”, “second”, and “third”, and the like, herein do not denote any order, quantity, or importance, but rather are used to distinguish one element from another.

[0035] Referring to the figures, Fig.l, according to an exemplary embodiment of present invention, an Artificial Intelligence (AI) based system (100) for food and nutrient estimation, and meal planning is disclosed. The system comprises a server processor (104) coupled with a database (106) in network communication with a plurality of users connected over the said network.

[0036] In accordance with the exemplary embodiment of the present invention, the database (106) of the system (100) stores characteristics that represent physical conditions about the users. The database (106) coupled with the said server processor (104) includes a diet plan dataset, and an ingredient nutritional information dataset.

[0037] In accordance with the exemplary embodiment of the present invention, the server processor (104) of the system (100) is operable to generate a meal profile for each of the users, wherein each meal profile comprises a plurality of individual characteristics representative of the user's physical condition.

[0038] In accordance with the exemplary embodiment of the present invention, the system (100) analyses the stored characteristics, and recommended nutritional intake levels to generate at least one meal plan. The characteristics that represents physical conditions about the users stored by the said database (106) of the said system (100) includes diagnoses information related to a diagnoses including DNA test results, family health history, BMI along with meal patterns, hunger, sleep patterns, and food habits.

[0039] In accordance with the exemplary embodiment of the present invention, the said system (100) is associated with a mobile application that each user communicates, comprises a rule-based valuation to deploy a mean occurrence of nutritive components, leading to a method for regulating the diversity and synchronization of the menus by tracking all primary health parameters, ailments, and / or symptoms.

[0040] In accordance with the exemplary embodiment of the present invention, the said system (100) enables the users to input information and / or allow access to health history and all other vital information of current food intake, or any vital information, and details of the nutrition goal for a healthy lifestyle.

[0041] In accordance with the exemplary embodiment of the present invention, the said system (100) enables a plurality of healthcare advisors to have seamless access to an online consultation with ability to access a user's primary health report in real-time ensuring designing of a meal plan based on the said rules-based engine using AI.

[0042] In accordance with the exemplary embodiment of the present invention, the ingredient nutritional information dataset comprises a plurality of food ingredients and wherein each food ingredient of the plurality is assigned a nutritional value.

[0043] In accordance with the exemplary embodiment of the present invention, the nutritional value includes at least one selected from the group consisting of a calorific value of the food ingredient, a protein content of the food ingredient, a carbohydrate content of the food ingredient, a fat content of the food ingredient, a mineral content of the food ingredient, a vitamin content of the food ingredient, a sugar content of the food ingredient, a salt content of the food ingredient, and a combination thereof.

[0044] In accordance with the exemplary embodiment of the present invention, the user specific characteristics include food ingredients allergy information for the user, the food ingredients allergy information.

[0045] In accordance with the exemplary embodiment of the present invention, the food ingredients allergy information comprises at least one selected from the group consisting of a food ingredient allergic for the user, a food ingredient non-allergic for the user and a combination thereof, and wherein the one or more food ingredients to be replaced in the selected diet plan are identified based on the food ingredients allergy information for the user.

[0046] In accordance with the exemplary embodiment of the present invention, the user specific characteristics includes food desirability information for the user, the food desirability information for the user comprising at least one selected from the group consisting of: a food ingredient desirable by the user, a food ingredient undesirable by the user and a combination thereof, and wherein the one or more food ingredients to be replaced in the diet plan are identified based on the food desirability information for the user.

[0047] In accordance with the exemplary embodiment of the present invention, the user specific characteristics include health advisor recommendation for the user, the healthcare advisor recommendation for the user.

[0048] In accordance with the exemplary embodiment of the present invention, the healthcare advisor recommendation for the user comprises at least one selected from the group consisting of a food ingredient recommended for the user by a healthcare advisor, a food ingredient rejected for the user by the healthcare advisor and a combination thereof, and wherein the one or more food ingredients to be replaced in the selected diet plan are identified based on the healthcare advisor recommendation information for the user.

[0049] In accordance with the exemplary embodiment of the present invention, the user specific characteristics includes biographical information of the user and wherein the nutritional requirement of the user is determined based on the biographical information of the user from a reference nutritional requirement dataset, wherein the reference nutritional requirement dataset includes a plurality of nutritional requirements for different persons classified at least according to one of genders of the different persons, ages of the different persons, body weights of the different persons, diagnoses of the different persons, or a combination thereof.

[0050] In according to an exemplary embodiment of present invention, an Artificial Intelligence (AI) based method for food and nutrient estimation, and meal planning for a user is disclosed. The method comprising steps of: receiving user specific characteristics that represents physical conditions stored by a database (106) of a system (100); receiving user specific characteristics from the database (106) coupled with the said server processor (104) includes a diet plan dataset, and an ingredient nutritional information dataset; receiving user specific characteristics from the diet plan dataset includes a set of standard diet plans from a plurality of standard diet plans, wherein each standard diet plan corresponds to one or more diagnoses of a plurality of diagnoses including DNA test results, family health history, BMI along with meal patterns, hunger, sleep patterns, and food habits; receiving user specific characteristics from the ingredient nutritional information dataset, selecting one of the standard diet plans from the set of standard diet plans based on a nutritional requirement of the user, wherein the selected diet plan comprises a set of food ingredients; identifying, in the selected diet plan, one or more food ingredients to be replaced; accessing the said ingredient nutritional information dataset to select one or more alternate food ingredients; selecting the one or more alternate food ingredients from the ingredient nutritional information dataset, wherein a nutritional value of the one or more alternate food ingredients corresponds to a nutritional value of the one or more food ingredients to be replaced from the selected diet plan; and substituting, in the selected diet plan, the one or more alternate food ingredients for the one or more food ingredients to be replaced to generate the preferred diet plan for the user.

[0051] In accordance with the exemplary embodiment of the present invention, the said database stores the nutritional intake of the user. An user mobile device is used to input the parameters needed for the generation of meal plan. The said system (100) accesses the attributes along with DNA profile structure to generate a meal plan.

[0052] In accordance with the exemplary embodiment of the present invention, the said client component of the said system (100) is installed in the user’s mobile device coupled to the database (106) accesses the data to calculate the nutritional intake, calorie intake and others for future meal plans of the user. The system (100) also considers user health considerations, user allergies, user preferences and user food dislikes in generation of meal plans.

[0053] Fig.2 illustrates the flow diagram depicting the determination of ideal body weight based on user attributes (202). The processor generated meal plan after the comparison of ideal weight and present weight (204). After comparison, if it is ideal, the meal plan is weight maintenance plan (206). If it is above ideal the meal plan is weight loss plan (208) as well if it is below the meal plan is weight gain plan (210).

[0054] In accordance with the exemplary embodiment of the present invention, referring to Fig.3, the said Artificial Intelligence (AI) based method illustrates a flow of steps a semantic analysis model and a nutritional model undergoes. It starts with receiving raw data and loading pre-trained model. Next going to segmentation of words and tagging the parts of speech and recognizes the entity.

[0055] Finally, converting the word into vector form. The AI nutritional analysis model comes into play and preprocesses the resultant data using AI precision Nutrient analysis model.

[0056] In accordance with the exemplary embodiment of the present invention, referring to figures, Fig.4 illustrates nutritional ingredient analysis done through fuzzy analysis, wherein recipe data is obtained by fuzzy analysis of AI model. The model automatically determines ingredients in a dish, wherein the analysis consolidates nutrients by means of portion size.

[0057] In accordance with the exemplary embodiment of the present invention, referring to figures, Fig.5 illustrates the operation of a rule-based valuation of precise nutritional analysis. The valuation is done by inputting the dietary record. The input data includes the name of the dish and its portion. The analysis is done by semantic analysis model. Its operation is to separate each ingredient of the dish as per recipe and calculates the 24 nutrients of each ingredient and results based on sum of the nutrients is given.

[0058] In accordance with the exemplary embodiment of the present invention, referring to figures, Fig.6 illustrates the example knowledge database used for providing nutritional knowledge by the application for growing knowledge about what to eat for reducing the risks of some of the diseases. The food node like ‘chicken’, ‘cabbage’, ‘lettuce’ along with other types of foods prevents the disease node like ‘breast cancer’, ‘pancreatic cancer’, ‘carcinoma’, ‘type 1 &type 2 diabetes’. The next node connected to it is phyto-chemicals includes ‘ursolic acid’, ‘ellagic acid’, ‘naringin’, ‘limonene’ and ‘theobromine’.

[0059] Example Diet plan in the data base for person suffering from Rheumatoid Arthritis: RA is a systematic auto immune condition that can affect several joints, most commonly the small joints in the hands and feet but can affect knees, hips and shoulder joints too. Several joints can be affected at the same time, usually symmetrically (on both sides of the body), such as both hands. RA causes the joint lining to become inflamed and swollen resulting in destruction of the joint surface, causing extreme tenderness and pain.

[0060] The main symptoms of rheumatoid arthritis are: • joint pain • joint swelling, warmth and redness • stiffness, especially early in the morning or after sitting still for a long time.

[0061] Care and Diet: The most important relationship between diet and arthritis is weight. Excess weight can make some specialist medications ineffective. It may increase disease activity and delay remission. If you are carrying more body weight than you should, try to lose excess weight by combining healthy eating with regular exercise.

[0062] Research specifically with RA has shown an improvement in clinical symptoms when people with RA followed a Mediterranean diet; benefits included reduced swollen and tender joints, reduced duration of morning stiffness and improved general wellbeing.

[0063] The Mediterranean way of eating is based on daily intakes of fresh fruits and vegetables, nuts, beans and pulses, olive oil, wholegrain cereals and regular oily fish and poultry consumption. Research suggests that consumption of a Mediterranean diet (MD) reduces the incidence of clinical symptoms related to the immune system and chronic inflammation. [00641 Nutritional requirements for RA: Dietary Fibre: The gastrointestinal (GI) tract has an upper and lower section. And RA can affect either one. Research shows that people with RA are about 70% more likely to develop a gastrointestinal problem than people without RA.

[0065] The Arthritis Foundation suggests that fiber foods help feed healthy bacteria in the gut, and these bacteria releases substances aimed to reduce inflammation

[0066] Whole grains and Cereals include wheat, com, rice, oats, barley, and rye. Foods like Wholegrain pasta, wholegrain bread, porridge, oat bran, potato skins, sweet potato, beans, baked beans, chickpeas, pulses, vegetables &fruits, especially where you eat the skin and seeds. • Seeds, e.g., linseeds, chia seeds, sunflower • Nuts, e.g., almonds, hazelnuts, peanut butter are a source of key nutrients such as antioxidants, vitamins, minerals and fibre.

[0067] Prebiotics and Probiotics: For people with RA, probiotics &prebiotics may help regulate the digestive microbiome and reduce inflammation in the digestive tract. They may also affect the immune response, which abnormally attacks the body during an RA flare. Fat free yogurts help for gut health.

[0068] Fish and Omega-3 fatty acids: Eat more oily fish Fish such as sardines, mackerel, herring, fresh tuna, salmon, and snapper have a darker flesh which is rich in omega-3 polyunsaturated fats. In addition to their heart-health benefits, fish oils have been shown to help dampen general inflammation and may help to reduce joint pain and stiffness. Try to eat two portions (1 portion = 140g or a small fillet) of oily fish a week. Some eggs and breads are enriched with omega-3. Omega-3 fats from plant sources (GLA) such as linseed, evening primrose and borage oils have a weaker effect on reducing inflammation and are of limited benefit.

[0069] Fruits, Vegetables and Antioxidants: Antioxidants are phytochemicals, non-nutrient plant compounds present in fruits and vegetables. Their regular consumption has been shown to diminish the symptoms of chronic diseases, including rheumatoid arthritis.

[0070] Antioxidants are found extensively in fruits and vegetables, particularly brightly coloured varieties such as oranges, apricots, mangos, carrots, peppers / capsicums, and tomatoes. The most common antioxidants are vitamins C, E and A. Fruit and vegetables are also low in calories and can help support a healthy diet and weight loss.

[0071] Vitamins and Minerals: • Iron, calcium and vitamin-D deficiencies are very common with RA people. • Foods rich in Iron- Lean meat, eggs, green leafy vegetables, peas, beans, lentils and fortified breakfast cereals • Calcium rich foods- Choose lower-fat varieties of milk, i.e. semi-skimmed or skimmed, as they have the same calcium, If using soya milk or other alternatives, use calcium-enriched products. Yoghurt, cheese, almonds, sardines / pilchards, fortified soy drinks, dark green leafy vegetables, fortified cereal and milk or milk-substitutes.

[0072] Vitamin-D sources - Vitamin D is needed to help the body absorb calcium. Approximately 20% of daily Vitamin D requirement is obtained from the diet; the remaining 80% come from exposure to the sun on the skin. Oily fish, fortified breakfast cereal, fortified margarine are good sources of Vitamin-D.

[0073] Foods to avoid: Red meat- red meat contains high levels of saturated fat, which can exacerbate inflammation and also contribute to obesity. Red meat also contains omega-6 fatty acids, which can contribute to inflammation if your intake is too high.

[0074] Sugar and refined flour: Your blood sugar levels can surge after you've eaten simple carbohydrates that are easily broken down by the body. Such foods include sugary snacks and drinks, white-flour bread and pasta, and white rice. A spike in your blood sugar prompts the body to produce pro-inflammatory chemicals called cytokines, which can worsen your RA symptoms if the inflammation affects your joints.

[0075] Fried Foods: Cutting out fried foods can reduce your levels of inflammation.

[0076] Gluten: A protein found in grains such as wheat, rye, and barley, may contribute to inflammation in some people as every person’s body is different from others.

[0077] Alcohol: Drinking too much alcohol can cause a spike in the body's levels of C-reactive protein, CRP is a powerful signal of inflammation, and the study's findings indicate that overindulgence in alcohol could increase inflammation and be detrimental to RA.

[0078] Processed foods: Processed foods and ready-to-eat meals tend to be loaded with ingredients that cause inflammation.

[0079] Rheumatoid Diet Sample Menu The meal plan includes recipes for breakfast, lunch and dinner for each day of the week which can be prepared at home (Preparation time- 5 to 15 min only) Day Breakfast Lunch Dinner Monday Banana Yogurt Pots Calories - 236, Protein - 14g, Carbs — 32g, Fat “7g, Fiber- 2.6g Cannell ini Bean Salad Calories - 302 Protein -- 20g Carbs - 54g Fat - 0g Fiber- 12.4g Quick Moussaka Calories - 577 Protein - 27g Carbs - 46g Fat - 27g Fiber-3.0g Tuesday Tomato and Watermelon Salad Calories --177 Protein - 5g Carbs - 13g Fat - 13g Fiber-3 g Edgy Veggie Wraps Calories -- 310 Protein - 11g Carbs - 39g Fat - 11g Fiber-6g Spicy Tomato Baked Eggs Calories -- 417 Protein - 19g Carbs - 45g Fat - 17g Fiber-3g Wednesday Blueberry’ Oats Bowl Carrot, Orange and Avocado Salad Salmon with Potatoes and Corn Salad Calories - 235 Protein — 13g Carbs - 38g Fat 4g Fiber-6g Calories - 177 Protein -- 5g Carbs -- 13g Fat — 13g Fiber-6g Calories - 479 Protein -- 43g Carbs -- 27g Fat -- 21g Fiber-3g Thursday Banana Yogurt Pots Calories -- 236, Protein -14g, Carbs - 32g, Fat -- 7g, Fiber-2.6g Mixed Bean Salad Calories - 240 Protein —11g Carbs -- 22g Fat - 12g Fiber-9.3g Spiced Carrot and Lentil Soup Calories - 238 Protein -11g Carbs - 34g Fat --7g Fiber-6g Friday Tomato and Watermelon Salad Panzanella Salad Med Chicken, Quinoa and Greek Salad Calories - 177 Protein - 5g Carbs - 13g Fat - 13g Calories - 452 Protein - 6g Carbs -- 37g Fat - 25g Calories -- 473 Protein --- 36g Carbs - 57g Fat “ 25g Saturday Blueberry Oats Bowl Quinoa and Stir-Fried Veg Grilled Vegetables with Bean Mash Calories - 235 Protein --- 13g Carbs - 38g Fat - 4g Fiber-3 g Calories - 473 Protein - 11g Carbs 56g Fat — 25 g Fiber-8g Calories -- 314 Protein - 19g Carbs - 33g Fat^ 16g Fiber-14g Sunday Berry chia pudding Calories-343 Protein 13.8 Fiber 14.9g Moroccan Chickpea Soup Calories - 408 Protein - 15g Carbs -- 63g Fat -- 11g Fiber-6g Spicy Mediterranean Beet Salad Calories - 548 Protein - 23g Carbs -- 58g Fat - 20g Fiber-11g

Claims

I / We Claim:

1. An Artificial Intelligence (AI) based system (100) for food and nutrient estimation, and meal planning, wherein the system comprises:a server processor (104) coupled with a database (106) in network communication with a plurality of users connected over the said network;wherein, the database (106) stores characteristics that represents physical conditions about the users;wherein, the database (106) coupled with the said server processor (104) includes a diet plan dataset, and an ingredient nutritional information dataset;wherein, the server processor (104) is operable to generate a meal profile for each of the users, wherein each meal profile comprises a plurality of individual characteristics representative of the user's physical condition; andwherein, the system (100) analyses the stored characteristics, and recommended nutritional intake levels to generate at least one meal plan.

2. The system as claimed in claim 1, wherein characteristics that represents physical conditions about the users stored by the said database (106) of the said system (100) includes diagnoses information related to a diagnoses including DNA test results, family health history, BMI along with meal patterns, hunger, sleep patterns, and food habits.

3. The system (100) as claimed in claim 1, wherein the said system (100) is associated with a mobile application that each user communicates, comprises a rule-based valuation to deploy a mean occurrence of nutritive components, leading to a method for regulating the diversity and synchronization of the menus by tracking all primary health parameters, ailments, and / or symptoms.

4. The system (100) as claimed in claim 1, wherein the said system (100) enables the users to input information and / or allow access to health history and all other vital information of current food intake, or any vital information, and details of the nutrition goal for a healthy lifestyle.

5. The system (100) as claimed in claim 1, wherein the said system (100) enables a plurality of healthcare advisors to have seamless access to an online consultation with ability to access a user's primary health report in real-time ensuring designing of a meal plan based on the said rules-based engine using AI.

6. The system (100) as claimed in claim 1, wherein the ingredient nutritional information dataset comprises a plurality of food ingredients and wherein each food ingredient of the plurality is assigned a nutritional value including at least one selected from the group consisting of:a calorific value of the food ingredient, a protein content of the food ingredient, a carbohydrate content of the food ingredient, a fat content of the food ingredient, a mineral content of the food ingredient, a vitamin content of the food ingredient, a sugar content of the food ingredient, a salt content of the food ingredient, and a combination thereof.

7. The system (100) as claimed in claim 1, wherein the user specific characteristics includes food ingredients allergy information for the user, the food ingredients allergy information comprising at least one selected from the group consisting of:a food ingredient allergic for the user, a food ingredient non-allergic for the user and a combination thereof, and wherein the one or more food ingredients to be replaced in the selected diet plan are identified based on the food ingredients allergy information for the user.

8. The system (100) as claimed in claim 1, wherein the user specific characteristics includes food desirability information for the user, the food desirability information for the user comprising at least one selected from the group consisting of: a food ingredient desirable by the user, a food ingredient undesirable by the user and a combination thereof, and wherein the one or more food ingredients to be replaced in the diet plan are identified based on the food desirability information for the user.

9. The system (100) as claimed in claim 1, wherein the user specific characteristics includes health advisor recommendation for the user, the healthcare advisor recommendation for the user comprising at least one selected from the group consisting of:a food ingredient recommended for the user by a healthcare advisor, a food ingredient rejected for the user by the healthcare advisor and a combination thereof, and wherein the one or more food ingredients to be replaced in the selected diet plan are identified based on the healthcare advisor recommendation information for the user.

10. The system (100) as claimed in claim 1, wherein the user specific characteristics includes biographical information of the user and wherein the nutritional requirement of the user is determined based on the biographical information of the user from a reference nutritional requirement dataset, wherein the reference nutritional requirement dataset includes a plurality of nutritional requirements for different persons classified at least according to one of genders of the different persons, ages of the different persons, body weights of the different persons, diagnoses of the different persons, or a combination thereof.

11. An Artificial Intelligence (AI) based method (200) for food and nutrient estimation, and meal planning for a user, wherein the method comprising steps of:receiving user specific characteristics that represents physical conditions stored by a database (106) of a system (100);receiving user specific characteristics from the database (106) coupled with the said server processor (104) includes a diet plan dataset, and an ingredient nutritional information dataset;receiving user specific characteristics from the diet plan dataset includes a set of standard diet plans from a plurality of standard diet plans, wherein each standard diet plan corresponds to one or more diagnoses of a plurality of diagnoses including DNA test results, family health history, BMI along with meal patterns, hunger, sleep patterns, and food habits;receiving user specific characteristics from the ingredient nutritional information dataset, selecting one of the standard diet plans from the set of standard diet plans based on a nutritional requirement of the user, wherein the selected diet plan comprises a set of food ingredients; identifying, in the selected diet plan, one or more food ingredients to be replaced;accessing the said ingredient nutritional information dataset to select one or more alternate food ingredients;selecting the one or more alternate food ingredients from the ingredient nutritional information dataset, wherein a nutritional value of the one or more alternate food ingredients corresponds to a nutritional value of the one or more food ingredients to be replaced from the selected diet plan; andsubstituting, in the selected diet plan, the one or more alternate food ingredients for the one or more food ingredients to be replaced to generate the preferred diet plan for the user.

12. An Artificial Intelligence (AI) based diet meal planner algorithm follows the steps of:receiving user specific characteristics that represent physical conditions;receiving user specific characteristics from the diet plan dataset includes diagnoses including DNA test results, family health history, BMI along with meal patterns, hunger, sleep patterns, and food habits;receiving user specific characteristics from the ingredient nutritional information dataset selecting one of the standard diet plans from the set of standard diet plan;wherein the selected diet plan comprises a set of food ingredients on identification one or more food ingredients to be replaced;receiving raw data like dishes and portions consumed;loading the collected data to pre-trained model for ingredient listing;segregating the words of the dishes by adding the external knowledge;tagging the parts of speech and recognizing the named entity;converting the word to vector form;loading the vector form of word for similarity calculation and ranking; andpre-processing the resultant data by AI precision nutrient analysis model.

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