KnowYourBite: AI -Based Nutrition Value Meal Tracker

In today's well-being-conscious era, individuals strive to maintain balanced nutrition and monitor their dietary intake, yet manual tracking methods remain cumbersome and prone to inaccuracies.The proposed Artificial Intelligence Driven AI-Powered Nutrition Evaluation System provides a smart and efficient solution to analyze and evaluate the nutritional composition of food items using artificial intelligence and image recognition.By capturing or uploading a meal image, the framework identifies the food components and estimates their nutritional values, including calories, proteins, carbohydrates, fats, and essential micronutrients.The framework employs Convolutional Neural Networks (CNNs) for image classification and integrates a nutritional database for value computation.It further customizes recommendations based on user-specific conditions such as diabetes, obesity, or deficiencies, assisting in well-beingy decision-making.The AI-driven approach significantly minimizes human error, enhances user engagement, and promotes sustainable well-being monitoring through automation and personalization.

Publication Details

Journal
IJARCCE
Published
2025-09-12
DOI
https://doi.org/10.17148/ijarcce.2025.14937
Primary Topic
Substance Abuse Treatment and Outcomes
Type
article
Field-Weighted Citation Impact
0.00
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article

KnowYourBite: AI -Based Nutrition Value Meal Tracker

IJARCCE
Substance Abuse Treatment and Outcomes
article

KnowYourBite: AI -Based Nutrition Value Meal Tracker

article en

Abstract

In today's well-being-conscious era, individuals strive to maintain balanced nutrition and monitor their dietary intake, yet manual tracking methods remain cumbersome and prone to inaccuracies.The proposed Artificial Intelligence Driven AI-Powered Nutrition Evaluation System provides a smart and efficient solution to analyze and evaluate the nutritional composition of food items using artificial intelligence and image recognition.By capturing or uploading a meal image, the framework identifies the food components and estimates their nutritional values, including calories, proteins, carbohydrates, fats, and essential micronutrients.The framework employs Convolutional Neural Networks (CNNs) for image classification and integrates a nutritional database for value computation.It further customizes recommendations based on user-specific conditions such as diabetes, obesity, or deficiencies, assisting in well-beingy decision-making.The AI-driven approach significantly minimizes human error, enhances user engagement, and promotes sustainable well-being monitoring through automation and personalization.

IJARCCEVol. 14(9)
Zero hunger
Openalex Percentile: Top 37%
Substance Abuse Treatment and Outcomes
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