Research Article
Nutrition Management System
@INPROCEEDINGS{10.4108/eai.1-5-2025.2361391, author={Diya Bino and Gourinanda G and Hanna Eldho and Meera Santhosh}, title={Nutrition Management System}, proceedings={Proceedings of the 7th MEC Student Research Conference on Artificial Intelligence and Cyber Security, MECSRC 2025, 01 May 2025, Muscat, Oman}, publisher={EAI}, proceedings_a={MECSRC}, year={2026}, month={3}, keywords={nutrition management machine learning decision tree algorithm health report analysis optical character recognition (ocr) allergy-based filtering personalized meal recommendations}, doi={10.4108/eai.1-5-2025.2361391} }- Diya Bino
Gourinanda G
Hanna Eldho
Meera Santhosh
Year: 2026
Nutrition Management System
MECSRC
EAI
DOI: 10.4108/eai.1-5-2025.2361391
Abstract
WHO recognizes the increase in various non-communicable diseases in today's world that people face, such as type 2 diabetes, digestive diseases, kidney diseases, weight management, and blood diseases, due to the inability to maintain a healthy diet. Owing to various factors like lack of nutritional knowledge, busy lifestyles, lack of motivation, easy access to fast food, or preferability over healthy food. The Nutrition Management System is a website designed to recommend personalized meals based on their health conditions. This system prompts users to upload their health reports, from which key values are extracted using Optical Character Recognition process and appropriate meals are recommended using machine learning algorithms. The Decision Tree machine learning algorithm has been selected due to simplicity, efficiency, and suitability in healthcare applications. The objective is to inculcate healthy eating habits, decrease ailments caused due to lifestyle and help individuals improve their health and wellbeing.
