Current Volume 9
NUTRISCAN: An AI-Powered Smart Food Scanner for Real-Time Nutrition Analysis Using Deep Learning
Abstract
NutriScan is an AI-powered food recognition and nutrition analysis system developed to automate calorie and nutrient estimation from food images. The system leverages a Convolutional Neural Network (CNN) model for accurate food classification and retrieves nutritional values including calories, proteins, fats, and carbohydrates in real time. The platform is built using a React and Tailwind CSS frontend for a responsive user interface, while Firebase cloud services handle authentication, real-time data storage, and cloud hosting. The system eliminates common errors arising from manual dietary entry and provides users with an analytics dashboard that visualizes daily intake and dietary trends to support informed decision-making. NutriScan demonstrates the practical integration of deep learning and cloud infrastructure to promote healthier lifestyle choices. Future enhancements include portion size detection via image segmentation and personalized meal recommendation engines.
Keywords
Convolutional Neural Network, Deep Learning, Firebase, Food Recognition, Nutrition Analysis, React.js.
Citations
IRE Journals:
S. Jothirharishh, G. Karthick, M. Harshavardhan, A. Jagadeeswaran "NUTRISCAN: An AI-Powered Smart Food Scanner for Real-Time Nutrition Analysis Using Deep Learning" Iconic Research And Engineering Journals Volume 9 Issue 11 2026 Page 1025-1031 https://doi.org/10.64388/IREV9I11-1717331
IEEE:
S. Jothirharishh, G. Karthick, M. Harshavardhan, A. Jagadeeswaran
"NUTRISCAN: An AI-Powered Smart Food Scanner for Real-Time Nutrition Analysis Using Deep Learning" Iconic Research And Engineering Journals, 9(11) https://doi.org/10.64388/IREV9I11-1717331
About IRE Journals
IRE Journals is an open access online journals established with an aim to publish high quality of research work in various diciplines. We have more than 6 years in publications. Over 2500+ papers already published.
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