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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM50034
Volume:
9 |
6 |
Jun 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
NutriScope is designed for food product analysis using image recognition and data analytics. It is built with a MERN stack. Users upload the images of food items, and the system processes through the Gemini API for obtaining nutritional information, which includes certain nutrients, possible health risks, and if it’s appropriate for a given age and gender. This enables appropriate dietary choices to be made. NutriScope feature allows users to compare several food products at a time. The system first groups products into high-protein, high- carb, and balanced, using k-means clustering and Chart.js. Nutritional data visualization enables users to see variations in nutrients and determine the most nutritious food product. A history sidebar also enables users to keep track of previous analyses and trends. MongoDB ensures security and stores users’ product analysis history. The application also employs AES encryption for user authentications. Real-time updates, API optimization, image validation, error handling, and user interaction enhance performance. The system can be accessed remotely via a responsive interface. NutriScope serve as an advanced food product analysis platform that enables users to make healthy lifestyle choices using data-driven nutritional decisions.
KEYWORDS
Publication Date
11/5/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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