Abstract :

The Detrimental Ingredient Detection System (DIDS) Is An Innovative Software Solution Designed To Help Users Identify Harmful Ingredients Present In Food Items And Cosmetic Products. In Today’s Market, Product Labels Often Contain Complex Chemical Names That Are Difficult For Consumers To Understand, Leading To Unintentional Exposure To Potentially Dangerous Substances. This System Addresses The Problem By Providing A Simple, Efficient, And Intelligent Method For Analyzing Ingredient Lists. Users Can Input Data Through Multiple Methods, Including Uploading Images Of Product Labels, Scanning Barcodes, Or Manually Entering Ingredient Details. The System Utilizes Optical Character Recognition (OCR) Technology, Supported By LSTM-based Models, To Accurately Extract Text From Images. The Extracted Ingredients Are Then Analyzed Using Machine Learning Techniques Such As The Multinomial Naive Bayes Algorithm, Which Classifies Each Ingredient As Safe, Harmful, Or Requiring Caution Based On A Predefined And Continuously Updated Database. The System Highlights Harmful Or Allergenic Substances, Provides Detailed Information About Their Potential Health Effects, And Suggests Safer Alternatives To Guide Users Toward Better Choices. Additionally, It Generates Comprehensive Reports That Can Be Saved Or Shared For Future Reference. With Its User-friendly Interface, High Accuracy, And Real-time Processing Capabilities, The Detrimental Ingredient Detection System Aims To Bridge The Gap Between Product Information And Consumer Awareness. Ultimately, It Empowers Users To Make Informed Decisions, Promotes Healthier Lifestyles, And Contributes To Increased Transparency And Safety In The Food And Cosmetic Industries

Published:

07-4-2026

Issue:

Vol. 26 No. 4 (2026)

Page Nos:

1582-1588

Section:

Articles

License:

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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