AI-powered personalized allergen detection and recipe modification tool for safer meal preparation

Nithiyananthan, Preevitha and Kurk, Wei Yi and Kasmuri, Emaliana and Nuruddin, Fadhlan Faizal (2025) AI-powered personalized allergen detection and recipe modification tool for safer meal preparation. International Journal of Research and Innovation in Social Science (IJRISS), IX (X). pp. 6788-6800. ISSN 2454-6186

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Abstract

The AI-Powered Personalized Allergen Detection and Recipe Modification Tool is a mobile application developed to assist individuals with food allergies helping them identifying harmful ingredients in recipes and offer safer alternatives tailored to their personal allergen profiles. Food allergy is a serious health concern that can lead to life-threatening reactions if not managed properly, especially when consuming meals with unfamiliar ingredients. This tool uses artificial intelligence (AI) and natural language processing (NLP) to analyse the textual format recipes specified by users and intelligently detect the presence of any allergen substances. Once allergens are identified, the tool accesses a built-in database integrated with machine learning/large language model to suggest appropriate and non-allergenic substitutes, allowing the users to prepare and modified a safer recipe. The tool includes features such as creating, editing, sharing, favouriting, and deleting recipes, along with user account settings that support allergen input and password management. With a focus on 90% accuracy rate in allergen detection and 44% substituion relecance score, the app ensures both speed and reliability. The tool was developed specifically for Android platform and intended for online use has provide an intuitive and userfriendly interface designed for convenience and efficiency. The tool helps users to make informed decisions about the ingredients and substitutions and early user feedback indicates improved confidence in meal preparation.

Item Type:	Article
Uncontrolled Keywords:	Food allergy, Allergen detection, Recipe modification, Artificial intelligence (AI), Mobile health Application
Divisions:	Faculty of Information and Communication Technology
Depositing User:	Sabariah Ismail
Date Deposited:	03 Feb 2026 06:50
Last Modified:	03 Feb 2026 06:50
URI:	http://eprints.utem.edu.my/id/eprint/29466
Statistic Details:	View Download Statistic

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