Abstract
Finding trustworthy halal food information remains challenging for the global Muslim population, projected to reach 2.2 billion by 2030 (Research Nester, 2024). Despite a significant recovery in Muslim travel, reaching approximately 145 million international arrivals in 2023, about 90% of pre-pandemic levels of accessibility to verified halal options remain problematic, particularly in diverse regions. HALALMATE is an AI-powered mobile application addressing this need through three core features: (1) nearby halal restaurant search and validation, (2) personalised food recommendations, and (3) packaged food scanning for instant halal verification. The application integrates Google Maps scraping, OpenAI OCR for menu extraction, Open Food Facts API for product verification, and an AI chatbot for interactive recommendations. Supported by a dynamic halal database and intelligent filtering system, HALALMATE enables users to make accurate, faith-compliant food choices anywhere. This innovation combines AI technology with real-world Muslim community needs, empowering confident halal consumption decisions in the digital era.
Metadata
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Creators: | Creators Email / ID Num. Raihan, Muhammad Daffa UNSPECIFIED Hidayat, Syarif UNSPECIFIED Fudholi, Dhomas Hatta UNSPECIFIED |
| Subjects: | G Geography. Anthropology. Recreation > G Geography (General) > Travel and the state. Tourism T Technology > TX Home economics > Cooking |
| Divisions: | Universiti Teknologi MARA, Perak > Seri Iskandar Campus > Faculty of Architecture, Planning and Surveying |
| Journal or Publication Title: | The 14th international invention, innovation & design competition 2025 (INDES 2025) |
| Event Title: | The 14th international invention, innovation & design competition 2025 (INDES 2025) |
| Event Dates: | 26 Jun 2025 |
| Page Range: | pp. 464-468 |
| Keywords: | Halal food, AI recommendation, Food scanner, Muslim lifestyle, Halal product verification, Smart eating |
| Date: | 2025 |
| URI: | https://ir.uitm.edu.my/id/eprint/133654 |
