| Row ID | Full name in Chinese/中文全名 | Full name in English/英文全名 | Gender/性別 | Current Year of Study/目前就讀的年級 |
|---|---|---|---|---|
| 1 | 梁雅俊 | Liang Patrick Yajun | Male/男性 | Grade 11 (Secondary 5)/中學十一年級（中五） |
Many families face daily stress over meal planning due to busy schedules, dietary restrictions, and conflicting preferences, leading to unhealthy takeout choices, nutritional gaps, and family tension. Poor meal habits can contribute to long-term health issues while wasted groceries strain budgets. The AI-powered NutriGenie solves this by generating personalized weekly meal plans in seconds, accounting for allergies, preferences, and pantry items. It ensures balanced nutrition, reduces decision fatigue, and suggests compromise meals to please picky eaters—transforming chaotic dinners into stress-free, healthy family moments.
NutriGenie is an AI-driven meal planning solution that combines machine learning, computational thinking, and smart programming to simplify healthy eating for families. The system uses collaborative filtering algorithms to analyze user preferences and suggest personalized recipes, while natural language processing enables voice-controlled searches like "quick vegetarian dinners." Through computational thinking, it decomposes meal planning into logical steps—filtering dietary restrictions, balancing nutrition, and generating shopping lists—while pattern recognition identifies family eating habits to improve suggestions. Built with Python and scikit-learn, the app integrates recipe APIs for real-time data and employs Firebase for adaptive user profiles, continuously refining recommendations. Optional computer vision allows pantry scans via smartphone, suggesting meals based on available ingredients. By automating meal decisions, NutriGenie reduces planning stress, minimizes food waste, and promotes balanced diets through intelligent technology.
NutriGenie stands out as the optimal solution because it intelligently automates the most frustrating aspects of meal planning while personalizing nutrition for busy families. Unlike generic recipe apps or static meal plans, it combines AI-driven adaptability (learning preferences over time) with real-world practicality (budget-conscious, time-saving options). The system’s computational efficiency ensures lightning-fast recommendations, while its error-proof filtering accommodates allergies and dietary needs—eliminating the stress of manual research. By integrating pantry-scanning tech and voice commands, it bridges the gap between digital convenience and real kitchen needs. Most importantly, it educates families on balanced eating through data-backed insights, fostering long-term health habits. Competing solutions lack this holistic AI-human collaboration, making NutriGenie the smartest, most sustainable choice for modern households.
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