Table of Contents
Meal-Match is a personalized recipe recommendation app that simplifies meal planning by considering users' available ingredients, dietary preferences, and nutritional goals. It utilizes ML models to provide customized recipe suggestions while integrating features like grocery shopping assistance and ingredient recognition. The app aims to minimize food waste and promote healthier eating habits. Meal-Match also supports multiple dietary plans, helping users maintain their nutritional goals while exploring new and exciting recipes. The app also features a collection feature that allows users to save their favorite meals for quick access, as well as a meal planner feature that enables users to schedule meal plans and receive timely notifications.
Features:
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Ingredient-Based Recipe Search – Users can input available ingredients, and the app suggests recipes accordingly.
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Grocery Shopping Assistance – Generates shopping lists and integrates with grocery delivery services.
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Personalized Recipe Recommendations – Machine learning models suggest meals based on user preferences and previous interactions.
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Meal Collection Feature – Allows users to save their favorite meals for quick access.
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Meal Planner & Notifications – Users can schedule meal plans and receive timely reminders.
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Audio recognition- the user can tell about the ingredients present and the recipes will be generated
- Dart
- Flutter
- Flutter Plugins
- cupertino_icons
- firebase_core
- firebase_auth
- cloud_firestore
- Firebase
- FIirebase
- Python
- Numpy
- Pandas
- Streamlit
- Sklearn
- K-nearest neighbors
Fully Implemented features-
- Ingredient-Based Recipe Search
- Grocery Shopping Assistance
- Audio recognition for ingredients
- Personalized Recipe Recommendations
- Pantry feature
- Meal Collection Feature
- Meal Planner & Notifications
Partially Implemented features-
- The camera feature to scan and add items
- Directing shopping list using shopping API
- Dietary Preference Support – Filters recipes based on dietary restrictions (vegan, gluten-free, nut allergies, etc.).
- Smart Image Recognition – Scan pantry items to identify and add ingredients to the database.
- Shopping API call - The pantry will direct the user to the shopping apps where the user can simply check out.
Meal-Match simplifies meal planning for users by offering intelligent recipe recommendations based on available ingredients and dietary needs. The app helps:
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Home cooks find recipes with what they have.
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Individuals with dietary restrictions get suitable meal options.
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Health-conscious users track their nutritional intake.
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Users reduce food waste by optimizing ingredient usage.
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The app also aims to enhance convenience by integrating grocery shopping features, enabling users to purchase missing ingredients directly.
To setup the app, you must first need an IDE, like android studio or VScode, which is capable of running dart code. You must also have a firebase account setup, if you want to access the database directly. After that download the libraries mentioned in the tech stack for AI/Ml to ensure that the model runs Then you can just clone the repository.
To setup the app, you must first need an IDE, like android studio or VScode, which is capable of running dart code. You must also have a firebase account setup, if you want to access the database directly. After that download the libraries mentioned in the tech stack for AI/Ml to ensure that the model runs Then you can just clone the repository.
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