Project Report: Meal Planner Website

Overview

Our team developed a simple yet effective meal planning web application that recommends meals based on a user's caloric goals and preferred cuisine. Built using the MERN stack, the platform provides users with personalised meal suggestions from a curated recipe database.

Key Features

Personalised Meal Planning:
Users input their caloric goals (e.g., weight loss, maintenance, or muscle gain).
The system recommends meals matching their required calorie intake.
Cuisine-Based Filtering:
Users can choose from various cuisines (e.g., Mediterranean, Indian, Asian, etc.).
Recipes are fetched from a pre-stored database to match user preferences.
Dynamic Recipe Selection:
The application selects meals from a MongoDB database based on the user's input.
Ensures a variety of meal options while meeting the user's dietary requirements.

Technical Implementation

Frontend: React.js for an intuitive and responsive UI.
Backend: Express.js and Node.js for handling user requests and database queries.
Database: MongoDB for storing and retrieving recipes.
Logic: Basic algorithm to filter recipes based on caloric goals and selected cuisine.

Challenges & Solutions

Balancing Caloric Accuracy:
Used a structured dataset to ensure precise calorie counts for meals.
Efficient Querying:
Optimised database queries for faster recipe retrieval.
Enhancing User Experience:
Designed a clean UI to simplify the meal selection process.

Impact & Future Scope

This meal planner can be expanded with nutritional tracking, allowing users to log their meals and track macronutrient intake.
Future enhancements could include AI-generated meal plans and integration with fitness apps for a more holistic health-tracking experience.