🍽️ Cafelytics – AI-Powered Smart Meal Recommendation & Canteen Analytics

An intelligent canteen management platform that leverages Machine Learning to generate personalized, budget-friendly meal recommendations while providing data-driven analytics for smarter food planning and inventory management.

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📸 Project Preview

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📖 Overview

Cafelytics is an AI-powered smart canteen management platform developed using Django, Machine Learning, and Data Analytics. The system recommends affordable meal combinations based on a user's budget, dietary preference (Veg/Non-Veg), and meal type, while helping administrators analyze food demand and customer preferences.

Unlike traditional canteen systems that only handle ordering, Cafelytics integrates a Random Forest-based recommendation engine to generate intelligent meal combinations and improve decision-making using real-world data.

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🎯 Problem Statement

Traditional canteen management systems primarily focus on billing and order management. They lack:

• Personalized meal recommendations
• Budget-aware suggestions
• Demand analytics
• Customer preference tracking
• Data-driven decision making

Cafelytics addresses these challenges by combining Machine Learning with a modern web application to improve both the student experience and canteen operations.

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🌐 Live Demo

🚀 Deployment in progress.

The application will be hosted on Render.

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✨ Features

👨‍🎓 Student Module

• Secure User Registration & Login
• Budget-Based Meal Recommendation
• Veg / Non-Veg Filtering
• Meal Type Selection
• AI-Generated Meal Combos
• Order Placement
• Dynamic Preference Updates

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👨‍💼 Admin Module

• Manage Menu Items
• Monitor Student Preferences
• Analyze Food Demand
• Track Ordering Trends
• Update Meal Data

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🤖 AI Features

• Random Forest-based Recommendation Engine
• Preference Score Prediction
• Budget Optimization
• Personalized Meal Recommendations
• Dynamic Recommendation Generation
• Continuous Learning through User Orders

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🧠 Machine Learning Workflow

Excel Dataset
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        ▼
Data Cleaning & Preprocessing
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Feature Engineering
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Random Forest Model
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Preference Score Prediction
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Budget-Aware Recommendation Engine
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Smart Meal Combination Generation

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🏗️ System Architecture

                 Student
                    │
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         Django Web Application
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        Recommendation Engine
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      Random Forest ML Model
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            SQLite Database
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 Personalized Meal Recommendations

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🛠️ Tech Stack

Category	Technologies
Backend	Django 5
Programming Language	Python 3.10
Machine Learning	Scikit-Learn (Random Forest)
Data Processing	Pandas, NumPy
Database	SQLite
Frontend	HTML5, CSS3, Bootstrap, JavaScript
Data Source	Excel (.xlsx)
Deployment	Render (Planned)

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📂 Project Structure

cafelytics/
│
├── cafelytics_proj/
├── canteen_app/
├── data/
├── Screenshots/
├── staticfiles/
├── build.sh
├── db.sqlite3
├── manage.py
├── requirements.txt
├── runtime.txt
├── render.yaml
└── README.md

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📊 Dataset

The recommendation engine is trained using a structured dataset containing:

• Food Item
• Category
• Price
• Meal Type
• Availability
• Preference Score

The dataset is utilized for:

• Meal Recommendation
• Preference Score Prediction
• Demand Analytics
• Budget Optimization
• Combo Generation

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📈 Results

• Successfully integrated Machine Learning into a Django web application.
• Generates personalized meal combinations based on user preferences.
• Supports budget-aware recommendations.
• Dynamically updates preference scores after each order.
• Provides meaningful analytics for canteen management.

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📸 Application Screenshots

🏠 Home Page

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🔐 Login Page

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🍽️ AI Meal Recommendation

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✅ Input Validation

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🚀 Installation

Clone the repository

git clone https://github.com/Arpithasingh10/Cafelytics.git

Move into the project directory

cd Cafelytics

Install dependencies

pip install -r requirements.txt

Run database migrations

python manage.py migrate

Start the development server

python manage.py runserver

Visit

http://127.0.0.1:8000/

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🚀 Roadmap

Future improvements include:

• AI Chatbot for Food Suggestions
• QR Code Ordering
• Online Payment Gateway
• Cloud Database Integration
• Inventory Prediction
• Sales Forecasting
• Personalized User Profiles
• Admin Analytics Dashboard
• Real-Time Recommendation Updates

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⭐ Project Highlights

• 🤖 AI-Powered Recommendation Engine
• 🍽️ Smart Meal Combination Generator
• 💰 Budget-Aware Meal Optimization
• 📊 Data-Driven Canteen Analytics
• 📈 Preference Score Prediction
• 🧠 Machine Learning Integration
• 🌐 Full-Stack Django Web Application
• 🗄️ SQLite Database Integration

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📌 Project Status

✅ Completed

This project was developed as part of an Artificial Intelligence & Machine Learning academic initiative to demonstrate the practical application of Machine Learning in smart canteen management.

Deployment and future enhancements are planned.

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👩‍💻 Developer

Arpitha Singh

B.Tech – Artificial Intelligence & Machine Learning

GitHub: https://github.com/Arpithasingh10

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⭐ Support

If you found this project interesting, consider giving it a ⭐ on GitHub.

It helps others discover the project and motivates future improvements.