Sustainable Nutrition Recommendation System Smart Meal Planning for a Better Future

A full‑stack web application integrating nutritional analysis, CO₂e sustainability indicators, pantry‑aware ingredient reuse and expiry‑date prioritisation into a transparent rule‑based recommendation framework for UK university students.

BSc (Hons) Computing Dissertation · Arden University · 2026

Watch Demo System Overview

Built with React.js · Spring Boot · MySQL · Python

Demo

System Demonstration

A walkthrough of weekly meal planning, pantry-aware prioritisation, sustainability indicators, recommendation explainability and dynamic pantry deduction.

Project Overview

Purpose & Contribution

A concise summary of the artefact’s purpose and academic contribution.

The Sustainable Nutrition Recommendation System is a full-stack web application developed to support healthier and more sustainable meal-planning behaviour for UK university students. The framework combines nutritional analysis, environmental sustainability indicators, pantry management and food-waste reduction within a transparent rule-based recommendation system implemented using React.js, Spring Boot, MySQL and Python preprocessing.

Key Features

Designed for Real Student Needs

Core functionality implemented in the artefact.

Weekly Meal Planning

Generate structured breakfast, lunch and dinner plans.

Nutrition‑Aware Scoring

Supports balanced meal selection using nutritional indicators.

CO₂e Sustainability Labels

Displays environmental impact indicators for each recipe.

Pantry Management

Track ingredient quantities, expiry dates and availability.

Expiry‑Aware Prioritisation

Prioritise near‑expiry ingredients to reduce waste.

Dynamic Pantry Deduction

Automatically deduct ingredients when meals are cooked.

System Architecture

Full-Stack Implementation

Overview of the layered architecture, preprocessing workflow, relational database structure and transparent recommendation logic.

The artefact follows a layered architecture where Python preprocessing prepares nutritional, recipe and sustainability datasets, MySQL analytical views support recommendation processing, Spring Boot exposes REST APIs, and the React frontend presents recommendation results through an interactive user interface.

Python Preprocessing
        ↓
MySQL Relational Database
        ↓
SQL Analytical Views
        ↓
Spring Boot REST APIs
        ↓
React Frontend Interface

Overall system architecture — Layered architecture showing Python preprocessing, MySQL integration, Spring Boot APIs and React frontend interaction.

Python preprocessing pipeline — Python preprocessing workflow for nutritional, recipe and sustainability dataset integration.

Database ERD — MySQL relational schema linking recipes, ingredients, nutrition, sustainability and pantry data.

Recommendation decision logic — Transparent rule-based recommendation logic combining nutrition, CO₂e impact, pantry reuse and expiry-aware prioritisation.

Interface

Screenshots

Visual overview of the working artefact.

Dashboard with sustainability and nutrition indicators — Dashboard displaying nutritional scores, sustainability indicators and pantry statistics.

Weekly meal planner and recommendation indicators — Weekly meal planner integrating nutritional indicators, CO₂e sustainability labels and pantry-aware recommendations.

Pantry management with expiry-date tracking — Pantry management interface with ingredient quantities, expiry-date monitoring and waste-risk classification.

Live Deployment

Live Application Access

Public access to the deployed dissertation artefact.

The Sustainable Nutrition Recommendation System is available as a live web application for demonstration and evaluation purposes. The deployed artefact includes the React frontend, Spring Boot backend and integrated MySQL database used throughout the implementation and evaluation of the project.

Launch Live Application

Access the deployed artefact and explore the dashboard, recommendation engine, weekly meal planner, pantry management functionality and sustainability-aware decision support features.

Open Live Application

Demonstration Notes

The application is hosted using free cloud services. If the backend has been inactive, the first request may require up to 60 seconds while the service wakes up.

The deployment uses a shared demonstration database; therefore pantry quantities, recommendation outputs and planning statistics may vary as the system is tested by different users.

Contact

Repository Access

The complete implementation repository contains the React frontend, Spring Boot backend, MySQL database scripts and Python preprocessing pipeline developed for this project.

Repository access can be provided upon request.

Request Repository Access