UseFresh

UseFresh is a web application that helps users keep track of food in their pantry, reduce food waste, and utilize ingredients before they expire. The application is a combination of expiration monitoring, inventory tracking, recipe suggestions, and AI-assisted camera scanner in one place.

Purpose

The purpose of UseFresh is to help users:

• Keep an organized record of the food items they have in their pantry
• Reduce unnecessary grocery waste
• See which items are expired or soon to be expired
• Have assistance in meal decision based on the ingredients already available
• Automate food entry with camera-based scanning tool

Features

User Account

• Create a new account with username, email, and password
• Log in with either username/email and password
• Store the logged in user's ID so food items can be associated with the correct logged in user

Food Inventory Management

• Add food items with a name, quantity, and expiration date
• View saved food items
• Edit food items
• Delete food items
• Search through food items in inventory

Expired Tracking

• Calculate how many days remain before an item expires
• Color code food items based on their expiration date
• Show recently added items on the home page
• Show soon to be expired and expired items on the home page

AI-Assisted Features

• Generate recipe ideas from first soon to be expired items and overall food items saved in the database
• Open the device camera from the View Items page
• Scan the product labels to detect the product name
• Scan the expiration date labels to detect the expiration of the product
• Save the scanned item information into the food inventory after completing the scan

Authentication and Security

• Passwords are hashed in the backend before being stored
• Input validation is included for user account creation, login, and food item entry

Tech Stack

Frontend

• React 19
• Vite (build tool)
• React Router DOM (routing)
• Axios (HTTP client)
• Bootstrap (styling)

Backend

• Node.js
• Express.js
• MongoDB with Mongoose
• bcrypt (password hashing)
• Nodemailer (email functionality)
• dotenv
• CORS

AI Component

• Node.js
• Express.js
• Hugging Face Inference API
• Multer (file uploads)
• MongoDB

UI Overview

Login Page

Figure 1: User authentication screen with login form

Home Dashboard

Figure 2: Main dashboard showing food inventory and quick actions

View Items

Figure 3: Main area showing color coded food inventory table and editing actions

Add Food Item

Figure 4: Form for manually adding food items with expiration dates

Camera Scanner

Figure 5: Camera interface for scanning food product labels

Recipe Suggestions

Figure 6: AI-generated recipe suggestions based on expiring ingredients

Saved Recipes

Figure 7: Collection of user-saved favorite recipes

Project Status

The project supports user account creation, login, password reset, food tracking, adding, editing, and deleting items, recipe suggestions, and camera based scanning.

Prerequisites

• Node.js (v16 or higher)
• MongoDB database
• Hugging Face account and API token

Installation

1. Clone the repository

   git clone <repository-url>
   cd UseFresh

2. Install root dependencies

   npm install

3. Set up the backend

   cd backend
   npm install

4. Set up the frontend

   cd ../frontend
   npm install

5. Set up the AI component

   cd ../AI_component
   npm install
   pip install -r requirements.txt  # If Python dependencies are needed

Project Structure

UseFresh/

|--frontend/ (React)

|--backend/ (Express +MongoDB)

|--AI_component/ (HuggingFace)

|--README.md

Environment Variables

Create .env files in the following directories:

Backend (.env)

MONGO_URI=mongodb://localhost:27017/usefresh
PORT=3001
# Add other environment variables as needed (e.g., email service credentials)

AI Component (.env)

MONGO_URI=mongodb://localhost:27017/usefresh
HF_TOKEN=your_hugging_face_api_token

Running the Application

1. Start MongoDB (ensure it's running on your system)

2. Start the AI Component (in a separate terminal)

   cd AI_component
   node Scanserver.js

   The AI service will run on http://localhost:5000

3. Start the Backend (in a separate terminal)

   cd backend
   npm start

   The backend API will run on http://localhost:3001

4. Start the Frontend (in a separate terminal)

   cd frontend
   npm run dev

   The frontend will run on http://localhost:5173 (or similar Vite default port)

Usage

1. Register/Login: Create an account or log in with existing credentials
2. Add Food Items:
   • Manually enter food items with expiration dates and quantities
   • Use the camera scanner to scan product packaging
3. View Inventory: See all your food items organized by expiration date
4. Generate Recipes: Get AI-suggested recipes for breakfast, lunch, or dinner using your expiring ingredients
5. Save Recipes: Keep track of your favorite recipes for later

API Endpoints (Backend)

User Routes

• POST /api/user/register - User registration
• POST /api/user/login - User login
• POST /api/user/forgot-password - Password reset request
• POST /api/user/reset-password - Password reset

Food Routes

• GET /api/foods/all - Get all user's food items
• POST /api/foods/add - Add new food item
• PUT /api/foods/update/:id - Update food item
• DELETE /api/foods/delete/:id - Delete food item

Recipe Routes

• POST /api/recipes/generate - Generate recipe suggestions
• GET /api/recipes/saved - Get saved recipes
• POST /api/recipes/save - Save a recipe
• DELETE /api/recipes/delete/:id - Delete saved recipe

AI Component

• POST /suggest-recipes - Get recipe suggestions based on expiring food

Main Routes (FRONTEND)

• /login : the user login

• /register: the user account creation

• /home: the dashboard that shows food insights

• /items: inventory page with add, edit, delete, search, scan, and filter tools

• /forgot_password: password reset request page

• /reset_password/:token: password reset page

Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

License

This project is licensed under the ISC License.

Acknowledgments

• Built as part of WSU-4110 course project
• Uses Hugging Face for AI-powered recipe suggestions

Contributors

• Natalia Dycha
• Hamsini Gupta
• Gloria Llakmani
• Sanika Annadate
• Zainab Bazoun