Food Waste Detection System using AI & Computer Vision 
Excited to share one of the projects I recently worked on — a Food Waste Detection System designed to identify whether food is fresh or rotten using AI and Computer Vision techniques.
Project Objective
The main goal of this project was to develop a smart solution that can help in:
• Detecting rotten and fresh food items
• Reducing food wastage
• Improving food quality monitoring
• Supporting smart waste management
• Providing quick and accurate food condition analysis
Dataset Collection & Processing
For this project, datasets containing images of fresh and rotten food items were collected and processed. Different food images were analyzed under various conditions to improve detection accuracy and model performance.
Model Development
The system was developed using:
• Python
• Flask
• Pandas
• Plotly
• Scikit-learn
The trained model scans food images and predicts whether the food item is:
Fresh
Rotten
The system also provides data visualization and analysis through an interactive dashboard.
Key Features
• Real-time food scanning and detection
• Fresh vs Rotten food classification
• Interactive dashboard and reports
• Data visualization and analysis
• User-friendly web interface
Key Learnings
Through this project, I gained hands-on experience in:
Computer Vision
Machine Learning Basics
Python & Flask Development
Data Analysis & Visualization
Dataset Processing & Model Training
Problem Solving & Team Collaboration
Special thanks to my mentors, faculty members, and teammates for their valuable guidance and support throughout the project development process.
This project helped me understand how AI and technology can be used to solve real-world problems related to food wastage and sustainability 
Video Demonstration-food waste detection – Google Drive