🔍 NutriDetect – AI Powered Food Quality & Nutrition Detection System

NutriDetect is an AI + IoT based smart system Hardware part is currently under development to analyze:

• Fruit/Vegetable type
• Freshness level
• Organic vs Inorganic status
• Nutrition insights

The goal of this project is to use hardware sensors and machine learning models to provide real-time food quality analysis for consumers and businesses.

⚠ Note: Hardware integration and real-time sensing phase is in progress.

Features (Planned & In Progress)

• Image based food detection
• Analysis by using Gas Sensor/Spectroscopy sensor
• Ethylene gas freshness detection
• ESP32 real-time data collection
• Web dashboard for results

Tech Stack

Hardware (Planned)

• ESP32
• Spectroscopy Sensor/Gas Sensor
• Ethylene Gas Sensor
• OLED Display

Software (Developed)

• Python
• TensorFlow
• OpenCV
• HTML, CSS, JavaScript
• Flask / FastAPI

How It Will Work

1. User will place fruit/vegetable near sensors.
2. Sensors will capture spectral & gas data.
3. Data will be sent to ML model.
4. Model will predict quality & nutrition.
5. Results will be displayed on dashboard.

Use Cases

• Smart grocery stores
• Farmer quality check
• Food safety labs
• Health & nutrition applications

Project Status

• Phase 1: System design & architecture ✅
• Phase 2: Hardware integration ⏳ (ongoing)
• Phase 3: ML model training ⏳ (planned)
• Phase 4: Web & mobile dashboard ⏳ (planned)

Developed By

Mohammed Sameer
BCA Student | AI + IoT Enthusiast

License

MIT License