AI-Powered Research Platform

FoodSense AI Sensor

Development of a smart chemical sensor sticker for visual detection of food spoilage integrated with artificial intelligence.

Capture an image of the chemical sensor using your phone camera or upload an image. Our CNN model analyzes the sensor color change and predicts the spoilage level instantly.

Sensor Analysis
Real-time classification
Fresh 92.4%
Safe 5.1%
Warning 1.8%
Spoiled 0.7%

How It Works

Three simple steps from sensor image capture to AI-powered spoilage prediction.

1
Capture Sensor Image

Use your mobile phone camera to capture the chemical sensor sticker, or upload an existing image from your device.

2
AI Color Analysis

Our CNN model (MobileNetV2) analyzes the sensor's color change pattern caused by gases produced during food decomposition.

3
Spoilage Prediction

Receive instant classification results — Fresh, Safe, Warning, or Spoiled — with confidence scores and detailed probability analysis.

Platform Features

Professional scientific research tools

Mobile Camera

Direct camera capture from any mobile device with real-time preview.

Image Upload

Upload sensor images in any common format (JPG, PNG, WebP, BMP).

CNN Classification

MobileNetV2 deep learning model with transfer learning for accurate results.

Research Dashboard

Professional analytics, prediction history, and data visualization.

Spoilage Classification

Four-level food freshness assessment

🟢
Fresh

No spoilage detected. Food is safe for consumption.

🔵
Safe

Still safe but minor early changes detected. Consume soon.

🟡
Warning

Early spoilage indicators present. Exercise caution.

🔴
Spoiled

Significant decomposition. Do not consume.

Technology Stack

Built with modern, production-grade technologies

Python
Flask
TensorFlow
PostgreSQL
Bootstrap 5
Chart.js
Docker
Gunicorn

Ready to Analyze?

Start using the FoodSense AI platform to detect food spoilage with our smart chemical sensor and machine learning technology.

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