IoT Edge Intelligence

Organic vs Synthetic Produce AI

Edge AI system classifying produce in real-time using spectral sensor fusion and embedded ML models.

Domain Agriculture
Tech Stack Edge Impulse / TFLite
Organic vs Synthetic Produce AI

Chemical Integrity Automation

Distinguishing organic apples from chemically treated ones on an industrial conveyor belt manually is impossible. We created a spectrometer-driven ML sensor.

Spectral Analysis

Uses non-visible light spectrum scattering to determine chemical coating.

MCU Embedded

Model runs entirely on an ARM Cortex M4 microcontroller.

Offline Independence

No cloud connectivity required for classification.

Technical Strategy

Instead of large image arrays, we relied on high-frequency 1D spectral data to drastically improve processing time.

1
1D CNN Architecture

Designed a custom 1D Convolutional Neural Network specifically to analyze spectral wavelength peaks.

2
Edge Impulse Integration

Utilized the Edge Impulse studio to rapidly prototype and compile the C++ firmware package.

3
Automated Sorting Gate

Wired the GPIO outputs from the MCU directly to a pneumatic arm, physically sorting products in under 12 milliseconds.

98.4%
Classification Accuracy
12ms
Reaction Time
12+
Materials Detected
RTOS
Operating System

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