IoT-Color-Sorting-System

IoT Color Sorting System (Arduino & Node-RED)

Overview

This project implements an IoT-based automatic color sorting system combining embedded systems, automation, and real-time data visualization. The system detects object colors, sorts them automatically using actuators, and displays sorting statistics on a Node-RED dashboard.

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Project Objectives

• Automate object sorting based on color
• Process sensor data in real time using an embedded system
• Control mechanical actuators for physical sorting
• Visualize sorting data through an IoT dashboard
• Study an industrial-oriented supervision solution (PLCnext / Proficloud)

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System Architecture

1. Color detection using a sensor
2. Data processing on Arduino
3. Mechanical actuation for sorting
4. Serial data transmission
5. Real-time visualization via Node-RED

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Hardware Components

• Arduino board
• TCS230 color sensor
• Nema 17HS4401S stepper motor
• DRV8825 stepper motor driver
• Three servo motors
• 2200 µF / 16 V capacitor
• External power supply (12V/2A) and (5V/2A)

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Software & Tools

• Arduino IDE (C/C++)
• Node-RED
• Node-RED Dashboard
• PLCnext Engineer (study)
• Proficloud (study)

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System Operation

Color Detection

The TCS230 sensor measures RGB light intensity using a matrix of photodiodes. The output is a frequency proportional to the detected light intensity.

Data Processing

• RGB frequency measurement
• Noise reduction using averaging
• Dominant color detection
• Object counting per color
• Serial transmission of results

Actuation

• A Nema 17 stepper motor, driven by the DRV8825, ensures object movement
• Servo motors direct objects according to the detected color

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Data Visualization (Node-RED)

Data received from Arduino are processed in Node-RED using:

• serial in
• csv
• change
• gauge

The dashboard displays the number of detected objects for each color in real time.

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Industrial Visualization Study

An industrial visualization architecture was studied using:

• PLCnext
• OPC UA communication
• Proficloud platform

This setup enables real-time industrial-level monitoring of sorting data.

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Challenges Encountered

• Insufficient motor torque, requiring a Nema 17 motor
• Driver incompatibility, leading to the use of DRV8825
• Electrical instability due to an undersized capacitor
• Connection issues between PLCnext and Proficloud

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Conclusion

This project delivers a functional IoT-based color sorting prototype, integrating sensing, processing, actuation, and visualization. It demonstrates practical implementation of embedded systems, automation, and IoT supervision concepts.

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To access the repository of the project