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  System Overview

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  System Interface Overview

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  System Hardware Overview

🌱 Smart Farming Solution using Arduino & HOG

🎥 Project Demo

Click the thumbnail above to watch the full capstone demo on YouTube.

📌 Project Overview

This capstone project explores how IoT and computer vision can transform agriculture.
By combining Arduino-based automation with Histogram Oriented Gradients (HOG) for leaf health detection, the system delivers a cost‑effective smart farming solution that improves yield, saves water, and simplifies monitoring.

🎨 Tech Stack

🎯 Problem Statement

• Climate shifts and poor fertilization reduce crop yield.
  
• Manual farming practices are inefficient and resource‑intensive.

🎯 Objectives

• Study current smart farming technologies.
  
• Build a real‑time automated irrigation system.
  
• Analyze leaf health using HOG image processing.
  
• Generate reports for farmers and stakeholders.

🛠️ System Functions

• 🌿 Automated Irrigation using soil moisture sensors.
  
• 💧 Real‑time Soil Monitoring for water efficiency.
  
• 🍃 Leaf Health Detection with HOG computer vision.
  
• 📊 Report Generation for actionable insights.

📖 Conclusion

This project demonstrates how automation + machine learning algortithms can address agricultural challenges.
The solution is scalable, sustainable, and adaptable for farmers seeking smarter resource management.

🏫 Academic Context

• Author: Krisha A/P Nandakumar
• Diploma in Computer Science
  

- Presented at ICANDIT 2025, Indonesia

Built With

• html
• iot
• python