🤖

AgroDrone

Drone
HTML/CSS
Python
C++
Bootstrap
Opencv
YOLO

🛸 AgroDrone: Smart Drone for Farmers

AgroDrone is a smart agricultural drone project developed by a team of IT students. It integrates IoT, C++, and Machine Learning technologies to assist farmers in monitoring crop health and improving agricultural productivity through real-time data analysis and automation.

🚀 Features

  • Drone Callibration: Initial setup and calibration using custom-written code.
  • Object Detection: Identifies objects and obstacles using onboard sensors.
  • Object Avoidance: Automatically avoids obstacles in flight.
  • Auto Take-off: Ensures smooth, automated drone launch.
  • Crop Quality Analysis: Captures footage and analyzes it using a YOLO ML model to assess crop health.

🏆 Achievements

  • 🥇 TechnoPro (State Level) – 1st Consolation
  • 🥇 Punyashlok Ahilyabai Holkar Solapur University (National Level) - 2nd Place

👨‍💻 Team

  • Prof. Abhijit Dongaonkar (Mentor)
  • Jignesh Rana (Myself)
  • Aayush Patel
  • Vedant Kambli
  • Krish Metha
  • Gaurang Waghela

📌 Purpose

AgroDrone was developed to leverage technology for solving real-world agricultural challenges. By combining drone capabilities with AI and IoT, it empowers farmers with a smart tool for crop monitoring and precision farming.

📷 Details and Screenshots in below blackbook

📜 License

This project is part of academic major project at Shri. Bhagubhai Mafatlal Polytechnic.