Home / Current Issue / Paper 1712022
AI Powered Drone: An Integrated Hexacopter System for Real-Time Fire Detection and Extinguishing
Subject area: Science,Engineering and Technology · Area of research: AI, Robotics, IoT
DOI: https://doi.org/10.64388/IREV9I5-1712022
Abstract
This research introduces the development of a semi-autonomous hexacopter drone designed for efficient fire detection and suppression, aimed at improving rapid response capabilities in hazardous environments. The system incorporates a Pixhawk flight controller powered by the ArduPilot firmware to achieve stable and precise navigation, alongside a YOLOv8 deep learning framework that enables real-time, vision-based fire recognition. The core advancement lies in the hybrid control architecture, which merges autonomous sensing with a manually triggered extinguishing mechanism, ensuring accurate operation while retaining essential human supervision for safety assurance. Experimental validation confirms the system?s practical functionality, showing consistent flight stability, precise waypoint tracking, and effective fire detection during live testing. The study concludes that this integrated methodology effectively connects AI-enabled detection with physical action, presenting a scalable and efficient approach to enhance industrial safety while minimizing human exposure to danger. Future improvements are directed toward incorporating edge computing for faster onboard processing and conducting extensive real-world trials for performance optimization.
Keywords
AI Drone, Fire Detection, YOLOv8, Pixhawk, Autonomous Systems, Fire Suppression, Hexacopter.
How to cite this paper
@article{1712022,
author = {Sahil Dighe, Sudarshan. A. Jundre, Prof. Omkar Wadne},
title = {AI Powered Drone: An Integrated Hexacopter System for Real-Time Fire Detection and Extinguishing},
journal = {Iconic Research And Engineering Journals},
year = {2025},
volume = {9},
number = {5},
pages = {825-834},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1712022.pdf},
abstract = {This research introduces the development of a semi-autonomous hexacopter drone designed for efficient fire detection and suppression, aimed at improving rapid response capabilities in hazardous environments. The system incorporates a Pixhawk flight controller powered by the ArduPilot firmware to achieve stable and precise navigation, alongside a YOLOv8 deep learning framework that enables real-time, vision-based fire recognition. The core advancement lies in the hybrid control architecture, which merges autonomous sensing with a manually triggered extinguishing mechanism, ensuring accurate operation while retaining essential human supervision for safety assurance. Experimental validation confirms the system?s practical functionality, showing consistent flight stability, precise waypoint tracking, and effective fire detection during live testing. The study concludes that this integrated methodology effectively connects AI-enabled detection with physical action, presenting a scalable and efficient approach to enhance industrial safety while minimizing human exposure to danger. Future improvements are directed toward incorporating edge computing for faster onboard processing and conducting extensive real-world trials for performance optimization.},
keywords = {AI Drone, Fire Detection, YOLOv8, Pixhawk, Autonomous Systems, Fire Suppression, Hexacopter.},
month = {November},
doi = {https://doi.org/10.64388/IREV9I5-1712022}
}