Real-Time Early Detection of Forest Fires Using Various YOLO11 Architectures

Sarvesh S Sanikop, Anoop Kadakol, Md Sami A Ghori, Prithvi M Ganiger, Uday Kulkarni, Shashank Hegde

2025

Abstract

Forest fires are an important environmental hazard threatening biodiversity, ecosystems, and human safety. Early and accurate detection is critical for minimizing damage and ensuring timely intervention. This proposed work leverages the YOLO11 architecture to create a robust and efficient forest fire detection framework. The proposed approach achieves superior detection performance under diverse environmental conditions by introducing advanced modules such as C3K2, SPFF, and C2PSA, and leveraging transfer learning. The framework is trained on a heterogeneous dataset combining satellite, drone, and ground-level imagery, capturing a wide spectrum of forest fire scenarios across varying terrains and lighting conditions. The inclusion of data augmentation techniques enhances model generalization to unseen fire patterns. The results indicate that YOLO11-M achieves the best trade-off between precision (85.3%) and recall (81.1%), with a mean average precision (mAP @ 50) of (84. 9%), while YOLO11-N offers high computational efficiency for deployment in resource-constrained environments such as edge devices. Furthermore, the integration of real-time detection capabilities enables rapid response to forest fire outbreaks, making this framework a valuable tool for disaster prevention, ecological preservation, and safeguarding human lives.

Paper Citation

in Harvard Style

Sanikop S., Kadakol A., Ghori M., Ganiger P., Kulkarni U. and Hegde S. (2025). Real-Time Early Detection of Forest Fires Using Various YOLO11 Architectures. In Proceedings of the 3rd International Conference on Futuristic Technology - Volume 2: INCOFT; ISBN 978-989-758-763-4, SciTePress, pages 747-753. DOI: 10.5220/0013601200004664

in Bibtex Style

@conference{incoft25,
author={Sarvesh Sanikop and Anoop Kadakol and Md Sami Ghori and Prithvi Ganiger and Uday Kulkarni and Shashank Hegde},
title={Real-Time Early Detection of Forest Fires Using Various YOLO11 Architectures},
booktitle={Proceedings of the 3rd International Conference on Futuristic Technology - Volume 2: INCOFT},
year={2025},
pages={747-753},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013601200004664},
isbn={978-989-758-763-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Futuristic Technology - Volume 2: INCOFT
TI - Real-Time Early Detection of Forest Fires Using Various YOLO11 Architectures
SN - 978-989-758-763-4
AU - Sanikop S.
AU - Kadakol A.
AU - Ghori M.
AU - Ganiger P.
AU - Kulkarni U.
AU - Hegde S.
PY - 2025
SP - 747
EP - 753
DO - 10.5220/0013601200004664
PB - SciTePress