AI-Driven UAV Surveillance for Agricultural Fire Safety

Fire, Journal Year: 2025, Volume and Issue: 8(4), P. 142 - 142

Published: April 2, 2025

The increasing frequency and severity of agricultural fires pose significant threats to food security, economic stability, environmental sustainability. Traditional fire-detection methods, relying on satellite imagery ground-based sensors, often suffer from delayed response times high false-positive rates, limiting their effectiveness in mitigating fire-related damages. In this study, we propose an advanced deep learning-based framework that integrates the Single-Shot MultiBox Detector (SSD) with computationally efficient MobileNetV2 architecture. This integration enhances real-time fire- smoke-detection capabilities while maintaining a lightweight deployable model suitable for Unmanned Aerial Vehicle (UAV)-based monitoring. proposed was trained evaluated custom dataset comprising diverse fire scenarios, including various conditions intensities. Comprehensive experiments comparative analyses against state-of-the-art object-detection models, such as You Only Look Once (YOLO), Faster Region-based Convolutional Neural Network (Faster R-CNN), SSD-based variants, demonstrated superior performance our model. results indicate approach achieves mean Average Precision (mAP) 97.7%, significantly surpassing conventional models detection speed 45 frames per second (fps) requiring only 5.0 GFLOPs computational power. These characteristics make it particularly deployment edge-computing environments, UAVs remote monitoring systems.

Language: Английский

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Integrating UAV, UGV and UAV-UGV collaboration in future industrialized agriculture: Analysis, opportunities and challenges

Computers and Electronics in Agriculture, Journal Year: 2024, Volume and Issue: 227, P. 109631 - 109631

Published: Nov. 23, 2024

Language: Английский

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Unmanned aerial system and machine learning driven Digital-Twin framework for in-season cotton growth forecasting

Computers and Electronics in Agriculture, Journal Year: 2024, Volume and Issue: 228, P. 109589 - 109589

Published: Nov. 28, 2024

Language: Английский

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Construction of flexible porous 3D biochar based on electrospun rice straw-derived cellulose acetate with excellent adsorption properties toward organic pollutants

International Journal of Biological Macromolecules, Journal Year: 2024, Volume and Issue: unknown, P. 138820 - 138820

Published: Dec. 1, 2024

Language: Английский

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