Abstract :

Forest Fires Pose A Significant Threat To Ecosystems, Biodiversity, Human Lives, And Property, Causing Severe Environmental And Economic Losses Worldwide. Conventional Fire Detection Methods, Including Manual Surveillance And Satellite Monitoring, Often Suffer From Delayed Response, Limited Coverage, And High Operational Costs, Making Early Wildfire Identification Difficult. This Paper Presents An AI-Based Forest Fire Detection And Analysis System That Employs Artificial Intelligence, Deep Learning, And Computer Vision Techniques For Accurate And Real-time Detection Of Forest Fires. The Proposed System Utilizes A Convolutional Neural Network (CNN) To Analyze Images And Video Streams Captured Through Surveillance Cameras Or Unmanned Aerial Vehicles (UAVs) To Identify Smoke And Flames At An Early Stage. Environmental Parameters Such As Temperature, Humidity, And Wind Speed Obtained From IoT Sensors Are Integrated To Improve Detection Reliability And Reduce False Alarms. The Collected Data Are Processed Through Cloud-based Services To Generate Instant Alerts For Forest Authorities, Enabling Rapid Response And Minimizing Fire Spread. The System Is Evaluated Using Standard Performance Metrics Including Accuracy, Precision, Recall, And F1-score, Demonstrating Superior Performance Compared To Traditional Image-processing Approaches. The Proposed Framework Offers A Scalable, Intelligent, And Costeffective Solution For Continuous Forest Monitoring And Wildfire Prevention, Contributing To Environmental Conservation, Disaster Management, And Public Safety Through Timely And Reliable Fire Detection. KEYWORDS-Artificial Intelligence (AI), Forest Fire Detection, Deep Learning, Convolutional Neural Network (CNN), Computer Vision, Internet Of Things (IoT), Wildfire Monitoring, Environmental Analysis, Real-Time Alert System.

Published:

05-8-2026

Issue:

Vol. 26 No. 8 (2026)

Page Nos:

681 - 689

Section:

Articles

License:

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

How to Cite