A Comparative Analysis of Open-Source Ai Solutions For Wildfire Detection Through Video Analysis

This study aims to identify and compare open-source AI solutions for wildfire detection through video analysis, focusing on evaluating scalability, accuracy, and integration capabilities. A systematic literature review was conducted using the Scopus and Web of Science databases, covering articles published in the last five years. The search strategy was carefully refined to isolate the most relevant and high-quality studies, which were then analyzed and compared based on features, performance, and suitability for large-scale wildfire monitoring. The review identified several leading open-source platforms, including TensorFlow, PyTorch, and OpenCV, each providing unique tools and algorithms for wildfire detection. TensorFlow's scalability and support for deep learning models make it particularly suitable for extensive image processing tasks. PyTorch stands out for its flexibility and user-friendly design, making it ideal for rapid prototyping and research applications. OpenCV's extensive image processing library enables efficient feature extraction and analysis. The comparative analysis highlights that deep learning models, particularly Convolutional Neural Networks (CNNs), consistently outperform traditional image processing techniques regarding accuracy and robustness.