Published Paper Details:

Thermal imaging drone technology has significantly transformed multiple industries, including search and rescue, agriculture, industrial inspections, and environmental monitoring. This study explores the advancements in thermal imaging drones, focusing on data collection, image processing, neural network training, and AI-driven analysis. The integration of artificial intelligence enhances detection accuracy, improves automation, and increases efficiency in real-time monitoring applications. This paper involved the design and implementation of a drone system equipped with a thermal imaging camera, supported by machine learning models to process and analyze captured data. The findings indicate that thermal imaging drones are highly effective in detecting temperature variations, identifying anomalies, and assisting in critical decision-making. Advanced segmentation techniques, deep learning-based object recognition, and multi-target tracking algorithms further enhance their capabilities .The study also highlights challenges such as environmental interference, data processing complexities, and the need for real-time optimization. Despite these challenges, continued advancements in AI, sensor technology, and edge computing will further expand the scope of thermal imaging drones in disaster response, infrastructure monitoring, and security applications. These innovations position thermal imaging drones as essential tools for modern aerial surveillance and thermal data analysis.