In recent years, there has been a lot of interest in the application of artificial intelligence (AI) for the categorization of aerial images in fire detection. Aerial photos taken by drones and satellites are becoming more widely available, which increases the demand for automated systems that can swiftly and correctly identify possible fire problems. AI-based categorization systems can assist in the analysis of huge amounts of data and the identification of characteristics, such as smoke, heat, and flames that point to the existence of a fire. As a result of today’s increased fire risk, early detection is essential for saving lives. Automated fire detection is a great tool for this. The current fire detection system is primarily carried out indoors using smoke detectors, but there is a need to develop a drone-based fire detection system for the early detection of outdoor fires, because outdoor fire detection systems are challenging to implement because they involve a classification problem that must be solved by a machine, the primary goal of this project is to gather data from existing outdoor fire detection systems.