Safe Fly Prediction Model for Unmanned Aerial Vehicle

In tropical regions like India, the weather is highly variable and can change rapidly, creating challenging conditions for Unmanned Aerial Vehicle operations. The lack of accurate, real-time predictive tools for assessing Unmanned Aerial Vehicle safety in such environments exacerbates the risk of accidents. Moreover, as Unmanned Aerial Vehicle become more integrated into commercial and public services, the demand for reliable safety protocols becomes even more urgent. This study evaluated the performance of various machine learning algorithms in predicting flight safety based on meteorological data. The Safe Fly Prediction Model, which employs machine learning algorithms to forecast flight safety based on meteorological data, obtained excellent accuracy and shown its potential for real-world use.