Epilots : A System to Predict Hard Landing During the Approach Phase of Commercial Flights

Abstract

This project aims to develop a system called E-Pilots that uses machine learning algorithms to predict hard landings during the approach phase of commercial flights.The system will analyze flight data to precede hard landings.The goal is to provide pilots with real-time warnings and guidance to prevent accidents and improve safety.The research methodology includes the collection and analysis of flight data, the development and testing of machine learning algorithms, and the integration of the E-Pilots system with existing flight systems.The findings of this project are expected to contribute to the improvement of aviation safety and reduce the occurrence of hard landings. The implications of this research may also extend to other areas of aviation safety and flight automation.