E-Pilots: A System to Predict Hard Landing During the Approach Phase of Commercial Flights - MLteam

G. Lucy, S. Sana Samrin, R. Devi Shraya, C. Geethanjali

2025

Abstract

Hard landings are among the most threatening issues to the safety of the aircraft, passengers' comfort, and the maintenance cost implications of commercial aviation. The E-Pilots system aims to foretell the risk of a hard landing during the approach using machine learning algorithms in correlation with real-time flight data. It continuously tracks critical flight parameters such as descent, rate of vertical acceleration, airspeed, and other environmental conditions to identify patterns characteristic of hard landings. Through the use of sophisticated predictive tools like Random Forest, Long Short-Term Memory (LSTM) networks, and Support Vector Machines (SVM), E-Pilots generate real-time warnings to pilots so that they can take corrective measures before touchdown. Unlike conventional post-flight analysis practices, this system allows proactive risk management through the use of AI-boosted decision support and real-time monitoring. The system architecture includes onboard sensor data acquisition, cloud-based computing, and a display of landing safety predictions specific to pilots. The system continuously learns from new flight data, thus improving its accuracy and responsiveness across different aircraft models and weather conditions. The use of E-Pilots greatly improves aviation safety by reducing the chances of harsh landings, lowering the costs incurred in maintaining aircraft and enhancing the comfort level felt by passengers. Future research activities can include integration with meteorological prediction models, compatibility with different aircraft types, and further development of automation to enhance landing effectiveness. This pioneering system is a significant improvement in predictive analytics for the aviation industry, and it helps ensure enhanced safety and efficiency of commercial flight operations.

Paper Citation

in Harvard Style

Lucy G., Samrin S., Shraya R. and Geethanjali C. (2025). E-Pilots: A System to Predict Hard Landing During the Approach Phase of Commercial Flights - MLteam. In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - Volume 4: ICRDICCT`25; ISBN 978-989-758-777-1, SciTePress, pages 62-68. DOI: 10.5220/0013908100004919

in Bibtex Style

@conference{icrdicct`2525,
author={G. Lucy and S. Samrin and R. Shraya and C. Geethanjali},
title={E-Pilots: A System to Predict Hard Landing During the Approach Phase of Commercial Flights - MLteam},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - Volume 4: ICRDICCT`25},
year={2025},
pages={62-68},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013908100004919},
isbn={978-989-758-777-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - Volume 4: ICRDICCT`25
TI - E-Pilots: A System to Predict Hard Landing During the Approach Phase of Commercial Flights - MLteam
SN - 978-989-758-777-1
AU - Lucy G.
AU - Samrin S.
AU - Shraya R.
AU - Geethanjali C.
PY - 2025
SP - 62
EP - 68
DO - 10.5220/0013908100004919
PB - SciTePress