I recently started my data science internship at Airbus Operations GmbH, Hamburg in September 2019 and was awarded the opportunity to participate in this ADS-B Hackathon at Airbus Leadership University, Toulouse, France.
Machine Learning for Air Traffic Management
Airsense (a division within Airbus - Munich) organized this 2 day ADS-B Hackathon at Airbus Leadership University, Toulouse on Oct 29 and Oct 30, 2018. The goal of this hackathon was to develop various data analytics and ML based solutions to optimize Air Traffic Management using the Automatic Dependent Surveillance Broadcast (ADS-B) data. The participants had to pick a particular user story (team). I joined the following team:
USER STORY - Runway and Holding Pattern Detection:
- Project Title: Runway and Holding analysis using LHR airport arrivals case
- My Task : Detect holding patterns and do runway classification with flight arrivals data for LHR (London Heathrow) airport.
In this team project I implemented various Machine Learning algorithms (such as LSTMs, MLPs and XGBoost) for predicting various parameters related to Air Traffic Control such as Flight Trajectory, ETA and Runway Classification. The collection of implementation works have been uploaded in this Git Repository: https://github.com/diliprk/ML_ADS-B_Hackathon
Presentation Slides: