Air Traffic Control using Big Data Analysis and Machine Learning

EasyChair Preprint 3398

Abstract

Nowadays, as there is a rapid increase in the amount of air traffic, so does the compulsion for virtuous, globally correlated, and interoperable Air Traffic Management systems. We are searching for a well-regulated, and widely harmonized Air Traffic Management framework, supported by a worthwhile and viable Communications, Navigation, and Surveillance (CNS) infrastructure. In today’s aeronautics practice, a human air traffic controller monitors and directs many aircraft flying through its baptized airspace zone.

Keyphrases: Air Traffic Control - ATC, Air Traffic Management - ATM, Control Process (CP), Federation Aviation Administration - FAA, Ground Delay Program - GDP, Machine Learning - ML

@booklet{EasyChair:3398,
  author    = {Parul Yadav and Preeti Verma and Anusha Ramachandran and Prachi Dhariwal},
  title     = {Air Traffic Control using Big Data Analysis and Machine Learning},
  howpublished = {EasyChair Preprint 3398},
  year      = {EasyChair, 2020}}