One of the great understudied bottlenecks at airports is the time aircraft spend taxiing to and from the runway. Sandy Brownlee, PhD, a senior research assistant at the University of Stirling in Scotland, and Jason Atkin, assistant professor at the University of Nottingham, turned their computer science expertise toward this problem.

Cloud computing is empowering the research team to analyze airport bottlenecks and create a model that will one day recommend better paths for every plane. They used Microsoft Azure to store data on thousands of taxiways at different airports and create open tools, now available to anyone on GitHub, to model and improve aircraft taxiing to reduce pollution and improve efficiency.

Modeling required Brownlee to bring together data for dozens of airports from publicly available sources, including Flight Radar 24 and Open Street Map. He was pleasantly surprised to find how easy it was to use open-source tools on Microsoft Azure, such as Linux virtual machines, and developing his methods using OpenJDK. Processing speeds using Azure enabled him to complete his work in one-tenth the time of just using his desktop computer.

To learn more about how scientists in the United Kingdom are working hard to improve airport operations, to reduce costs and impact on the environment, check out the Microsoft Research blog and the below video. Visit the Microsoft Azure site for more on open source solutions and the Azure cloud.