Using Artificial Neural Networks to Analyze Trends of a Global Aircraft Fleet

I’m an intern in the Commercial Mobility group at ViaSat.  Our group is responsible for all of the company’s commercial aviation clients, providing internet services to aircraft. While providing the world’s best in-flight internet service to airplanes traveling over 500 miles per hour 30,000 feet above the ground is no small feat, it is also a challenge to analyze and predict user demand of our network. There are typically several hundred planes connected to ViaSat’s network at any given time amounting to 15,000-40,000 flights a week depending on the season. With this much range and traffic, and flights leaving all times of day, all over the world, modeling anything about them becomes very difficult.