How do you reduce flight delays as an airport when you have limited insight in the operations involved? Schiphol Airport is one of the busiest airports in the world, with over 70 million passengers per year. Aiming to improve operational performance and customer experience, Schiphol is looking for ways to reduce flight delays caused by airplane turn-arounds.
Limited insight in airline operations
While Schiphol is attempting to reduce delays, their impact on turn-around times is hampered by a lack of insight in the process. As an airport, Schiphol is not responsible for the execution of these turn-arounds. The airlines use a variety of companies and handlers to manage turn-arounds, further complicating insight and limiting the information available to Schiphol.
Fully automated, near real-time solution
GoDataDriven's Data Engineers Tim van Cann and Daniel van der Ende developed a deep learning solution using the real-time camera images feed of the aircraft at the gate. Using these images they generate a near real-time feed of events happening during the turn-around. The solution was created using Apache Kafka and Tensorflow, backed by Azure Kubernetes Service. While the solution is still in development Tim and Daniel will share insights into the learnings so far.
Interested in learning more about how they approached this problem and are developing a solution.? Join Tim and Daniel next week for Data Council New York to hear all about it. Can't make it to New York? Check back after Data Council finishes for the recording of their talk.