Reducing operational costs with Innov’ATM/AI
Sharing knowledge and know-how is caring about the Air Transport Industry as a whole, not only about our clients. At Innov’ATM we truly believe that only through the sharing of our algorithms logic and outcomes we can constantly improve our models and assumptions. Today we launch our blog series on Artificial Intelligence (AI) and Machine Learning (ML) algorithms applied to Air Transport Industry. AI is increasingly used in many aspects of every day lives and its capabilities are being implemented in research innovation to improve the efficiency of many processes. Air Traffic Management, Airport and Airline operations cannot be excluded from such an optimization.
Over the next few months, we will be releasing a series of articles looking at AI and ML in ATI from a range of viewpoints, showcasing what AI and ML are, how they are being used, what their current limitations are, and how we can use AI and ML in the future. If you have any burning questions about AI and ML in research that you would like us to find answers to, please email us or find us on LinkedIn. As new articles are released, we will add a link to them on this page.
Our first article is an overview from Laurent Nicolas and Olivier Carron. Their jobs are also their passion: understanding the interplay of emerging technologies, data strategy and AI & ML algorithms, to better support Air Transport Industry forecasting estimations.
Episode 1 : Ground holding time
Airports are busy places where different stakeholders have key roles and a common goal to manage safely and efficiently the flow of flights departing and arriving. However, airport infrastructures are not exploited in the most optimal manner and increasing traffic makes it difficult for operations to be proactive rather than reactive. This is due to the lack of good information sharing procedures, each of the stakeholders involved in operations has a piece of the information rather than the global picture.
With a 3 hour look-ahead, the airport collaborative decision making (A-CDM) process enables all stakeholders to benefit from sharing the same information as early as possible in order to… read more
