Image by Markus Spiske from Pixabay

In aviation industry several profit-oriented players like airlines, airports and air navigation services would have the chance to bring a positive impact to their KPIs by sharing data. However, up to now they are mainly focused on optimizing their particular processes, meeting only their own business targets. Software tools, developed in the recent years, have consequently been developed only to provide optimal particular results by using own data.

With perceptions changing and technologies evolving, new interlinked approaches based on machine learning technologies are on the rise that are capable of accessing and processing huge amounts of shared data, leveraging on collaboration with other players to achieve better overall results.

One cornerstone of enhancements is the increasing availability of live process data, provided by ubiquitous sensors and transported through high speed networks, that give deep insights into the actual progress of an ongoing flight, the aircraft health status, the actual situation of the airport resources, latest weather changes and other relevant topics.

Another cornerstone is the availability of massive parallel computing power and machine supported learning and analysis methods, which allow extraction of key findings as well as their assessment and evolution in real time.

A third cornerstone is the shifting from the local awareness to the global awareness, e. g. saving the environment by the reduction of fuel consumption to lower the pollution of CO2, NOx and noise, and the understanding, that global goals will only be met by collaboration.

Together, these cornerstones have the potential to fundamentally change the way of working in aviation industry. For example, the airline would identify the need to adapt a flight plan due to changed weather conditions or based on the knowledge of an urgently required maintenance activity due to unexpected sensor data provided by the aircraft. In a collaborative world, the airline is enabled to synchronize its own planning with the consideration of the resource situation at the destination airport and the airspace granted by the air navigation services.

Today, data becomes a crucial resource and each player has the opportunity and in their own interest the duty to reorganize data management to keep the pace in the industrial environment. Processes must be adapted; new skills must be developed and new tools and ways of collaboration must be implemented to plan and realize the optimal exploitation of the resource data.

The ICARUS platform provides a wide range of functionalities to connected aviation organizations to enable them to exploit their own data for their own commercial benefit.  The main capabilities for this are intelligent search and data provision & retrieval mechanisms, the definition of pricing models and contracts, the provision of data analytics functions, as well as machine learning and artificial intelligence algorithms in a secured environment.

As one of four demonstrators in the project, PACE and TXT utilize the ICARUS platform to improve the Pollution Data Analysis of single flights by enabling the Pacelab Mission Suite (PLMS) software to consider detailed flight tracks and weather data, e. g. provided by the project partner OAG.

Blogpost by:PACE TXT

Featured Image: by Markus Spiske from Pixabay