E-PILOTS: Machine Learning and Sensor-based solutions for aviation and pilot cognitive monitoring.

DESCRIPTION:

The introduction of new technologies in the flight deck has allowed important advances in flight control, communication, navigation, and engine management technologies. This has resulted in a simplified and consolidated control mechanism that reduces flight crew workload for a variety of tasks. However, the increased system complexity that comes with the new technologies also created novel issues that could increase flight crew workload.

It is well accepted by pilots, human factors researchers/practitioners and artificial intelligence community that in order to achieve optimum performance in a particular task, the real challenge is to provide the flight crew with the most appropriate data/information/knowledge at the right time. This information should also take into account the type of task, i.e. skill-based, rule-based, or knowledge-based. E-PILOTS aims to provide situational-relevant information with the use of cognitive computing technology.

E-PILOTS aims to explore the benefits of applying cognitive computing to provide assistance to the flight crew in the decision-making process in key areas and unexpected or very complex circumstances. The project will look at how E-PILOTS can support flight crew for example in navigating by taking into account surrounding traffic or other constraints, and managing non- normal situations.