ΑΙhub.org
 

Fly AI report – demystifying and accelerating AI in aviation

by
19 November 2020



share this:
Fly AI report | AIhub

By Benjamin Cramet and Sylvie Grand-Perret

The first Fly AI report provides an overview of the many ways that artificial intelligence is already applied in the industry and assesses its potential to transform the sector.

The report aims to demystify AI, help its uptake in aviation and advance understanding of its potential for example in areas such as reducing human workload, driving the development of new air traffic management (ATM)/U-Space services, or increasing safety and cyber resilience. It includes a Fly Action Plan which sets out the practical actions that could be taken to accelerate the development of AI in European aviation and ATM.

A joint effort

The report was developed by the European Aviation High Level Group on AI (EAAI HLG) – a high level group composed of key representatives from all aviation sectors (airlines, airports, Air Navigation Service Providers, manufacturers, EU bodies, military and staff associations). Experts from a range of organisations were involved: EUROCONTROL, the European Commission, ACI-Europe, Airbus, ASD, CANSO, Heathrow Airport, Honeywell, IATA, IFATCA, IFATSEA, the SESAR JU, Thales, as well as our military partners EDA and NATO.

Read the report in full here.




AI4EU




            AIhub is supported by:


Related posts :



Interview with Mike Lee: Communicating AI decision-making through demonstrations

We hear from AAAI/SIGAI Doctoral Consortium participant Mike Lee about his research on explainable AI.
23 April 2024, by

Machine learning viability modelling of vertical-axis wind turbines

Researchers have used a genetic learning algorithm to identify optimal pitch profiles for the turbine blades.
22 April 2024, by

The Machine Ethics podcast: What is AI? Volume 3

This is a bonus episode looking back over answers to our question: What is AI?
19 April 2024, by

DataLike: Interview with Tẹjúmádé Àfọ̀njá

"I place an emphasis on wellness and meticulously plan my schedule to ensure I can make meaningful contributions to what's important to me."

Beyond the mud: Datasets, benchmarks, and methods for computer vision in off-road racing

Off-road motorcycle racing poses unique challenges that push the boundaries of what existing computer vision systems can handle
17 April 2024, by

Interview with Bálint Gyevnár: Creating explanations for AI-based decision-making systems

PhD student and AAAI/SIGAI Doctoral Consortium participant tells us about his research.
16 April 2024, by




AIhub is supported by:






©2024 - Association for the Understanding of Artificial Intelligence


 












©2021 - ROBOTS Association