Sessions

• FACE Developing Technical Standards & Updates

  The Future Airborne Capability Environment (FACE) is an open real-time standard for making safety-critical computing operations more robust, interoperable, portable and secure in the aerospace domain. The FACE approach is a government-industry software standard and business strategy for acquisition of affordable software systems that promotes innovation and rapid integration of portable capabilities across programs, including standardized approaches for using open standards within avionics systems and standards that support a robust architecture and enable quality software development for portability of applications across multiple FACE systems and vendors. What are the latest standards and how are the FACE standards developing for future programs? How do these standards affect programs such as Pyramid and ECOA?

• AI and ML in Testing

  AI and ML have provided some great opportunities for assisting speed and quality of testing, when such large amounts of data require analysis, and highlighted the importance of a robust testing strategy for AI systems. While AI can effectively analyze and digest large datasets, ensuring the quality of the AI algorithm and the accuracy of its model is paramount. Factors such as avoiding biases, balancing accuracy with computational costs, and considering on-board processing limitations must be carefully addressed. How can AI assist when an aircraft is in flight, no longer ‘connected’? Qualifying an AI tool involves defining parameters, setting targets, and identifying patterns within the data. How can accuracy be achieve with several AI algorithms running concurrently?

• AI and Automation in the Cockpit

  The integration of artificial intelligence (AI) into aviation is rapidly transforming the industry. As AI capabilities advance, there is growing interest in exploring human autonomy, where AI systems share operational responsibilities with pilots. While regulations are evolving to address the implications of AI and Machine Learning in aviation, the relatively unregulated nature of EVTOL aircraft provides an opportunity. The EUROCAE WG114 working group is actively involved in developing technical standards for AI in aviation. AI can significantly enhance cockpit operations by assisting with data analysis and providing valuable insights. Automation and workload balance are also key considerations, as the increasing complexity of aircraft systems raises questions about the optimal number of crew members required. Connected flight management systems (FMS) play a vital role in facilitating data exchange and providing pilots with advanced decision-support tools. By emulating flight management functions, how can AI assist pilots in making better informed decisions and optimizing flight operations?