Qualcomm has awarded its first Tech for Good Grant in the Middle East to Abu Dhabi’s Technology Innovation Institute (TII), supporting a collaboration aimed at bringing AI-powered predictive maintenance directly onboard autonomous aircraft. The grant will fund the co-development of TII’s SADEED Prognostics and Health Management (PHM) platform for deployment on Qualcomm’s Dragonwing IQ9 edge AI processor.
The technology is being developed to help future cargo drones and electric vertical take-off and landing (eVTOL) aircraft identify early signs of component degradation before they develop into failures. Instead of sending aircraft health data to the cloud for analysis, SADEED is designed to process it onboard, enabling faster decisions while reducing reliance on continuous connectivity.
The collaboration comes as Abu Dhabi seeks to establish itself as a hub for Advanced Air Mobility (AAM). While autonomous flight, AI and electric propulsion are advancing rapidly, ensuring the safety and reliability of aircraft remains one of the key challenges to wider commercial adoption.
Much of aircraft maintenance today relies on scheduled inspections and predetermined maintenance intervals. TII’s SADEED platform is designed to support a shift towards condition-based and predictive maintenance, continuously monitoring safety-critical systems and using AI to identify anomalies and patterns that could indicate developing faults.
Running the technology at the edge could also have implications beyond aircraft maintenance. Processing safety-critical operational data locally can reduce latency, limit dependence on cloud connectivity and provide greater control over sensitive data. The project builds on more than two years of research by TII’s AI Diagnostics and Prognostics team, part of its Propulsion and Space Research Center. The collaboration with Qualcomm is intended to move SADEED beyond the research environment towards real-world onboard deployment.
“The future of aviation will depend not only on how aircraft fly, but on how intelligently they understand and manage their own health,” said Dr Najwa Aaraj, CEO of Technology Innovation Institute. She said SADEED could help identify emerging problems before they become critical failures while reducing unplanned downtime and maintenance costs. Because the platform is platform-agnostic, its applications could also extend to other industries where the reliability and safety of critical machinery are important.
For Qualcomm, the project is an example of how edge AI and Physical AI can be applied to autonomous systems that cannot depend on a permanent cloud connection. “Autonomous aircraft and cargo drones are a powerful example of Physical AI in action and cannot rely on a connection to the cloud to know something is wrong,” said Dev Singh, Vice President, Business Development at Qualcomm International, Inc.
According to Singh, deploying SADEED on the Dragonwing IQ9 series is intended to give operators greater real-time control over safety-critical health data while allowing autonomous systems to make decisions closer to where they operate. The project also builds on TII’s wider involvement in developing the technical foundations for Abu Dhabi’s Advanced Air Mobility ecosystem, including work supporting future air corridors.
By combining autonomous aircraft, edge AI and predictive maintenance, the latest initiative targets one of the practical barriers to commercial AAM deployment: ensuring aircraft can detect and respond to potential failures before they become operational or safety issues. The collaboration gives Abu Dhabi another opportunity to test technologies that could shape the future of autonomous aviation while demonstrating how edge AI can move beyond conventional computing environments into safety-critical physical systems.
