Grant supports the co-development of onboard edge AI predictive maintenance technology designed to improve the safety and reliability of Advanced Air Mobility.
Abu Dhabi, UAE – 08, Sep, 2026: The Technology Innovation Institute (TII), the applied research arm of Abu Dhabi’s Advanced Technology Research Council (ATRC), has become the first institution in the Middle East to receive Qualcomm’s Tech for Good Grant. The grant will support a research collaboration to advance TII’s proprietary SADEED Prognostics and Health Management (PHM) platform for deployment on Qualcomm’s Dragonwing™ IQ9 edge AI processor.
The collaboration will enable SADEED to analyze the health of safety-critical systems directly onboard aircraft, without relying on continuous cloud connectivity. By bringing AI-powered predictive maintenance to the edge, the technology is designed to help cargo drones and future electric vertical take-off and landing (eVTOL) aircraft identify early indicators of component degradation before they develop into failures.
As Abu Dhabi accelerates its vision to become a global leader in Advanced Air Mobility (AAM), ensuring safety and reliability has become one of the industry's most critical challenges. While advances in AI, autonomy and electric propulsion are bringing cargo drones and eVTOL aircraft closer to commercial deployment, aircraft maintenance continues to rely heavily on scheduledinspections and predefined maintenance intervals.
SADEED is designed to support the transition toward condition-based and predictive maintenance. The platform continuously monitors the health of critical systems and applies AI to identify patterns and anomalies that can signal emerging faults. Running these capabilities directly onboard enables faster local decision-making, reduces dependence on connectivity and allows safety-critical operational data to be processed securely at the edge.
The collaboration builds on more than two years of research by TII’s AI Diagnostics and Prognostics team within its Propulsion and Space Research Center. By adapting SADEED for Qualcomm’s advanced edge AI platform, TII is taking its PHM capabilities from the research environment toward real-world onboard deployment.
Dr. Najwa Aaraj, CEO of Technology Innovation Institute, said: “The future of aviation will depend not only on how aircraft fly, but on how intelligently they understand and manage their own health. SADEED gives aircraft the ability to identify emerging issues before they become critical failures, helping enhance safety while reducing unplanned downtime and maintenance costs. Through this collaboration with Qualcomm, we are taking an important step toward moving our PHM technology from advanced research to real-world onboard operations.
Because SADEED is platform-agnostic, its potential also extends well beyond Advanced Air Mobility to industries where the reliability, performance and safety of critical machinery are paramount.”
Dev Singh, Vice President, Business Development at Qualcomm International, Inc., said: “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. Running TII’s SADEED platform on the Dragonwing IQ9 series processor aims to move that intelligence onboard, helping to give operators real-time, sovereign control over safety-critical health data instead of sending it elsewhere. This is exactly the kind of physical AI capability we’re working to build for the region: edge processing that is designed to help autonomous systems operate more safely and reliably in the field.”
The project complements TII’s broader work in shaping Abu Dhabi’s Advanced Air Mobility ecosystem. Having helped establish the technical foundations for the UAE’s future air corridors, TII is now tackling another key barrier to commercial adoption: enabling autonomous aircraft to catch faults before they become operational issues. Together, these initiatives strengthen Abu Dhabi’s position as a testbed for the technologies that will define the future of aviation.
