Enhancing MQ-9 Aircrew Situational Awareness by Automated Image Recognition from Aerial Images, based on Explainable-AI

In this SBIR Phase II project, ZAC detailed image recognition solution, based on Explainable-AI (artificial intelligence), will be adapted to the USAF needs: It will provide detailed intelligence and full picture from satellite or aerial/drone images to warfighters, to enhance drone aircrew situational awareness and performance. The solution will automatically and accurately locate, recognize, and identify objects (e.g., tanks, trucks, people), targets and potential threats, with details, in real-time, from any view direction, from aerial images (e.g., from MQ-9) under varying conditions. For example, it will automatically and accurately identify the detected airplane as C-130, and it will provide decision quality information to end-users, such as MQ-9 aircrew, ISR community, and tactical forces, to minimize risks and better execute and achieve their missions. In addition, ZAC’s Explainable-AI image recognition has the advantage of using less computational power, while being modular in nature, making it capable of being deployed in the field or at the edge (i.e., on-board the UAV), as it will occupy a smaller footprint/weight, and require less battery power due to lower power consumption.