With the proliferation of satellites in space, low Earth orbit traffic becomes “jammed”, making it necessary to be more efficient in space-based data collection and downlink. From the perspective of Earth observers, the way to accomplish this efficiency goal is twofold: 1) Use small satellites (CubeSats), which have shorter mission lifetimes and more easily satisfy regulations limiting time in orbit; and 2) make onboard processing more sophisticated so that downlink time is reduced. The objective of this project is to develop methods and devices to implement complex detection and data processing tasks on CubeSats using artificial intelligence.
This team is able to offer a limited number of $1,000 research awards to students.
Team Leads: Deepak R. Mishra (Geography), Marguerite Madden (Geography), Susanne Ullrich (Physics and Astronomy), Lakshmish Ramaswamy (School of Computing), Fred Beyette (College of Engineering), In Kee Kim (School of Computing), Ramana Pidaparti (College of Engineering)
