Space-Based Data Processing & Edge Computing

Process satellite imagery in orbit for wildfire detection, maritime vessel tracking, and severe weather nowcasting. Eliminates downlink latency for time-critical alerts.

On-board AI enables satellites to perform collision avoidance, orbit adjustments, and payload scheduling without waiting for ground commands.

In-orbit compute nodes act as intelligent relays, routing data between satellites, aggregating telemetry, and reducing ground station dependency.

Physically isolated compute infrastructure in orbit provides an air-gapped processing environment for classified data and sensitive national security workloads.

Space telescopes and science missions generate terabytes of raw data. On-board processing filters noise, compresses data, and identifies high-priority observations before downlink.

Single event upsets (SEUs), total ionizing dose (TID), and displacement damage degrade electronics. LEO provides some shielding from the Van Allen belts, but GEO and deep space are far harsher.

Satellite solar panels provide limited power, typically 1-15 kW for most spacecraft. Modern GPUs alone can draw 300W+. Every watt consumed as compute generates heat that must be radiated away.

No convective cooling in space means all heat must be radiated. Compute-intensive workloads require large radiator panels, adding mass and complexity. Temperature cycling between sun and shadow stresses components.

LEO satellites have ground contact windows of only 5-15 minutes per pass. Uploading new models, downloading results, and managing operations must fit within these windows or use inter-satellite links.

Launching compute hardware to orbit costs $2,000-5,000/kg. A space-rated server rack weighing 50kg costs $100K-250K in launch costs alone, before the hardware itself. Only justified when downlink savings or latency requirements offset the premium.