The IoT data volume problem
A growing class of satellite constellations is built not to collect imagery but to receive and relay signals from ground-based IoT sensors — ships, agricultural tags, container trackers, environmental monitors. These constellations serve as the sky-facing backbone of distributed sensing networks.
The economic challenge is the data volume. A constellation passing over a busy shipping lane might receive signals from thousands of vessels in a single pass. Most of those signals are routine position reports with no operational relevance. All of it must be buffered, then downlinked, then processed on the ground to find the handful of signals that actually matter.
TILE for IoT constellation operators
Maritime Domain Awareness
AIS signal aggregation with on-orbit anomaly detection. Vessels deviating from expected tracks, spoofing indicators, and dark vessel events identified in orbit before the satellite downlinks.
Agricultural IoT
Soil moisture sensor, weather station, and crop health tag data aggregated per field per pass. Anomaly thresholds trigger alerts. Most routine sensor readings are summarized, not forwarded individually.
Asset Tracking at Scale
Logistics container, pipeline monitor, and infrastructure sensor signals processed in orbit. Deviations from expected state — location, temperature, vibration — filtered and summarized before downlink.
Downlink Volume Reduction
An IoT constellation pass over a dense sensor region may receive thousands of raw messages. On-orbit aggregation with TILE reduces that to a structured exception report: flagged anomalies, summary statistics per region, and routing metadata for the ground system. The ground segment scales with exception count, not raw sensor message volume — which means ground infrastructure costs stop growing linearly with constellation size.