DRAIDIS Use Case
Process mission video at the point of collection and transmit prioritized products
The Challenge
ISR platforms can generate more full-motion video than constrained links and available analysts can process at once. Sending every raw stream to a central facility can delay exploitation, especially when bandwidth is limited.
How DRAIDIS Solves It
DRAIDIS processes selected ISR video near the point of collection, applies object and change detection on the node, and presents pattern observations for analyst review. Your transmission rules decide which metadata and clips cross a constrained link. During the pilot, analysts measure recognition quality, throughput, latency, and bandwidth impact with your sensors, codecs, data, and network. Your team controls whether collected video may be used to evaluate or improve a model.
Video Ingest
Connect selected RTSP or GMSL video feeds from a UAS payload or ground relay. A BRAVO pilot can test the current design target of up to eight streams.
Frame Analysis
Process selected frames through detection models tested for the object classes and operating conditions your mission needs.
Object Classification Support
Compare candidate objects with the mission library your team provides and present confidence and evidence for analyst confirmation.
Change Detection
Compare current imagery with geo-registered baseline images and flag possible changes such as new structures, vehicle movement, terrain disturbance, or field fortifications.
Activity Pattern Analysis
Compare multiple collection passes to build reviewed activity baselines for traffic, movement, and site use, then flag possible deviations.
Draft Intelligence Product
Prepare annotated imagery, track histories, change-detection overlays, and pattern summaries with confidence for analyst review.
Metadata Transmission
Transmit the metadata, candidate detections, and clips your team selects. Your policy sets source-video retention, encryption, access, and transfer rules.
Analyst Query Interface
Let analysts query processed data in natural language and inspect the underlying collection before using the result.
Deployment Configuration
This reference design spans 2 DRAIDIS tiers. The pilot defines and tests the coverage needed for your environment.
DRAIDIS ALPHA
Portable design for small tactical-UAS ground-control workflows. The pilot measures stream count and latency with the selected payload, codec, compute, and mission environment.
DRAIDIS BRAVO
Multi-stream design for ISR cells. Integration tests confirm the supported stream count and cross-stream correlation on the selected hardware and payloads.
Key Capabilities
Purpose-built AI capabilities for this mission set.
Object Recognition Support
Classify selected mission objects and present confidence and evidence. Analysts measure accuracy on representative test data their team selects.
Change Detection
Compare imagery with a geo-registered baseline and flag possible terrain changes, new construction, and disturbance patterns.
Activity Pattern Analysis
Compare multiple collection passes and flag possible changes in traffic, schedules, or positions for analyst review.
Controlled Transmission
Prioritize metadata and selected clips instead of sending every raw stream, then measure bandwidth impact on your network.
Natural Language Querying
Let analysts query processed ISR data conversationally and inspect the supporting collection.
Multi-Stream Processing
Configure BRAVO for multiple simultaneous feeds and measure throughput and cross-stream correlation with the selected hardware and payloads.
Performance Metrics
Measure
Bandwidth impact by configuration
Test
Mission-specific recognition
Measure
Processing and alert latency
Test
Concurrent stream capacity
Plan a Pilot for This Workflow
Review how DRAIDIS could support tactical isr processing, then define the interfaces, data, hardware, controls, and operating conditions your team wants to test.