Modern UAV ISR systems should separate AI detection providers from mission computer logic. This architecture allows AI models, camera systems, and edge AI hardware to be replaced independently without rewriting tactical UI or replay systems.
Most UAV systems tightly couple detection models to operational interfaces. This creates scalability problems when changing from OpenCV to RT-DETR, Raspberry Pi AI Camera, Edge TPU, or custom neural network pipelines.
FUKUSHIMA UAV uses a provider abstraction layer to normalize detections into a common schema.
The mission computer receives normalized detections regardless of the provider implementation. This enables tactical replay systems, AI event timelines, fleet coordination, watchdog systems, and browser-based GCS interfaces to remain stable while AI models evolve independently.
Related article: Browser-Based UAV Mission Computer Platform
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