Hardware Edge GPU/NPU Nodes Converting Raw Radar Echoes into Semantic Object Metadata

Deploying neural accelerators at cellular base stations to convert raw radar returns into rich semantic object classes (Car, Pedestrian, Drone).

Edge PointNet++ and Transformer Inference

Raw 3D point clouds pass through optimized PointNet++ neural networks running on edge TensorRT accelerators. The model segments individual objects, outputting 3D bounding boxes, velocities, and semantic classification in under 8 milliseconds.

Drastic Telemetry Bandwidth Reduction

By classifying targets at the base station edge, the gateway transmits compact JSON object metadata (5 kbps per target) rather than multi-gigabit raw point clouds, preserving cellular core backhaul capacity.

PointNet++ neural networks executing 3D object detection in under 8 ms
Automated bounding box, heading vector, and semantic classification
99.9% telemetry bandwidth reduction by extracting edge metadata
Hardware acceleration using NVIDIA TensorRT and ARM Ethos NPUs

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