Flutter and Jetson: Building a Thermal- and Memory-Aware Operator UI

This advanced tutorial positions Flutter as the operator-facing layer, leaving device-specific and compute-heavy tasks to wearable SDKs, Jetson services, ROS 2 nodes, and NVIDIA-accelerated inference. Its aims are predictable latency, bounded memory, useful observability, and graceful degradation rather than maximizing message throughput. It stresses that safety-critical control must stay on the robot, since a Flutter app is not a hard real-time controller. The guide recommends tracking data freshness, end-to-end latency, frame pacing, resource use, and command acknowledgements, and profiling on physical hardware in profile mode. It also advises using latest-value caches, bounded queues with overflow policies, and controlled presentation cadence to keep high-rate data from forcing constant widget rebuilds.