Beyond Benchmarks: Continuous Edge Inference for Traffic Sign Recognition on Embedded Vehicular Hardware
Overview
This research introduces Edge-TSR, a continuous edge inference system designed for traffic sign recognition (TSR) on NVIDIA Jetson Orin Nano hardware.
Generated from attributed reports · Updated 2 days ago
Event evidence and corrections
0 attributed source owners. Ownership does not establish independent confirmation. Quantities are reported separately and are never added together.
Reported quantity · distance_traveled: 26 other · Basis not reported
“ghput rather than thermal throttling. A 55-minute, 26 km vehicular deployment demonstrates sustained online operation at 16.18 FPS within safe thermal limits without cloud offload. We also release the annotated 50,732-frame streaming evaluation dataset and full implementation.”
Exact source · revision 1Source owner not reported
Reported quantity · frames_processed: 50732 other · Basis not reported
“ghput rather than thermal throttling. A 55-minute, 26 km vehicular deployment demonstrates sustained online operation at 16.18 FPS within safe thermal limits without cloud offload. We also release the annotated 50,732-frame streaming evaluation dataset and full implementation.”
Exact source · revision 1Source owner not reported
Reported quantity · fps: 16.18 other · Basis not reported
“ghput rather than thermal throttling. A 55-minute, 26 km vehicular deployment demonstrates sustained online operation at 16.18 FPS within safe thermal limits without cloud offload. We also release the annotated 50,732-frame streaming evaluation dataset and full implementation.”
Exact source · revision 1Source owner not reported
Reported quantity · latency_increase: 0.07 other · Basis not reported
“etson Orin Nano that combines sparse detection, multi-object tracking, region-level fine-grained classification, and a lightweight track-aware temporal stabilization mechanism adding only 0.07~ms per sampled frame. Evaluating on the source videos of the INTSD benchmark, we find that the state-of-the-art TSR models lose 20-30 percentage points of mAP@50 when moving from image-based to streaming evaluation. Edge-TSR ac”
Exact source · revision 1Source owner not reported
Artifact availability · dataset: reported pending
“ghput rather than thermal throttling. A 55-minute, 26 km vehicular deployment demonstrates sustained online operation at 16.18 FPS within safe thermal limits without cloud offload. We also release the annotated 50,732-frame streaming evaluation dataset and full implementation.”
Exact source · revision 1Source owner not reported
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- arXiv Robotics — research abstractsSignalBeyond Benchmarks: Continuous Edge Inference for Traffic Sign Recognition on Embedded Vehicular Hardware
This research introduces Edge-TSR, a continuous edge inference system designed for traffic sign recognition (TSR) on NVIDIA Jetson Orin Nano hardware.
Event coverage history
Current attention 3·Peak within the comparable range 4（2026-11-10 16:00 UTC）·Change within the comparable range over 24 hours –
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