NCA Edge AI & Embedded Systems 2

Question 1

Which NVIDIA Jetson module is specifically designed for entry-level edge AI applications with the lowest power envelope in the Jetson lineup?

Accepted Answer

Jetson Nano

Answer

Jetson Nano targets entry-level edge AI with a ~5–10W power envelope, making it ideal for cost-sensitive embedded deployments.

Question 2

What is the primary role of NVIDIA DeepStream SDK in an edge AI pipeline?

Accepted Answer

Streaming optimized inference on multi-sensor video inputs

Answer

DeepStream is a streaming analytics toolkit that enables real-time, multi-stream video inference on NVIDIA edge hardware.

Question 3

When deploying a TensorRT engine on a Jetson device, why must the engine be rebuilt on the target device rather than transferred from a desktop GPU?

Accepted Answer

Engine files are architecture-specific and not portable across different GPU architectures

Answer

TensorRT engines are optimized for the specific GPU architecture and are not portable; an engine built on an Ampere desktop GPU will not run on a Jetson Volta or Ampere variant without rebuilding.

Question 4

Which power mode on Jetson devices allows users to cap the TDP and limit active CPU/GPU cores to reduce thermal output?

Accepted Answer

nvpmodel modes

Answer

nvpmodel lets you select predefined power modes that constrain TDP, CPU frequency, and active core counts on Jetson modules.

Question 5

In an edge AI camera pipeline, what does the term 'sensor fusion' refer to?

Accepted Answer

Combining data from multiple sensor modalities (e.g., RGB, lidar, radar) to produce richer scene understanding

Answer

Sensor fusion integrates outputs from heterogeneous sensors to improve perception accuracy beyond what any single sensor can provide.

(NCA) NVIDIA-Certified Associate Practice Test

(NCA) NVIDIA-Certified Associate Practice Test

NCA Edge AI & Embedded Systems 2