Power Requirements Evaluation of Embedded Devices for Real-Time Video Line Detection

Jakub Suder (), Kacper Podbucki and Tomasz Marciniak
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Jakub Suder: Division of Electronic Systems and Signal Processing, Institute of Automatic Control and Robotics, Poznan University of Technology, Piotrowo 3A, 60-965 Poznan, Poland
Kacper Podbucki: Division of Electronic Systems and Signal Processing, Institute of Automatic Control and Robotics, Poznan University of Technology, Piotrowo 3A, 60-965 Poznan, Poland
Tomasz Marciniak: Division of Electronic Systems and Signal Processing, Institute of Automatic Control and Robotics, Poznan University of Technology, Piotrowo 3A, 60-965 Poznan, Poland

Energies, 2023, vol. 16, issue 18, 1-20

Abstract: In this paper, the comparison of the power requirements during real-time processing of video sequences in embedded systems was investigated. During the experimental tests, four modules were tested: Raspberry Pi 4B, NVIDIA Jetson Nano, NVIDIA Jetson Xavier AGX, and NVIDIA Jetson Orin AGX. The processing speed and energy consumption have been checked, depending on input frame size resolution and the particular power mode. Two vision algorithms for detecting lines located in airport areas were tested. The results show that the power modes of the NVIDIA Jetson modules have sufficient computing resources to effectively detect lines based on the camera image, such as Jetson Xavier in mode MAXN or Jetson Orin in mode MAXN, with a resolution of 1920 × 1080 pixels and a power consumption of about 19 W for 24 FPS for both algorithms tested.

Keywords: microprocessor power modes; embedded systems; DVFS; NVIDIA Jetson; Raspberry Pi; video analysis; line detection (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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