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Article

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Title

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

Authors

[ 1 ] Instytut Automatyki i Robotyki, Wydział Automatyki, Robotyki i Elektrotechniki, Politechnika Poznańska | [ SzD ] doctoral school student | [ P ] employee

Scientific discipline (Law 2.0)

[2.2] Automation, electronics, electrical engineering and space technologies

Year of publication

2023

Published in

Energies

Journal year: 2023 | Journal volume: vol. 16 | Journal number: iss. 18

Article type

scientific article

Publication language

english

Keywords
EN
  • microprocessor power modes
  • embedded systems
  • DVFS
  • NVIDIA Jetson
  • Raspberry Pi
  • video analysis
  • line detection
Abstract

EN 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.

Date of online publication

18.09.2023

Pages (from - to)

6677-1 - 6677-20

DOI

10.3390/en16186677

URL

https://www.mdpi.com/1996-1073/16/18/6677

Comments

Article Number: 6677

License type

CC BY (attribution alone)

Open Access Mode

open journal

Open Access Text Version

final published version

Date of Open Access to the publication

at the time of publication

Ministry points / journal

140

Impact Factor

3

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