Journal article
Implementation of Wireless Vision Sensor Node With a Lightweight Bi-Level Video Coding

Authors/Editors
No matching items found.


Research Areas
No matching items found.

Publication Details
Author list: IMRAN M, LAWAL N, O'NILS M, IMRAN M, IMRAN M, Ahmad N, Khursheed K, Malik W, LAWAL N, O'NILS M
Publisher: IEEE Press
Publication year: 2013
Start page: 198
End page: 209
Number of pages: 12
ISSN: 2156-3357
View additional information: View in Web of Science¬ô

Abstract

Wireless vision sensor networks (WVSNs) consist ofa number of wireless vision sensor nodes (VSNs) which have limitedresources i.e., energy, memory, processing, and wireless bandwidth.The processing and communication energy requirements ofindividual VSN have been a challenge because of limited energyavailability. To meet this challenge, we have proposed and implementeda programmable and energy efficient VSN architecturewhich has lower energy requirements and has a reduced designcomplexity. In the proposed system, vision tasks are partitionedbetween the hardware implemented VSN and a server. The initialdata dominated tasks are implemented on the VSN while thecontrol dominated complex tasks are processed on a server. Thisstrategy will reduce both the processing energy consumption andthe design complexity. The communication energy consumption isreduced by implementing a lightweight bi-level video coding on theVSN. The energy consumption is measured on real hardware fordifferent applications and proposed VSN is compared against publishedsystems. The results show that, depending on the application,the energy consumption can be reduced by a factor of approximately1.5 up to 376 as compared to VSN without the bi-level videocoding. The proposed VSN offers energy efficient, generic architecturewith smaller design complexity on hardware reconfigurableplatform and offers easy adaptation for a number of applicationsas compared to published systems.


Projects
No matching items found.

Keywords
No matching items found.

Documents
No matching items found.