A cross-layer power analysis and profiling of wireless video sensor node platform applications

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Description
Wireless video sensor networks has been examined and evaluated for wide range

of applications comprising of video surveillance, video tracking, computer vision, remote

live video and control. The reason behind importance of sensor nodes is its ease

of implementation, ability to operate in

Wireless video sensor networks has been examined and evaluated for wide range

of applications comprising of video surveillance, video tracking, computer vision, remote

live video and control. The reason behind importance of sensor nodes is its ease

of implementation, ability to operate in adverse environments, easy to troubleshoot,

repair and the high performance level. The biggest challenges with the architectural

design of wireless video sensor networks are power consumption, node failure,

throughput, durability and scalability. The whole project here is to create a gateway

node to integrate between "Internet of things" framework and wireless sensor network.

Our Flexi-Wireless Video Sensor Node Platform (WVSNP) is a low cost, low

power and compatible with traditional sensor network where the main focus was on

maximizing throughput or minimizing node deployment. My task here in this project

was to address the challenges of video power consumption for wireless video sensor

nodes. While addressing the challenges, I performed analysis of predicting the nodes

durability when it is battery operated and to choose appropriate design parameters.

I created a small optimized image to boot up Wandboard DUAL/QUAD board, capture

videos in small/big chunks from the board. The power analysis was performed

for only capturing scenarios, playback of reference videos and, live capturing and realtime

playing of videos on WVSNP player. Each sensor node in sensor network are

battery operated and runs without human intervention. Thus to predict nodes durability,

for dierent video size and format, I have collected power consumption results

and based on this I have provided some recommendation of HW/SW architecture.

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Date Created
2014
Agent