Short-Term Prediction-Based Optimistic Object Tracking Strategy in Wireless Sensor Networks

Authors:
Jenq Muh Hsu;Chao Chun Chen;Chia Chi Li
Affiliations:
-;-;-
Venue:
IMIS '11 Proceedings of the 2011 Fifth International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing
Year:
2011

Citing 0
Cited 2

POOT: An efficient object tracking strategy based on short-term optimistic predictions for face-structured sensor networks

Computers & Mathematics with Applications
Performance evaluation of selective and adaptive heads clustering algorithms over wireless sensor networks

Journal of Network and Computer Applications

Quantified Score

Hi-index	0.00

Visualization

Abstract

The advance of wireless sensor networks enables a great amount of applications in various areas, such as biology, military, environment surveillance. Among these applications, the object tracking system is one of killer functions, and has been studied by researchers in recent years. In the design of a sensor network system, the energy consumption is one of the most critical considerations. In this paper, we propose a short-term prediction-based optimistic object tracking (POOT) strategy to reduce energy consumption and prolong the lifetime for sensor nodes by sacrificing only slight tracking precision. Through a set of conducted experiments, our proposed prediction-based optimistic object tracking scheme indeed effectively conserve energy and completely achieve the mission of tracking moving object simultaneously.