Paper Info
Title
Scalable continuous object detection and tracking in sensor networks
Abstract
With the advancement of MEMS technologies, sensor networks have opened up broad application prospects. An important issue in wireless sensor networks is object detection and tracking, which typically involves two basic components, collaborative data processing and object location reporting. The former aims to have sensors collaborating in determining a concise digest of object location information, while the latter aims to transport a concise digest to sink in a timely manner. This issue has been intensively studied in individual objects, such as intruders. However, the characteristic of continuous objects has posed new challenges to this issue. Continuous objects can diffuse, increase in size, or split into multiple continuous objects, such as a noxious gas. In this paper, a scalable, topology-control-based approach for continuous object detection and tracking is proposed. Extensive simulations are conducted, which show a significant improvement over existing solutions.
Year
DOI
Venue
2010
10.1016/j.jpdc.2009.12.001
J. Parallel Distrib. Comput.
Keywords
Field
DocType
individual object,wireless sensor network,multiple continuous object,moving objects,sensor network,boundary detection,scalable continuous object detection,important issue,continuous object,object detection,object location reporting,object tracking,wireless sensor networks,continuous object detection,object location information,data processing
Object detection,Wireless network,Data processing,Computer science,Sensor array,Video tracking,Wireless sensor network,Distributed computing,Scalability,Cognitive neuroscience of visual object recognition
Journal
Volume
Issue
ISSN
70
3
Journal of Parallel and Distributed Computing
Citations 
PageRank 
References 
8
0.53
19
Authors
5
Name
Order
Citations
PageRank
Shin-Chih Tu1796.58
Guey-Yun Chang227317.86
Jang-Ping Sheu34173451.70
Wei Li431071.89
Kun-ying Hsieh5695.10