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DISTRIBUTED EDGE AND CONTOUR LINE DETECTION FOR
ENVIRONMENTAL MONITORING WITH WIRELESS SENSOR NETWORKS
by
Pei-kai Liao
A Dissertation Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Ful¯llment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(ELECTRICAL ENGINEERING)
May 2007
Copyright 2007 Pei-kai Liao
Object Description
| Title | Distributed edge and contour line detection for environmental monitoring with wireless sensor networks |
| Author | Liao, Pei-kai |
| Author email | pliao@usc.edu |
| Degree | Doctor of Philosophy |
| Document type | Dissertation |
| Degree program | Electrical Engineering |
| School | Viterbi School of Engineering |
| Date defended/completed | 2007-02-08 |
| Date submitted | 2007 |
| Restricted until | Unrestricted |
| Date published | 2007-04-17 |
| Advisor (committee chair) | Kuo, C.-C. Jay |
| Advisor (committee member) |
Ortega, Antonio Govindan, Ramesh |
| Abstract | Several signal processing problems associated with wireless sensor networks deployed for the monitoring of certain environmental physical phenomena are examined in this research. A couple of distributed algorithms are proposed to extract the essential information of the monitored physical phenomena such as edges and contour lines so that a remote base station may utilize the information for further analysis. These networks often span over a large geographical area and they cannot be adequately monitored or tracked using traditional localization techniques.; Due to different sensing devices of deployed sensor nodes, measured sensor data can take a binary or a scalar value. For a binary field (phenomenon observed through the sensing devices which provide binary outputs only), the edge (or the boundary region) often provides the important information of concern. A new statistical approach together with a false alarm control scheme to edge region detection is proposed to increase the discrimination capability of the true edge line location. Unlike previous work in the literature, no hierarchical network topology and geographical information about sensor nodes are needed. Simulation results demonstrate that the proposed approach has better performance when the noise interference is high and the probing range is small. For a scalar field (phenomenon observed through the sensing devices which are able to provide real-number measurements), the two-dimensional contour lines offer an efficient way to depict its density distribution. Three approaches to contour lines estimation are proposed to provide different levels of system performance for density observation based on the cost of system installment and its computation capability. Simulation results demonstrate that the proposed approaches can extract contour lines of the density distribution well in the presence of sensing and channel noise. |
| Keyword | wireless sensor networks; distributed algorithm; data fusion; edge detection; contour line |
| Language | English |
| Part of collection | University of Southern California dissertations and theses |
| Publisher (of the original version) | University of Southern California |
| Place of publication (of the original version) | Los Angeles, California |
| Publisher (of the digital version) | University of Southern California. Libraries |
| Type | texts |
| Legacy record ID | usctheses-m404 |
| Rights | Liao, Pei-kai |
| Repository name | Libraries, University of Southern California |
| Repository address | Los Angeles, California |
| Repository email | http://www.usc.edu/isd/libraries/services/ask_a_librarian/email/ |
| Filename | etd-Liao-20070417 |
| Archival file | uscthesesreloadpub_Volume14/etd-Liao-20070417.pdf |
Description
| Title | Page 1 |
| Full text | DISTRIBUTED EDGE AND CONTOUR LINE DETECTION FOR ENVIRONMENTAL MONITORING WITH WIRELESS SENSOR NETWORKS by Pei-kai Liao A Dissertation Presented to the FACULTY OF THE GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Ful¯llment of the Requirements for the Degree DOCTOR OF PHILOSOPHY (ELECTRICAL ENGINEERING) May 2007 Copyright 2007 Pei-kai Liao |
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