Sensors 2007, 7(8), 1359-1386; doi:10.3390/s7081359
Article

Agent Collaborative Target Localization and Classification in Wireless Sensor Networks

Received: 26 June 2007; Accepted: 27 July 2007 / Published: 30 July 2007
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract: Wireless sensor networks (WSNs) are autonomous networks that have beenfrequently deployed to collaboratively perform target localization and classification tasks.Their autonomous and collaborative features resemble the characteristics of agents. Suchsimilarities inspire the development of heterogeneous agent architecture for WSN in thispaper. The proposed agent architecture views WSN as multi-agent systems and mobileagents are employed to reduce in-network communication. According to the architecture,an energy based acoustic localization algorithm is proposed. In localization, estimate oftarget location is obtained by steepest descent search. The search algorithm adapts tomeasurement environments by dynamically adjusting its termination condition. With theagent architecture, target classification is accomplished by distributed support vectormachine (SVM). Mobile agents are employed for feature extraction and distributed SVMlearning to reduce communication load. Desirable learning performance is guaranteed bycombining support vectors and convex hull vectors. Fusion algorithms are designed tomerge SVM classification decisions made from various modalities. Real world experimentswith MICAz sensor nodes are conducted for vehicle localization and classification.Experimental results show the proposed agent architecture remarkably facilitates WSNdesigns and algorithm implementation. The localization and classification algorithms alsoprove to be accurate and energy efficient.
Keywords: wireless sensor networks; multi-agent system; mobile agent; target localization and classification; support vector machine.
PDF Full-text Download PDF Full-Text [557 KB, uploaded 21 June 2014 00:48 CEST]

Export to BibTeX |
EndNote


MDPI and ACS Style

Wang, X.; Bi, D.-W.; Ding, L.; Wang, S. Agent Collaborative Target Localization and Classification in Wireless Sensor Networks. Sensors 2007, 7, 1359-1386.

AMA Style

Wang X, Bi D-W, Ding L, Wang S. Agent Collaborative Target Localization and Classification in Wireless Sensor Networks. Sensors. 2007; 7(8):1359-1386.

Chicago/Turabian Style

Wang, Xue; Bi, Dao-wei; Ding, Liang; Wang, Sheng. 2007. "Agent Collaborative Target Localization and Classification in Wireless Sensor Networks." Sensors 7, no. 8: 1359-1386.

Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert