Open AccessThis article is
- freely available
Agent Collaborative Target Localization and Classification in Wireless Sensor Networks
State Key Laboratory of Precision Measurement Technology and Instrument, Tsinghua University, Beijing 100084, P. R. China
* Author to whom correspondence should be addressed.
Received: 26 June 2007; Accepted: 27 July 2007 / Published: 30 July 2007
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.
Article StatisticsClick here to load and display the download statistics.
Notes: Multiple requests from the same IP address are counted as one view.
Cite This Article
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.
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.
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.