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International Journal of Distributed Sensor Networks
Volume 2012 (2012), Article ID 417830, 8 pages
Research Article

Efficient Sensor Localization Method with Classifying Environmental Sensor Data

Department of Computer Science and Engineering, Konkuk University, Seoul 143-701, Republic of Korea

Received 31 July 2012; Revised 15 October 2012; Accepted 30 October 2012

Academic Editor: Shan Lin

Copyright © 2012 Ae-cheoun Eun and Young-guk Ha. 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.


Sensor location estimation is important for many location-based systems in ubiquitous environments. Sensor location is usually determined using a global positioning system. For indoor localization, methods that use the received signal strength (RSS) of wireless sensors are used instead of a global positioning system because of the lack of availability of a global positioning system for indoor environments. However, there is a problem in determining sensor locations from the RSS: radio signal interference occurs because of the presence of indoor obstacles. To avoid this problem, we propose a novel localization method that uses environmental data recorded at each sensor location and a data classification technique to identify the location of sensor nodes. In this study, we used a wireless sensor node to collect data on various environmental parameters—temperature, humidity, sound, and light. We then extracted some features from the collected data and trained the location data classifier to identify the location of the wireless sensor node.