期刊名称：International Journal of Distributed Sensor Networks
印刷版ISSN：1550-1329
电子版ISSN：1550-1477
出版年度：2012
卷号：2012
DOI：10.1155/2012/417830
出版社：Hindawi Publishing Corporation
摘要：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.
