Sensor network topology estimation using time-series data from infrared human presence sensors

Yuta Watanabe*, Satoshi Kurihara, Toshiharu Sugawara

*この研究の対応する著者

研究成果: Conference contribution

7 被引用数 (Scopus)

抄録

We describe a method for accurately estimating the topology of sensor networks from time-series data collected from infrared proximity sensors. Our method is a hybrid combining two different methodologies: ant colony optimization (ACO), which is an evolutionary computation algorithm; and an adjacency score, which is a novel statistical measure based on heuristic knowledge. We show that, using actual data gathered from a real-world environment, our method can estimate a sensor network topology whose accuracy is approximately 95% in our environment. This is an acceptable result for real-world sensor-network applications.

本文言語English
ホスト出版物のタイトルIEEE Sensors 2010 Conference, SENSORS 2010
ページ664-667
ページ数4
DOI
出版ステータスPublished - 2010
イベント9th IEEE Sensors Conference 2010, SENSORS 2010 - Waikoloa, HI, United States
継続期間: 2010 11 12010 11 4

出版物シリーズ

名前Proceedings of IEEE Sensors

Conference

Conference9th IEEE Sensors Conference 2010, SENSORS 2010
国/地域United States
CityWaikoloa, HI
Period10/11/110/11/4

ASJC Scopus subject areas

  • 電子工学および電気工学

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