Sensor similarity search in the Web of Things

Cuong Truong; Kay Römer; Kai Chen

doi:10.1109/WoWMoM.2012.6263791

Sensor similarity search in the Web of Things

Cuong Truong, Kay Römer, Kai Chen

Institute of Computer Engineering

Institute of Computer Engineering

14 Citations (Scopus)

Abstract

An increasing number of sensors is being connected to the Internet and their output is published on theWeb, resulting in the formation of a Web of Things (WoT) that will soon connect tens of Billions of devices. We propose sensor similarity search, where given a sensor, other sensors on the WoT are found that produced similar output in the past. At the heart of our approach is an algorithm that exploits fuzzy sets for efficiently computing a similarity score for a pair of sensors that is used to obtain a ranked list of matching sensors. Using sensor data sets from real deployments, we find that this approach results in a high accuracy.

Original language	English
Title of host publication	2012 IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks, WoWMoM 2012 - Digital Proceedings
Number of pages	6
Publisher	IEEE
Publication date	24.09.2012
Pages	1-6
Article number	6263791
ISBN (Print)	978-1-4673-1238-7
ISBN (Electronic)	978-1-4673-1239-4
DOIs	https://doi.org/10.1109/WoWMoM.2012.6263791
Publication status	Published - 24.09.2012
Event	13th IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks - San Francisco, United States Duration: 25.06.2012 → 28.06.2012 Conference number: 92704

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This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

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Cite this

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Truong, C, Römer, K & Chen, K 2012, Sensor similarity search in the Web of Things. in 2012 IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks, WoWMoM 2012 - Digital Proceedings., 6263791, IEEE Proceedings, IEEE, pp. 1-6, 13th IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks, San Francisco, California, United States, 25.06.12. https://doi.org/10.1109/WoWMoM.2012.6263791

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Sensor similarity search in the Web of Things

Abstract

UN SDGs

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