Home // ICIW 2013, The Eighth International Conference on Internet and Web Applications and Services // View article
Authors:
Jong Yoon
Keywords: microcontroller;smartphone; wireless sensor networks; big data
Abstract:
As smartphones become an emerging interface platform between humans and systems, they also enable wireless sensors to interface with host servers. As sensors monitor application domains and sensor data is frequently polled and transmitted to a host server, the server data will be a big volume, big variety and big velocity, which is the characteristic of big data. Mining patterns from big data is a very important and active research topic since it can be used to forecast and “nowcast” for any dynamisms in application domains. However, typical data mining algorithms are not successful yet due to the characteristics of big data. This paper describes three-tied data mining paradigm. Alongside the streamline of sensor data transmission, at the microcontroller tier, sensor data sets are mined to form patterns, at the smartphone tier, negative and positive patterns are grouped and verified, and finally at the host server tier, human expertise is associated with the patterns. The contribution includes 1) lowering data transmission by mining from the lower tiers, 2) mining time-critical data earlier than it would be done at the host server tier and 3) hence urgent responses can be made timely at the proper tier.
Pages: 18 to 24
Copyright: Copyright (c) IARIA, 2013
Publication date: June 23, 2013
Published in: conference
ISSN: 2308-3972
ISBN: 978-1-61208-280-6
Location: Rome, Italy
Dates: from June 23, 2013 to June 28, 2013