NDLI: MobiS: a distributed paradigm of mobile sensor data analytics for evaluating environmental exposures

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MobiS: a distributed paradigm of mobile sensor data analytics for evaluating environmental exposures

Content Provider	ACM Digital Library
Author	Bae, Kye Y. Narayanappa, Sada Alkobaisi, Shayma Bae, Wan D.
Abstract	Continued advances and cost reduction in personal mobile devices such as smart phones made them widely used in daily-life practices. Mobile devices can be integrated with a growing set of cheap powerful embedded sensors that enable the emergence of mobile sensing applications, including healthcare, environmental monitoring and transportation. As the size of the sensor data continuously grows, managing the data becomes increasingly difficult using traditional database systems. This paper proposes a new framework for large-scale continuously changing mobile sensor data analysis. We discuss the emerging environmental sensing paradigms and opportunities to apply HBase and MapReduce for managing multiple sensor data in the environmental exposome domain. Moreover, we provide an architectural framework and present a concrete use case with a set of data models, spatio-temporal queries, and MapReduce functions.
Starting Page	93
Ending Page	96
Page Count	4
File Format	PDF
ISBN	9781450316996
DOI	10.1145/2442810.2442827
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2012-11-06
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Environmental exposome Health monitoring Mobile sensor data Hadoop Mapreduce Hbase
Content Type	Text
Resource Type	Article

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