Mobile sensor data classification for human activity recognition using MapReduce on Cloud

dc.contributor.author Paniagua, Carlos
dc.contributor.author Flores, Huber
dc.contributor.author Srirama, Satish Narayana
dc.date.accessioned 2022-03-27T06:06:09Z
dc.date.available 2022-03-27T06:06:09Z
dc.date.issued 2012-01-01
dc.description.abstract Mobiles are equipped with different sensors like accelerometer, magnetic field, and air pressure meter, which help in the process of extracting context of the user like location, situation etc. However, processing the extracted sensor data is generally a resource intensive task, which can be offloaded to the public cloud from mobiles. This paper specifically targets at extracting useful information from the accelerometer sensor data. The paper proposes the utilization of parallel computing using MapReduce on the cloud for training and recognizing human activities based on classifiers that can easily scale in performance and accuracy. The sensor data is extracted from the mobile, offloaded to the cloud and processed using three different classification algorithms, Iterative Dichotomizer 3, Naive Bayes Classifier and K-Nearest-Neighbors. The MapReduce based algorithms are mentioned in detail along with one of their performance on Amazon cloud. The recognized activities can be used in mobile applications like our Zompopo that utilizes the information in creating an intelligent calendar. © 2012 Published by Elsevier Ltd.
dc.identifier.citation Procedia Computer Science. v.10
dc.identifier.issn 18770509
dc.identifier.uri 10.1016/j.procs.2012.06.075
dc.identifier.uri https://www.sciencedirect.com/science/article/abs/pii/S1877050912004322
dc.identifier.uri https://dspace.uohyd.ac.in/handle/1/9334
dc.subject Accelerometer
dc.subject Classification algorithm
dc.subject MapReduce
dc.subject Middleware
dc.subject Mobile cloud
dc.subject Sensor data
dc.title Mobile sensor data classification for human activity recognition using MapReduce on Cloud
dc.type Conference Proceeding. Conference Paper
dspace.entity.type
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