Mobile Data Mining Using Smartphone

Abstract

More and more data mining applications are running on mobile devices such as ‘Tablet PCs’, smart phones and
Personal Digital Assistants (PDAs). The ability to make phone calls and send SMS messages nowadays seems to be merely an additional
feature rather than the core functionality of a smart phone. Smartphone’s offer a wide variety of sensors such as cameras and
gyroscope as well as network technologies such as Bluetooth, and Wi-Fi with which a variety of different data can be generated, received
and recorded. Furthermore smartphones are computationally able to perform data analysis tasks on these received, or sensed data such
as data mining. Many data mining technologies for smartphones are tailored for data streams due to the fact that sensed data is usually
received and generated in real-time, and due to the fact that limited storage capacity on mobile devices requires that the data is
analyzed and mined on the fly while it is being generated or received. For example, the Open Mobile Miner (OMM) tool allows the
implementation of data mining algorithms for data streams that can be run on smartphones. However, to the best of our knowledge, all
existing data mining systems for mobile devices either facilitate data mining on a single node or follow a centralized approach where
data mining results are communicated back to a server which makes decisions based on the submitted results.