Title: Learning human-mobile nearness with multiple sensors data from steady and non-steady spaces

Authors: Sylvester Olubolu Orimaye; Chen Hui Lee; Eddy Cheng Han Ng

Addresses: School of Information Technology, Monash University Malaysia, Jalan Lagoon Selatan, 47500 Bandar Sunway, Selangor Darul Ehsan, Malaysia ' School of Information Technology, Monash University Malaysia, Jalan Lagoon Selatan, 47500 Bandar Sunway, Selangor Darul Ehsan, Malaysia ' School of Information Technology, Monash University Malaysia, Jalan Lagoon Selatan, 47500 Bandar Sunway, Selangor Darul Ehsan, Malaysia

Abstract: As mobile devices are becoming equipped with modern sensors, so is the opportunity to develop more intelligent applications in the areas of internet of-things (IoT) and ambient health intelligence using intelligent data analysis techniques. As such, we present the results of our study on recognising nearness of the human body to a mobile device in a three-dimensional space without having any physical contact with the device. The nearness recognition is done by analysing data from several sensors that are available on a mobile device. We show that the human body generates wave patterns that interact with other naturally occurring ambient signals that could be measured by a mobile device, such as, temperature, humidity, magnetic field, acceleration, gravity, and light. This interaction consequentially alters the patterns of the naturally occurring signals in a steady space to form a non-steady space, and thus, exhibits characteristics that could be learned to predict the nearness of the human body to a mobile device with good accuracy.

Keywords: sensor mining; data mining; nearness recognition; proximity recognition; mobile sensors; human-mobile nearness; multiple sensors; multi-sensor data; steady spaces; non-steady spaces; internet of-things; IoT; ambient intelligence; mobile devices; human body; wave patterns; signal interaction.

DOI: 10.1504/IJISTA.2017.081313

International Journal of Intelligent Systems Technologies and Applications, 2017 Vol.16 No.1, pp.32 - 52

Accepted: 03 May 2016
Published online: 04 Jan 2017 *

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