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

Document Type

Conference Proceeding

Publication Title

International Journal of Intelligent Systems Technologies and Applications


As mobile devices are becoming equipped with modern sensors, so is the opportunity to develop more intelligent applications in the areas of internetof- 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.

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