An empirical study on mobile phone usage

One of the major scientific undertakings over the past few years has been exploring the interaction between humans and machines in mobile environments. We have smart devices with high computational power. Some devices are also aware of context. For example, some mobile devices have built in GPS, light sensor and other detection devices like [1]. In this work, we will examine how mobile device could predict users’ wishes regarding the push services like incoming mobile phone call. We conducted some experiments in order to get contextual data and then did analysis, a limited number of sensors were tagged to the user which were meant to detect certain characteristics of the environment the users were in, such as light sensor, temperature sensor, surrounding audio/noise level. Our results show that machine learning algorithms were able to classify the instances correctly with a high accuracy rate.