Abstract
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.
Highlights
Mobile phones are supposed to be carried around and their widespread use accounts for their presence in nearly every situation, their alarm can be a real nuisance, but turning them off is no solution as people might want to receive urgent messages from senders
A mobile device should be able to adapt to the environment and control the device’s settings
Such a system that would help users to avoid irrelevant calls without disturbing others should be available for all mobile phone users
Summary
Mobile phones are supposed to be carried around and their widespread use accounts for their presence in nearly every situation, their alarm can be a real nuisance, but turning them off is no solution as people might want to receive urgent messages from senders. Callers can be grouped according to their relevance and profiles of availability can be specified. All this has to be implemented, activated and changed manually by the user, who might find these activities too cumbersome to use them regularly. A mobile device should be able to adapt to the environment and control the device’s settings. Such a system that would help users to avoid irrelevant calls without disturbing others should be available for all mobile phone users. In order to overcome the problem described above, a system can be implemented, using machine learning algorithms, which is aware of the availability of the user in everyday situations
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