• Journal of Information Processing Systems
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• v.14 no.4
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• pp.948-960
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• 2018

Many mobile sensing frameworks have been developed to help researcher doing their mobile sensing research. However, energy consumption is still an issue in the mobile sensing research, and the existing frameworks do not provide enough solution for solving the issue. We have surveyed several mobile sensing frameworks and carefully chose one framework to improve. We have designed an adaptive sampling module for a mobile sensing framework to help solve the energy consumption issue. However, in this study, we limit our design to an adaptive sampling module for the location and motion sensors. In our adaptive sampling module, we utilize the significant motion sensor to help the adaptive sampling. We experimented with two sampling strategies that utilized the significant motion sensor to achieve low-power consumption during the continuous sampling. The first strategy is to utilize the sensor naively only while the second one is to add the duty cycle to the naive approach. We show that both strategies achieve low energy consumption, but the one that is combined with the duty cycle achieves better result.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.9
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• pp.621-628
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• 2013

This paper presents a framework for context-aware smart phone applications based on Android. The mobile context-aware system is composed of a low level context collection module, a high level context generation module and a service provision module. Existing android system cannot provide an appropriate application framework to integrate these independent modules. In this paper, we provide an application framework which make each module a component, and provide appropriate services to each component. This framework hides the Android platform, so that the complexity for organical combination can be minimized and the application developers can make the mobile context-aware applications easily.