Article ID Journal Published Year Pages File Type
425215 Future Generation Computer Systems 2014 11 Pages PDF
Abstract

•We profile the energy consumption of different computing and communication use cases.•An accelerometer-based method for adaptively managing the use of the WiFi adapter is proposed.•We propose a sensor management strategy for adaptive duty cycling and a data upload strategy for indoor situations.

Continuously identifying a user’s location context provides new opportunities to understand daily life and human behavior. Indoor location systems have been mainly based on WiFi infrastructures which consume a great deal of energy mostly due to keeping the user’s WiFi device connected to the infrastructure and network communication, limiting the overall time when a user can be tracked. Particularly such tracking systems on battery-limited mobile devices must be energy-efficient to limit the impact on the experience of using a phone. Recently, there have been a lot of studies of energy-efficient positioning systems, but these have focused on outdoor positioning technologies. In this paper, we propose a novel indoor tracking framework that intelligently determines the location sampling rate and the frequency of network communication, to optimize the accuracy of the location data while being energy-efficient at the same time. This framework leverages an accelerometer, widely available on everyday smartphones, to reduce the duty cycle and the network communication frequency when a tracked user is moving slowly or not at all. Our framework can work for 14 h without charging, supporting applications that require this location information without affecting user experience.

Related Topics
Physical Sciences and Engineering Computer Science Computational Theory and Mathematics
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