MSF: An Efficient Mobile Phone Sensing Framework

Recent evolutions in smartphones, today provided with several sensors, have the strong processing capabilities needed to extract from raw sensed data sensor meaningful high-level views of the physical context around the user. A new promising research area called mobile sensing promotes completely decentralized sensing based on smartphone capabilities only. However, current mobile sensing solutions are not very mature; yet, because they are based on ad hoc software solutions tailored to one specific technical problem (e.g., power management, resource locking, etc.), they are difficult to reuse and integrate in different projects, and they do not focus on the performance efficiency of the monitoring support. To overcome those limitations, this paper proposes Mobile Sensing Framework (MSF), a flexible platform to ease the development of mobile sensing applications through the definition of a common set of facilities that mask all low-level technical details in reading and processing raw sensor data. MSF has been optimized also to enhance performances for Android-based systems, and we report an extensive set of experimental results that assess our architecture and quantitatively compare it with a selection of other mobile sensing systems by showing that MSF outperforms them by presenting lower CPU usage and memory footprints.