SeeMon: scalable and energy-efficient context monitoring framework for sensor-rich mobile environments

  • Authors:

  • Seungwoo Kang;Jinwon Lee;Hyukjae Jang;Hyonik Lee;Youngki Lee;Souneil Park;Taiwoo Park;Junehwa Song

  • Affiliations:

  • KAIST, Daejeon, South Korea;KAIST, Daejeon, South Korea;KAIST, Daejeon, South Korea;KAIST, Daejeon, South Korea;KAIST, Daejeon, South Korea;KAIST, Daejeon, South Korea;KAIST, Daejeon, South Korea;KAIST, Daejeon, South Korea

  • Venue:
  • Proceedings of the 6th international conference on Mobile systems, applications, and services
  • Year:
  • 2008

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Abstract

Proactively providing services to mobile individuals is essential for emerging ubiquitous applications. The major challenge in providing users with proactive services lies in continuously monitoring their contexts based on numerous sensors. The context monitoring with rich sensors imposes heavy workloads on mobile devices with limited computing and battery power. We present SeeMon, a scalable and energy-efficient context monitoring framework for sensor-rich, resource-limited mobile environments. Running on a personal mobile device, SeeMon effectively performs context monitoring involving numerous sensors and applications. On top of SeeMon, multiple applications on the device can proactively understand users' contexts and react appropriately. This paper proposes a novel context monitoring approach that provides efficient processing and sensor control mechanisms. We implement and test a prototype system on two mobile devices: a UMPC and a wearable device with a diverse set of sensors. Example applications are also developed based on the implemented system. Experimental results show that SeeMon achieves a high level of scalability and energy efficiency.