ReLiSCE: Utilizing Resource-Limited Sensors for Office Activity Context Extraction

Homin Park, Jongjun Park, Hyunhak Kim, Jongarm Jun, Sang Hyuk Son, Taejoon Park, Jeonggil Ko

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

The capability to extract human activity context in a room environment can be used as meaningful feedback for various wireless indoor application systems. Being able to do so with easily installable resource-limited sensing components can even further increase the system's applicability for various purposes. This paper introduces our efforts to design a system consisting of heterogeneous low-cost, resource-limited, wireless sensing platforms for accurately extracting the human activity context from an indoor environment. Specifically, we introduce Resource Limited Sensor-based activity Context Extraction (ReLiSCE), a system consisting of microphone array, passive infra-red (PIR), and illumination sensors that effectively detect the activities that occur in an office (meeting room) environment. The signal processing schemes used in ReLiSCE are designed so that their size and complexity is suitable for the resource limitations that many embedded computing platforms introduce. Using empirical evaluations with a prototype system, we show that despite the simplicity of its data processing schemes, ReLiSCE successfully classifies human activity states in various meeting scenarios. Furthermore, we show that high accuracy is achieved by combining results from heterogeneous sensors. We foresee this paper as a sub-system that interconnects with various application systems for autonomously configuring people's everyday living environments in a more comfortable and energy-efficient manner.

Original languageEnglish
Article number6964784
Pages (from-to)1151-1164
Number of pages14
JournalIEEE Transactions on Systems, Man, and Cybernetics: Systems
Volume45
Issue number8
DOIs
StatePublished - 1 Aug 2015

Bibliographical note

Publisher Copyright:
© 2013 IEEE.

Keywords

  • Computers and information processing software
  • context extraction
  • embedded software
  • low-power signal processing
  • smart environments

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