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 journalArticle

8 Citations (Scopus)

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
Publication statusPublished - 2015 Aug 1

Fingerprint

Sensors
Microphones
Signal processing
Lighting
Infrared radiation
Feedback
Costs

All Science Journal Classification (ASJC) codes

  • Software
  • Control and Systems Engineering
  • Human-Computer Interaction
  • Computer Science Applications
  • Electrical and Electronic Engineering

Cite this

Park, Homin ; Park, Jongjun ; Kim, Hyunhak ; Jun, Jongarm ; Hyuk Son, Sang ; Park, Taejoon ; Ko, Jeonggil. / ReLiSCE : Utilizing Resource-Limited Sensors for Office Activity Context Extraction. In: IEEE Transactions on Systems, Man, and Cybernetics: Systems. 2015 ; Vol. 45, No. 8. pp. 1151-1164.
@article{22d208269fdf43848c90cb8ee69f6bcc,
title = "ReLiSCE: Utilizing Resource-Limited Sensors for Office Activity Context Extraction",
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.",
author = "Homin Park and Jongjun Park and Hyunhak Kim and Jongarm Jun and {Hyuk Son}, Sang and Taejoon Park and Jeonggil Ko",
year = "2015",
month = "8",
day = "1",
doi = "10.1109/TSMC.2014.2364560",
language = "English",
volume = "45",
pages = "1151--1164",
journal = "IEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans",
issn = "1083-4427",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "8",

}

ReLiSCE : Utilizing Resource-Limited Sensors for Office Activity Context Extraction. / Park, Homin; Park, Jongjun; Kim, Hyunhak; Jun, Jongarm; Hyuk Son, Sang; Park, Taejoon; Ko, Jeonggil.

In: IEEE Transactions on Systems, Man, and Cybernetics: Systems, Vol. 45, No. 8, 6964784, 01.08.2015, p. 1151-1164.

Research output: Contribution to journalArticle

TY - JOUR

T1 - ReLiSCE

T2 - Utilizing Resource-Limited Sensors for Office Activity Context Extraction

AU - Park, Homin

AU - Park, Jongjun

AU - Kim, Hyunhak

AU - Jun, Jongarm

AU - Hyuk Son, Sang

AU - Park, Taejoon

AU - Ko, Jeonggil

PY - 2015/8/1

Y1 - 2015/8/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84937696493&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84937696493&partnerID=8YFLogxK

U2 - 10.1109/TSMC.2014.2364560

DO - 10.1109/TSMC.2014.2364560

M3 - Article

AN - SCOPUS:84937696493

VL - 45

SP - 1151

EP - 1164

JO - IEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans

JF - IEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans

SN - 1083-4427

IS - 8

M1 - 6964784

ER -