Context-Aware Resource Management in Heterogenous Smart Environments
Summary :
An information-theoretic, optimal framework is developed for tracking the residents in a Context-aware Heterogenous Smart Environment. The resident-tracking problem is formulated in terms of weighted entropy. The framework provides an optimal, online learning and prediction of users movement, location as well as most probable path segments from the symbolic domain. Successful prediction helps in on-demand operations of automated indoor devices along the users future paths and locations, thus providing the necessary comfort at a near-optimal cost. Simulation results corroborate the high prediction success, thereby providing resident-comfort while reducing energy consumption and manual operations.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E92-B No.1 pp.318-321
- Publication Date
- 2009/01/01
- Publicized
- Online ISSN
- 1745-1345
- DOI
- 10.1587/transcom.E92.B.318
- Type of Manuscript
- LETTER
- Category
- Network
Authors
Keyword
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Abhishek ROY, Navrati SAXENA, Jitae SHIN, "Context-Aware Resource Management in Heterogenous Smart Environments" in IEICE TRANSACTIONS on Communications,
vol. E92-B, no. 1, pp. 318-321, January 2009, doi: 10.1587/transcom.E92.B.318.
Abstract: An information-theoretic, optimal framework is developed for tracking the residents in a Context-aware Heterogenous Smart Environment. The resident-tracking problem is formulated in terms of weighted entropy. The framework provides an optimal, online learning and prediction of users movement, location as well as most probable path segments from the symbolic domain. Successful prediction helps in on-demand operations of automated indoor devices along the users future paths and locations, thus providing the necessary comfort at a near-optimal cost. Simulation results corroborate the high prediction success, thereby providing resident-comfort while reducing energy consumption and manual operations.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.E92.B.318/_p
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@ARTICLE{e92-b_1_318,
author={Abhishek ROY, Navrati SAXENA, Jitae SHIN, },
journal={IEICE TRANSACTIONS on Communications},
title={Context-Aware Resource Management in Heterogenous Smart Environments},
year={2009},
volume={E92-B},
number={1},
pages={318-321},
abstract={An information-theoretic, optimal framework is developed for tracking the residents in a Context-aware Heterogenous Smart Environment. The resident-tracking problem is formulated in terms of weighted entropy. The framework provides an optimal, online learning and prediction of users movement, location as well as most probable path segments from the symbolic domain. Successful prediction helps in on-demand operations of automated indoor devices along the users future paths and locations, thus providing the necessary comfort at a near-optimal cost. Simulation results corroborate the high prediction success, thereby providing resident-comfort while reducing energy consumption and manual operations.},
keywords={},
doi={10.1587/transcom.E92.B.318},
ISSN={1745-1345},
month={January},}
Copy
TY - JOUR
TI - Context-Aware Resource Management in Heterogenous Smart Environments
T2 - IEICE TRANSACTIONS on Communications
SP - 318
EP - 321
AU - Abhishek ROY
AU - Navrati SAXENA
AU - Jitae SHIN
PY - 2009
DO - 10.1587/transcom.E92.B.318
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E92-B
IS - 1
JA - IEICE TRANSACTIONS on Communications
Y1 - January 2009
AB - An information-theoretic, optimal framework is developed for tracking the residents in a Context-aware Heterogenous Smart Environment. The resident-tracking problem is formulated in terms of weighted entropy. The framework provides an optimal, online learning and prediction of users movement, location as well as most probable path segments from the symbolic domain. Successful prediction helps in on-demand operations of automated indoor devices along the users future paths and locations, thus providing the necessary comfort at a near-optimal cost. Simulation results corroborate the high prediction success, thereby providing resident-comfort while reducing energy consumption and manual operations.
ER -
English
