The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Rangka kerja yang berteori maklumat dan optimum dibangunkan untuk menjejaki penduduk dalam Persekitaran Pintar Heterogen yang sedar Konteks. Masalah pengesanan pemastautin dirumuskan dari segi entropi berwajaran. Rangka kerja ini menyediakan pembelajaran dalam talian yang optimum dan ramalan pergerakan pengguna, lokasi serta segmen laluan yang paling berkemungkinan daripada domain simbolik. Ramalan yang berjaya membantu dalam operasi atas permintaan peranti dalaman automatik di sepanjang laluan dan lokasi masa hadapan pengguna, sekali gus memberikan keselesaan yang diperlukan pada kos yang hampir optimum. Keputusan simulasi menyokong kejayaan ramalan yang tinggi, dengan itu memberikan keselesaan kepada penduduk sambil mengurangkan penggunaan tenaga dan operasi manual.
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Salinan
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
Salinan
@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},}
Salinan
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 -