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Specification and synthesis of sensory datasets in pervasive spaces

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Specification and synthesis of sensory datasets in pervasive spaces. / Helal, Sumi; Andres, M.-V.; Hossain, S.
IEEE Symposium on Computers and Communications 2009, ISCC 2009. IEEE, 2009. p. 920-925.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

Harvard

Helal, S, Andres, M-V & Hossain, S 2009, Specification and synthesis of sensory datasets in pervasive spaces. in IEEE Symposium on Computers and Communications 2009, ISCC 2009. IEEE, pp. 920-925. https://doi.org/10.1109/ISCC.2009.5202263

APA

Helal, S., Andres, M-V., & Hossain, S. (2009). Specification and synthesis of sensory datasets in pervasive spaces. In IEEE Symposium on Computers and Communications 2009, ISCC 2009 (pp. 920-925). IEEE. https://doi.org/10.1109/ISCC.2009.5202263

Vancouver

Helal S, Andres M-V, Hossain S. Specification and synthesis of sensory datasets in pervasive spaces. In IEEE Symposium on Computers and Communications 2009, ISCC 2009. IEEE. 2009. p. 920-925 doi: 10.1109/ISCC.2009.5202263

Author

Helal, Sumi ; Andres, M.-V. ; Hossain, S. / Specification and synthesis of sensory datasets in pervasive spaces. IEEE Symposium on Computers and Communications 2009, ISCC 2009. IEEE, 2009. pp. 920-925

Bibtex

@inproceedings{8b04ab6eecbc48e9ae6f3b4d6a5e211d,
title = "Specification and synthesis of sensory datasets in pervasive spaces",
abstract = "The generation of actual sensory data in real-world deployments of pervasive spaces is very costly and requires significant preparation and access to human subjects. This situation can be mitigated if practical forms of sharing of existing datasets are enabled among the research community. In this paper we address two main problems. First, we propose a standard for the representation of smart space datasets, based on a careful examination of several existing data. The standard specification should allow researchers to effortlessly position their existing or future datasets for sharing. We briefly present the specifications. Second, to enable higher utility of shared datasets, we propose algorithms and tools that can extend a shared dataset into a similar set of a slightly customized pervasive space (e.g., an original space with additional sensors/actuators or behaviors). Specifically, we propose the use of machine learning algorithms to generate the additional patterns of events and to automatically integrate them into the original shared dataset. {\textcopyright} 2009 IEEE.",
keywords = "Event simulation, Markov chain, Poisson process, Sensor data schema, Sensory dataset, Standard data representation, State machine, Contour followers, Learning systems, Markov processes, Poisson distribution, Poisson equation, Sensors, Specifications, Standards, Ubiquitous computing, Learning algorithms",
author = "Sumi Helal and M.-V. Andres and S. Hossain",
year = "2009",
doi = "10.1109/ISCC.2009.5202263",
language = "English",
isbn = "9781424446728",
pages = "920--925",
booktitle = "IEEE Symposium on Computers and Communications 2009, ISCC 2009",
publisher = "IEEE",

}

RIS

TY - GEN

T1 - Specification and synthesis of sensory datasets in pervasive spaces

AU - Helal, Sumi

AU - Andres, M.-V.

AU - Hossain, S.

PY - 2009

Y1 - 2009

N2 - The generation of actual sensory data in real-world deployments of pervasive spaces is very costly and requires significant preparation and access to human subjects. This situation can be mitigated if practical forms of sharing of existing datasets are enabled among the research community. In this paper we address two main problems. First, we propose a standard for the representation of smart space datasets, based on a careful examination of several existing data. The standard specification should allow researchers to effortlessly position their existing or future datasets for sharing. We briefly present the specifications. Second, to enable higher utility of shared datasets, we propose algorithms and tools that can extend a shared dataset into a similar set of a slightly customized pervasive space (e.g., an original space with additional sensors/actuators or behaviors). Specifically, we propose the use of machine learning algorithms to generate the additional patterns of events and to automatically integrate them into the original shared dataset. © 2009 IEEE.

AB - The generation of actual sensory data in real-world deployments of pervasive spaces is very costly and requires significant preparation and access to human subjects. This situation can be mitigated if practical forms of sharing of existing datasets are enabled among the research community. In this paper we address two main problems. First, we propose a standard for the representation of smart space datasets, based on a careful examination of several existing data. The standard specification should allow researchers to effortlessly position their existing or future datasets for sharing. We briefly present the specifications. Second, to enable higher utility of shared datasets, we propose algorithms and tools that can extend a shared dataset into a similar set of a slightly customized pervasive space (e.g., an original space with additional sensors/actuators or behaviors). Specifically, we propose the use of machine learning algorithms to generate the additional patterns of events and to automatically integrate them into the original shared dataset. © 2009 IEEE.

KW - Event simulation

KW - Markov chain

KW - Poisson process

KW - Sensor data schema

KW - Sensory dataset

KW - Standard data representation

KW - State machine

KW - Contour followers

KW - Learning systems

KW - Markov processes

KW - Poisson distribution

KW - Poisson equation

KW - Sensors

KW - Specifications

KW - Standards

KW - Ubiquitous computing

KW - Learning algorithms

U2 - 10.1109/ISCC.2009.5202263

DO - 10.1109/ISCC.2009.5202263

M3 - Conference contribution/Paper

SN - 9781424446728

SP - 920

EP - 925

BT - IEEE Symposium on Computers and Communications 2009, ISCC 2009

PB - IEEE

ER -