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An approach to dealing with uncertainty in context-aware pervasive systems

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Published

Standard

An approach to dealing with uncertainty in context-aware pervasive systems. / Clear, Adrian; Dobson, Simon.
Proceedings of the UK/IE IEEE SMC Cybernetic Systems Conference. 2007.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Harvard

Clear, A & Dobson, S 2007, An approach to dealing with uncertainty in context-aware pervasive systems. in Proceedings of the UK/IE IEEE SMC Cybernetic Systems Conference. <http://www.adrianclear.com/papers/clear_uncert.pdf>

APA

Clear, A., & Dobson, S. (2007). An approach to dealing with uncertainty in context-aware pervasive systems. In Proceedings of the UK/IE IEEE SMC Cybernetic Systems Conference http://www.adrianclear.com/papers/clear_uncert.pdf

Vancouver

Clear A, Dobson S. An approach to dealing with uncertainty in context-aware pervasive systems. In Proceedings of the UK/IE IEEE SMC Cybernetic Systems Conference. 2007

Author

Clear, Adrian ; Dobson, Simon. / An approach to dealing with uncertainty in context-aware pervasive systems. Proceedings of the UK/IE IEEE SMC Cybernetic Systems Conference. 2007.

Bibtex

@inproceedings{6ff1c4c155d84c90803aea0a3f3f7717,
title = "An approach to dealing with uncertainty in context-aware pervasive systems",
abstract = "Pervasive computing introduces complex systems consisting of many users, sensors, and applications that should react to context data, provide services, and manipulate devices in a predictable and reliable manner. Context data sensed from the environment is largely uncertain due to lack of precision andimperfect or faulty sensors. Uncertainty is generally dealt with at the level of individual context data. Due to the difficulties associated with catering for data of such fine granularity in applications, the environment can be divided into larger chunks of context called situations. Situations, comprising of finer-grainedevents in the form of context data, warrant a different approach to dealing with uncertainty. Furthermore, we demonstrate that the uncertainty threshold of an event that triggers a behaviour is determined by the severity of the behaviour, making this task non-trivial. In this paper we detail an approach to dealing withuncertainty at the level of situations that takes into account the severity of the behaviour that it is triggering.",
author = "Adrian Clear and Simon Dobson",
year = "2007",
language = "English",
booktitle = "Proceedings of the UK/IE IEEE SMC Cybernetic Systems Conference",

}

RIS

TY - GEN

T1 - An approach to dealing with uncertainty in context-aware pervasive systems

AU - Clear, Adrian

AU - Dobson, Simon

PY - 2007

Y1 - 2007

N2 - Pervasive computing introduces complex systems consisting of many users, sensors, and applications that should react to context data, provide services, and manipulate devices in a predictable and reliable manner. Context data sensed from the environment is largely uncertain due to lack of precision andimperfect or faulty sensors. Uncertainty is generally dealt with at the level of individual context data. Due to the difficulties associated with catering for data of such fine granularity in applications, the environment can be divided into larger chunks of context called situations. Situations, comprising of finer-grainedevents in the form of context data, warrant a different approach to dealing with uncertainty. Furthermore, we demonstrate that the uncertainty threshold of an event that triggers a behaviour is determined by the severity of the behaviour, making this task non-trivial. In this paper we detail an approach to dealing withuncertainty at the level of situations that takes into account the severity of the behaviour that it is triggering.

AB - Pervasive computing introduces complex systems consisting of many users, sensors, and applications that should react to context data, provide services, and manipulate devices in a predictable and reliable manner. Context data sensed from the environment is largely uncertain due to lack of precision andimperfect or faulty sensors. Uncertainty is generally dealt with at the level of individual context data. Due to the difficulties associated with catering for data of such fine granularity in applications, the environment can be divided into larger chunks of context called situations. Situations, comprising of finer-grainedevents in the form of context data, warrant a different approach to dealing with uncertainty. Furthermore, we demonstrate that the uncertainty threshold of an event that triggers a behaviour is determined by the severity of the behaviour, making this task non-trivial. In this paper we detail an approach to dealing withuncertainty at the level of situations that takes into account the severity of the behaviour that it is triggering.

M3 - Conference contribution/Paper

BT - Proceedings of the UK/IE IEEE SMC Cybernetic Systems Conference

ER -