Abstract
| Language | English |
|---|---|
| Title of host publication | Unknown Host Publication |
| Pages | 1-6 |
| Number of pages | 6 |
| Publication status | Published - 2007 |
| Event | IEEE SMC UK&RI 6th Conference on Cybernetic Systems - University College Dublin Duration: 1 Jan 2007 → … |
Conference
| Conference | IEEE SMC UK&RI 6th Conference on Cybernetic Systems |
|---|---|
| Period | 1/01/07 → … |
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An approach to dealing with uncertainty in context-aware pervasive systems. / Clear, AK; Dobson, S; Nixon, P.
Unknown Host Publication. 2007. p. 1-6.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - An approach to dealing with uncertainty in context-aware pervasive systems
AU - Clear, AK
AU - Dobson, S
AU - Nixon, P
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 and imperfect 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-grained events 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 with uncertainty 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 and imperfect 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-grained events 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 with uncertainty at the level of situations that takes into account the severity of the behaviour that it is triggering.
KW - n/a
M3 - Conference contribution
SP - 1
EP - 6
BT - Unknown Host Publication
ER -