Information Agents for Pervasive Sensor Networks
Information Agents for Pervasive Sensor Networks
In this paper, we describe an information agent, that resides on a mobile computer or personal digital assistant (PDA), that can autonomously acquire sensor readings from pervasive sensor networks (deciding when and which sensor to acquire readings from at any time). Moreover, it can perform a range of information processing tasks including modelling the accuracy of the sensor readings, predicting the value of missing sensor readings, and predicting how the monitored environmental parameters will evolve into the future. Our motivating scenario is the need to provide situational awareness support to first responders at the scene of a large scale incident, and we describe how we use an iterative formulation of a multi-output Gaussian process to build a probabilistic model of the environmental parameters being measured by local sensors, and the correlations and delays that exist between them. We validate our approach using data collected from a network of weather sensors located on the south coast of England.
294-299
Rogers, Alex
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Osborne, Michael A
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Ramchurn, Sarvapali
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Roberts, Stephen J
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Jennings, N. R.
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March 2008
Rogers, Alex
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Osborne, Michael A
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Ramchurn, Sarvapali
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Roberts, Stephen J
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Jennings, N. R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30
Rogers, Alex, Osborne, Michael A, Ramchurn, Sarvapali, Roberts, Stephen J and Jennings, N. R.
(2008)
Information Agents for Pervasive Sensor Networks.
Sixth Annual IEEE International Conference on Pervasive Computing and Communications (PerCom 2008), Hong Kong, China.
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Conference or Workshop Item
(Paper)
Abstract
In this paper, we describe an information agent, that resides on a mobile computer or personal digital assistant (PDA), that can autonomously acquire sensor readings from pervasive sensor networks (deciding when and which sensor to acquire readings from at any time). Moreover, it can perform a range of information processing tasks including modelling the accuracy of the sensor readings, predicting the value of missing sensor readings, and predicting how the monitored environmental parameters will evolve into the future. Our motivating scenario is the need to provide situational awareness support to first responders at the scene of a large scale incident, and we describe how we use an iterative formulation of a multi-output Gaussian process to build a probabilistic model of the environmental parameters being measured by local sensors, and the correlations and delays that exist between them. We validate our approach using data collected from a network of weather sensors located on the south coast of England.
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rogers-InformationAgents.pdf
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Published date: March 2008
Additional Information:
Event Dates: March 2008
Venue - Dates:
Sixth Annual IEEE International Conference on Pervasive Computing and Communications (PerCom 2008), Hong Kong, China, 2008-03-01
Organisations:
Agents, Interactions & Complexity
Identifiers
Local EPrints ID: 264967
URI: http://eprints.soton.ac.uk/id/eprint/264967
PURE UUID: d65d53ab-d683-4744-b4d1-788568a4061d
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Date deposited: 13 Dec 2007 11:18
Last modified: 15 Mar 2024 03:22
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Contributors
Author:
Alex Rogers
Author:
Michael A Osborne
Author:
Sarvapali Ramchurn
Author:
Stephen J Roberts
Author:
N. R. Jennings
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