Proceedings:
Information Refinement and Revision for Decision Making: Modeling for Diagnostics, Prognostics, and Prediction
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Papers from the 2002 AAAI Spring Symposium
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Abstract:
MEMS (microelectronic mechanical systems) sensors make a rich design space of distributed networked sensors viable. They can be deeply embedded in the physical world and spread throughout our environment like "smart dust". Today, networked sensors called Smart Dust motes can be constructed using commercial components on the scale of a square inch in size and a fraction of a watt in power. Highdensity distributed networked sensors have recently been targeted for use in research devoted to the efficient use of energy. Such networks require a large number of sensors for control at different levels. However, in reality, sensor information is always corrupted to some degree by noise and degradation, which vary with operating conditions, environmental conditions, and other factors. To overcome these shortcomings, sensor validation is needed to assess the integrity of the sensor information and adjust or correct as appropriate. Sensor fusion of both disparate and redundant (physical and functional) sensors is essential for control and to achieve high sensor data fidelity. In this paper we have isolated a specific domain within the built environment, and present an influence diagram model by which to answer the decisions concerning how to most efficiently condition that space throughout the day. Key issues include the aggregation of heterogeneous information, management of uncertainty at various levels, appropriateness assessment of current validation and fusion algorithms, temporal changes and decision-making strategies.
Spring
Papers from the 2002 AAAI Spring Symposium