Sunday, November 18, 2007

2.2 A Probabilistic Reasoning Framework for Smart Homes

Todor Dimitrov, Fraunhofer IMS
Josef Pauli, Universität Duisburg-Essen
Edwin Naroska, Fraunhofer IMS

Inference and reasoning in modern AmI (Ambient Intelligence) middlewares is still a complex task. Currently no common patterns for building smart applications can be identified. This paper presents an ongoing effort to build a generic probabilistic reasoning framework for the networked homes. The framework can be utilized for designing smart agents in a systematic and unified way. The developed modeling and reasoning algorithms make an extensive use of the information about the user and the way he/she interacts with the system. To achieve this, several levels of knowledge representation are combined. Each level enriches the domain knowledge in a way that a consistent, user-adaptable probabilistic knowledge base is constructed. The facts in the knowledge base can be used to encode the logic for a specific application scenario.

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Steve Neely said...

This paper will be presented by Todor who says:

I'm a PhD student at the University of Duisburg-Essen in Germany. In
addition, I work as a research associate for the Fraunhofer Instutute IMS where actually the topic of my PhD research comes from. The Fraunhofer IMS operates the inHaus labs ( which are primarily used to do research and development in the areas of ambient assisted living, senior care, ambient intelligence, home automation, etc. With the construction of the new inHaus2 lab, the inHaus campus is to become the world's largest testbed for software and hardware solutions in those areas. The major topics of interest to me are sensor data fusion, knowledge acquisition, knowledge representation.

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