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Challenges for Personal Data Stream Management in Smart Buildings

Challenges for Personal Data Stream Management in Smart Buildings
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Author(s): Dennis Geesen (University of Oldenburg, Germany), H. Jürgen Appelrath (University of Oldenburg, Germany), Marco Grawunder (University of Oldenburg, Germany) and Daniela Nicklas (University of Oldenburg, Germany)
Copyright: 2014
Pages: 19
Source title: Creating Personal, Social, and Urban Awareness through Pervasive Computing
Source Author(s)/Editor(s): Bin Guo (Northwestern Polytechnical University, China), Daniele Riboni (University of Milano, Italy) and Peizhao Hu (NICTA, Australia)
DOI: 10.4018/978-1-4666-4695-7.ch009

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Abstract

Smart homes are equipped with multiple sensors and actuators to observe the residents and environmental phenomena, to interpret the situation out of that, and finally, to react accordingly. While the data processing for a single smart home is facile, the data processing for multiple smart homes in one smart building is more complex because there are different people (e.g., like several residents, administrators, or a property management) with different interests concerning the processed data. On that point, this chapter shows which kind of typical roles can be found in a smart building and what requirements and challenges they demand for managing and processing the data. Secondly, Data Stream Management Systems (DSMS) are introduced as an approach for processing and managing data in a smart building by presenting an appropriate architecture. Finally, the chapter discusses further concepts from DSMS and illustrates how they additionally meet and solve the requirements and the challenges.

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