Abstract
We illustrate the application of automated representation of knowledge acquired from sensor network data to quality of life services. Specifically, for a sensor network used to monitor a residential building we acquire knowledge about events of interest to occupants and represent such knowledge in ontology. An event of particular interest to quality of life which we discuss is ‘unhealthy’ exposure to carbon monoxide. Hence, we aim at reducing the considerable gap between raw sensor data and abstract domain terminology. Our results support the claim that computational techniques in signal processing, machine learning, and ontology engineering are important elements to systems that make use of environmental sensing, including systems for quality of life information services.
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Stocker, M., Rönkkö, M., Kolehmainen, M. (2012). Making Sense of Sensor Data Using Ontology: A Discussion for Residential Building Monitoring. In: Iliadis, L., Maglogiannis, I., Papadopoulos, H., Karatzas, K., Sioutas, S. (eds) Artificial Intelligence Applications and Innovations. AIAI 2012. IFIP Advances in Information and Communication Technology, vol 382. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33412-2_35
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DOI: https://doi.org/10.1007/978-3-642-33412-2_35
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