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The Human Face of Ambient Intelligence pp 129–195Cite as

Context Recognition in AmI Environments: Sensor and MMES Technology, Recognition Approaches, and Pattern Recognition Methods

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Part of the book series: Atlantis Ambient and Pervasive Intelligence ((ATLANTISAPI,volume 9))

Abstract

The intent of chapter is to review the state-of-the-art sensor devices, recognition approaches, data processing techniques, and pattern recognition methods underlying context recognition in AmI environments. An overview of the recent advances and future development trends in the area of sensor technology is provided, focusing on novel multi-sensor data fusion techniques and related signal processing methods. In addition, the evolving trend of miniaturization is highlighted, with a focus on MEMS technology and its role in the advancement of sensing and computing devices. The observed future development trends include: the miniaturization of sensing devices, the widespread use of multi sensor fusion techniques and systems, and the increasing applicability of autonomous sensors. As to data processing and pattern recognition methods, emphasis is laid on machine learning probabilistic techniques, particularly in relation to emotional and cognitive context awareness and affective systems.

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    Simon Elias Bibri

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Bibri, S.E. (2015). Context Recognition in AmI Environments: Sensor and MMES Technology, Recognition Approaches, and Pattern Recognition Methods. In: The Human Face of Ambient Intelligence. Atlantis Ambient and Pervasive Intelligence, vol 9. Atlantis Press, Paris. https://doi.org/10.2991/978-94-6239-130-7_4

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  • DOI: https://doi.org/10.2991/978-94-6239-130-7_4

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  • Online ISBN: 978-94-6239-130-7

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