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Standalone Sound-Based Mobile Activity Recognition for Ambient Assistance in a Home Environment

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Ambient Intelligence (AmI 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9425))

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Abstract

Developments of ambient assistance systems and energy consumption optimization in home environments are one of the main goals of ambient intelligent systems. In this work we propose a wearable standalone solution, which combines the assistance task and the energy optimization task. For this purpose we develop a real-time mobile sound-based device and activity recognizer that senses the audible part of the environment to support its owner during his daily tasks and to help him optimize them in terms of resource consumption.

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Notes

  1. 1.

    EASY-IMP is a European research project aiming to develop methodologies, tools and platforms for the design and production of personalized meta-products, combining wearable sensors embedded into garment with mobile and cloud computing (www.easy-imp.eu).

References

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Acknowledgement

This work has been partly developed for the EASY-IMPFootnote 1 project funded by the European Union under grant agreement No 609078.

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Authors and Affiliations

  1. DFKI, Kaiserslautern, Germany

    Svilen Dimitrov, Norbert Schmitz & Didier Stricker

Authors
  1. Svilen Dimitrov
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  2. Norbert Schmitz
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  3. Didier Stricker
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Corresponding author

Correspondence to Svilen Dimitrov .

Editor information

Editors and Affiliations

  1. Philips Research, Eindhoven, The Netherlands

    Boris De Ruyter

  2. Hellenic Open University, Patras, Greece

    Achilles Kameas

  3. Institute of Thessaloniki, Alexander Technological Educational, Sindos, Greece

    Periklis Chatzimisios

  4. Hellenic Open University, Patras, Greece

    Irene Mavrommati

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© 2015 Springer International Publishing Switzerland

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Dimitrov, S., Schmitz, N., Stricker, D. (2015). Standalone Sound-Based Mobile Activity Recognition for Ambient Assistance in a Home Environment. In: De Ruyter, B., Kameas, A., Chatzimisios, P., Mavrommati, I. (eds) Ambient Intelligence. AmI 2015. Lecture Notes in Computer Science(), vol 9425. Springer, Cham. https://doi.org/10.1007/978-3-319-26005-1_24

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  • DOI: https://doi.org/10.1007/978-3-319-26005-1_24

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26004-4

  • Online ISBN: 978-3-319-26005-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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