Abstract
In this paper, we propose a method for recognizing the complex activity using audio sensors and the machine learning techniques. To do so, we will look for the patterns of combined monophonic sounds to recognize complex activity. At this time, we use only audio sensors and the machine learning techniques like Deep Neural Network (DNN) and Support Vector Machine (SVM) to recognize complex activities. And, we develop the novel framework to support overall procedures. Through the implementation of this framework, the user can support to increase quality of life of elders’.
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Acknowledgements
This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (NRF-2016 R1D1A1B03932110).
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Kang, J., Kim, J., Kim, K., Sohn, M. (2019). Complex Activity Recognition Using Polyphonic Sound Event Detection. In: Barolli, L., Xhafa, F., Javaid, N., Enokido, T. (eds) Innovative Mobile and Internet Services in Ubiquitous Computing. IMIS 2018. Advances in Intelligent Systems and Computing, vol 773. Springer, Cham. https://doi.org/10.1007/978-3-319-93554-6_66
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DOI: https://doi.org/10.1007/978-3-319-93554-6_66
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