Abstract
In recent years, with IoT(Internet of Things) technology as the main focus, device operation and control technology in smart homes has been attracting considerable attention, and home IoT device management services are being provided by various companies, including communication companies. The smart home manager system manages smart devices used in homes, and it provides only the status value information and control function of the currently registered devices. Thus, unnecessary access procedures occur due to the characteristic of the smart home, which uses a smart device repeatedly for the same purpose. To resolve such shortcomings, in this paper, the Proactive Smart Home Manager has been designed, which can predict and suggest users the next steps to take by user usage pattern analysis and inference via machine learning.
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Park, MH., Jang, YH., Ju, YW., Park, SC. (2018). Design of TensorFlow-Based Proactive Smart Home Managers. In: Park, J., Loia, V., Yi, G., Sung, Y. (eds) Advances in Computer Science and Ubiquitous Computing. CUTE CSA 2017 2017. Lecture Notes in Electrical Engineering, vol 474. Springer, Singapore. https://doi.org/10.1007/978-981-10-7605-3_14
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DOI: https://doi.org/10.1007/978-981-10-7605-3_14
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