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Smart Home System Network Architecture

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Smart Grid Inspired Future Technologies

Abstract

A four-tier based Smart Home System is proposed in this paper; this type of network architecture is inspired by both the concept of the Internet of Things (IoT) and Machine to Machine (M2M) technologies. The main purpose of this structure is to establish a centralized resource management system, which can monitor and control each home appliance within a house. This aim and structure can help to overcome the most notable research challenge which is called interoperability of the system. The interoperability can be reflected from how other services such as assisted living and vehicle tracking are able to share and utilize the same resources. One of the structure advantages is to help existing house owners to live in a modern and convenient environment; it is also environmentally friendly by reducing the overall energy consumption within a household. A novel Home System Data Reflect Arc is proposed to minimalize the response time and limit unnecessary data transmission. Finally, with the aid and optimization of wireless sensor networks, a Received Signal Strength Indicator (RSSI) based indoor localization approach is proposed which is novel based on the fact that it does not require specialized implementation, nor does it require people to wear specialized hardware as it is part of a passive device free environment.

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Correspondence to Chenqi Yang .

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© 2017 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Yang, C., Mistretta, E., Chaychian, S., Siau, J. (2017). Smart Home System Network Architecture. In: Hu, J., Leung, V., Yang, K., Zhang, Y., Gao, J., Yang, S. (eds) Smart Grid Inspired Future Technologies. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 175. Springer, Cham. https://doi.org/10.1007/978-3-319-47729-9_18

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  • DOI: https://doi.org/10.1007/978-3-319-47729-9_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-47728-2

  • Online ISBN: 978-3-319-47729-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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