High-Level Design and Implementation of a Home Autonomous System Based on CPS Modeling

High-Level Design and Implementation of a Home Autonomous System Based on CPS Modeling

Basman M. Alhafidh, William H. Allen
Copyright: © 2018 |Pages: 22
DOI: 10.4018/978-1-5225-5510-0.ch006
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Abstract

The process used to build an autonomous smart home system based on cyber-physical systems (CPS) principles has recently received increased attention from researchers and developers. However, there are many challenges to be resolved before designing and implementing such a system. In this chapter, the authors present a high-level design approach that simulates a smart home system by implementing three levels of the 5C architecture used in CPS modeling and uses well-known machine learning algorithms to predict future user actions. The simulation demonstrates how users will interact with the smart home system to make more efficient use of resources. The authors also present results from analyzing real-world user data to validate the accuracy of prediction of user actions. This research illustrates the benefits of considering CPS principles when designing a home autonomous system that reliably predicts a user's needs.
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Background

Cyber-Physical System (CPS) has become a very interesting field for many researchers, and the United States government labeled CPS as one of its strategic developments in 2007 (Kao, Jin, Siegel, & Lee, 2015). CPS have been defined as” engineered systems that are built from, and depend upon, the seamless integration of computational and physical components” (Horvath & Gerritsen, 2012). Other researchers present CPS as software and hardware elements which are connected together for a certain purpose by saying:” A Cyber-physical system can be viewed as an advanced collaborative collection of both software and physical entities which share data, information, and knowledge to achieve a function (which can be technical, service, or social in nature)” (Lu & Cecil, 2016). CPS can be applied to many research topics including, but not limited to, Swarm Robotics, Sensor Networks, Automotive, Aviation, Internet of Things (IoT), and the Smart Home, which can represent the basic unit in a Smart City (Alhafidh & Allen, 2016; Kao et al., 2015; Hu, 2013).

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