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The world has entered into a “smart” era. One area becoming smart is the place where we live-homes. Smart homes are expected to be equipped with numerous sensors to continually monitor, sense, and actuate the space. The data from these sensors can be used to provide various types of services by automating common tasks while causing minimal disruption to daily life. In order to provide these services, a system must have sufficient intelligence to predict future events based on its observations. This paper first examines the requirements for smart home predictions. It then comprehensively reviews prediction algorithms and variations that have been proposed and investigated in smart environments, such as smart homes. It is these prediction algorithms that provide the intelligence required by a smart home. Comparisons are also made upon these prediction algorithms on their features and models.
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Shaoen Wu
Kennesaw State University
Jacob Rendall
University of Notre Dame
Matthew J. Smith
Worcester Polytechnic Institute
IEEE Internet of Things Journal
Montana State University
Nanjing University of Information Science and Technology
Ball State University
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Wu et al. (Mon,) studied this question.
synapsesocial.com/papers/6a0f026953f874f2b2231060 — DOI: https://doi.org/10.1109/jiot.2017.2668061