Survey on Prediction Algorithms in Smart Homes

TLDR

Smart homes use numerous sensors to monitor and actuate spaces, generating data that can automate tasks with minimal disruption; to provide these services, systems must predict future events. The study examines the requirements for smart home predictions and reviews proposed algorithms. The authors compare these algorithms on their features and models. Prediction algorithms supply the intelligence needed for smart homes.

Abstract

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.