SLASH: Self-learning and adaptive smart home framework by integrating IoT with big data analytics

Over the last decades, smart home systems have failed to spread widely in every home and be a coherent part of our life like what smartphones did in half this period of time. However, the latest evolution of Internet of Things (IoT) and Big Data analysis gave new insights of smart platforms that can potentially lead to the new dream of `smart cities'. The paper presented a survey such latest technologies that can lead to a new paradigm of a smart home, based on classifying the basic components of such systems and present the previous work in each component. Moreover, SLASH framework is proposed for designing and implementing smart home systems that are both adaptive and self-learning. Our framework suggests integrating IoT across every home with a large network connected to Big Data analyser. Such an engine that supports analysing inhabitants' behaviours on a large-scale can enable a new type of home automation that depends on machine learning and develops on-going automation decision over time. Essentially, this approach holds some challenges that are considered throughout the framework or state for future enhancements.