MACHINE LEARNING IN INTERNET OF THINGs

IoT have the potential to revolutionize the way we view and sense the physical world in the area of Health, Governance, Buildings (Smart Building and Smart Houses), Security, exploration of the universe, etc. But this revolution can only be effective with Machine Learning in the core of analyzing IoT “Big Data”. After all, “of what use then is harvesting huge amount of data across the globe if we cannot analyze them to make predictive decisions for a future that is uncertain and dynamic”. IoT is the concept of everyday objects from industrial machines to wearable devices using built in sensors to gather data and take actions on that data across a network. At this stage of technology, it is unclear whether we have optimal machine learning algorithm to process and handle such huge amount of future data. But big cooperation’s like Google, Facebook, Amazon, etc are already taking the stage to address this issues, thus, we need to optimize machine learning algorithms to take over this data analyses, because we are not going to be able to have a human interface every time we want something to prove with analyzing IoT data and because most IoT data are real-time which can prove difficult for humans to process and analyze. This seminar work is to outline the concert of Machine Learning and how it has and will accept analysis and processing of IoT data (Big Data).