Real-Time Data Analytics in Internet of Things Systems

Abstract

AbstractWith the pervasive deployment of the Internet of Things (IoT) technology, the number of connected IoT end devices increases in an explosive trend, which continuously generates a massive amount of data. Real-time analytics of the IoT data can timely provide useful information for decision-making in the IoT systems, which can enhance both system efficiency and reliability. More specifically, real-time data analytics in IoT systems is utilized to effectively process the discrete IoT data series within a bounded completion time and provide services such as data classification, pattern analysis, and tendency prediction. However, the continuous generation of IoT data from heterogeneous devices brings huge technical challenges to real-time analytics. Thus, how to timely process the massive and heterogeneous IoT data needs to be seriously considered in the design of IoT systems. This chapter provides a comprehensive study of real-time data analytics in IoT systems. The characteristics of real-time analytics in IoT systems are firstly elucidated. Suitable architectures of IoT systems that can support real-time data analytics are thoroughly analyzed. Afterward, a comprehensive survey on the existing applications of real-time analytics in IoT systems is conducted from the perspectives of system design and shortcomings of performance. Finally, the main challenges remaining in the application of real-time analytics in IoT systems are pointed out, and the future research directions of related areas are also identified.KeywordsReal-time analyticsBig data analyticsEdge computingCloud computingInternet of Things (IoT)