A Software Framework for Efficient IoT Contexts Acquisition and Big Data Analytics

Abstract

Internet-of-Things (IoT) computing is characterized by the internet connectivity and the capabilities of sensing contexts and controlling actuators. IoT context is a collection of values acquired from IoT devices and their environments, which reveals the same 3 Vs of big data; Volume, Variety, and Velocity. Hence, various methods and tools available for big data analytics can also be applied to process IoT contexts. In this paper, we present a framework for efficiently acquiring and analyzing IoT contexts by utilizing big data approaches. We first discuss characteristics of IoT contexts, and define the requirement of a framework for managing IoT contexts. And, we present the design model and an implementation of the framework. Finally, we show the result of applying the framework in developing Safety Surveillance System for secure buildings.