Detecting situations from heterogeneous internet of things data in smart city context

Abstract

Internet of Things (IoT) offers a lot of benefits for building smart city today and tomorrow. In a smart city, large number of heterogeneous IoT devices are likely to be embedded, which will generate huge volume of data with different formats. Therefore, it is a challenge to address such IoT data heterogeneity and process them together to support decision makers with information of interest. This paper provides a framework to achieve this goal. Our experiment shows that the information obtained from raw IoT data provides situational awareness for the decision makers of smart city in a seamless fashion.