Toward Data Discovery in Dynamic Smart City Applications.

A smart city leverages the IoT capabilities to ensure the well-being of the inhabitants and their activities in the city. IoT based data collection and data analytics are the fundamental technologies to achieve the goal. Due to the wide varieties of environment conditions and activities that are to be monitored for the urban environment, a large number of sensors of all sorts are deployed across the city and the number of different data streams collected from these sensors can be tremendous. At the same time, different analysis tasks and dynamic queries may be issued and, correspondingly, the relevant data need to be efficiently discovered, retrieved, and analyzed in order to provide the desired answers. As can be seen, how to manage all the IoT data streams to facilitate data discovery can be highly challenging. In this paper, we discuss a set of scenarios to show the importance of data management and discovery in the smart city environment. Then, we present a semantic model for smart city data specification to facilitate data discovery. Finally, we discuss an edge-centric architecture and the data discovery approach for enabling efficient and effective dynamic smart city data analytics.