Abstract
A smart city requires the intelligent management of infrastructure like the Internet of Things (IoT) devices in order to provide smart services that improve the quality of human life. To obtain the information needed to implement smart city services, stream reasoning is used to intelligently process the big data stream constantly generated from IoT devices. However, there are constraints associated with the real-time processing of large streams of big data from the smart city infrastructure. In this paper, we propose a stream reasoning system model for the smart city application, which was implemented using real-time big data processing technology in the smart city middleware. We use Apache Kafka, a message processing system, and Apache Storm, a real-time distributed processing system, to overcome the constraints associated with real-time processing. We evaluate the performance of our system implementation by measuring the throughput per second and the maximum capacity of the experimental system.
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