Wireless sensor networks have increasingly become contributors of very large amounts of data. The recent deployment of wireless sensor networks in Smart City infrastructures has led to very large amounts of data being generated each day across a variety of domains, with applications including environmental monitoring, healthcare monitoring and transport monitoring. To take advantage of the increasing amounts of data there is a need for new methods and techniques for effective data management and analysis to generate information that can assist in managing the utilization of resources intelligently and dynamically. Through this research, a Multi-Level Smart City architecture is proposed based on semantic web technologies and Dempster-Shafer uncertainty theory. The proposed architecture is described and explained in terms of its functionality and some real-time context-aware scenarios.
In order to take advantage of the increasing amounts of data, there is a need for new methods and techniques for an effective data management for the IoT REF .
Smart City Architecture and its Applications Based on IoT
ANT/SEIT
Computer Science