Abstract
This paper presents a general Semantic Smart World framework (SSWF), to cover the Migratory birds’ paths. This framework combines semantic and big data technologies to support meaning for big data. In order to build the proposed smart world framework, technologies such as cloud computing, semantic technology, big data, data visualization, and the Internet of Things are hybrid. We demonstrate the proposed framework through a case study of automatic prediction of air quality index and different weather phenomena in the different locations in the world. We discover the association between air pollution and increasing weather conditions. The experimental results indicate that the framework performance is suitable for heterogeneous big data.
Highlights
Migratory birds can move from one place to another without borders between countries; so, we need to use the concept of “Smart World”
E rapid evolution of Information and Communication Technologies (ICT) and the Internet of ings (IoT) has impacted cities in the physical infrastructure, buildings, transportation systems, governance, environmental monitoring, healthcare, etc. e integration of devices, platforms, and applications using ICT is of great signi cance to smart cities [1]
Other authors focus on a set of Information and Communication Technology (ICT) tools to integrate the Smart City environment [2]
Summary
Migratory birds can move from one place to another without borders between countries; so, we need to use the concept of “Smart World”. An important issue is how to build a generic smart world framework to support all dimensions of any city regardless of its size and characteristics. Many frameworks have been proposed in di erent dimensions of smart cities including transportation [4], environment [5], energy [6], social [7], economy [8], and public safety and security [9]. Most of these frameworks did not include semantic interpretation of the results and focused on speci c domains.
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