الفهرس | Only 14 pages are availabe for public view |
Abstract Due to the recent deployments of Internet of Things (IoT) technologies in many real-life applications, an enormous amount of diverse data streams are generated. IoT systems are naturally heterogeneous in terms of devices, communication technologies, data formats, protocols, and semantics. As that the generated data from various sources are represented using different semantics, it makes semantic interoperability one of the main challenges facing seamless communication and services over diverse IoT platforms. Semantic technologies help in exchanging semantically annotated information among such heterogeneous applications in a meaningful way. Semantic technologies help to introduce well-explained and machine-encoded definitions of the vocabularies, integrate different datasets, deduce new facts from the existing ones and resolve the issue of data heterogeneity among the data.To facilitate dealing with the heterogeneity of IoT data streams, semantic technologies became the key factor to guarantee data interoperability, with its nature to unify concepts, extend knowledge, and share a machine-readable representation of data. In this thesis, we propose an adaptable approach for IoT data semantic annotation, to achieve an efficient way to enrich data semantically considering its heterogeneity, volume, and frequency |