Semantics associates meaning with Internet of Things (IoT) data and facilitates the development of intelligent IoT applications and services. However, the big volume of the data generated by IoT devices and resource limitations of these devices have given rise to challenges for applying semantic technologies. In this article, we present Cloud and edge based IoT architectures for semantic reasoning. We report three experiments that demonstrate how edge computing can facilitate IoT systems in terms of data transfer and semantic reasoning. We also analyze how distributing reasoning tasks between the Cloud and edge devices affects system performance.

Health applications involve many data sources, individuals, and services that work against guarantees that an individual's personal data will not be used without consent. The proposed privacy-centered architecture integrates data security and semantic descriptions into a trust-query framework, enabling the provision of user consent as a service.

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Edge computing paradigm allows computation to be moved from the central high powered Cloud or data center to the edge of the network. This paradigm often enables more efficient data processing near its source and sends only the data and knowledge that have value over the network. Our study focuses on performing semantic reasoning at the edge computing devices, which requires transferring ontologies to the edge devices. This paper presents different representations for transferring Web Ontology language (OWL) version 2 ontologies to the edge. We evaluate different representations in an experimental IoT system with edge nodes and compare lengths of different syntaxes and their computation effort of building models in Cloud and edge computing devices in terms of processing time.