SEIF: A Semantic-enabled IoT Service Framework for Realizing Interoperable Data and Knowledge Retrieval

Abstract

The Internet of Things (IoT) has enabled interconnection of embedded computing devices comprised of their own data models in existing infrastructure. Currently, many IoT platforms provide data modeling and information retrieval services. However, the use of various data models and standards causes interoperability issues. Semantic technologies ease such barriers by providing the means to annotate semantic information as IoT data based on common data models. For this reason, semantics is becoming a growing requirement and a major challenge for IoT service layer platforms. The addition of semantic support empowers IoT systems with enhanced meaning in the data gathered from various devices and vertical silos. This paper presents a semantic IoT framework that includes agile support for adding semantic meaning to data, and for knowledge discovery, semantic validation, and accessibility to IoT data through a standardized semantic query language. The proposed evaluation matrix for a possible enhancement-anddevelopment guideline based on a global IoT standard is measured through smart office use cases comprising different sensor information. This paper provides a detailed description of semantic enablement on IoT platforms, including details of its implementation. The results provide a clear guideline for integrating semantic features into the IoT service layer and for data management.