Work

Internet of Things: A comprehensive survey on syntactic and semantic interoperability for effective inter-entity communication

Year: 2026

Type: article

Abstract: In the current landscape, the Internet of Things (IoT) represents a fragmented ecosystem, driven by the development of non-interoperable systems, intelligent solutions, and platforms. This fragmentation generates significant challenges for the integration of solutions and the advancement of IoT itself, due to the diversity of protocols, data models, ontologies, technologies, and heterogeneous devices. Interoperability is crucial to unlock the potential of IoT and data-driven solutions by enabling effective communication between the various entities that make up the ecosystem. This paper analyzes IoT standards to establish a structured, multi-layered framework for interoperability to enable a systematic classification of related research. Based on this framework, it presents a comprehensive analysis of the state-of-the-art in IoT interoperability, with a particular emphasis on the syntactic and semantic levels, which are crucial for effective data exchange and communication. This analysis evaluates the most representative proposals in the current literature and identifies the main approaches to achieve an interoperable IoT ecosystem. After their identification, the most suitable approaches for achieving semantic interoperability in the IoT are discussed, with the aim of solving the current fragmentation of the ecosystem, eliminating data silos, and enhancing the achievement of a next-generation IoT. Finally, a novel approach is proposed, based on the development of a system that takes advantage of fuzzy string matching algorithms, and the spatio-temporal semantic nature of the data generated in IoT. This proposal has the potential to solve the current problem, enable communication between entities and intelligent solutions, and lay the foundation for future research in this field.

Source: Array

DOI: 10.1016/j.array.2026.100942

Authors: Mario San Emeterio de la Parte, José-Fernán Martínez-Ortega, Yiting Wang, Sara Lana Serrano

Institution: Universidad Politécnica de Madrid

Language: English

Topic: Semantic Web and Ontologies

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $1,680