Search

The current Internet of Things (IoT) ecosystem consists of non-interoperable products and services. The Web of Things (WoT) advances the IoT by allowing consumers to interact with the IoT ecosystem through the open and standard web technologies. But the Web alone does not solve the interoperability issues. It is widely acknowledged that Semantic Web Technologies hold the potential of achieving data and platform interoperability in both the IoT and WoT landscapes. In this context, the paper attempts to review and analyze the current state of ontology-based software tools for semantic interoperability.

Semantic Web of Things is a new field combining Semantic Web and Internet of Things technologies to be surrounded by smart objects and applications connected to the Web. On one hand, one of the Linked Open Data applications, called DataHub aims at referencing datasets, on the other hand, the Linked Open Vocabularies (LOV) references more than 400 ontologies. However, we discovered that more than 200 ontology-based projects relevant for IoT are not referenced on such tools since domain experts are not aware of them nor of the semantic web best practices. We propose the Machine-to-Machine Measurement (M3) framework, available online, to rapidly design and develop semantic-based cross-domain IoT applications by reusing as much as possible the domain knowledge (ontologies, datasets and rules). To achieve this goal, there are challenging steps: (1) referencing and classifying semantic-based projects relevant for IoT, (2) re-engineering a dataset of interoperable domain rules to deduce high-level abstractions from sensor data, (3) re-engineering an interoperable cross-domain knowledge to combine domains, and (4) assisting developers in designing IoT applications by designing pre-defined templates. In this article, we are focused on referencing and classifying semantic-based projects relevant for IoT by designing the Linked Open Vocabularies for Internet of Things (LOV4IoT) dataset. We also design a dataset of interoperable domain rules to deduce high-level abstractions from sensor data by designing the Sensor-based Linked Open Rules (S-LOR). This work has been applied to two uses cases: (1) redesigning a security and cross-domain knowledge base to assist users in suggesting security mechanisms to secure their applications, and (2) designing semantic-based IoT applications embedded in Android-powered devices.

The Internet of Things (IoT) is driving the technology and advances of the Internet and every day it is becoming more popular to talk about IoT systems in multiple domains: Smart Cities, Agriculture, and Industrial Internet, etc. Increasingly, IoT systems will need to interact and be interconnected for offering the always-promoted everything-connected paradigm. Current IoT systems rely on semantic web technologies for integrating data and ensure web services interoperability. However there are yet a gap to ensure semantic interoperability among IoT systems. Most of the existing proposed (open) approaches and solutions lack on formal methodologies for interoperability in technology and standard format of the data. We studied and analyzed most available semantic-based IoT approaches to identify the main requirements hindering IoT semantic interoperability. In this paper, we present SEG 3.0 a methodology to federate, unify and provide semantic interoperability. SEG 3.0 emerges from methodologies for ontology engineering and the idea of unification and federated systems. We propose SEG 3.0 and apply it to Internet of Things (IoT) and particularly on use cases for smart cities as proof of concept. Firstly, we define characteristics required for the methodology. Secondly, we describe the processes and the different formal steps. Thirdly, we provide a proof of concept framework and architecture applying this methodology, thus the benefits of using SEG 3.0 methodology in IoT domains are described. Finally, we demonstrate that the SEG 3.0 methodology is applied to three use cases: (1) the M3 framework to assist developers in designing semantic-based IoT applications, (2) the VITAL EU project for smart cities, and (3) the FIESTA-IoT EU project for IoT semantic interoperability. SEG 3.0 is a formal methodology generic enough to be applied to other domains than IoT and smart cities, since the main benefit of the SEG 3.0 is integrating heterogeneous data and adding value to it to build innovative applications.

We discuss in this paper, semantic web methodologies, best practices and recommendations beyond the IERC Cluster Semantic Interoperability Best Practices and Recommendations (IERC AC4). The semantic web community designed best practices and methodologies which are unknown from the IoT community. In this paper, we synthesize and highlight the most relevant work regarding ontology methodologies, engineering, best practices and tools that could be applied to Internet of Things (IoT). To the best of our knowledge, this is the first work aiming at bridging such methodologies to the IoT community and go beyond the IERC AC4 cluster. This research is being applied to three uses cases: (1) the M3 framework assisting IoT developers in designing interoperable ontology-based IoT applications, (2) the FIESTA-IoT EU project encouraging semantic interoperability within IoT, and (3) a collaborative publication of legacy ontologies.

International audience; Semantics is becoming a requirement in Internet of Things (IoT). Recent works underline future challenges for IoT: (1) integrate semantic web technologies, (2) provide interoperability, (3) interpret IoT data, (4) ease the development of IoT applications, and (5) fit to the different requirements of people and applications. In this paper, we design a semantic engine to meet these requirements and integrate it in different components available in IoT architectures. To the best of our knowledge, the main novelty of this paper is the semantic engine flexible enough for different IoT architectures where semantics is integrated in: (1) cloud, (2) devices such as smart phones or tablets, and (3) M2M gateways. As proof of concepts, we discuss deployment of the proposed semantic engine at cloud systems and mobile devices. Moreover, we show that such deployments are coherent with ETSI M2M and oneM2M standardizations.