Semantic Web and Internet of Things: Challenges, Applications and Perspectives


  • Fatima Zahra Amara 1)University of Abbes Laghrour, Khenchela, Algeria, 2)ICOSI Laboratory, Khenchela, Algeria
  • Mounir Hemam 1)University of Abbes Laghrour, Khenchela, Algeria, 2) ICOSI Laboratory, Khenchela, Algeria
  • Meriem Djezzar 1) University of Abbes Laghrour, Khenchela, Algeria, 2)LIRE Laboratory, Constantine, Algeria
  • Moufida Maimor University of Lorraine, CNRS, CRAN, F-54000 Nancy, France



Internet of Things, semantic Web technologies, semantic interoperability, ontology, heterogeneous data, linked data


The apparent growth of the internet of things (IoT) has allowed its deployment in many domains. The IoT devices sense their surroundings and transmit the data via the Web. According to statistics, due to the proliferation of smart devices, the number of active IoT devices is expected to exceed 25.4 billion by 2030.1 A large number of IoT objects gather an enormous amount of raw data. The data generated by various IoT objects and sensors are heterogeneous, with varying types and formats. Therefore, it is difficult for IoT systems to share and reuse raw IoT data, which causes the problem of lack of interoperability. The lack of interoperability in IoT systems creates a problematic issue that prevents IoT systems from performing well. To address this issue, data modeling and knowledge representation using semantic web technologies may be an appropriate solution to give meaning to raw IoT data and convert it to an enriched data format. The primary goal of this research section is to highlight the best outcomes for semantic interoperability among IoT systems, which can serve as a guideline for future studies via the presentation of a literature review on semantic interoperability for Internet of Things systems, including challenges, prospects, and recent work. The paper also provides an overview of the application of semantic web technologies in IoT systems, such as specific ontologies, frameworks, and application domains that use semantic technologies in the IoT areas to solve interoperability and heterogeneity problems.


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Author Biographies

Fatima Zahra Amara, 1)University of Abbes Laghrour, Khenchela, Algeria, 2)ICOSI Laboratory, Khenchela, Algeria

Fatima Zahra Amara is a Ph.D. student in Computer Sciences, in Security and Web Technologies specialty, at Abbas Laghrour Khenchela University, Algeria. Fatima Zahra obtained his Master’s degree and License’s degree at the same university. His research interest includes semantic interoperability, Internet of Things, Knowledge representation, and semantic reasoning.

Mounir Hemam, 1)University of Abbes Laghrour, Khenchela, Algeria, 2) ICOSI Laboratory, Khenchela, Algeria

Mounir Hemam is an Associate Professor at University of Khenchela Algeria. He has completed PhD degree in Computer sciences from Mentouri University in January 2012. He received his habilitation qualifications (Accreditation to supervise research -HDR-) from Mohamed Khider University in 2017. His research interests include knowledge representation and reasoning; formal knowledge representation for Semantic Web, and Semantic IoT Interoperability.

Meriem Djezzar, 1) University of Abbes Laghrour, Khenchela, Algeria, 2)LIRE Laboratory, Constantine, Algeria

Meriem Djezzar is an Associate Professor in Computer Science at the University of Khenchela, Algeria and a Research Assistant in the LIRE Laboratory. She completed his PhD in Computer sciences from University of Constantine 2 in January 2016. Her research interests include knowledge representation and reasoning; formal knowledge representation models and query languages for the Semantic Web.

Moufida Maimor, University of Lorraine, CNRS, CRAN, F-54000 Nancy, France

Moufida Maimour is an Associate Professor at Lorraine University in Nancy, France, member of the CRAN (Centre de Recherches en Automatique de Nancy). She received her engineer degree in Computer Science from the University of Constantine (Algeria) in 1998. She conducted her doctoral research at the LIP (Laboratoire Informatique du Parralélisme) at the ENS of Lyon, France and obtained her PhD from Claude Bernard University in 2003. She mainly worked on reliable multicast and congestion control in the Internet and took part in multiple networking and grid computing projects. Upon to her nomination at the Lorraine University in 2004, she became more involved in the area of wireless sensor networks especially energy-efficient routing protocols, congestion control, mobility and multimedia transport. Currently, she is working on knowledge-defined networks in the context of the IoT with a focus on the IIoT (Industrial Internet of Things) and the IoMT (Internet of Multimedia Things). Machine learning algorithms are leveraged to solve issues related to Industry 4.0 in the former and to multimedia environment surveillance in the latter.


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