Journal: International Journal of Distributed Sensor Networks (SCI 4区) 

Special Collection: Recent Advances on Semantic Annotation and Integration for IoT Sensor Data

Submission Deadline: 2022.6.30

Official Website: https://journals.sagepub.com/page/dsn/collections/special-issues/recent-advances-on-semantic-annotation-and-integration-for-iot-sensor-data

To have your paper considered for this Special Collection, submit by June 30, 2022.

Please review the Manuscript Submission Guidelines before submitting your paper.  

Click here to submit your paper.

Lead Guest Editor:

Xingsi Xue
Fujian University of Technology, China
xxs@fjut.edu.cn

Co-Guest Editors:

Jeng-Shyang Pan
Shandong University of Science and Technology, China
jengshyangpan@gmail.com

Yuemin Ding
University of Navarra, Spain
yuemin.ding1986@gmail.com

Pei-Wei Tsai
Swinburne University of Technology, Australia
ptsai@swin.edu.au

Overview

The rapid increase in the number of network-enabled devices and sensors deployed in the physical environments is changing information communication networks. It is predicted that within the next decade billions of devices will generate myriad real-world data for many applications and services in a variety of areas such as smart grids, smart homes, e-health, automotive, transport, logistics, and environmental monitoring. The related technologies and solutions that enable the integration of real-world data and services into the current information networking technologies are often described under the umbrella term of the Internet of Things (IoT). As most of the IoT devices operate in real-world environments, the exposed services are not as reliable and stable as those well-engineered and maintained business services and the quality of information and services in the IoT domain can vary over time. The heterogeneity of underlying devices and networks also makes it difficult to provide one-fits-all solutions to represent data and services that emerge from the IoT networks. This brings significant challenges to data integration, data fusion, and discovery mechanisms that require interoperable and machine-interpretable data and quality descriptions.

A potential solution to face this challenge is to model IoT data using machine-interpretable and interoperable formats. The existing work often uses solutions that are adapted from the Semantic Web (SW) and semantic data modelling to overcome the interoperability issues and to provide semantically rich descriptions for the IoT data. The recent advancements in this area are discussed in several existing works such as the Semantic Sensor Web (SSW) and Linked Sensor Data (LSD) on the Linked Open Data (LOD) cloud. Research on the IoT data so far has largely focused on knowledge representation, such as how to semantically describe capabilities of IoT devices and services, data annotation, and publications, for example, how to create and publish semantically annotated IoT data and linked data models. However, modelling and integrating the observation and measurement data, streaming sensor data, and providing discovery mechanisms to enable distributed query mechanisms are other key issues to enable end-to-end solutions for publications and consumption of the sensory data emerging from IoT resources.

Potential topics include but are not limited to the following:

• Sensor Knowledge Modeling and Representation

• Sensor Data Analysis and Knowledge Discovery

• Sensor Knowledge Graph and Its Applications

• Sensor Ontology Engineering and Sensor Data Annotation

• Sensor Ontology Alignment and Linked Sensor Data Integration

• Instance Coreference Resolution on Semantic Sensor Web and Linked Sensor Data

• Intelligent Sensor Data Storage and Management

• Sensor Data-Driven Security Ontology in Semantic Sensor Web and Its Applications

• Semantic Enquiry Technique on Sensor Data Markets and Search Engines in Semantic Sensor Web

• Sensor Security Ontology Matching Technique in Linked Sensor Data and Its Applications

The submitted manuscripts for this Special Collection will be peer-reviewed before publication.

Submit your paper.

Please submit your paper according to the following timetable for the Special Collection:

Manuscript Deadline

June 30, 2022

An article processing charge may apply upon acceptance of your paper. 

Lead Guest Editor

Dr Xingsi Xue received his PhD degree in Computer Application Technology from Xidian University, China in 2014. He is an associate professor at Center for Information Development and Management, Fujian University of Technology, and the director of Intelligent Information Processing Research Center, Fujian University of Technique. His research interests include intelligent computation, data mining and large-scale ontology matching technology. He is the member of IEEE and ACM.

Co-Guest Editors

Dr Jeng-Shyang Pan received his PhD degree in electrical engineering from the University of Edinburgh in 1996. He is currently the Professor of Shandong University of Science and Technology. He is the IET Fellow, U.K., and has been the Vice Chair of the IEEE Tainan Section and Tainan Chapter Chair of IEEE Signal Processing Society. His current research interest includes the information hiding, artificial intelligence and wireless sensor networks.

Dr Yuemin Ding obtained his PhD degree from Department of Electronic Systems Engineering, Hanyang University, Ansan, Korea, in 2014 and worked as an associate professor at School of Computer Science and Engineering at Tianjin University of Technology, Tianjin, China, from 2015 to 2019. He worked as a postdoctoral research fellow at the Department of Energy and Process Engineering, Norwegian University of Technology, Trondheim, Norway, from 2019 to 2021. He is currently an Associate Professor at the Tecnun Engineering School of Engineering, University of Navarra, San Sebastian, Spain. His research interests include Internet-of-Things (IoT), smart grid communication, and energy-efficient management of user-side facilities.

Dr Pei-Wei Tsai received his PhD in Electronic Engineering in 2012 at the National Kaohsiung University of Applied Sciences in Taiwan. He was an invited speaker in 2021 International Symposium on Novel and Sustainable Technology (2021 ISNST) in Taiwan. He is a technical committee of the Application-Specific CE for Smart Cities in IEEE Consumer Technology Society. Currently, he is a lecturer at Swinburne University of Technology in Australia. His research interests include intelligent optimization, machine learning, and data analytics.