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Data Intelligence for IoT

Internet of Things (IoT) are increasingly deployed to enable smart manufacturing, smart transportation, smart healthcare, smart building, and other smart world applications. Various types of data are accumulated continuously during the running of these applications. How to manage and make use of these IoT data to derive intelligence for making the smart world a reality is attracting both industrial and academic efforts. E.g., tremendous amount of surveillance videos is collected and to be mined for knowing the road status, security situation, and so on. It is still challenging to efficiently trace people across cameras, esp. in bad weather conditions. New efforts have constantly arise to make maximum use of these IoT. E.g. some latest endeavors are the combination of deep learning with stream processing directed to facilitate the intelligent processing of smart manufacturing data to enable the analysis and prediction of industrial equipment faults.

Though quite some progress has been made in this area, there is still a need for high data intelligence for IoT applications to make a real smart world. Examples include, but not limited to: efficient management of both high volume and fast speed IoT data; streaming cloud-based IoT data intelligent processing; IoT data analysis platforms that provide data mining services; various machine learning approaches to perform IoT data processing and analysis in a more accurate and efficient manner; edge and fog computing infrastructure for IoT data processing; mechanisms to preserve IoT data privacy and provide secure services for interconnected users; graph computing for IoT data processing; social computing for processing Internet of People; crowd sensing to provide more intelligent IoT data solutions; and so on.

The Digital Communications and Networks Special Issue on Data Intelligence for IoT aims to cover various aspects related to IoT data processing and analysis to provide better intelligence for IoT applications. 

We invite authors to submit their latest original research results on the following topics, but are not limited to:

  • Data management mechanisms and algorithms for IoT data usage
  • Stream processing for efficient IoT data processing 
  • IoT data mining platforms and tools
  • Machine learning for IoT data processing and analysis
  • Intelligent big IoT data solutions based on IoT data mining 
  • Social data mining and computing
  • IoT data privacy and secured IoT services 
  • Edge and fog computing for IoT data processing
  • Blockchain integrated with IoT services
  • New applications for smart IoT services

 

Important Dates 

  • Paper submission: 31 December 2019
  • First round review notification: 1 March 2020
  • First revision due: 1 April 2020
  • Second round review notification: 1 May 2020
  • Final acceptance notification: 1 June 2020

Guest Editors

  • Weishan Zhang, China University of Petroleum (East China), China
  • Paolo Bellavista, University of Bologna, Italy
  • Jiehan Zhou, University of Oulu, Finland
  • Liming Chen, De Montfort University, UK
  • Chunsheng Zhu, The University of British Columbia, Canada

Submission Guidelines

Digital Communications and Networks (DCN), indexed by SCIE and Scopus and fully open access  through ScienceDirect, publishes rigorously peer-reviewed and high quality original articles and authoritative reviews. Only original and unpublished research papers will be considered in this special issue. Authors should follow the DCN manuscript format described in the Information for Authors at DCN journal website (http://www.keaipublishing.com/en/journals/digital-communications-and-networks/). Prospective authors should submit an electronic copy to the Elsevier DCN on-line manuscript system via (https://www.evise.com/profile/#/DCAN/login) according to the following timetable.

 

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