Deep Learning for IoT Big Data and Streaming Analytics

SCOPE:

The special issue aims to present a collection of high-quality research papers on the state-of-the-art in emerging technologies for the applications of recent trends in Deep Learning (DL) technologies for the IoT domain. We are soliciting original contributions that have not been published and are not currently under consideration by any other journals. Both theoretical studies and state-of-the-art practical applications are welcome for submission. All submitted papers will be peer-reviewed and selected on the basis of both their quality and their relevance to the theme of this special issue.

TOPICS:

We are soliciting original contributions that have not been published and are not currently under consideration by any other journals. Both theoretical studies and state-of-the-art practical applications are welcome for submission. All submitted papers will be peer-reviewed and selected on the basis of both their quality and their relevance to the theme of this special issue. This special issue solicits the following topics, but not limited to:

  • Topics of interest include, but are not limited to, the following scope:
  • Deep Learning (DL) technologies for IoT domain applications
  • Machine learning for IoT data processing
  • IoT big data analytics and IoT streaming data analytics
  • Emerging DL Techniques for IoT data analytics
  • DL for smart IoT devices
  • Data-Driven Decision-Making Systems in IoT Applications
  • Deep Learning Models for Time Series Data and IoT
  • Multi-Task IoT System Modelling and Analysis
  • Hybrid Intelligent Models for IoT Context-Aware Systems
  • Multimodal Data Analysis and Information Fusion in IoT
  • Prediction of Situational Awareness with IoT Data
  • Streaming data learning algorithms for IoT
  • Swarm Intelligence and Big Data for IoT
  • Cloud-Assisted Data Fusion and Sensor Selection for Internet of Things
  • Secure and Privacy-Preserving Steam Analytics
  • IoT Analytics for Improving the Dependability of IoT Systems
  • Emerging Hardware Architectures for IoT and Big Data
  • IoT and Big Data Analytics on Energy-Constrained platforms
  • Optimization, Control, and Automation
  • Computational and Artificial Intelligence algorithms
  • Fog and Cloud Computing for (near) real-time analytics
  • Smart cities and systems
  • Blockchain for data security and privacy
  • Fault tolerant, redundant systems
  • Visualization techniques

IMPORTANT DATES

  • Manuscript submission deadline: 1-12-2023
  • Notification of acceptance: 1-03-2024
  • Submission of final revised paper: 1-04-2024
  • Publication of special issue (tentative): 1-05-2024

MAIN GUEST EDITOR: Zhigao Zheng, Wuhan University, China, zhengzhigao@pku.edu.cn

GUEST EDITORS:

  • Shahid Mumtaz, IET Fellow, Nottingham Trent Univeristy, UK, shahid.mumtaz@ntu.ac.uk
  • Joel J. P. C. Rodrigues, IEEE Fellow, Federal University of Piauí (UFPI), Brazil, joeljr@ieee.org