Intelligent Big Data Analytics for Internet of Things, Services and People

Submission Deadline:  31 May 2021

IEEE Access invites manuscript submissions in the area of Intelligent Big Data Analytics for Internet of Things, Services and People.   

In the envisaged future internet, which consists of billions of digital devices, people, services and other physical objects, people will utilize these digital devices and physical objects to exchange data about themselves and their perceived surrounding environments over a web-based service infrastructure, in what we refer to as the Internet of Things. Because of its openness, multi-source heterogeneity, and ubiquity, interconnecting things, services and people via the internet improves data analysis, boosts productivity, enhances reliability, saves energy and costs, and generates new revenue opportunities through innovative business models. However, the increasing number of IoT users and services leads to fast-growing IoT data, while the quality of service of IoT should also be maintained regardless of the number of IoT users and services. Therefore, the data transmission and processing in IoT should be performed in a more intelligent manner. A large number of computational intelligent technologies such as artificial neural networks, machine learning and data mining can be applied in IoT to improve the IoT data transmission and processing. The adoption of intelligence technologies and big data in handling IoT could offer a number of advantages as big data technology could handle various data effectively, while artificial intelligence technology could further facilitate capturing and structuring the big data.

This Special Section in IEEE Access will focus on intelligent big data analytics for advancing IoT. Novel applications by the integration of big data and artificial intelligence for IoT are particularly welcome.

The topics of interest include, but are not limited to:

  • Big-data analytics in IoT
  • Machine learning algorithms in IoT
  • Scalable/parallel/distributed algorithms in IoT
  • Privacy preserving and security approaches for large scale analytics in IoT
  • Big data technology for intelligent system
  • Artificial intelligence technology for data integration in IoT
  • Artificial intelligence technology for data mining in IoT
  • Artificial intelligence technology for data prediction in IoT
  • Artificial intelligence technology for data storage in IoT
  • Artificial intelligence technology for multimedia data processing
  • Intelligent optimization algorithms in IoT
  • Advances in artificial learning and their applications for information security
  • Intelligent big data analytics for prediction and applications in IoT
  • Novel applications of intelligent big data analytics for IoT
  • Big data technology for intelligent monitoring in IoT

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility and downloads of articles.

 

  Associate Editor: Zhaoqing Pan, Nanjing University of Information Science and Technology, China

  Guest Editors:

    1. Yang Xiao, University of Alabama, USA
    2. Muhammad Khurram Khan, King Saud University, Saudi Arabia
    3. Markku Oivo, University of Oulu, Finland
    4. Vidyasagar Potdar, Curtin University, Australia
    5. Yuan Tian, Nanjing Institute of Technology, China

 

Relevant IEEE Access Special Sections:

    1. Scalable Deep Learning for Big Data
    2. Intelligent Systems for the Internet of Things
    3. Human-Centered Smart Systems and Technologies

 

IEEE Access Editor-in-Chief:  Prof. Derek Abbott, University of Adelaide

Article submission: Contact Associate Editor and submit manuscript to:
http://mc.manuscriptcentral.com/ieee-access

 For inquiries regarding this Special Section, please contact: zhaoqingpan@nuist.edu.cn.