Special Issue: Intelligent computing with internet of things learning

Selective papers from “2021 2nd International Symposium on Automation, Information and Computing (ISAIC 2021)”

Theme and Scope

As an effective way to promote knowledge exchange and information sharing, the learning has been playing an important role in the development and progress of human society for thousands of years. Various mediums, material, tools, and methods have been provided for communication among researchers, engineer, practitioners, and policy makers. In recent years, the booming development of information technologies have made significant changes on the traditional learning ways. For instance, the communication mode is moving from offline to online; the audiences are moving from the school-aged students to all the people; the knowledge is moving from a single discipline to interdisciplinarity. Hence, how to scientifically handle with the unprecedented changes in human history is becoming an increasingly popular research hotspot in internet of things learning fields.

In recent years, the intelligent computing methods becomes a feasible and promising tool to meet the challenges. It can connect a wide range of terminal computing nodes (like mobile phone, tablet computer, laptop or servers) to realize the goal of high-computing and low-latency operating environment required in internet of things learning applications. However, there are few reports about using the advanced computer methods to address learning-associated problems by far. Under this background, it is of great importance to deepen the intelligent computing methods in the internet of things learning sciences, learning analytics, and networked learning, and educational evaluation and assessment.

Potential readers include the research community, scientists, engineers, policy makers and operator of the internet of things learning as well as other related fields. Any topic related to advanced intelligent computing methods as well as their applications with internet of things learning will be considered. All aspects of design, theory and realization are of interest.

Topics of interest for the special issue include but are not limited to the following areas:

  • Intelligent computing methods for internet of things learning
  • High-efficiency computing databases in internet of things learning
  • Interactive computing software in internet of things learning
  • Cloud platforms of computing in internet of things learning
  • Innovative learning systems via intelligent computing methods
  • Adaptative learning assessment via intelligent computing methods
  • Safe learning system design via intelligent computing methods
  • Learning risk analysis via intelligent computing methods
  • Big data in computer learning via intelligent computing methods
  • Efficient learning features extraction via intelligent computing methods

Instructions for Manuscripts

Each paper, written in English, the maximum words number in each paper should be below 8,000 words, including references and illustrations. More information can be found at http://jit.ndhu.edu.tw. Before submission authors should carefully read over the journal’s Author Guidelines, which are located at https://jit.ndhu.edu.tw/about/submissions#authorGuidelines.

Prospective authors should submit an electronic copy of their complete manuscript through the journal Manuscript Tracking System at https://mc04.manuscriptcentral.com/internet-tech. When submitting papers, authors should specify that the manuscript is for Special Issue on “Intelligent computing with internet of things learning”. The manuscript template can be found at https://jit.ndhu.edu.tw/about/submissions#authorGuidelines

Important dates

Manuscript Submission Deadline: December 31, 2021

Notification of Acceptance/Rejection/Revision: February 28, 2022

Revise Manuscript Due: April 30, 2022

Final Manuscript Due: May 31, 2022

Tentative Publication Date: Fourth Quarter in 2022

Guest Editors:

Dr. Shiping Wen (Lead Guest Editor)

University of Technology Sydney, Australia

Email: shiping.wen@uts.edu.au

Dr. Zhong-Kai Feng

Huazhong University of Science and Technology, China

Email: myfellow@163.com

Dr. Neal N. Xiong

Northeastern State University, USA

Email: xiong31@nsuok.edu