The journal Computers & Electrical Engineering provides rapid publication of topical research into the integration of computer technology and computational techniques with electrical and communication and information systems. The journal publishes papers featuring novel implementations of computers and computational techniques in areas like:

    Signal Processing
    Power Engineering (including renewable and green energies)
    Artificial Intelligence - methods and applications
    Security
    Privacy
    Communication

The journal regularly publishes special sections covering specific topics of interest. Proposals for special sections should be submitted to the Editor-in-Chief. The list of current special sections can be found at https://www.sciencedirect.com/journal/computers-and-electrical-engineering/special-issues.

Special Issue on Internet of Things-Aided Intelligent Transport Systems: Sensors, Methods, and Applications
截稿日期: 2024-12-30

The rapid advancement of Internet of Things (IoT) technology has revolutionized various industries, including the field of Intelligent Transport Systems (ITS). IoT has enabled the deployment of sensors and interconnected devices in transportation networks, which exhibits high potential in enhancing safety, efficiency, and sustainability. This special issue aims to explore the latest developments and applications of IoT in the realm of ITS, with a focus on sensors, methods, and real- world applications.

Guest editors:

Dr. Maohan Liang
    National University of Singapore
    Email: mhliang@nus.edu.sg

Prof. Hua Wang
    Hefei University of Technology
    Email: hwang191901@hfut.edu.cn

Prof. Guoqing Zhang 
    Dalian Maritime University 
    Email: zgq_dlmu@163.com

Special issue information:

Overview:

In recent years, the rapid advancement of Internet of Things (IoT) technology has heralded a transformative era in the field of Intelligent Transport Systems (ITS). The combination of IoT and ITS has led to a proliferation of innovative applications, driven by creative sensor technology, advanced modeling techniques, and real-world implementations. This special issue is dedicated to exploring the multifaceted impact of IoT on ITS, delving into the intricacies of sensors, models, and practical applications that are shaping the future of transportation.

In the realm of IoT-aided ITS, a diverse array of sensors, including cameras, satellite remote sensing, and GPS devices, serve as the foundation for data acquisition within the transportation domain. These sensors provide a wealth of information, which is crucial for enhancing safety, efficiency, and sustainability for our transportation society. Integrated with cutting-edge technologies in deep learning and machine learning, these sensors enable real-time decision-making by analyzing data streams. The applications of IoT- aided ITS cover various transport-related aspects, such as autonomous driving, environmental protection, accident prevention, decision systems for intelligent vehicles, and traffic planning. These advancements are pivotal in reshaping the future of transportation, spanning across multiple transportation modes including road, maritime, and aviation.

In this special issue, we invite authors to focus on the profound impact of IoT across these diverse transportation domains. We encourage contributions that address the challenges, opportunities, and innovations arising from the integration of IoT and ITS.

Topics of Interest:

We invite authors to submit original research articles, reviews, and case studies related to IoT-Aided ITS. Topics of interest include but are not limited to:

    Artificial Intelligence (AI) Model in IoT-Aided ITS
    Deep Learning Applications in IoT-Aided ITS
    Machine Learning Based Traffic Optimization
    Traffic Forecasting and Traffic Simulation
    Traffic Pattern Recognition Methods and Applications
    IoT Solutions for Sustainable and Efficient Transportation
    IoT-Based Vehicle Monitoring and Safety Systems
    Autonomous Vehicle Technologies
    Security and Privacy in IoT-Aided ITS
    IoT-Enabled Digital Twins for ITS
    Advanced Vehicle-to-Infrastructure (V2I) Communication Systems
    Advanced Vehicle-to-Vehicle (V2V) Communication Systems

Manuscript submission information:

Submission Guidelines

New papers, or extended versions of papers presented at related conferences, are welcome. Submissions must not be currently under review for publication elsewhere. Conference papers may be submitted only if they are substantially extended (more than 50%), and must be referenced. All submitted papers will be peer-reviewed using the normal standards of CAEE, and accepted based on quality, originality, novelty, and relevance to the theme of the special section. By submitting a paper to this issue, the authors agree to referee one paper (if asked) within the time frame of the Special Section.

Before submission, authors should carefully read the Guide for Authors. Authors should submit their papers through the journal's web submission tool by selecting “VSI-IoTA” under the “Issues” tab.

Important Dates:

    VSI Submission Opens: 30th Jan 2024 
    VSI submission Closes: 30th Dec 2024 
    Expected Review Duration: 2-3 Months

Keywords:

Internet of Things; Intelligent Transport Systems; Deep Learning

Special Issue on TinyML Empowered Intelligent Systems (VSI: TinyML IS)
截稿日期: 2024-12-31

Intelligent systems refer to the combination of software and hardware to imitate humans’ cognition, judgment and reasoning abilities. The software mainly refers to artificial intelligence (AI) models, while the hardware may be personal computer, cloud server or even a mobile computing platform. In general, the performance of intelligent system depends on the scale of existing knowledge library. The larger the knowledge library is, the better the expert system performs. However, the hardware may restrict the scale of knowledge library or AI model. For example, edge nodes in edge computing have limited memory and computing ability; the microcontroller unit (MCU) deployed in outside must keep low power consumption for long time. It has become a challenge to implement intelligent systems under limited hardware.

Compared with traditional machine learning (ML) models or large models, TinyML models require less memory, fewer computing resources, and lower power consumption. These merits make TinyML model can adapt the intelligence under limited resource environment. For example, TinyML models can be deployed in the intelligent edge nodes which are widely used in the Internet of Things (IoTs) or Artificial Intelligence of Things (AIoTs). This special issue will focus on the advances and challenges of TinyML to spur the development of intelligent system.

Guest editors:

    Fa Zhu, Nanjing Forestry University, China, fazhu@njfu.edu.cn
    Muhammad Waqas, University of Greenwich, UK, muhammad.waqas@greenwich.ac.uk
    Zhiyuan Tan, Edinburgh Napier University, UK, z.tan@napier.ac.uk
    Jalil Piran, Sejong University, South Korea, piran@sejong.ac.kr
    Massimo Merenda, Università Mediterranea di Reggio Calabria, Reggio Calabria, Italy, massimo.merenda@unirc.it

Special issue information:

Intelligent systems refer to the combination of software and hardware to imitate humans’ cognition, judgment and reasoning abilities. The software mainly refers to artificial intelligence (AI) models, while the hardware may be personal computer, cloud server or even a mobile computing platform. In general, the performance of intelligent system depends on the scale of existing knowledge library. The larger the knowledge library is, the better the expert system performs. However, the hardware may restrict the scale of knowledge library or AI model. For example, edge nodes in edge computing have limited memory and computing ability; the microcontroller unit (MCU) deployed in outside must keep low power consumption for long time. It has become a challenge to implement intelligent systems under limited hardware.

Compared with traditional machine learning (ML) models or large models, TinyML models require less memory, fewer computing resources, and lower power consumption. These merits make TinyML model can adapt the intelligence under limited resource environment. For example, TinyML models can be deployed in the intelligent edge nodes which are widely used in the Internet of Things (IoTs) or Artificial Intelligence of Things (AIoTs). This special issue will focus on the advances and challenges of TinyML to spur the development of intelligent system.

The object of this special issue is to promote the researches on TinyML to empower intelligent system under limited resource environment. Researchers from academic and practitioners from industry are welcome to share their recent works that adopt TinyML to handle aforementioned challenges of theory or application in intelligent system using limited resources.

Topics of interest include, but are not limited to, the following

    Novel findings of TinyML for intelligent system deployed in IoTs and IIoTs
    Explainability and interpretability of TinyML for intelligent systems
    Novel intelligent applications of intelligent system using TinyML in smart devices
    Security and privacy protection using TinyML in intelligent systems
    Intelligent systems in edge-cloud collaborating learning using TinyML
    Data processing using TinyML to enhance intelligent systems
    Intelligent systems in human behavior analysis using TinyML
    Intelligent systems using TinyML in Internet of Medical Things (IoMT)
    Intelligent systems using TinyML in Smart Grids and Energy Internet
    Intelligent systems using TinyML in Smart Agriculture

Manuscript submission information:

Submission Guidelines:New papers, or extended versions of papers presented at related conferences, are welcome. Submissions must not be currently under review for publication elsewhere. Conference papers may be submitted only if they are substantially extended (more than 50%), and must be referenced. All submitted papers will be peer-reviewed using the normal standards of CAEE, and accepted based on quality, originality, novelty, and relevance to the theme of the special section. By submitting a paper to this issue, the authors agree to referee one paper (if asked) within the time frame of the special section. 

Before submission, authors should carefully read the Guide for Authors available at https://www.elsevier.com/journals/computers-and-electrical-engineering/0045-7906/guide-for-authors 

Authors should submit their papers through the journal's web submission tool at https://www.editorialmanager.com/compeleceng/default.aspx by selecting “VSI-TinyML IS” under the “Article Type” tab. For additional questions, contact the Main Guest Editor. 

Important dates:

    Submissions Deadline: December 31, 2024
    First Reviews Due: March 30, 2025
    Revision Due: May 30, 2025
    Second Reviews Due/Notification: June 30, 2025
    Final Decision Due: July 31, 2025
    Tentative Publication Date: 4th quarter 2025