Optimal Operation of Active Buildings as an Energy System

Submission Deadline:  31 August 2021

IEEE Access invites manuscript submissions in the area of Optimal Operation of Active Buildings as an Energy System.   

The increasing share of buildings in the consumption of energy and carbon emission indicates that any solutions provided in this regard would have to consider the energy efficiency of the buildings, to obtain promising results. Active Buildings are viable solutions to this issue, in which intelligent integration of renewable-based energy technologies, heating, cooling, and transport systems would be able to make a multi-vector energy system.

Active Buildings can work in an isolated way as a self-sufficient energy system, or can interact with the other ABs in a district area and trade energy via the network. They have the potential of interacting with local as well as national level energy grids and, by behaving as zero or positive energy buildings, they are able to deliver various energy services to reduce the pressure on the upstream energy networks, and defer new investment requirements. As a result, the operation of Active Buildings is being developed as fundamental research and part of the future smart energy systems that call for a (re)thinking on the definition of the control, operation and optimization of the Active Buildings as an energy system.

This Special Section in IEEE Access will target numerous prospects in the operation of active buildings as an energy system. Both review and research articles are welcome. Real-world use cases discussing new application areas and resulting new developments are especially welcome.

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

  • A holistic approach in modeling of the energy systems of Active Buildings (ABs)
  • The role of ABs in energy systems
  • Building physics-based modeling of ABs
  • Zero energy and net-zero energy buildings
  • Coordinated operation and control of ABs at the district/city level
  • Application of model predictive control in ABs operation
  • IoT-based operation and control of ABs
  • Energy management systems of ABs
  • AC, DC, or Hybrid model of ABs
  • AB as a service provider in the electricity networks
  • Resilience-based operation of ABs
  • Reliability-based modeling of ABs
  • Uncertainty aware energy management of ABs
  • Artificial intelligence for the operation of ABs
  • Market-based operation of ABs including Building-to-Building (B2B), Building-to-Grid (B2G), Building-to-Vehicle (B2V), and Vehicle-to-Building (V2B) energy transactions as well as peer-to-peer (P2P) energy transactions

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

 

Associate Editor:  Behnam Mohammadi-Ivatloo, University of Tabriz, Iran

Guest Editors:

    1. Vahid Vahidinasab, Newcastle University, UK
    2. Somayeh Asadi, Pennsylvania State University, USA
    3. Fei Wang, North China Electric Power University, China

 

Relevant IEEE Access Special Sections:

    1. Key Enabling Technologies for Prosumer Energy Management
    2. Evolving Technologies in Energy Storage Systems for Energy Systems Applications
    3. Advanced Internet of Things for Smart Cyber-Physical Infrastructure Systems

 

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

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

 For inquiries regarding this Special Section, please contact: mohammadi@ieee.org.

Emerging Approaches to Mobile Cooperative Sensing and Its Applications in Smart Environments

Submission Deadline: CLOSED

IEEE Access invites manuscript submissions in the area of Emerging Approaches to Mobile Cooperative Sensing and Its Applications in Smart Environments.

Mobile cooperative sensing is becoming a popular paradigm to collect information and outsource tasks to mobile users. Detected events are then reported continuously through the integration and cooperation of sensors, actuators, controllers, and artificial intelligence. Mobile cooperative sensing refers to estimating the event information and simulating the situation of smart environments through the analysis of data from sensor networks deployed in the environment. The systems are able to actively obtain information of occupancy, such as identification, activity, and even gestures with mobile cooperative sensing. For instance, intrusion detection and human identification help to detect intruders automatically. In smart environments, light and temperature can be adjusted according to the occupancy, which conserves the energy. For children and the elderly, activities such as falling can be monitored to prevent potential hazards. Mobile cooperative sensing is becoming a vital part of the fvarious emerging applications in smart environments, such as energy consumption estimation, security surveillance, and human behavior analysis. Generally speaking, mobile cooperative sensing provides an active detected input for smart systems, so  it can make judgment or feedback accordingly.

At present, with the increasing mobile cooperative sensing technology in the field of Mobile Internet of Things (M-IoT) and the continuous improvement and upgrading of the current internet infrastructure, application and business model innovations are constantly emerging. Mobile cooperative sensing is further penetrating traditional fields, such as finance, transportation, medical treatment, education, etc… Mobile cooperative sensing technology can already be found in the fields of intelligent transportation, internet finance, and intelligent medical treatment, for example. In the future, some preliminary application results can be expected to be used in other fields, especially in the application areas of smart environments (e.g., smart homes and cities), which will have a far-reaching impact. Mobile cooperative sensing technology is not just about the detection via sensor networks; it is also about enabling a wide range of new capabilities, architectures, and service paradigms. The development of mobile cooperative sensing is set to have major economic, social, and environmental impacts, the intersection of which forms future sustainable growth.

As a result, the development of mobile cooperative sensing in smart environments is fundamentally important; however, many problems still remain.. For example, how to construct and improve the framework and platform for mobile cooperative sensing; how to collect, measure, process, analysis, and optimize mobile cooperative sensing data; and how to improve the effectiveness and decrease the energy in mobile cooperative sensing. These are all vital but unavoidable problems for mobile cooperative sensing in smart environments.

This Special Section is intended to provide a specific opportunity to argue the state-of-the-art technologies around mobile cooperative sensing in smart environments and invite researchers in the relevant fields to share the latest progress, novel methodologies, and potential research topics.

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

  • Construction and improvement of framework and platform for mobile cooperative sensing
  • Collection, measurement, processing, analysis, and optimization of mobile cooperative sensing data
  • Improvement of effectiveness and decrease of energy in mobile cooperative sensing
  • Evaluation of performance relevant to mobile cooperative sensing systems
  • Adaptability of mobile cooperative sensing systems in complex and variable environments
  • Emerging technologies in smart environments
  • Artificial intelligence in smart environments
  • Smart environment-based machine learning for mobile cooperative sensing
  • Security and privacy of mobile cooperative sensing in smart environments
  • Quality of Service (QoS) and Mobile Internet of Things (M-IoT) services in mobile cooperative sensing systems

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

 

Associate Editor: Mu Zhou, Chongqing University of Posts and Telecommunications, China

Guest Editors:

    1. Hongying Meng, Brunel University London, UK
    2. Haiying Wang, Ulster University, UK
    3. Lei Chen, Georgia Southern University, USA
    4. Kunjie Xu, Intel Corporation, USA

 

Relevant IEEE Access Special Sections:

  1. Innovation and Application of Internet of Things and Emerging Technologies in Smart Sensing
  2. Intelligent Information Services
  3. Advances in Machine Learning and Cognitive Computing for Industry Applications

 

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

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

For inquiries regarding this Special Section, please contact: zhoumu@cqupt.edu.cn.

Lightweight Security and Provenance for Internet of Health Things

Submission Deadline: 31 October 2020

IEEE Access invites manuscript submissions in the area of Lightweight Security and Provenance for Internet of Health Things.

As an extension of the Internet of Things (IoT), the Internet of Health Things (IoHT), play an important role in the remote exchange of data of different physical processes such as patient monitoring, treatment progress, observation and consultation. In IoHT, the connectivity, integration, computation and interoperability are enabled through various sensors, actuators, and controllers, thereby providing seamless connectivity with efficient utilization of resources. In emergency situations, when a patient is being shifted to a hospital, seamless connectivity between Ambulance to Hospital (A2H), Hospital to Hospital (H2H) and Hospital to Ambulance (H2A), is very critical. With advances in tele-medicine, telesurgery, and other health-care applications, streaming has become an essential part of IoHT. The data traffic in IoHT applications, such as interactive multimedia streaming, traffic generated from faulty sensors, and vital signs, can tolerate packet loss but have stringent delay requirements. On the other hand, video streaming applications cannot tolerate jitter. Similarly, the low-power devices are sensitive to packet loss, and the periodic physiological traffic of medical traffic can tolerate delay, or jitter, but not packet loss.  Routing data in different IoHT applications has varying quality of service (QoS) requirements in terms of delay, packet loss, jitter, and throughput. Most of the algorithms used today to secure the data and cryptography techniques in IoHT contain high computational complexities with high energy consumption. However, due to the energy limitations of low-power embedded devices, traditional cryptographic solutions are not viable for most of the IoHT applications. Less computational complexity, less space acquisition and energy-efficient security primitives are key building blocks for end-to-end content protection, user authentication, and consumer confidentiality in the IoHT.  Once the data is gathered from different applications, it must be accurate and information about its origin should also be known. Due to scalability, tiny devices installed in IoHT are not usually physically protected. Data security and provenance therefore serve as the backbone for implementing IoHT applications.

This Special Section targets original technical articles with novel contributions on the improvement of security of IoHT, in particular by finding the correct lightweight solution. Review articles of high quality that provide thorough overview of the subject will also be considered. The topics of interest include, but are not limited to:

  • Lightweight security for IoHT
  • Low energy IoHT systems
  • Low energy security algorithms for A2H, H2H, and H2A in IoHT
  • Lightweight solutions for data forensics in IoHT
  • Lightweight routing algorithms for data provenance in IoHT
  • Secure lightweight protocols for A2H, H2H, and H2A in IoHT
  • Security framework and architecture for IoHT
  • Lightweight video streaming mechanism for IoHT

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

 

Associate Editor:  Muhammad Tariq, FAST National University of computer & Emerging Sciences, Pakistan and Princeton University, USA

 

Guest Editors:

    1. Takuro Sato, Waseda University, Waseda University, Tokyo, Japan
    2. Gautam Srivastava, Brandon University, Canada
    3. Vuk Marojevic, Mississippi State University, USA
    4. Mario Goldenbaum, Bremen University, Bremen, Germany

 

Relevant IEEE Access Special Sections:

  1. Secure Communication for the Next Generation 5G and IoT Networks
  2. Deep Learning: Security and Forensics Research Advances and Challenges
  3. Emerging Approaches to Cyber Security


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

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

For inquiries regarding this Special Section, please contact: mtariq@princeton.edu.

Key Enabling Technologies for Prosumer Energy Management

Submission Deadline: 31 December 2020

IEEE Access invites manuscript submissions in the area of Key Enabling Technologies for Prosumer Energy Management.

Distributed energy resources (DERs), such as photovoltaics, electric vehicles, energy storage and heat pump devices, play a central role in the energy transition from fossil fuels to renewables. The growing penetration of DERs has made it possible for traditional passive consumers to evolve into active prosumers. Compared with traditional consumers, prosumers are capable of managing their energy generation, storage and consumption simultaneously. Prosumers can not only participate in electricity market transactions, e.g., minimizing the cost of energy procurement, but also facilitate smart grid operations, e.g., providing ancillary service to power grids. With the booming development of prosumers, a prosumer energy management system is urgently needed to take full advantage of prosumers’ flexibility while taking the interests of other parties into account. In recent years, several prosumer energy management strategies have been proposed in literature, such as the peer-to-peer approach, coordinated scheduling-based scheme and centralized control method. However, these strategies have the following deficiencies: (1) they lack comprehensive analytics and intelligent control tools compatible with the existing energy management systems to reduce energy costs; (2) they do not address how to increase the prosumer profitability through improved customer segmentation; (3) they do not analyze the intrinsic revenue streams among prosumers.

To handle these deficiencies, the current energy management system needs to be rigorously re-engineered into an integrated and intelligent system that manages not only the smart grid but also the multi-energy system with couplings of electricity, thermal and natural gas networks. To this end, a large number of prosumers will actively participate in system-wide and local coordination tasks. Therefore, the modeling methods and related key enabling technologies are still hot topics that require substantial scientific research.

Research into prosumer energy management involves a wide range of disciplines, including power engineering, computer science, (micro) economics, thermal and control engineering. This Special Section will bring together researchers and practitioners to introduce and discuss key enabling technologies covering monitoring, operation, planning, marketing and control architectures related to the prosumer energy management.

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

  • Electricity market design for prosumer energy management
  • Prosumer-oriented home energy management system
  • Data management and ICT technologies to promote energy trading between prosumers
  • IoTs/Cloud based solutions for prosumer monitoring, management and control
  • Aggregation and disaggregation technologies for integrating and managing prosumers’ DERs
  • New coordinated control methodologies to integrate prosumers’ flexibility into smart grid operations
  • Automated technologies based on market behavior analysis to improve the robustness of prosumer energy management system
  • Market modeling methods based on peer to peer (P2P) energy trading and blockchain
  • Cyber physical modeling and cyber security of prosumer energy management system
  • Interactive energy management system that facilitates the prosumers’ operation
  • Transactive energy system for enabling the operation of prosumer energy management
  • Experiences and lessons learned from the field implementations
  • Renewable energy policies that can promote the development of prosumers in future smart grid
  • Standardization and new technologies that facilitate the application of prosumer energy management

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

 

Associate Editor:  Bin Zhou, Hunan University, China

Guest Editors:

  1. Nian Liu, North China Electric Power University, China
  2. Junjie Hu, North China Electric Power University, China
  3. Guangya Yang, Technical University of Denmark, Denmark
  4. Ahmad F. Taha, University of Texas, USA
  5. Huaizhi Wang, Shenzhen University, China
  6. Hugo Morais, EDF R&D Department, France
  7. Siqi Bu, The Hong Kong Polytechnic University, Hong Kong
  8. Jiayong Li, Hunan University, China

Relevant IEEE Access Special Sections:

  1. Artificial Intelligence Technologies for Electric Power Systems
  2. Emerging Technologies for Energy Internet
  3. Smart Caching, Communications, Computing and Cybersecurity for Information-Centric Internet of Things

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

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

For inquiries regarding this Special Section, please contact: binzhou@hnu.edu.cn.

Behavioral Biometrics for eHealth and Well-Being

Submission Deadline: 28 February 2021

IEEE Access invites manuscript submissions in the area of Behavioral Biometrics for eHealth and Well-Being.

Artificial Intelligence (AI) is changing the healthcare industry from many perspectives. A very challenging issue deals with the development of non-intrusive AI technologies that could be integrated into everyday activities, thus allowing continuous health state monitoring and enabling automatic warnings when a dangerous change is predicted. Behavioral biometrics play a crucial role within this challenge. Behavioral biometrics, such as speech, handwriting, gait, etc. can be used to quantify human physiology, pathophysiological mechanisms, and actions. The final acquired signal is a mixture of at least four components:

  • The physical one, which enables the user to make the action (e.g. mouth, lips, tongue, etc.);
  • The cognitive one, which deals with mental abilities (learning, thinking, reasoning, remembering, problem-solving, decision-making, and attention);
  • The learned one, which deals with culture, habits, personalization, etc.;
  • The contingent contour one, which deals with the acquisition device, the emotional state, the specific task to be performed, etc.

It is evident that disease at its early stage, as well as during its course, could affect one or more of these components. Behavioral biometrics in eHealth seek solutions to diagnose, assess, and monitor diseases that are measurable just when the patient performs an action. This action could be walking, talking, writing or typing on a touchscreen, and many more. Behavioral biometrics also deal with the way the human being responds to natural and social events around her/him and emotions. The adoption of non-intrusive behavioral biometrics techniques in the set of daily activities would be pervasive: the user would be asked to do what she/he already does normally. The output of these systems could be provided to doctors, thus helping them in a deep disease inspection. At the same time these technologies could be directly adopted by doctors. These aspects are extremely important for the development of Computer Aided Diagnosis (CAD) tools. Nevertheless, specific behavioral biometrics tasks and activities could be planned to support rehabilitation activities.

This Special Section in IEEE Access aims to attract original research articles that advance the state of the art in behavioral biometrics for e-health and well-being. The goal is that it provides an opportunity to gain a significantly better understanding of the field’s current developments and future direction.

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

  • Signal processing techniques
  • Pattern Recognition techniques
  • Computer Vision techniques
  • Artificial Intelligence techniques
  • Continuous learning and recognition
  • Acquisition tools, procedures and protocols
  • Biometrics data mining
  • Wearable and non-intrusive sensors
  • Brain signals analysis for disease and emotional states recognition
  • Eye movement analysis for disease recognition
  • Face analysis for disease and emotional state recognition
  • Gait analysis for disease and emotional state recognition
  • Handwriting analysis for disease and emotional state recognition
  • Keystroke dynamics for disease and emotional state recognition
  • Sleep analysis for disease and emotional state recognition
  • Speech analysis for disease and emotional state recognition
  • Biometric data and clinical data fusion
  • Multiple behavioral biometrics
  • Development of complete CAD systems
  • Real-time health alerts and long-term health trend analytics
  • Applications

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

 

Associate Editor:  Donato Impedovo, University of Bari Aldo Moro, Italy

Guest Editors:

    1. Thurmon Lockhart, Arizona State University, United States
    2. Jiri Mekyska, Brno University of Technology, Czech Republic
    3. Bijan Najafi, Baylor College of Medicine, United States
    4. Toshihisa Tanaka, Tokyo University of Agriculture and Technology, Japan

 

Relevant IEEE Access Special Sections:

  1. Data-Enabled Intelligence for Digital Health
  2. Smart Health Sensing and Computational Intelligence: From Big Data to Big Impacts
  3. Data Analytics and Artificial Intelligence for Prognostics and Health Management (PHM) Using Disparate Data Streams


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

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

For inquiries regarding this Special Section, please contact: donato.impedovo@uniba.it.

Blockchain Technology: Principles and Applications

Submission Deadline: 31 January 2021

IEEE Access invites manuscript submissions in the area of Blockchain Technology: Principles and Applications.

Blockchain is a disruptive technology for building consensus and trust in a peer-to-peer network without centralized control. It was first used in bitcoin, the very first cryptocurrency released at the beginning of 2009, to implement a secure ledger of transactions. This secure ledger ensures that once a transaction is placed in the ledger, it cannot be altered without being detected, which is a prerequisite for any digital currency implementation because it must guarantee that no one can double-spend one’s money. After a quiet period, the interest on blockchain has exploded in recent years. The number publications indexed by Web of Science on blockchain increased from 2 in 2013 (the first year in which publications on blockchain started to appear), to 4 in 2014, 21 in 2015, 118 in 2016, 521 in 2017, and 1,080 in 2018.

The research and developmental activities related to blockchain technology can be roughly divided into two areas: (1) The application of the blockchain in various industry sectors, such as fintech, medicine and health, energy and power generation systems, real estate, travel, manufacturing, education, or even government; (2) Fundamental research on blockchain technology itself, such as alternative consensus algorithms that consume less energy, provide better scalability, are more robust to cyberattacks, and are more scalable. In the former area, interesting issues could arise due to the particular needs of an application. For example, blockchain could be used to secure the data produced from a sensor network. However, the amount of data could easily exceed the capacity of any current blockchain platform. For the latter area, we have seen alternative consensus algorithms being proposed, such as proof of stake, that are likely to make blockchains more scalable, secure, and robust in the long term.

This Special Section welcomes original research and review articles on all aspects of blockchain technology.

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

  • Consensus algorithms
  • Cyberattacks on blockchains
  • Economic impact on cyberattacks
  • Security and trust on permissioned blockchains
  • Scalability of blockchains
  • Reliability analysis on blockchain-based systems
  • Smart contracts
  • Visualization of blockchain data
  • Blockchain for Banking and Finance
  • Blockchain for Supply Chain
  • Blockchain for Consumer Products and Retail
  • Blockchain for Government
  • Blockchain for Automotive
  • Blockchain for Medicine and Health Care
  • Blockchain for Travel and Transportation
  • Blockchain for Internet of Things
  • Blockchain for Agriculture

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

 

Associate Editor: Wenbing Zhao, Cleveland State University, USA

Guest Editors:

    1. Chunming Rong, University of Stavanger, Norway
    2. Jun Wu, Shanghai Jiao Tong University, China
    3. Zhixin Sun, Nanjing University of Posts and Telecommunications, China
    4. Srinivas Sampalli, Dalhousie University, Canada

 

Relevant IEEE Access Special Sections:

  1. Innovation and Application of Internet of Things and Emerging Technologies in Smart Sensing
  2. Innovation and Application of Intelligent Processing of Data, Information and Knowledge as Resources in Edge Computing
  3. New Technologies for Smart Farming 4.0: Research Challenges and Opportunities


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

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

For inquiries regarding this Special Section, please contact: w.zhao1@csuohio.edu.

Internet-of-Things Attacks and Defenses: Recent Advances and Challenges

Submission Deadline: 30 September 2020

IEEE Access invites manuscript submissions in the area of Internet-of-Things Attacks and Defenses: Recent Advances and Challenges.

The Internet of Things (IoT) technology has been widely adopted by the vast majority of businesses and is influencing every aspect of the world. However, the nature of the Internet, communication, embedded OS and backend recourses make IoT objects vulnerable to cyber attacks. In addition, most standard security solutions designed for enterprise systems are not applicable to IoT devices. As a result, we are facing a big IoT security and protection challenge, and it is urgent to analyze IoT-specific cyber attacks, and design novel and efficient security mechanisms.

The objective of the Special Section is to compile recent developments and efforts dedicated to research IoT attacks and defenses. The main purpose of this Special Section is to provide both academic and industry researchers with a forum to discuss either practical or theoretical solutions to identify IoT vulnerabilities and relevant security mechanisms. For this purpose, we encourage original research articles related to this topic, as well as high-quality review articles describing the current state of the art.

This Special Section will mainly focus on IoT-related attacks and defenses across IoT networks and devices.

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

  • Malware and unwanted software for IoT
  • Vulnerability analysis and reverse engineering for IoT
  • IoT security and privacy
  • IoT forensic techniques
  • Usable security and privacy for IoT
  • Intrusion detection and prevention for IoT
  • Cyber intelligence techniques for IoT
  • IoT infrastructures and mitigation techniques
  • IoT Hardware security
  • Cyber physical systems security
  • Adversarial learning for IoT
  • IoT Cyber crime
  • Denial-of-Service attacks for IoT
  • Security measurement for IoT
  • IoT security visualization techniques
  • Edge/Fog computing attack and defense
  • Trust models and management
  • Phishing and spam prevention

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

 

Associate Editor:  Weizhi Meng, Technical University of Denmark, Denmark

Guest Editors:

    1. Javier Lopez, University of Malaga, Spain
    2. Shouhuai Xu, University of Texas at San Antonio, USA
    3. Chunhua Su, University of Aizu, Japan
    4. Rongxing Lu, University of New Brunswick, Canada

 

Relevant IEEE Access Special Sections:

  1. Security and Trusted Computing for Industrial Internet of Things
  2. Internet-of-Things (IoT) Big Data Trust Management
  3. Security and Privacy in Applications and Services for Future Internet of Things


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

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

For inquiries regarding this Special Section, please contact: weme@dtu.dk.

Human-driven Edge Computing (HEC)

Submission Deadline: 01 September 2020

IEEE Access invites manuscript submissions in the area of Human-driven Edge Computing (HEC).

The advent of Fifth Generation (5G) and Internet of Things (IoT) is expected to  make it possible to collect and disseminate information for various crowd-sensing services in densely populated environments. It will also result in greater demand for these services, with the rapid evolution of artificial intelligence and edge computing, which provides cloud computing and cache capabilities to reduce the computational load of cellular networks, the edges of such networks. However, the costs for deployment and maintenance of Mobile Edge Computing (MEC) are still high. Human-driven Edge Computing (HEC) is a novel model which integrates the elements of Humans, Devices, Internet and Information, and combines the power of MEC architecture and the large-scale sensing ability of Mobile Crowd-sensing (MCS). There is a great deal of research interest, from both academia and industry, on how to improve data spreading methods and environmental coverage in smart cities based on HEC. Although the study of human-driven edge computing for 5G and IoT is attractive, there are still many issues, such as fusion analysis, efficient resource usage, low latency communication, large-scale search, and data security and privacy. The objective of this Special Section is to present a collection of high-quality research articles to report the latest research advances addressing the related challenges and limitations in the area of human-driven edge computing.

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

  • Cognitive inspired HEC
  • New model, architecture and framework of HEC
  • Computation offloading in HEC
  • Resource allocation and management in HEC
  • Data harvesting, fusion and analytics
  • Fusion analysis and computing
  • Large-scale data search and recommendation
  • Deep learning and data mining in HEC
  • AI Hardware Accelerators in HEC
  • Emerging AI techniques and their combination with MEC
  • Energy-efficient and low-latency communication and computation
  • Novel QoS and QoE improvement techniques
  • Security and privacy challenges
  • Application and case studies of HEC for 5G and IoT
  • Novel techniques and future perspective in HEC

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

 

Associate Editor: Rongbo Zhu, South-Central University for Nationalities, China

Guest Editors:

    1. Lu Liu, University of Leicester, UK
    2. Ashiq Anjum, University of Derby, UK
    3. Maode Ma, Nanyang Technological University, Singapore
    4. Shiwen Mao, Auburn University, USA

 

Relevant IEEE Access Special Sections:

  1. Communication and Fog/Edge Computing Towards Intelligent Connected Vehicles (ICVs)
  2. Information Centric Wireless Networking with Edge Computing for 5G and IoT
  3. Innovation and Application of Intelligent Processing of Data, Information and Knowledge as Resources in Edge Computing


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

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

For inquiries regarding this Special Section, please contact: rbzhu@mail.scuec.edu.cn.

Body Area Networks

Submission Deadline: 30 July 2020

IEEE Access invites manuscript submissions in the area of body area networks, wireless sensors networks, medical ICT, intelligent health management, and big data analysis.

Wearable communications and personal health management are the future trends of the healthcare industry. To make this happen, new technologies are required to provide trustable measurement and communication mechanisms, from the data source to medical health databases. Wireless body area networks (WBAN) are the focus of this Special Section, not just on-body devices, but also technologies providing information from inside the body. Dependable communications combined with accurate localization and behavior analysis will benefit WBAN technology and make healthcare processes more effective.

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

  • Wearable computing
  • Embedded devices and medical applications
  • In-, on- and off-body communications & networking
  • Antennas and propagation
  • Security and privacy of health data communications
  • Smart BAN for social inclusion
  • Socio-economic aspects of health caring
  • Medical device regulation
  • Human bond communications
  • Remote patient management and preventive care
  • Radio coexistence and interference management
  • Rehabilitation and activity monitoring
  • Wellness and sport applications of body area networks
  • ICT solutions for health and wellness education
  • Molecular communications
  • WBANs supporting cognitive impairments

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

 

Associate Editor:  Lorenzo Mucchi, University of Florence, Italy

Guest Editors:

    1. Matti Hämäläinen, University of Oulu, Finland
    2. Massimiliano Pierobon, University of Nebraska-Lincoln, USA
    3. Diep Nguyen, University of Technology Sydney, Australia
    4. Hirokazu Tanaka, Hiroshima Hiroshima City University, Dept. of Biomedical Information Sciences

 

Relevant IEEE Access Special Sections:

  1. Wearable and Implantable Devices and Systems
  2. Molecular Communication Networks
  3. Advances of Multisensory Services and Technologies for Healthcare in Smart Cities


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

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

For inquiries regarding this Special Section, please contact: lorenzo.mucchi@unifi.it.

Artificial Intelligence in Parallel and Distributed Computing

Submission Deadline: 15 January 2020

IEEE Access invites manuscript submissions in the area of Artificial Intelligence in Parallel and Distributed Computing.

Traditional computation is driven by parallel accelerators or distributed computation nodes in order to improve computing performance, save energy, and decrease delays in accessing memory. Recently, artificial intelligent algorithms, frameworks, and computing models are growing to help with high computational performance.

To coordinate communication among professional researchers, engineers and students, and to attract and filter high quality academic contributions recommended from the International Symposium on Advanced Parallel Processing Technology (APPT 2019, http://tc.ccf.org.cn/tcarch/appt2019/), we have organized this Special Section in IEEE Access on “Artificial Intelligence in Parallel and Distributed Computing” (AIPDC). High quality contributions within the field but not presented at the conference are highly encouraged and also considered in this Special Section.

To tackle issues and challenges from the new era of artificial intelligence on computer systems, this Special Section will present innovative solutions and recent advances in the fields of intelligent algorithms, parallel computing methodologies, distributed computing models, new computer architectures, cloud computing, data centers, and so on. We are hoping the articles in this Special Section will guide future applications and research on computer architectures and computer systems.

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

  • Parallel Architectures and Hardware Systems
  • Parallel Software
  • Distributed and Cloud Computing
  • Parallel Algorithms and Applications
  • GPU neuromorphic computing, intelligent control and computing on FPGAs

 

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

Associate Editor:  Songwen Pei, University of Shanghai for Science and Technology, China

Guest Editors:

    1. Junjie Wu, National University of Defense Technology, China
    2. Tao Li, Nankai University, China
    3. Yong Chen, Texas Tech University, USA
    4. Stéphane Zuckerman, University of Cergy-Pontoise, France

 

Relevant IEEE Access Special Sections:

  1. Artificial Intelligence in CyberSecurity
  2. Innovation and Application of Intelligent Processing of Data, Information and Knowledge as Resources in Edge Computing
  3. Distributed Computing Infrastructure for Cyber-Physical Systems


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

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

For inquiries regarding this Special Section, please contact:  swpei@usst.edu.cn or songwenpei@gmail.com.