Innovation and Application of Internet of Things and Emerging Technologies in Smart Sensing

Submission Deadline: 01 January 2020

IEEE Access invites manuscript submissions in the area of Innovation and Application of Internet of Things and Emerging Technologies in Smart Sensing.

Internet of Things (IoT) technology is not just about the connection among billions of devices, it is about enabling a wide range of new capabilities, architectures, or service paradigms. The scale of the IoT is set to have major economic, social, and environmental impact, the intersection of which forms future sustainable growth.

However, the implementation of IoT faces various challenges, including sensing ability, energy consumption, power supply, data security, privacy, and data accountability. To mitigate this issue, more and more IoT systems are embracing the new IoT paradigm, such as mmWave, sensor-less sensing, backscattering Wi-Fi/RFID, wireless/vision hybrid, block chain, fat client, etc. These modes shed light on the emerging technologies that could revolutionize the conventional IoT system.

This Special Section in IEEE Access invites manuscript submissions in the area of Internet of Things (IoT). We particularly encourage articles demonstrating novel methods and systems to the latest IoT applications. Applications may be drawn by investigating the usage of novel methods for all aspects of sensing, energy saving, mixed architecture, and security management.

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

  • Emerging technologies in smart sensing
  • Edge computing in IoT fat client
  • Emerging architecture in mixed IoT and edge computing
  • Joint sensing and communication in IoT network
  • Modeling of sensor systems in IoT network
  • IoT and Edge Computing for Smart Cities
  • Big Data in IoT system
  • Low-latency, High-reliability Communications for IoT
  • Security, privacy and forensics in IoT
  • 5G support for IoT data transmission

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

 

Associate Editor:  Honghao Gao, Shanghai University, China

Guest Editors:

  1. Shaojie Tang, The University of Texas at Dallas, USA
  2. Wan Du, University of California, USA
  3. Xinheng Wang,  Xi’an Jiaotong Liverpool University, China
  4. Yuyu Yin, Hangzhou Dianzi University, China

 

Relevant IEEE Access Special Sections:

  1. Heterogeneous Crowdsourced Data Analytics
  2. Trends and Advances for Ambient Intelligence with Internet of Things (IoT) systems
  3. Healthcare Big Data


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: gaohonghao@shu.edu.cn.

Artificial Intelligence Technologies for Electric Power Systems

Submission Deadline: 31 December 2019

IEEE Access invites manuscript submissions in the area of Artificial Intelligence Technologies for Electric Power Systems.

As the main energy supply system and the most complicated artificial system, the electric power system is undergoing revolutionary changes, including high-penetration renewable energy resources, complicated networks with tremendous data communications, and numerous power devices with the feature of bi-directional energy flow. Developing an intelligent power and energy system is becoming more and more urgent to promote the power production and consumption revolution and construct a clean, low-carbon, safe, and efficient energy system. Currently, artificial intelligence, as a newly developed scientific technology used to imitate, stretch, and extend the theory, method, technology, and application of human intelligence, is providing a great support for promoting the intelligence revolution of power and energy system. Artificial intelligence technology with attractive features such as deep learning, cross-border integration, man-machine cooperation, open group intelligence, and autonomous control shows the strong handling capacity in perceptual intelligence, computational intelligence, and cognitive intelligence, which shows great potential in reshaping the way of producing and utilizing the electrical energy. In particular, the combination of artificial intelligence with cloud computing, big data, internet of things (IoT), and mobile interconnection can endow the power system with features of intelligent interaction, safety, and controllability. Thus, the security, reliability, and flexibility of the power grid can be significantly improved. The revolution of the power and energy system can be highly sped up.

The goal of this Special Section in IEEE Access is to welcome the latest research in the area of Artificial Intelligence Technologies for Electric Power Systems. Reviews, surveys and traditional research articles are welcome to submit to this Special Section.

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

  • Image recognition technology and its application in power system security management
  • Intelligent optimization and its application in power system planning, market trade, and dispatch
  • Intelligent electric power equipment
  • Big-data-based intelligent prediction and assistant decision-making
  • Intelligence integration of renewable energy resources
  • Artificial-intelligence-based power management and consumption
  • Application of artificial intelligence in power system security and stability
  • Artificial-intelligence-based power equipment maintenance plan

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

 

Associate Editor:  Canbing Li, Hunan University, China

Guest Editors:

  1. Hui Liu, Guangxi University, China
  2. Long Zhou, Guangdong Power Grid Co., Ltd, China
  3. Sheng Huang, Technical University of Denmark, Denmark
  4. Mingjian Cui, Southern Methodist University, USA
  5. Wuhui Chen, Jiangsu University, China
  6. Cong Zhang, Hunan University, China
  7. Jin Ma, The University of Sydney, Australia

 

Relevant IEEE Access Special Sections:

  1. Software Defined Networks for Energy Internet and Smart Grid Communications
  2. Artificial Intelligence and Cognitive Computing for Communications and Networks
  3. AI-Driven Big Data Processing: Theory, Methodology, and Applications


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

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

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

Innovation and Application of Intelligent Processing of Data, Information and Knowledge as Resources in Edge Computing

Submission Deadline:  29 February 2020

IEEE Access invites manuscript submissions in the area of Innovation and Application of Intelligent Processing of Data, Information and Knowledge as Resources in Edge Computing.

Recently, edge computing is proposed as a new computing paradigm where resources like computation and storage are placed closer to the data and information source. Compared to cloud computing, edge computing enables a new class of latency and bandwidth sensitive applications since data can be processed at the network edge. It also brings new possibilities for the security and privacy research field, especially in data resilience and accessibility. A foreseeable developing direction is that more types of resources will be automatically and cooperatively processed at the edge and at the Cloud. Specifically, the resources to be processed will cover all types of data, information, knowledge and wisdom (DIKW) pyramid; the supported processing will include data sensing and acquisition, information analysis and abstraction, and knowledge generation and reasoning (potentially in the form of graphs).

However, there are still several issues which need to be solved: (a) conceptual modeling of the typed resources of data, information and knowledge at the source, (b) data-driven scheduling policies, especially the tradeoff of the computation/bandwidth cost and the performance improvement with the potential offloading overhead between the edge and the Cloud, and (c) the optimal organization of the network nodes at both the edge and the Cloud in terms of storage, bandwidth and computation distribution.

The goals of this Special Section in IEEE Access are (1) to present the state-of-the-art research on typed resource processing in Edge computing, and (2) to provide a forum for experts to disseminate their recent advanced views and ideas on future directions in this field.

In this Special Section, we encourage articles that present new theories, methods and techniques applied to value or quality-driven resource processing in Edge Computing. We particularly prefer articles demonstrating novel strategies to handle the types of processed resources. Applications may be drawn by investigating the usage of novel methods for all aspects of resource processing, including system design, performance optimization, algorithm design, scheduling, energy saving, and security management.

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

  • Typed resources modeling for Edge Computing
  • Data acquisition and linking for Edge Computing
  • Services composition and recommendation for Edge Computing
  • Testing technology for Edge Computing
  • Information analysis and abstraction for Edge Computing
  • Knowledge creation and reasoning for Edge Computing
  • Quality evaluation for resources management
  • Resources management, transfer and storage
  • Energy efficiency in Edge Computing
  • Value-driven optimization of resources processing
  • Smart Technologies for resource processing and utilization
  • Formal Modeling and Verification for resources processing
  • Big data and data analysis in Edge Computing
  • Security and privacy in resources processing and utilization
  • Device management (configuration, performance, and capacity) at the Edge
  • Offloading and cooperation between Edge and Cloud

 

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

 

Associate Editor: Honghao Gao, Shanghai University, China

Guest Editors:

  1. Ying Li, Zhejiang University, China
  2. Antonella Longo, Unversity of Salento, Italy
  3. Gongzhu Hu, Central Michigan University , USA
  4. Christophe Cruz, University of Bourgogne, France
  5. Jung-Yoon Kim, Gachon University, South Korea
  6. Alex Norta, Tallinn University of Technology, Estonia

 

Relevant IEEE Access Special Sections:

  1. Trusted Computing
  2. Internet-of-Things (IoT) Big Data Trust Management
  3. Data Mining and Granular Computing in Big Data and Knowledge Processing


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

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

For inquiries regarding this Special Section, please contact: gaohonghao@shu.edu.cn.

Information Centric Wireless Networking with Edge Computing for 5G and IoT

Submission Deadline:  15 March 2020

IEEE Access invites manuscript submissions in the area of Information Centric Wireless Networking with Edge Computing for 5G and IoT.

The advent of the Internet of Things (IoTs) and Fifth Generation (5G) high-speed communication networks is expected not only to make it necessary to rapidly increase the number of communication nodes and generate large amounts of data, but also to change the nature of the network to a more dynamic environment. However, the present network structure and operation method have various problems to be solved in order to cope with the aforementioned changes. Some issues, for example, are Transmission Control Protocol/Internet Protocol (TCP/IP)-based and end-to-end-based centralized and rigid network structure, the lack and allocation difficulties of IP addresses, increasing network traffic forwarding massive data to the cloud at remote locations for high capacity data processing, increasing delays in receiving effective analytic results from the remote cloud server, etc.

To address these issues, Information Centric Networking (ICN) technology is proposed to replace the current TCP/IP structure and present a flexible network structure in the IoT environment. Edge Computing technology is proposed to provide low-delay services by processing large amounts of data quickly in short proximity. Well-known related projects are Content Centric Networking (CCN) and Named Data Networking (NDN). While ICN has actively been studied, ICN for wireless networks has not been studied much. In addition, since ICN and Edge Computing have common functionalities such as caching, the two technologies may need to be co-located, and cooperate with each other. Integrating the technologies has not extensively been studied, and even less so for wireless environments.

Therefore, in this Special Section in IEEE Access, we invite researchers and experts to contribute original research articles as well as review articles about the research topics related to Information Centric Wireless Networking (ICWN). It adopts ICN technology for efficient and seamless wireless networks and Information Centric Wireless Edge Networking (ICWEN) technology, which integrates ICWN and EDGE computing technologies for the high reliability and low delay communication networks required by 5G LTE.

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

  • Architecture and protocols for adopting ICN technologies to distributed and centralized wireless networks
  • Network-wide architecture and node architecture for ICWN and ICWEN
  • Naming schemes for ICWN and ICWEN
  • Applications for ICWN and ICWEN
  • Caching schemes for ICWN and ICWEN
  • Performance evaluations in regard to: ICN vs. ICWN, ICN with Edge vs. ICN without Edge
  • Reliability, QoS support, Sustainability, Mobility support, Energy efficiency, Securities of ICWN and ICWEN
  • Interoperability of ICWN and ICWEN with other heterogeneous networks
  • Theoretical and experimental performance evaluations of ICWN and ICWEN
  • Analytic models for the behavior of ICWN and ICWEN, especially for scalability properties
  • Test-Bed implementation and measurement using CCNx, CCN-Lite, NDN
  • ICWN and ICWEN with IoT, 5G LTE, and Autonomous Driving, etc.

 

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

 

Associate Editor: Byung-Seo Kim, Hongik University, Korea

Guest Editors:

  1. Chi Zhang, University of Science and Technology of China, China
  2. Yuanxiong Guo, Oklahoma State University, USA
  3. Muhammad Khalil Afzal, COMSATS Institute of Information Technology, Pakistan
  4. Balazs Sonkoly, Budapest University of Technology and Economics (BME), Hungary

 

Relevant IEEE Access Special Sections:

  1. Fog Radio Access Networks (F-RANs) for 5G: Recent Advances and Future Trends
  2. Sustainable Infrastructures, Protocols, and Research Challenges for Fog Computing
  3. Smart Caching, Communications, Computing and Cybersecurity for Information-Centric Internet of Things


IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

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

For inquiries regarding this Special Section, please contact: jsnbs@hongik.ac.kr.

Biologically inspired image processing challenges and future directions

Submission Deadline: 31 August 2019

IEEE Access invites manuscript submissions in the area of Biologically inspired image processing challenges and future directions.

Human beings are exposed to large amounts of data. According to statistics, more than 80% of the information received by humans comes from the visual system. Therefore, image information processing is not only an important research topic, but also a challenging task. The unique information processing mechanism of the human visual system makes it have fast, accurate and efficient image processing capability. At present, many advanced techniques of image analysis and processing have been widely used in image communication, geographic information system, medical image analysis and virtual reality. However, there is still a big gap between these technologies and the human visual system. Therefore, building an image system research mechanism based on the biological vision system is an attractive but difficult target. Although it is a challenge, it also can be considered as an opportunity which utilizes biologically inspired ideas. Meanwhile, through the integration of neural biology, biological perception mechanism, computer science and mathematical science, the related research can bridge biological vision and computer vision. Finally, the biologically inspired image analysis and processing system is expected to be built on the basis of further consideration of the learning mechanism of the human brain.

The goal of this Special Section in IEEE Access is to explore biological vision mechanisms and characteristics to establish an objective image-processing model and algorithm that is closer to the human visual information-processing model. This Special Section is encouraging advanced research related to biologically inspired image system study and to promote the synergetic development of biological vision and computer vision. Original research articles seeking all biologically inspired aspects of image analysis and processing techniques, including emerging trends and applications, theoretical studies, and experimental prototypes are welcome. The manuscripts should not be submitted simultaneously for publication elsewhere. Submissions of high quality manuscripts describing future potential or ongoing work are sought.

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

  • Biologically inspired novel color image enhancement techniques
  • Biologically inspired image/video feature modeling and extraction
  • Research on bio inspired virtual reality and human-computer interaction
  • Biologically inspired depth learning for unsupervised & semi-supervised learning
  • Biologically inspired big data analysis of image system
  • Biologically inspired multimedia quality evaluation
  • Biologically inspired target recognition technology in Real-time dynamic system
  • Biologically inspired image restoration Research and Application
  • Biologically inspired target detection and classification
  • Research and application of biologically inspired visual characteristics
  • Biologically inspired statistical learning model for image processing
  • Biologically inspired graph optimization algorithms and application

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

Associate Editor: Jiachen Yang, Tianjin University, China

Guest Editors:

  1. Qinggang Meng, Loughborough University, UK
  2. Maurizio Murroni, University of Cagliari, Italy
  3. Shiqi Wang, City University of Hong Kong, China
  4. Feng Shao, Ningbo University, China

Relevant IEEE Access Special Sections:

  1. Visual Surveillance and Biometrics: Practices, Challenges, and Possibilities
  2. Recent Advantages of Computer Vision based on Chinese Conference on Computer Vision (CCCV) 2017
  3. New Trends in Brain Signal Processing and Analysis


IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

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

For inquiries regarding this Special Section, please contact: yangjiachen@tju.edu.cn.

Urban Computing and Intelligence

Submission Deadline: 31 August 2019

IEEE Access invites manuscript submissions in the area of Urban Computing and Intelligence.

Urban computing and intelligence will bridge the gap of ubiquitous sensing, intelligent computing, cooperative communication and mass data management technologies to create novel solutions to improve urban environments, quality of life and smart city systems.

With the help of cloud computing, Internet of Things, device to device (D2D) communication, artificial intelligence and big data, urban computing and intelligence novel solutions can be created to improve urban environment, human life quality, and smart city systems. Thus, urban computing and intelligence have recently attracted significant attention from industry and academia for building smart cities. However, it faces significant challenges. As the city size increases, the total costs and resource consumption will rise, the performance will decrease, and the security of the systems faces serious threats.

The objective of this Special Section in IEEE Access is to present a collection of high-quality research articles reporting the latest research advances in the area of urban computing and intelligence, mainly including artificial intelligence models, intelligent networking, heterogeneous data analytics, urban sensing and energy management, etc., to cope with the challenges in real world.

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

  • Artificial Intelligence Models
  • Intelligent Services and Innovative Applications for Urban Regions
  • User-centric Ultra-dense Intelligent Networking
  • Big data Infrastructures for Urban Analytics
  • Acquisition, Management, and Real-time Analysis for Big and Heterogeneous Data
  • Data Mining and Machine Learning For Smart Cites
  • Urban Sensing and City Intelligent Sensing
  • Security, Trust and Privacy of Urban Computing
  • Intelligent Energy Management
  • QoS (Quality of Service) and QoE (Quality of Experience)
  • City infrastructures and Operation Systems for Smart Cites
  • Semantic Technologies for Smart Cities
  • Urban Visualization Methods
  • Hybrid Systems Bridging the Physical and Digital World
  • Urban Environment Monitoring, Analytics and Prediction

 

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 Derby, UK
  2. Maode Ma, Nanyang Technological University, Singapore
  3. Hongxiang Li, University of Louisville, USA
  4. Shiwen Mao, Auburn University, USA

 

Relevant IEEE Access Special Sections:

  1. Urban Computing & Well-being in Smart Cities: Services, Applications, Policymaking Considerations
  2. Smart Caching, Communications, Computing and Cybersecurity for Information-Centric IoT
  3. Artificial Intelligence and Cognitive Computing for Communications and Networks


IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

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

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

Data-Enabled Intelligence for Digital Health

Submission Deadline: 15 September 2019

IEEE Access invites manuscript submissions in the area of Data-Enabled Intelligence for Digital Health.

The worldwide increase in the aging population presents an urgent need for new technologies to improve the quality of life for the elderly. In recent years we have seen rapid development of healthcare technologies along with the widespread use of Internet, mobile technologies, data analytics and artificial intelligence in healthcare. These developments have resulted in highly multi-disciplinary research in digital health and smart health, and have also driven the move towards more personalized care.

Digital health aims to apply data sciences, machine learning, artificial intelligence and the internet of things to tackle the health problems and challenges faced by patients and the care professionals. For example, tracking personalized health indicators regularly such as blood pressure, heart rate and others can help with the management of the health and well-being of patients with heart issues.

New technologies developed in the digital industry, particularly in the emerging interfacing area between big data and artificial intelligence, are changing the way healthcare is delivered and can have an enormous economic impact on healthcare provision. We are experiencing extensive research in health care including the development of new smart sensing, new algorithms, and new systems or devices for personalized healthcare. One of the fundamentals of these developments is to ensure that healthcare data can be accessed and analyzed effectively in order to support accurate decision-making. Most digital health system design has been focused on the functionalities defined by the domain expertise. For these types of systems, user experience and effectiveness of the systems will very much depend on the users’ knowledge of the system. This can be a challenging issue for personalized healthcare, particularly for users with disabilities and in an aging society.

Extensive research is currently taking place worldwide in the related areas, which in return raises new scientific questions as well as practical issues; for example (1) what will the next generation of Artificial Intelligence (AI) provide for us to achieve a better quality of life, particularly for our aging society? (2) How can healthcare systems be data-enabled to exploit a learning capability and fit in personal needs? (3) How can data-enabled technologies support effective human-machine cooperation and adapt to each other, and ultimately support humans and machines to work together? and (4) How can human-machine cooperation drive new intelligence to improve the quality of life for people in the healthcare systems?

This Special Section in IEEE Access aims to attract original research articles that advance the state of the art in digital health as well as data science and artificial intelligence. The goal is that it provides an opportunity for us to gain a significantly better understanding of the current developments and the future direction of artificial intelligence and data science in relation to healthcare.

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

  • New technologies and frameworks that support human-machine interaction and human-machine collaborative intelligence
  • Brain-Computer modeling for human-machine cooperation
  • Cognitive computing for healthcare and data intelligence
  • Brain-Computer modeling for cognitive intelligence
  • The design and implementation of personalized healthcare systems
  • The value and challenges of human-machine collaboration in healthcare
  • Data Science and artificial intelligence in digital health, and health management
  • Data science and artificial intelligence in public health
  • Machine learning to understand human behavior and well-being
  • New algorithms for medical and healthcare data analytics
  • Predictive analysis in personalized healthcare
  • Intelligent and predictive analytics for early warning, feedback and in-time intervention for personalized healthcare
  • The cutting edge development of digital health
  • New digital technologies to assist mental healthcare
  • New technology to enable personal data security and effective use in healthcare

 

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

 

Associate Editor:  Yonghong Peng, University of Sunderland, UK

Guest Editors:

  1. Wenbing Zhao, Cleveland State University, United States
  2. Yongtao Hao, Tongji University, China
  3. Yongqiang Cheng, University of Hull, United Kingdom
  4. Linbo Qing, Sichuan University, China
  5. Weihong Huang, Xiangya Hospital, China
  6. Ying Song, West China Hospital, China

 

Relevant IEEE Access Special Sections:

  1. Advanced Information Sensing and Learning Technologies for Data-centric Smart Health Applications
  2. Mobile Multimedia for Healthcare
  3. Healthcare Big Data


IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

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

For inquiries regarding this Special Section, please contact: Yonghong.Peng@Sunderland.ac.uk

Security, Privacy, and Trust Management in Smart Cities

Submission Deadline: 30 June 2019

IEEE Access invites manuscript submissions in the area of Security, Privacy, and Trust Management in Smart Cities.

Building a smart city is no longer just a vision, it’s close to a reality. Many organizations, government agencies, and research institutes are working toward the fulfillment of interconnected, instrumented, and intelligent smart cities. Such cities will offer intelligent and advanced services to its citizens — education, transport, surveillance, housing, healthcare, energy, and other services — to improve the quality of lives. However, this comes at a cost of collecting, storing, processing, and analyzing a huge volume of heterogeneous data sensed from the environment and often contributed by the citizens. The evolution of Internet of Things, cloud computing, social networking, and other Industry 4.0 influencers is pushing technology inside the fabric of smart society, which also brings potential vulnerabilities in smart city data, services, and applications. These vulnerabilities  then lead to concerns about whether the data of the citizens is securely transmitted and stored, whether it is kept private and restricted to unauthorized access, and whether the offered services are trustworthy and dependable.

Many efforts are underway to address these concerns of security, privacy, and trust. Existing security and privacy solutions work reasonably well in different scenarios, although we witness an increasing attempt by hackers and intruders to often prove it otherwise. Therefore, providing security and privacy to smart city data, services, and applications would require further investigation on emerging solutions. Besides security and privacy, smart city services and applications must be trustworthy and reliable against all odds such that any attacks on security or privacy violations are immediately detected and resolved; this is a challenging task. The proposed  Special Section in IEEE Access aims to attract researchers and experts from different institutes and organizations working in security, privacy, and trust in smart cities.

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

  • Dynamic security solutions for smart city data, services, and applications
  • Security and privacy requirements engineering of smart city services
  • Privacy enhancement for future IoT-cloud based applications in smart city
  • Architecture and design of smart city service infrastructure
  • Security and privacy vulnerability assessment in smart city
  • Trust-based privacy protection in smart city
  • Trustworthy computing model for smart city
  • Dependability of smart city services and applications
  • Privacy protection of big data in IoT-cloud enabled smart city
  • Techniques for preserving security and privacy of different smart city services and applications
  • Security and privacy for networked vehicles.

 

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

 

Associate Editor:  Mehedi Masud, Taif University, Saudi Arabia

Guest Editors:

  1. Wen-Huang Cheng, National Chiao Tung University, Taiwan
  2. Carlisle Adams, University of Ottawa, Canada
  3. Mukesh Saini, IIT Ropar, India
  4. Jorge Parra, IK4-Ikerlan, Spain

 

Relevant IEEE Access Special Sections:

  1. Smart Caching, Communications, Computing and Cyber Security for Information-Centric Internet of Things
  2. New Era of Smart Cities: Sensors, Communication Technologies, and Applications
  3. Security and Privacy in Applications and Services for Future Internet of Things


IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

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

For inquiries regarding this Special Section, please contact: mehediku@hotmail.com

New Technologies for Smart Farming 4.0: Research Challenges and Opportunities

Submission Deadline: 15 August 2019

IEEE Access invites manuscript submissions in the area of New Technologies for Smart Farming 4.0: Research Challenges and Opportunities.

According to a United Nations report published in June 2017, the world population is expected to reach 9.8 billion in 2050 [1]. Agriculture consumes a tremendous amount of natural resources. For example, agriculture uses 70% of the world’s fresh water supply [2]. Under the constraints of limited planet resources and the deteriorating climate environments, how to produce sufficient and high quality food to feed the increasing population is a pressing issue faced by the human race.

Since the beginning of the 20th century, agriculture has been advancing continuously to precision agriculture, commonly referred to as agriculture 3.0, through the adoption of new technologies, such as GPS, satellite imaging and advanced image analysis. Smart farming 4.0 is posed to significantly advance the state-of-the-art of agriculture through the integration of a broad range of additional advanced technologies, including Internet-of-things (IoT), cloud computing, etc. [4]. In the report, “The future of technology in agriculture” published by a Netherlands research center in 2016, 20 new technologies have been identified to increase agricultural and livestock yield while using less resources and preserving natural environments and biodiversity [3].

Currently many organizations and private companies (e.g., IRSTEA and MOSANTO) throughout the world are actively investigating new technologies for agriculture. They are from many different industries and economic sectors, ranging from finance, engineering, food retailers, to industry associations and groups of small farming suppliers [2]. Due to the diversity and heterogeneity of the stakeholders, it is important to facilitate dialogues and cooperation in the process of developing standards for smart farming and improving interoperability between different systems and technologies.

This Special Section in IEEE Access aims to present cutting-edge research in the areas of cyber physical systems, IoT, and cloud platform and services for smart farming 4.0. We solicit theoretical and practical contributions, as well as surveys or reviews with clear use cases.

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

  • Holistic cyber physical systems for smart farming
  • User-friendly and application-oriented visualization and decision support system
  • Interoperability of heterogeneous devices and actuators
  • Multi-support edge routers and communication protocols
  • Ontology, sensor metadata and semantic data
  • Big data systems and technologies
  • Scalable IoT cloud platforms for small to large farms
  • Massive data integration and fusion
  • Unmanned robotic vehicle, unmanned aerial vehicle, and collaborative processing of remote and proximity sensory data
  • Wireless network access medium, low power WiFi and BLE
  • Robust, energy efficient and long lifetime architecture of WSN node for outdoor application and field test
  • Robust and low cost user-friendly plug and play wireless sensor node, network architecture and implementation
  • New environment sensor technologies
  • Energy harvesting techniques for battery-less IoT node
  • AI and machine vision for agriculture and aquaculture.

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

 

Associate Editor:  Kun Mean Hou, University Clermont Auvergne, France

Guest Editors:

  1. Hadi M. Aggoune, Sensor Networks and Cellular Systems Research Center, University of Tabuk, Saudi Arabia
  2. Jean-Pierre Chanet, L’Institut national de recherche en sciences et technologies pour l’environnement et l’agriculture, France
  3. Yongsheng Gao, Griffith University, Australia
  4. Chengcheng Guo, Wuhan University, China
  5. Sudip Misra, School of Information Technology, Indian Institute of Technology Kharagpur, India
  6. Yi Shang, University of Missouri, USA.

 

Relevant IEEE Access Special Sections:

  1. Big Data Analytics in Internet-of-Things And Cyber-Physical System
  2. Convergence of Sensor Networks, Cloud Computing, and Big Data in Industrial Internet of Things
  3. Fairness in Futuristic Wireless Networks: Applications, Implementation, Issues, and Opportunities


IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

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

For inquiries regarding this Special Section, please contact: kun-mean.hou@uca.fr

Network Resource Management in Flying Ad Hoc Networks: Challenges, Potentials, Future Applications, and Wayforward

Submission Deadline: 01 July 2019

IEEE Access invites manuscript submissions in the area of Network Resource Management in Flying Ad Hoc Networks: Challenges, Potentials, Future Applications, and Wayforward.

With the rapid development in the fields of wireless ad hoc networks that do not rely on any pre-existing infrastructure, Flying Ad hoc networks (FANETs) have recently captured the attention of vendors and investors due to the flying nature of entities in the network. FANET is composed of unmanned nodes that fly at high altitude platforms such as balloons, unmanned aerial vehicles or drones. The network of nodes that fly at high altitude has gained commercial and industrial popularity because of its applications in surveillance, agriculture, photography, etc.  New applications that are being developed for FANET bring up new challenges such as multipath propagations, severe shadowing, traffic load balancing, mobility, congestion, high error rates, etc., that usually result in performance degradation of the network. However, the applications developed and used in FANET may also result in collision with other air traffic due to the above challenges.

The Federal Aviation Administration has  reported about the tremendous increase of more than 50% in  air traffic in unmanned vehicles in 2017. However, such an increase in the UAVs results in an increase in the network traffic of FANET that may lead to an unbalanced traffic distribution, resulting in an increase in packet loss. Furthermore, the high data traffic generated by the number of nodes in FANET is one of the leading causes of accidents with the commercial flights. In order to cope with such challenges, the network traffic of FANET must be distributed in such a way that it does not disturb commercial flights or the communication among the nodes that fly at high altitudes in a network.

This Special Section in IEEE Access therefore solicits original research work, novel protocols, methodologies and survey papers addressing the future challenges and solutions that embark on network resource management in FANETs.

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

  • Efficient deployment of unmanned aerial vehicles (UAVs) at high altitude platforms (HAPs) for congestion avoidance and control
  • Dynamic traffic load balancing for congestion avoidance through routing in Flying Ad hoc Networks
  • Performance investigation of 5G systems with flying ad hoc networks (FANETs)
  • An optimal data collection and dissemination technique for balanced traffic utilization in FANETs
  • Distributed congestion-aware position oriented MAC/Routing protocols for FANETs
  • Performance evaluation of layered protocols of TCP/IP for multimedia traffic in flying ad hoc networks (FANETs) at different altitude platforms
  • Analysis of Reactive, proactive, and hybrid routing protocols for flying Ad Hoc networks
  • Opportunistic routing for distributed video traffic dissemination over flying ad hoc networks
  • A cross layer design for distributed information dissemination over flying ad hoc networks
  • Agricultural environment monitoring system based on UAV in FANETs
  • Congestion avoidance, detection, and mitigation in Flying Ad-Hoc Network for efficient utilization of network resources
  • Distributed clustering approach for FANETs
  • Enhanced connectivity for robust multimedia transmission in UAV networks
  • Active Queue Management for resource sharing in Flying Ad hoc Networks
  • Bio-inspired routing protocols for FANET routing
  • Multi-hop and relay-based communications for distributed traffic load balancing
  • Smart solutions to reduce congestion in FANETs
  • Interaction of FANET with IoT
  • Distributed Emergency Message Dissemination in FANET

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

 

Associate Editor: Omer Chughtai, COMSATS University Islamabad, Wah Campus, Pakistan

Guest Editors:

  1. Mubashir Husain Rehmani, Waterford Institute of Technology, Ireland
  2. Leila Musavian, University of Essex, UK
  3. Sidi-Mohammed Senouci, University of Bourgogne, France
  4. Soumaya Cherkaoui, Université de Sherbrooke, Canada
  5. Shiwen Mao, Auburn University, USA
  6. Onur Alparslan, Osaka University, Japan

 

Relevant IEEE Access Special Sections:

  1. Fairness in Futuristic Wireless Networks: Applications, Implementation, Issues, and Opportunities
  2. Networks of Unmanned Aerial Vehicles: Wireless Communications, Applications, Control and Modelling
  3. Convergence of Sensor Networks, Cloud Computing, and Big Data in Industrial Internet of Things


IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

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

For inquiries regarding this Special Section, please contact:  umar.chughtai@gmail.com