Impact Score 2.97
Aims and Scope:
In today’s era of connected digital world, Intelligent Embedded Systems (IES) represent a novel and promising generation of embedded systems and have the capacity of reasoning about their external environments and adapt their behavior accordingly. While embedded systems are a very mature technology overall, with the steady advancement of new and more powerful processors, the technology now enables the next-generation of intelligent devices, machines, equipment, and factories. Technologies such as smart sensing, RFID tagging, embedded internet, edge computing, and predictive data mining all work to permeate intelligence and decision making into the physical world with the ultimate aim of continually enhancing human experience in real-time. “Big data” is another important technology, in which analytics provides real-time insights, which need to be actioned upon quickly to support decisions, gain better value, and mitigate risk. Moreover, artificial intelligence (AI), and particularly the machine learning, has been intensively applied to deal with large-scale heterogeneous data to help innovate and transform businesses. The convergence of these two technology paths is highly promising, and opens up new avenues of IES.
The aim of this special issue is to discuss how large-scale data systems and AI can be leveraged to enhance the learning, reasoning, and decision-making in embedded systems, in real-time. Data governance, data integration, data storage, data quality and data security are some criticalities associated with this problem, while conventional embedded system architectures and protocols are used to prepare data are inadequate. Unlike traditional data sets that are commonly associated with embedded systems, big data tends to be unstructured, multi-modal, and in the case of human-centric text, perhaps multi-lingual. The incompleteness, fuzziness and uncertainty make it even more intricate to tap and analyse information using contemporary tools. We invite researchers to discuss intelligent embedded system design methods, optimization techniques, protocols and architectures. Novel approaches to information discovery and decision making which use multiple intelligent technologies such as machine learning, deep learning, artificial intelligence, natural language processing and image recognition among others are required to understand data & then generate insights. We also welcome implementation papers on analyzing and processing of big data and practical data-driven decision making by discovering and understanding knowledge from the data.
The topics of interest include, but are not limited to:
Manuscript Submission Deadline : 30 Jun, 2021
Decision notification (1st Round) : 30 Sep, 2021
Revision Submission : 30 Oct, 2021
Decision on Revision (2nd Round) : 30 Nov, 2021
Final manuscript Submission : 15 Dec, 2021
Publication Date : As per Journal Decision
Submission of a manuscript implies: that the work described has not been published before; that it is not under consideration for publication anywhere else; that its publication has been approved by all co-authors, if any, as well as by the responsible authorities – tacitly or explicitly – at the institute where the work has been carried out. The publisher will not be held legally responsible should there be any claims for compensation:
Dr. V.Vinoth Kumar (Leading Guest Editor)
Associate Professor, Department of Computer Science and EngineeringMVJ College of Engineering, Bangalore, IndiaE-mail:
Dr. Muhammad Shafique
Associate Professor of Electrical and Computer Engineering
New York University Abu Dhabi
Email: [email protected]
Dr. Ahmed A.Elngar
Faculty of computers & Artificial Intelligence
Email: [email protected]
Dr. Polinpapilinho F. Katina
Department of Informatics and Engineering systems
University of South Carolina Upstate,
Guest Editors Detail:
Lead Guest Editor
Dr. V.Vinoth Kumar, MVJ College of Engineering, India
Dr.V.Vinoth Kumar is an Associate Professor at Department of Computer Science, MVJ College of Engineering, India. His current research interests include Big Data Analytics, Internet of Things, machine learning and wireless networks. He is the author/co-author of papers in international journals and conferences including SCI indexed papers. He has published as over than 35 papers in IEEE Access, Springer, Elsevier, IGI Global, Emerald etc.. He is a reviewer for Elsevier, IEEE Access, IEEE Transactions, and Springer journal. He has demonstrable experience in leading large-scale research projects and has achieved many established research outcomes that have been published and highly cited in many significant Journals and Conferences. He is the Associate Editor of International Journal of e-Collaboration (IJeC) and Editorial member of various journals. He has also been a guest editor of several international journals including, Journal of Intelligent Manufacturing (Springer), International Journal of Intelligent Computing and Cybernetics, International Journal of e-Collaboration (IJeC), International Journal of Pervasive Computing and Communications(IJPCC), International Journal of System of Systems Engineering(IJSSE), International Journal Speech Technology (IJST)-Springer, Journal of Reliable Intelligent Environments (JRIE), International journal of Information Technology and Web Engineering (IJITWE),International Journal of Machine Learning and Computing (IJMLC),International Journal of Cloud Computing (IJCC),International Journal of Information Quality (IJIQ) ,Journal of Computational and Theoretical Nanoscience and International Journal of Intelligent Enterprise (IJIE).
He has been professional society member of ISTE, IACIST and IAENG. He has co-chaired major Conferences Program Committees such as: ICACB’18, ICAIIS’19 etc. He has filed 3 IPR patents in IOT applications and currently doing funding project to CSIR and ISRO.
Dr. Muhammad Shafique, NYU Abu Dhabi, UAE
Email: [email protected]
Muhammad Shafique (M’11 - SM’16) received the Ph.D. degree in computer science from the Karlsruhe Institute of Technology (KIT), Germany, in 2011. Afterwards, he established and led a highly recognized research group at KIT for several years as well as conducted impactful R&D activities in Pakistan. Besides co-founding a technology startup in Pakistan, he was also an initiator and team lead of an ICT R&D project. In Oct.2016, he joined the Institute of Computer Engineering at the Faculty of Informatics, Technische Universität Wien (TU Wien), Vienna, Austria as a Full Professor of Computer Architecture and Robust, Energy-Efficient Technologies. Since Sep.2020, he is with the Division of Engineering, New York University Abu Dhabi (NYUAD), UAE, and a global faculty at the Tandon School of Engineering at NYU, USA.
His research interests are in brain-inspired computing, AI & machine learning hardware and system-level design, energy-efficient systems, robust computing, hardware security, emerging technologies, FPGAs, MPSoCs, and embedded systems. His research has a special focus on cross-layer analysis, modeling, design, and optimization of computing and memory systems. The researched technologies and tools are deployed in application use cases from Internet-of-Things (IoT), smart Cyber-Physical Systems (CPS), and ICT for Development (ICT4D) domains.
Dr. Shafique has given several Keynotes, Invited Talks, and Tutorials, as well as organized many special sessions at premier venues. He has served as the PC Chair, General Chair, Track Chair, and PC member for several prestigious IEEE/ACM conferences. Dr. Shafique holds one U.S. patent has (co-)authored 6 Books, 10+ Book Chapters, and over 300 papers in premier journals and conferences. He received the 2015 ACM/SIGDA Outstanding New Faculty Award, AI 2000 Chip Technology Most Influential Scholar Award in 2020, six gold medals in educational career, and several best paper awards and nominations at prestigious conferences like DATE, DAC, ICCAD, and Codes+ISSS. He also received two IEEE Transactions of Computer "Feature Paper of the Month" Awards, DAC'14 Designer Track Best Poster Award, and a Best Lecturer Award. He is a senior member of the IEEE and IEEE Signal Processing Society (SPS), and a member of the ACM, SIGARCH, SIGDA, SIGBED, and HIPEAC.
Dr. Elngar, Beni-Suef University, EGYPT
Dr. Elngar is the Founder and Head of Scientific Innovation Research Group (SIRG) and Assistant Professor of Computer Science at the Faculty of Computers and Information, Beni-Suef University. Dr. Elngar is a Director of the Technological and Informatics Studies Center (TISC), Faculty of Computers and Information, Beni-Suef University. He is a Managing Editor: Journal of Cyber security and Information Management (JCIM) Dr. Elngar has more than 25 scientific research papers published in prestigious international journals and over 5 books covering such diverse topics as data mining, intelligent systems, social networks and smart environment. He is a member in Egyptian Mathematical Society (EMS) and International Rough Set Society (IRSS). His other research areas include Internet of Things (IoT), Network Security, Intrusion Detection, Machine Learning, Data Mining, Artificial Intelligence. Big Data, Authentication, Cryptology, Healthcare Systems, Automation Systems. He is a editorial member of International Journal of Hybrid Intelligence (IJHI) (inderscience), Azerbaijan Journal of High-Performance Computing, International Institute of Academic Research & Publications (IIARP), International journal for innovative research in Multidisciplinary field (IJIRMF), International journal of research culture society(IJRCS),International Journal of Engineering and Designing Innovation (IJEDI),International Journal of Computer science and mobile computing(IJCSMC),Journal of Mathematical Sciences & Computational Mathematics(JMSCM),IJBST Group of Journals, International Journal of Research in Engineering and Management [IJREM],Journal of Mathematical Control Science and Applications (JMCSA). He is a Managing Editor of Journal of Cyber security and Information Management (JCIM) and Hon'ble Editorial Board Member, IJBST Journal Group.
Dr. Polinpapilinho F. Katina, University of South Carolina Upstate, USA
Email: [email protected]
Polinpapilinho F. Katina is an Assistant Professor (Tenure track) in the Department of Informatics and Engineering Systems at the University of South Carolina Upstate (Spartanburg, South Carolina, USA). He previously served as a Postdoctoral Researcher for the National Centers for System of Systems Engineering (Norfolk, Virginia, USA) and Adjunct Professor in the Department of Engineering and Systems Engineering at Old Dominion University (Norfolk, Virginia, USA). Dr. Katina holds a B.Sc. in Engineering Technology with a minor in Engineering Management, a M.Eng. in Systems Engineering and a Ph.D. in Engineering Management/Systems Engineering, all from Old Dominion University (Norfolk, Virginia, USA). He has received additional training from, among others, Environmental Systems Research Institute (Redlands, California) and Politecnico di Milano (Milan, Italy). He is a editorial member of various journals, Complex System Governance, Critical Infrastructure Systems, Decision Making and Analysis (under uncertainty), Emerging Technologies, Energy Systems (Smart Grids), Engineering Management, Infranomics, Manufacturing Systems, System-of-Systems, Systems Engineering, Systems pathology, and Systems Thinking. Dr. Katina’s profile includes more than 150 scholarly outputs in the form of peer-reviewed journal articles, conference proceedings, book chapters and books. Other highlights include: Named in the top 1% for the 2018 Publons Global Peer Review Awards, Serving as a Guest Editor for the International Journal of Critical Infrastructures (2014), Serving as a Guest Editor for the International Journal of System of Systems Engineering (2015), Panellist for the 2017 National Defense Science and Engineering Graduate Fellowship, Panel list for the 2019 National Defense Science and Engineering Graduate Fellowship, Founding board member for the International Society for Systems Pathology (Claremont, California), Course developer (2018 – 2019) of four new courses in a newly formed program at the University of South Carolina Upstate.