Complex Embedded Systems for Mobile Sensors

Overview of Special Issue:

Complex Embedded systems (CES) design is crucial for the development of industry, technology and science; and it is an area that has significantly grown in recent years throughout the world, both in academia and industry.

Recent advancements in CES are paving the way for mobile and intelligent IoT sensors through a wide variety of protocols, architectures, services, and configurations. In the IoT era, mobile embedded systems are becoming increasingly complex and need understanding in various training tools such as signal processing, artificial intelligence, and multimedia communication. “Artificial intelligent and Big data” are the recent buzzword in which analytics provides real-time insights, which need to be actioned upon quickly to support decisions, gain better value, and mitigate risk. Concurrently, machine learning has been intensively applied to deal with large-scale heterogeneous data to help innovate and transform businesses.

The aim of this special issue is to discuss how CES can be leveraged to enhance the capabilities of Mobile Sensors using large-scale data systems and AI, in real-time. This Special Issue will focus on the high-quality research papers that articulate recent advancements on the subject, highlight open research issues and challenges, and indicate future directions. We invite investigators to contribute original research articles as well as review articles that will stimulate continuing efforts to understand Architectures using fundamental or applied algorithms such as AI and Big Data for CES.

 

Brief Highlights about this Special Issue:

1. Includes the new technologies for CES which will be a novel and promising field approximately in 10 years,

2. Provide a state-of-the-art and give a comprehensive overview of the different CES for Mobile Sensors using AI and Big Data.

3. Identify promising directions and future trends for those seeking to contribute and to the future literature of the field of CES for Mobile Sensors.

 

Topics and Techniques

Submissions of papers describing original work in following topics are enthusiastically encouraged.

• Intelligent sensors using Complex Embedded Systems
• Cloud-assisted sensors networks
• New algorithms for geolocation of mobile devices
• Embedded systems for data processing and for wireless signal transfer
• Intelligent embedded system protocols for high performance mobile sensors.
• Embedded-aware protocols for data quality and integrity in sensors.
• Privacy preservation, trust and security in intelligent embedded systems.
• New generation of multimedia sensors using AI and Big Data
• Multimedia techniques for mobile sensor devices
• Intelligent embedded computer vision and natural language processing systems using AI and big data.
• Intelligent sensing for smart cities using CES.
• CES for large-scale smart healthcare, avionics, transportation, and automotive.
• Mobile sensors and multimedia system design using CES
• Spatial and temporal estimation and protection of media streams
• Image resizing technique using multiple sensors using AI
• Big data analytics for embedded systems
• Intelligent sensors for CES
• Distributed computation, in-network processing, and data mining
• Case studies or applications of mobile sensors using CES

 

Schedule:

· Submission of manuscript: September 25, 2021

· First notification: November 25, 2021

· Submission of revised manuscript: January 30, 2022

· Final notification: April 25, 2022

 

Guest Editor(s):

Rohit Sharma, Ph.D. SMIEEE (Managing GE)

SRM Institute of Science and Technology,

Ghaziabad, India

Email: [email protected]

Web: https://sites.google.com/view/dr-rohit-sharma

 

 

Prof. Masoud Daneshtalab

Masoud has a accountFull Professor, Intelligent Future Technology,
Mälardalen University

Stockholm County, Sweden

Email: [email protected]

Web:www.idt.mdh.se/~md

https://scholar.google.com/citations?user=DO0lHt8AAAAJ&hl=en

 

Prof. Danda B. Rawat, PhD, IET Fellow

Professor, Department of Electrical Engineering & Computer Science

Director, DoD Center of Excellence in Artificial Intelligence & Machine Learning

Howard University, Washington, DC, 20059, USA.

E-mail: [email protected]

Web: http://www.cs.cea.howard.edu/users/drawat

https://scholar.google.com/citations?user=Klr5kY4AAAAJ&hl=en&oi=ao

 

Editor(s) Bios:

Rohit Sharma

Rohit Sharma is currently an Assistant Professor in the Department of Electronics and Communication Engineering, SRM Institute of Science and Technology, Delhi NCR Campus Ghaziabad, India. He is an active member of ISTE, IEEE, ICS, IAENG, and IACSIT. He is an editorial board member and reviewer of more than 12 international journals and conferences, including the topmost journal IEEE Access and IEEE Internet of Things Journal. He serves as a Book Editor for 7 different titles to be published by CRC Press, Taylor & Francis Group, USA and Apple Academic Press, CRC Press, Taylor & Francis Group, USA, Springer, etc. He has received the Young Researcher Award in “2nd Global Outreach Research and Education Summit & Awards 2019” hosted by Global Outreach Research & Education Association (GOREA). He is serving as Guest Editor in SCI journal of Elsevier, CEE. He has actively been an organizing end of various reputed International conferences. He is serving as an Editor and Organizing Chair to 3rd Springer International Conference on Microelectronics and Telecommunication (2019), and have served as the Editor and Organizing Chair to 2nd IEEE International Conference on Microelectronics and Telecommunication (2018), Editor and Organizing Chair to IEEE International Conference on Microelectronics and Telecommunication (ICMETE-2016) held in India, Technical Committee member in “CSMA2017, Wuhan, Hubei, China”, “EEWC 2017, Tianjin, China” IWMSE2017 “Guangzhou, Guangdong, China”, “ICG2016, Guangzhou, Guangdong, China” “ICCEIS2016 Dalian Liaoning Province, China”.

 

Masoud Daneshtalab

Masoud Daneshtalab is currently a full professor at Mälardalen University (MDH). He joined KTH as European Marie Curie Fellow in 2014. Before that, he was a university lecturer and group leader at University of Turku in Finland from 2012-2014. He has been appointed as Associate Editors of Elsevier Journals of Computers & Electrical Engineering and Microprocessors and Microsystems; and in the Editorial Board of The Scientific World Journal, IJDST, IJARAS, IJERTCS, and IJDATICS. He has also served as a Guest Editor for several prestige Journals, like Springer Computing, IET CDT, ACM TECS, ACM JETC, Elseviers’ JSA, MICPRO, Integration, and CEE. He is also the key organizer of SIGMARC ACM/IEEE International workshop Network-on-Chip Architectures (NoCArc / 8 editions) and ACM International workshop on Many-core Embedded Systems (MES / 4 editions). He has represented Sweden in the management committee of the EU COST Actions IC1202: Timing Analysis on Code-Level (TACLe). Since 2016 he is in Eurimicro board of Director and a member of the HiPEAC network. He has published 1 book, 4 book chapters, and over 180 refereed international journals and conference papers within H-index 24. He is currently in a Technical Program Committee member of different IEEE and ACM conferences, including NOCS, DATE, ASPDAC, ICCAD, ESTIMedia, VLSI Design, ICA3PP, SOCC, VDAT, DSD, PDP, ICESS, Norchip, MCSoC, CADS, EUC, DTIS, NESEA, CASEMANS, NoCArc, MES, HPIN, PACBB, MobileHealth, and JEC-ECC. He has co-leaded several national and international research projects (AMEBA, AGENT, ERoT, CRS, MANAGE, CUBRIC, and µBrain) funded by different resources.

 

Danda B. Rawat

Danda B. Rawat is a Full Professor in the Department of Electrical Engineering & Computer Science (EECS), Founder and Director of the Howard University Data Science and Cybersecurity Center, ​Director of Cyber-security and Wireless Networking Innovations (CWiNs) Research Lab, Graduate Program Director of Howard-CS Graduate Programs and Director of Graduate Cybersecurity Certificate Program at Howard University, Washington, DC, USA. Dr. Rawat is engaged in research and teaching in the areas of cybersecurity, machine learning, big data analytics and wireless networking for emerging networked systems including cyber-physical systems, Internet-of-Things, multi battle domain, smart cities, software defined systems and vehicular networks. His professional career comprises more than 15 years in academia, government, and industry. He has secured over $6 million in research funding from the US National Science Foundation (NSF), US Department of Homeland Security (DHS), US National Security Agency (NSA), US Department of Energy, National Nuclear Security Administration (NNSA), DoD Research Labs, Industry (Microsoft, Intel, etc.) and private Foundations. Dr. Rawat is the recipient of NSF CAREER Award in 2016, Department of Homeland Security (DHS) Scientific Leadership Award in 2017, ​Researcher Exemplar Award 2019 and Graduate Faculty Exemplar Award 2019 from Howard University, the US Air Force Research Laboratory (AFRL) Summer Faculty Visiting Fellowship in 2017, Outstanding Research Faculty Award (Award for Excellence in Scholarly Activity) at GSU in 2015, the Best Paper Awards and Outstanding PhD Researcher Award in 2009. He has delivered over 20 Keynotes and invited speeches at international conferences and workshops. Dr. Rawat has published over 200 scientific/technical articles and 10 books. He has been serving as an Editor/Guest Editor for over 30 international journals. He has been in Organizing Committees for several IEEE flagship conferences such as IEEE INFOCOM, IEEE CNS, IEEE ICC, IEEE GLOBECOM and so on. He served as a technical program committee (TPC) member for several international conferences including IEEE INFOCOM, IEEE GLOBECOM, IEEE CCNC, IEEE GreenCom, IEEE ICC, IEEE WCNC and IEEE VTC conferences. He served as a Vice Chair of the Executive Committee of the IEEE Savannah Section from 2013 to 2017. Dr. Rawat received the Ph.D. degree from Old Dominion University, Norfolk, Virginia. Dr. Rawat is a Senior Member of IEEE and ACM, a member of ASEE and AAAS, and a Fellow of ​​the Institution of Engineering and Technology (IET).