Two categories of best paper awards are being given as part of ICSCC 2021.

• One “Best Paper Award” from each track carries Rs.7500 and certificate on behalf of the conference secretariat.
• One paper from each track (as applicable) will be given a “MathWorks Best Impact Paper Award” based on the appropriateness of usage of MATLAB and Simulink, and carries a memento and certificate.

Norms for deciding best paper

Best Paper Award winners

MathWorks Best Impact Paper Award winners

The conference will bring together experts from the Smart computing and Communication systems community to discuss the timely issue of smart computing and low energy system design. This will provide a forum for sharing insights, experiences and interaction on various aspects of evolving technologies and patterns related to Computer Science, Information Technology, Electronics, and associated Energy Systems. The conference provides a platform for not only to the researchers from Asia but also from other continents across the globe, making this conference more international and attractive for participants.

The conference will include a peer reviewed program of technical sessions, workshops, tutorials, and demonstration sessions. This conference provides a forum for leading experts from the smart computing, embedded systems programming,  high-performance computing and power systems community to present their latest research, exchange ideas, and conduct brainstorming applications.

ICSCC 2021 has a special theme this time, that is ‘Artificial Intelligence (AI) Driven Applications for a Smart World‘. The theme is considered to be of great interest to many countries in general, and to India in particular.

“Artificial Intelligence Driven Applications for a Smart World”

Whether we realise it or not, Artificial Intelligence (AI) is lurking in the background, assisting, monitoring or influencing humans in most activities of their daily life. The range of applications that make use of AI gets increasing with each passing day. Some of such popular applications include personalising experience-based content-driven browsing, social-media interactions, online-shopping, travel and navigation to quote a few.

There are also many other domains like finance, healthcare, automated navigation, smart automotives, smart home environment, creative arts, and even smart customer interactions. AI based solutions for smart surveillance, smart forensics and investigation also lie at the other end of the application spectrum, some of which are made heavy use of by those states that attempt to govern lives of citizens by deploying instruments of control. The theme, therefore is both fascinating and intriguing at the same time, as AI applications appear to possess capabilities to enhance the human experiences through smarter services, and also make people vulnerable to be victims in the ever expanding automated surveillance mechanism as well.

With the availability of improved and sophisticated frameworks for rapid prototyping, testing and deployment, human imaginations on AI based applications seem to be taking less time to realise. These unique characteristics inhibiting the overall AI environment, are bound to make this Conference more interesting and appealing to a wide section of researchers and users.

Keynote section

Register here if you want to listen to the keynote sessions, even if you are not an author.
	Prof. Saifur Rahman, PhD Past-President, IEEE Power & Energy Society Joseph Loring Professor & Director Virginia Tech Advanced Research Institute, USA
Title : AI and Machine Learning in System Load Forecasting Research [Show Abstract] Forecasting is important in traffic volume management, optimum loading of mobile phone networks, managing electric power networks and managing building environmental control as a function of building occupancy levels. If we focus on the electric power system, we observe that the system operation is getting more and more complex due to the following reasons: more electrification means more demand which needs more reliable electricity requiring more efficient supply with less available margins. On top of this, the increased use of renewables causes system integration challenges. The research community needs new tools for dealing with uncertainty where artificial intelligence (AI) and machine learning (ML) can be used to supplement human intelligence. Artificial intelligence enables computers and machines to mimic the perception, learning, problem-solving, and decision-making capabilities of the human mind. These issues are highlighted in this presentation. [Close Abstract]
	Prof. Philippe Descamps Full Professor, Director of Research and Development at ESIGELEC/IRSEEM Director of IRSEEM laboratory, Institute of Research in Embedded Electronic Systems, France
Title : Embedded electronic systems applied to Industry, Transport and Health: new needs, new uses, new challenges, new applications [Show Abstract] In autonomous vehicle systems, the quality of scene perception is of great importance for security preoccupation in road environments. In this context, an accurate localization of potential obstacles is one of the most challenging tasks. In recent years, substantial progress has been made in the field of depth estimation for detection purposes with the spread of methods relying on deep learning with monocular or stereoscopic camera(s). These two families of approaches did show an upstanding yet inconsistent performance in different road scenes circumstances. A deep understanding and comparison of these approaches is required to allow the community an easier assessment, which breeds to more adequate choice for their own systems. In this paper, we propose a comparative study of state-of-the-art deep learning depth estimation methods using monocular and stereoscopic cameras. The evaluation is performed on road environment over the challenging KITTI dataset. On-road behavior analysis is a key task required for robust autonomous vehicles. Unlike traditional perception tasks, the goal here is to achieve high-level understanding of the road agents activities to better operate under challenging contexts and allow drivers and road supervisors better decision making and interaction with their environment. In this paper, we tackle the problem of discriminating spatio-temporal features that capture the visual instants which require more attention. We propose a new approach called STAF (Spatio-Temporal Attention Framework) by means of Long Short Term Memory (LSTM) layers that uses multi-head attention mechanism on its past cell state to focus on what is relevant over the time. Experiments have been carried out on two different scenarios over data from Joint Attention in Autonomous Driving (JAAD) and Honda Research Institute Driving Dataset (HDD) dataset devoted both for understanding the behavior road agents. The evaluation proves that the proposed approach is outperforming previously reported driving behavior understanding state-of-the-art results. We also present our platform dedicated to the development of an Advanced Driver Assistance System (ADAS) for a smart electric wheelchair in order to improve the autonomy of disable and reduced mobility people. Our use case, built from a serious and formal clinical study, is based on the detection, depth estimation, localization and tracking of objects in wheelchair’s indoor environment, namely: doors, doors’ handles, light switches, etc. The aim of this work is not only to improve perception around the wheelchair for high security but also it’s visual control to move, semi-autonomously, towards these targets (move the wheelchair to the door to open it, move it to a switch to turn on the light, etc.). Firstly, we present an adaptation of the YOLOv3 object detection algorithm to our use case. Then, we will present our depth estimation approach using an Intel RealSense camera. Finally, as a third and last step of our approach, we present our 3D object tracking approach based on the SORT algorithm. In order to validate all the developments, we have carried out different experiments in a controlled indoor environment. Detection, distance estimation and object tracking are experimented using our own dataset. This one includes corridors, doors, handles and switches. One of the scenarios studied to validate the developed platform includes not only the detection and tracking of objects, but also the wheelchair navigation towards one of these targets which designated as points of interest. [Close Abstract]
	Prof. Yann Busnel Full Professor, IMT Atlantique, Bretagne-Pays de la Loire Head of SRCD department (Network Systems, Cybersecurity and Digital Law), Rennes Campus, France
Title : How self-organisation and decentralisation should make a smarter world? [Show Abstract] Decentralization and hybridization of distributed systems has given birth to edge and fog computing. At the same time, artificial intelligence and self-adaptive mechanisms have allowed great progress in the autonomy of networks. In this keynote, we will look at the need for self-organization, where local decisions give rise to globally consistent system behavior. We will illustrate our talk by presenting an algorithm for target discovery following a disaster, using autonomous drones. We have propose VESPA, a distributed algorithm using only one-hop information of the drones, to discover targets with unknown location and auto-organize themselves to ensure connectivity between them and the sink in a multi-hop aerial wireless network. We have proved that connectivity, termination and coverage are preserved during all stages of our algorithm, and we evaluate the algorithm performances through simulations. [Close Abstract]
	Mr. Vinod Tharakan Founder and Managing Director, ClaySys and Chairman of CU NextGen, USA
Title : AI and the transition to a world of ‘Abundance’ [Show Abstract] The focus of this presentation is to demonstrate the current state of production ready AI, especially in leading edge Financial Services, and to map out its impact on mainstream economics. With the production capacity of the world, especially around essential goods, far exceeding the demand for it already, we are going to see an exponential increase in the capacity to build or manufacture pretty much anything that we may require in the world, and that too at ever decreasing costs and prices. With AI and Automation in general at the center of it all, powered by sustainable and renewable energy sources, we are truly transitioning to a world of abundance. But this transition is having, and will continue to have an exponential impact of most of the current mainstream ‘jobs’. So what are the new types of ‘jobs’ that are going to evolve in this new world of abundance? And how can we better manage this transition, without too much of pain impacting our citizens, as the economy evolves, and the nature of jobs and work changes. [Close Abstract]
	Dr. Praful P. Pai Education Technical Evangelist, MathWorks, IN-Delhi
Title : Building Intelligent Systems – From Development to Deployment – AI / ML / DL Workflows in MATLAB & Simulink [Show Abstract] AI, or Artificial Intelligence, is powering a massive shift in the roles that computers play in our personal and professional lives. Different workflows for AI, namely, machine learning, deep learning, and reinforcement learning, are transforming industries and improving applications around multiple domains. This talk dives into how MathWorks MATLAB & Simulink supports AI workflows across different industry verticals, including capabilities on Machine Learning (Working on Predictive Models using Signal / Vision Processing), Deep Learning (Labeling Data, Training Networks, and Tuning Hyperparameters), Inter-operability with other Deep Learning frameworks for collaboration in the AI ecosystem, Design and Train policies using Reinforcement Learning, and Automatic Code Generation and Deployment of AI/ML/DL Models. [Close Abstract]
	Dr. Ashwin Ashok Assistant Professor, Computer Science Honors College Faculty Associate Georgia State University, USA
Title : New Frontiers in Visible Light Camera Communication [Show Abstract] Cameras have become pervasive and the number of novel and intelligent applications using cameras are increasing by the day. Fundamentally, a camera is a light reception device, and today’s world is more familiar with the digital cameras which convert the incoming light reflected from objects into numbers or pixel intensities. Through a process of understanding and perceiving the scene, using the pixel intensity values registered on the image sensor of the camera, these devices have become a very powerful tool for visualization of the environment around us. The advent of machine learning, and the steep advances in deep neural networks, have enabled the power of intelligence to the cameras. In this talk, I will present the unique opportunity for using cameras, beyond their fundamental capacity to register a scene, as a communication reception device. I will introduce the concept of visible light communication (VLC) where light is used as the medium for (optical) wireless communication and present the concept of camera communication where in a light emitting device communicates digital information to a camera device through the optical wireless channel. I will further present different applications for camera communication, particularly for mobile communication on the ground, underwater and air. I will present some of our past and ongoing works in the car-to-car networking, underwater communication, and VLC for Unmanned Aerial Vehicles. I will conclude the talk with an overview of some of the key challenges in this space and open research problems, solving which can lead to a new frontier in mobile visible light communication.. [Close Abstract]
	Dr. Jeffrey Chuang Professor, The Jackson Laboratory for Genomic Medicine, Connecticut, USA
Title : Artificial Intelligence Approaches for Biomedical Image Analysis [Show Abstract] Broad advances in sequencing, imaging, and machine learning are rapidly transforming the nature of biology research. I will discuss how artificial intelligence approaches can be applied to high-throughput biological image data to identify regular patterns in cancers and their potential susceptibility to treatment. Our studies make use of deep learning approaches combining both transfer learning and fully trained models. We use these for prediction of genetic features and clinicial outcomes from large-scale histopathological data and other imaging types. [Close Abstract]
	Dr. Garenth Lim King Hann Associate Professor, Department of Electrical & Computer Engineering Curtin University, Malaysia
Title : Backpropagation in Deep Learning Neural Network using Two-phase switching optimization strategy. [Show Abstract] Deep structured learning has emerged as a new area of machine learning research with its wide range of applications in signal and information processing. There are two general aspects often discussed in various high-level descriptions of deep learning, i.e. (1) its structural models consisting of multiple layers of nonlinear activation processing, (2) optimization techniques for supervised or unsupervised learning of feature representation at sequentially higher more abstract layers. However, the non-linear transformation of higher-level abstraction has led to the complex learning mechanism in extracting optimum parameters in the neural network’s objective function. In addition, it increases the cost of training problems such as ill-conditioning and local minima. The increasing number of hidden layers in the deep learning architecture often encounter the issue of vanishing gradient in the backpropagation. Inspired by multistage decision control systems, the stochastic diagonal approximate greatest descent (SDAGD) algorithm is proposed to seek for optimal learning weights using a two-phase switching optimization strategy. The proposed optimizer controls the relative step length derived based on the long-term optimal trajectory and adopts the diagonal approximated Hessian for efficient weight update. In Phase-I, it computes the greatest step length at the boundary of each local spherical search region and, subsequently, descends rapidly toward the direction of an optimal solution. In Phase-II, it switches to an approximate Newton method automatically once it is closer to the optimal solution to achieve fast convergence. The experiments show that SDAGD produces steeper learning curves and achieves lower misclassification rates compared with other optimization techniques. Implementation of the proposed optimizer to deeper networks is also investigated to study the vanishing gradient problem. [Close Abstract]

Conference Tracks:

We invite all the prospective authors to submit original and high quality papers out of the following topics/tracks but not limited to.

Track 1: Smart Computing
Topics: Artificial Intelligence and Machine Learning; Trusted Computing; Cloud Computing; Data Management, Exploration and Mining; Grid Computing; Mobile Computing; Natural Language Processing and Machine Translation; P2P Competing Parallel and Distributed Algorithms; Pattern Recognition and Analysis; Reconfigurable Computing Robotics and Human Machine Interface Security; Trust and Privacy Simulation; Modeling Systems and Software Engineering; Ubiquitous and High-Performance Computing.

Track 2: Communication and Signal Processing
Topics: Cognitive Radio and Cognitive Networks; Communication Architecture; Algorithms, Modeling and Evaluation; Control Systems and Applications; Delay Tolerant Networks; Fault Tolerance, Reliability and Survivability; Flow and Congestion Control; Multimedia and Real-Time Networking; Optical Networks and Systems Protocols and Standards; Satellite and Space Communications; Sensor/Embedded Networks and Pervasive; Computing Smart Spaces and Personal Area Networks; Social Network Behaviors; Modeling, And Analysis; Vehicular, Underground and Underwater Networks; Software Defined Networking. , Smart Grid Systems, Intelligent Control, Robotics, Smart Communication System Models.

Track 3: Technology (Systems for a secure world)
Topics: 5G Networks & Internet of Things (IoT); Heterogeneous Networks; Web of Things; High Performance Internet Protocols; Identity Management and Object Recognition; Information Theory and Coding; Internet Security and Privacy Localization; Technologies Mobility Models and Mobile Networks Mobility; Localization and Management Aspects Routing and Control Protocols; Wearables, Body Sensor Networks; Smart Portable Devices; Web-based Learning; Innovation and Challenges. , Smart Machine learning Systems and models, Deep learnt networks, Evolutionary Systems,NLP, Secture Systems, IoT/IoE Security.

Track 4: Intelligent Systems and Analytics
Topics: Agricultural Informatics and Communication; Big Data Analytics; Bio-inspired Optimization; Community Information Systems; Remote Sensing; GIS and GPS; Disaster Management; E-governance; E-Commerce; E-Business; E-Learning Forensics and Informatics; Informatics Hybrid Evolutionary Algorithms; Hybrid Intelligent Systems; Neural Networks; Neuro-Fuzzy Models and Applications; Neuro Informatics Open Source: Challenges and Opportunities; Smart grid and Renewable Energy.

Track 5: Smart Embedded Systems
Topics: Low Power Electronics; VLSI Systems; Nano Electronics; FPGA Development; System on Chip; Embedded Applications; Embedded Memory Architecture; System Automation; Power Electronics and Control Scheme.

Track 6: Power Systems, Energy Systems and Power Electronics
Topics: Power Generation; Transmission and Distribution; Power System Monitoring; Control and Protection; Energy: Renewable Energy Sources , Grid integration of renewables, system integration of renewables, power system operation and control, power electronics for renewables, grid code regulation, demand side response, forecasting of renewable resources and load; Microgrids, smart grids and distributed generation: Architecture, sizing, topologies and control methods, distributed generation; Energy storage: methods, modelling, design and simulation. Electric Vehicles: Charging (slow, medium, boost), battery management system, hybrid vehicles, grid integration of electric vehicles. Control theory and applications: Industrial Applications of Control, Process Control Systems.

IMPORTANT DATES :

Call for Papers Announcement: 1st July 2020

Extended Full Paper Submission: 1st March 2021 31st March 2021 15th April 2021 (final deadline) Closed

Notification of Paper Acceptance: 30th April 2021 10th May 2021 (Closed)

Registration fee due: 20th May 2021 (Closed)

Final Camera-Ready Paper: 20th May 2021 25th May 2021 (Closed)

Conference Date: 1st, 2nd, 3rd July 2021

Patrons

Mr. George Alexander Muthoot, Managing Director, Muthoot Group

Mr. P. George Varghese, Executive Director, MITS

General Chairs

Prof. Dhiraj K. Pradhan, University of Bristol, UK.

Dr. Michael Evzelman, Ben-Gurion University, Israel

Prof. Philippe Descamps, ESIGELEC, France

Dr. Aswin Ashok, Georgia State University Georgia, US

Steering Committee

Dr. San Murugesan, University of Western Sydney, Australia

Prof. Ir. Dr. Aduwati Sali, Universiti Putra Malaysia, Malaysia

Prof. Dhiraj Pradhan, University of Bristol, UK

Prof. Dr. Mohamad Yusoff Bin Alias, Multimedia University, Malaysia

Prof. Ved Ram Singh, National Physical Laboratory, India

Dr. Bijoy Jose, CUSAT, Kochi

Dr. Jos Prakash Vacko, UCD, Belfield, Ireland

Prof. K. Chandrasekaran, NIT, Suratkal, India

Prof. Ashutosh Kumar Singh, NIT, Kurukshetra, India

Dr. Jimson Mathew, IIT Patna

Dr. Chikku Abraham, MITS Kochi

Program Chairs

Dr. Jimson Mathew, IIT Patna, India

Dr P.C. Neelakantan, MITS Kochi

Organizing Chairs

Dr. Abhilash Antony, MITS Kochi

Dr. Anand Hareendran S., MITS Kochi

Dr. Jani Das, MITS Kochi

Dr. Rijo Sebastian, MITS Kochi

Track Co-Chairs

Smart Computing

Dr. Vinod Chandra S. S., Department of Computer Science, Kerala University

Dr. Resmi N. G., MITS Kochi

Prof. Cerene Mariam Abraham, MITS Kochi

Communications and Signal Processing

Dr. Dhanya S., MITS Kochi

Dr. Arun Joy, MITS Kochi

Technology (Systems for a secure world)

Dr.Shruti R. Kulkarni, Oak Ridge National Laboratory, USA

Dr. Shoba Gopalakrishnan, MITS Kochi

Prof. Venugopalan Kuruppath, MITS Kochi

Intelligent Systems and Analytics

Dr. Jos Prakash Vacko, UCD, Belfield, Ireland

Dr. Gylson Thomas, MITS Kochi

Dr. Rijo Sebastian, MITS Kochi

Smart Embedded Systems 

Dr. Bijoy Antony Jose, CUSAT,India

Dr. Selvia Kuriakose. MITS Kochi

Dr. Arunkant A. Jose, MITS Kochi

Power Systems, Energy Systems and Power Electronics

Dr.Ammu Susanna Jacob, Centre for Science, Technology and Policy,Bangalore

Dr. Anjali Varghese, MITS Kochi

Dr. Jani Das, MITS Kochi

Publication Chairs

Prof. Mahalingam P. R., MITS Kochi

Dr. Dheeba Jacob, Vellore Institute of Technology, India

Registration Chairs

Dr. Krishnapriya S., MITS Kochi

Prof. Rakhee M., MITS Kochi

Publicity Chair

Prof. Preenu Paul,  MITS Kochi

Prof. Anjali A., MITS Kochi

Abdelmadjid Bouabdallah, Université de Technologie de Compiègne (UTC), France

Abdul Halim Ali, Universiti Kuala Lumpur, Malaysia

Abinkant A Jose, Wipro, India

Abraham T Mathew, National Institute of Technology Calicut, India

Aby Joseph, CDAC India

Adel Al-Jumaily, University of Technology, Sydney

Ajith Abraham, Machine Intelligence Research Labs, USA

Ali Tekeoglu, University of New Brunswick & Canadian Institute for Cybersecurity

Amitabh Mishra, University of Delaware, USA

Ammu Susanna Jacob, Centre for Science, Technology and Policy Bangalore, India

Anand Pavithran, Redhat India

Ananthalakshmi Ammal, Centre for Development of Advanced Computing, India

Aniello Castiglione, University of Naples Parthenope, Italy

Anju S Pillai, Amrita Vishwavidyapeetam Coimbatore, India

Anna Antonyová (University of Prešov, Slovak Republic)

Anzar SM, TKMCE Kollam, India

Asha Daniel, Cochin University of Science and Technology, India

Aswin Ashok, Georgia State University Georgia, US

Avishek Nag, University College Dublin, Ireland

Babita R Jose, Cochin University of Science and Technology, India

Babu.C.A, Cochin Univerity of Science And Technology, India

Bijoy Antony Jose, Cochin University of Science and Technology, Kochi

Bijumon T., APJ Abdul Kalam Technological University, India

Binod Kumar, Qualcomm, Bangalore, India

Bogdan Cristea, Bogdan Eugen Cristea, Romania

Chin-Chih Chang, Chung Hua University, Taiwan

Christian Esposito, University of Salerno, Italy

Deepak Mishra, Indian Institute of Space Science and Technology, India

Deepak Padmanabhan, Queens University, Belfast

Deepak PM, CEWiT, IIT Madras, India

Deepesh Kumar, NUS Singapore

Deepti Das Krishna, Cochin University of Science and Technology, India

Dheeba J., Vellore Institute of Technology, India

Dmitry Namiot, Lomonosov Moscow State University, Russia

Dong Chen, Florida International University, US

Elizabeth Rita Samuel, Rajagiri School of Engg and Technology, India

Emilio Jiménez Macías, University of La Rioja, Spain

Fan Jiang, Bloomsburg University, USA

Filbert Juwono, Curtin University, Malaysia

Francisco Torrens, Universitat de Valencia, Spain

Georgina Binoy Joseph, Toc H Institute of Science & Technology, India

Giandomenico Spezzano, CNR-ICAR, Italy

Gopi Krishna S, NIT Calicut, India

Haseena H, NIT Calicut, India

Irek Czarnowski, Gdynia Maritime University, Poland

Jalaja MJ, GEC Idukki, India

Janardhanan P. S., SunTec, India

Jasmin E.A, Government Engineering College Idukki, India

Jayanand.B, GEC Thrissur, India

Jayaraj P B, National Institute of Technology Calicut, India

Jayasankar.V.N, National Institute of Engineering Mysuru, India

Jeevamma Jacob, National Institute of Technology Calicut, India

Jereesh A S, Cochin University of Science and Technology, India

Jiji K S, GEC Thrissur, India

Jiju K, CDAC, India

Joan Bas, Centre Tecnològic de Telecomunicacions de Catalunya (CTTC), Spain

José Luis Hernandez Ramos, European Commission – JRC, Belgium

Jyothi Parikh, Integrated Research and Action for Development (IRADe), India

K B Karthikeyan, Instituto Italiano di Tecnologia, Genoa, Italy

K. P. Kesavan Nair, Indira Gandhi Centre for Atomic Research, India

Katerina Kabassi, Ionian University, Greece

Kedar Kumthekar, Nokia, Kenya

Klaus David, University of Kassel, Germany

Lajish VL, University of Calicut, India

Lillykutty Jacob, NIT Calicut

Lim Tek Yong, Multimedia University, Malaysia

Lintu Rajan, NIT Calicut, India

Lisandro Lovisolo, Universidade do Estado do Rio de Janeiro, Brazil

Ljiljana Trajković, Simon Fraser University, Canada

Lyla B Das, NIT Calicut, India

M Mustafa Rafique, Rochester Institute of Technology, NY

M V Rajesh, Govt.Model Engineering College Thrikkakara, India

Madhu Kumar S D, National Institute of Technology Calicut, India

Manju B, Rajiv Gandhi Institute of Technology Kottayam, India

Massimo Villari, Università di Messina, Italy

Mehran Asadi, Lincoln University, USA

Meng Yu, Roosevelt University Chicago, USA

Mily Wilson, Bridj, Sourth Brisbane 4101, Queensland, Australia.

Moeiz Miraoui, University of Gafsa, Tunisia

Mohamed Mosbah, University of Bordeaux, France

Mohammad Rakib Uddin, Universiti Teknologi Brunei (UTB), Brunei Darussalam.

Mohammed Ahamed Qasim Al-Shabi, University of Sharjah, UAE

Mohammed Bait-Suwailam, Sultan Qaboos University Oman

Mojin Abraham Kottarathil, Synopsis, Austin, Texas, USA

N Sundararajan, Nanyang Technological University, Singapore

Nadera Beevi S., TKMCE Kollam, India

Namitha AS, VIT Chennai, India

Nandakumar Nair .P, Carborundum Universal Ltd., India

Nandakumar R, NIELIT Calicut

Narottam Das, CQUniversity, Australia

Nelson Antunes, University of Algarve, Portugal

Nisha Haridas, Qualcomm

Nishant Doshi, Pandit Deendayal Petroleum University, India

P.P. Deepthi, NIT Calicut, India

Paulose Jacob, Cochin University of Science And Technology, India

Pavel Loskot, College of Engineering, Swansea University, UK

Pierluigi Siano, University of Salerno, Italy

Prajish C, Tata Elxsi, Germany

Prakash Chandra Ghosh, IIT Bombay, India

Praseeth KS, Samsung Electronics America

Pratap Kumar S, NIELIT Calicut, India

Praveen.R.P, Majmaah University, Kingdom of Saudi Arabia

Preetha K. G, Rajagiri School of Engg and Technology, India

Purushothaman A, Amritha School of Engineering Kollam, India

Radu Vasiu, Politehnica University of Timisoara, Romania

Raghesh A, AMD India

Rekha James, Cochin University of Science and Technology, Kochi

Renjith P., IIITDM Kurnool, India

Rhythm Singh, IIT Roorkee. India

Rosaura Palma Orozco, Instituto Politécnico Nacional, Mexico

Saidhalavi, National Institute of Technology Calicut, India

Salim A, CET, India

Samir Ladaci, N.P. School of Constantine, Algeria

Sangeetha Jose, Government Engineering College Idukki, India

Sanjeet Dwivedi, Danfoss, Denmark

Sarat Chandra Nagavarapu, Nanyang Technological University (NTU), Singapore

Saritha R, CET, India

Sathidevi P S, NIT Calicut, India

Satyanarayana Vuppala, United Technologies Research Center, Ireland

Satyasis Mishra, Adama Science and Technology University, Ethiopia

Scott Burleigh, California Institute of Technology, USA

Seekumari B, CDAC, India

Seng Hansun, Universitas Multimedia Nusantara, Indonesia

Seyed M Buhari, King Abdulazeez University, KSA

Shadi I. Abudalfa, University Collage of Applied Sciences, Palestine

Shahana T.K., Cochin University of Science and Technology, India

Shaheen, Princess Nourah University, Riyadh

Sheeba.V.S., GEC Thrissur, India

Sherali Zeadally, University of Kentucky, USA

Sherly.K.K, Rajagiri School of Engg and Technology, India

Shibu K V, Microsoft Corp, US

Shoukat Cherukat, NIELIT Calicut, India

Shruti R. Kulkarni, Postdoctoral Research Associate, Oak Ridge National Laboratory, Tennessee, USA

Sminu Izudheen, Rajagiri School of Engg and Technology, India

Sobin CC, SRMU Amaravati, India

Soman K P, Amrita Viswa Vidyapeetham Coimbatore, India

Sreelekha G, NIT Calicut, India

Stefano Chessa, Universita’ di Pisa, Italy

Sudheesh P G, Manipal Institute of Technology, India

Sudhish N George, NIT Calicut, India

Suja K.J, NIT Calicut, India

Sumit Jha, University of Central Florida, USA

Susan Elias, VIT Chennai, India

T Purusothaman, GCT Coimbatore, India

Thierry Monteil, LAAS-CNRS, University of Toulouse, France

Tomonobu Senjyu, University of the Ryukyus, Japan

Toral Shah, NMIMS, Navi Mumbai, India

Unnikrishnan A, NPOL DRDO, India

Vijayakumar Ambat, Cochin University of Science And Technology, India

Vinod Chandra S.S., University of Kerala, India

Vishwas Kher, Boeing India Defense Pvt Ltd

Vivek Agrawal, IIT Bombay, India

Vuong M. Ngo, University College Dublin, Ireland

Yiming Ji, Georgia Southern University, USA

Yun Ii Go, Heriot-Watt University Malaysia, Malaysia

Zakkir Kharim, Nokia Seimens Networks

Zbigniew Dziong, Universiti de Quebec, Canada

Zoran Bojkovic, University of Belgrade, Serbia

Conference Secretariat, ICSCC 2021
Muthoot Institute of Technology and Science
Puthencruz, Ernakulam, Kerala, India
http://mgmits.ac.in/
Email: [email protected]
Conference website – http://icscc.online/

Get more details about Kochi at https://www.keralatourism.org/

The objective of the International Conference on Smart Computing and Communications (ICSCC 2021) is to provide a congenial yet serious platform for experts from academia and industry to interact with young researchers in Computer Science, Electrical Engineering, and Electronics & Communication Engineering.

This is an interdisciplinary conference that aims at diverse fields of engineering and technology with a focus on smart and energy efficient computing, green technology and sustainable systems design and development. The major attempt of the conference is to bring out this event to be a forum for researchers and practitioners to come together from all different fields of Electronics, Communications, and Computer Engineering to foster the needs of modern human life.

The wide range of topics covered in this conference includes Sustainable Computing and Communications, Green Technology, Smart Grid, Green Data Centers, Green Building and Sustainable ICT. Smart and energy efficient computing are considered to be important areas that need to be further explored. ICSCC 2021 welcomes submissions that have not been published and that are not under review by another conference or journal. All submissions will be evaluated on their originality, technical soundness, significance, presentation, and interest to the conference attendees.

Submission:

Technical papers describing original, previously unpublished papers are solicited in all areas described above.

Authors are invited to submit papers through Microsoft’s Conference Management Toolkit (CMT). Please see “Submission Instruction” for paper formatting and guidelines.

Submission Instructions:

ICSCC only considers original papers that have not been published or submitted for publication elsewhere. Full papers can be submitted through https://cmt3.research.microsoft.com/ICSCC2021/. All submitted papers will be peer-reviewed based on their quality and relevance.

Guidelines for Authors : After logging to the Conference Management System, please click on the “Create new submission” tab and follow the instructions. The Title of the paper and the Abstract are to be entered separately, before uploading the paper.

Formatting Requirements:

Submitted papers should be written in the English language, IEEE two-column format with single-spaced, 10-point font in the text.

The documents should be formatted for standard Letter-size (8-1/2″ by 11″) paper or A4 format.

The manuscript should have a length limit of 5 printed pages, including all the figures, references, and appendices.

One extra page is permitted with additional charges.

Use the Manuscript Templates for Conference Proceedings (Microsoft Word or LaTeX) which can be found https://www.ieee.org/conferences/publishing/templates.html.