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IssuesSpecial Issues
Human-centric Computing and Information Sciences (HCIS) Korea Information Processing Society-Computer Software Research Group (KIPS-CSWG)(ISSN: 2192-1962)

(IF 5.900) Special issue on

Quantum Computing and Intelligence for Human-centric IoT Applications

These days, many technologies have emerged in different domains such as 5G that enable wireless communication and cloud ubiquitous services accessible from everywhere. The technologies motivate the for Human-centric IoT Applications (HIoT), which convert human physical monitoring based on machine monitoring. These new HIoTand systems are geographically distributed and have many concerns, such as The Industrial Internet of Thingsdata security, anomaly avoidance, services cost, delay, mobility and automation. However, existing The Industrial IoT Applicationsor methods are fixed or statics. These complex dynamic problems cannot be solved with the existing techniques. Therefore, dynamic uncertainty with time and space complexity in ubiquitous poses many research challenges. Quantum computing has the potential to improve the analysis of Industrial IoT Applications.Together, these use cases significantly help advance Human-centric IoT Applications quadruple aim. It supports a product's entire lifecycle, from design and manufacturing to use, service, and remanufacture.The Human-centric IoT Applications (HIoT) is no longer a trend that has proved to be an extremely successful technology that many modern digital-based businesses use to quickly expand their operations. The HIoTprovides real-time data that is critical for making snap decisions based on different efficient AI methods. It supports a product's entire lifecycle, from design and manufacturing to use, service, and remanufacture. Through technical and financial information, the HIoTconnects the user with the product and the business. It also creates emotional and immersive links between the user and the product. Advanced intertwined networks of smart sensors and personalized cloud services are the means of delivering the right data at the right time to allow for faster decision making for more adaptive, agile, and scalable services that make the difference for businesses that cater to their customers' needs.
Thus, this special issue well all intelligent techniques, approaches, and architectures based on Explainable Artificial Intelligence (XAI) for Human-centric IoT Applications. XAI is a widely researched environment where Industrial IoT Applications and systemsare developed based on dynamic techniques such as supervised, unsupervised, reinforcement learning, deep learning, and neural network. In XAI, the incremental approaches, iterative approaches and novel approaches widely welcome to solve the dynamic problem of HIoT. These methods can integrate with the offloading problem, application partitioning problem, task scheduling problem, resource allocation problem, and graph problems.It is well known that quantum computing method can solve and resolve many difficult problems in the field of classical computation. Therefore, quantum methods are chosen to be implemented into the learning of Neural Network and Elman Recurrent Neural Network using Multi-Layer Perceptron (MLP).
The main objective of this special issue is to bring together diverse, novel and impactful research work on Explainable Deep Learning for Human-centric IoT Applications, thereby accelerating research in this field.

Quantum-enhanced machine learning techniques could allow earlier, more accurate, and more granular Human-centric IoT Applications

Quantum Computing for Smart Sensors with Edge AI Blockchain

Quantum Computing with XAI for Internet of Medical Things

XAI methodologies to HIoTfog-cloud network

Quantum Computing with XAI and Medical data fusion

Robotics and HIoTwith AI Searching

XAI Big Data based on HIoTnetwork

Real-time Explainable AI for medical image and data processing for Human-centric IoT Applications

Machine and deep learning Algorithms for remote HIoTdata collection and filtering

Deep learning approach towards Green HIoT

Blockchain solutions for AI-enabled HIoTscheme

Ubiquitous computing for AI-enabled smart city

Machine learning approach towards effective routing protocol for packet scheduling in HIoT

Real-time load prediction and balancing at the Edge of HIoT

XAI and COVID-19 Detection and Classification based HIoTsystems

Future directions of intelligent XAI medical data in HIoTservices

Transportation Systems based on Human-centric IoT Applications

Important Dates

Open submission : 30 Jan 2022

Submission deadline : 30 June 2022

Author notification : within 4 weeks after submission

Revised manuscript due : within 2 weeks after notification

Notification of acceptance : within 2 weeks after revision submission

Tentative accepted paper publication date : within 2 months after final version

Tentative SI paper collection and its web open: 4th Quarter, 2022 (TBA)

Submission Guideline

All submitted papers must be clearly written in excellent English and contain only original work. All papers must be submitted in an electronic format, e.g., PDF format (preferred) or MS Word. Manuscripts should follow the formatting of the sample manuscript and references. You can refer to the details in the submission menu http://hcisj.com/submission/preparing_manuscript.php
All papers and some supplementary materials should be submitted through ScholarOne Manuscripts. The authors must select “SI2022-01Quantum Intelligence-HIoT”. when they reach the “Article Type” step in the submission process https://mc04.manuscriptcentral.com/hcis.

Guest Editors

Dr. Mazin Abed Mohammed [Lead Guest Editor]
College of Computer Science and Information Technolgy, University of Anbar, Iraq
Email: mazinalshujeary@uoanbar.edu.iq

Prof. Dr. SeifedineKadry
Department of Applied Data Science, Norrof University College, Kristiansand, Norway
Email: seifedine.kadry@noroff.no

Dr. Ahmed Farouk
Faculty of Computers and Artificial Intelligence, South Valley University, Hurghada, Egypt.
E-mail: ahmed.farouk@sci.svu.edu.eg

Dr. OanaGeman
Department of Health and Human Development, Universitatea Stefan cel Mare din Suceava, Suceava, Romania
Email: oana.geman@usm.ro