Human−Computer Interaction in the Era of Smart Cities and Spaces

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: 31 August 2024 | Viewed by 5052

Special Issue Editors

Associate Professor, Faculty of Computer and Information Systems, Islamic University of Madinah, Medina 42351, Saudi Arabia
Interests: human computer interaction; intelligent interactive systems; machine learning; smart cities; end user development
Department of Information Systems, Universiti Teknologi Malaysia, Skudai 81310, Johor, Malaysia
Interests: information systems; human–computer interaction; knowledge management; sustainable information systems; technology acceptance
Faculty of Computing, Universiti Teknologi Malaysia, Skudai 81310, Johor, Malaysia
Interests: system usability; human–computer interaction; usability methods; evaluation of information systems; web analytics; e-learning; e-government
School of Digital Science, Universiti Brunei Darussalam, Tungku Link, Gadong BE1410, Brunei
Interests: IoT; cyber security; smart cities; physical computing; intelligent systems

Special Issue Information

Dear Colleagues,

We are inviting submissions to the Special Issue on human−computer interaction in the era of smart cities and spaces. This Special Issue focuses on exploring the theoretical underpinnings of recent interactive technologies and techniques and their practical implications on the effective use of smart digital services and applications.

The rapid developments in ICT, the Internet of things, cloud computing, and machine learning have caused a massive disruption to the ways in which we interact with modern technologies and have led to the creation of smart cities and spaces. Indeed, the advantages are limitless, including enhanced quality of life, reduced costs and resource consumption, and improved citizens’ engagement through digital transformations. 

The fast-paced digital changes in the form of multi-dimensional, multi-display, and multi-modal systems, autonomous robots, immersive virtual worlds, and context-aware intelligence are all examples of the revolutionary technologies that we are experiencing in our so-called smart cities and spaces. Whether in the comfort of our homes or outdoors, smart interactive systems and devices have invaded every corner of our life and we no longer can adapt to our routine tasks without the existence of these heterogeneous multi-display environments.

However, there is a growing need to establish human-centric design strategies and models, and smart interaction techniques to successfully integrate these disruptive technologies into our daily life and make the best of them to meet our evolving expectations and desires. How to make smart cities and spaces more productive, unobtrusive, ethical, affective, and sustainable remains a big research challenge. Other issues that we constantly encounter in the interaction include the privacy and security of our personal data.

Potential topics of this Special Issue include, but are not limited to:

Topics

  • Human–machine interaction
  • Human–robot interaction
  • Intelligent multi-modal interactions
  • Smart cities, spaces, and homes
  • Multi-display, multi-dimensional environments
  • Predictive models and theories of interaction
  • Computational cognitive models
  • Adaptive and personalized systems
  • Digital humans, chatbots, and natural language systems
  • Physical computing
  • Intelligent systems
  • Virtual, augmented, and mixed reality interfaces
  • Haptic, gesture, and brain computer interfaces
  • Accessible and assistive technologies
  • Future learning technologies
  • User experience and satisfaction
  • Citizens e-participation, engagement, and quality of life
  • Privacy and security in smart cities
  • Sustainable development goals in HCI
  • Evaluation methodologies and techniques
  • Adoption, acceptance, and use of emerging technologies in smart cities and spaces
  • Trust management in future smart cities systems and services
  • Impact of cultural and societal factors on smart city adoption
  • Role of smart cities in achieving sustainable development goals (SDGs)
  • Impact of smart city technologies on environmental sustainability

Dr. Abdallah Namoun
Dr. Mohammed A. Al-Sharafi
Dr. Layla Hasan
Dr. Ali Tufail
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (2 papers)

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Research

14 pages, 1298 KiB  
Article
Enhancing P300-Based Brain-Computer Interfaces with Hybrid Transfer Learning: A Data Alignment and Fine-Tuning Approach
by Sepideh Kilani, Seyedeh Nadia Aghili and Mircea Hulea
Appl. Sci. 2023, 13(10), 6283; https://doi.org/10.3390/app13106283 - 21 May 2023
Cited by 2 | Viewed by 1379
Abstract
A new approach is introduced to address the subject dependency problem in P300-based brain-computer interfaces (BCI) by using transfer learning. The occurrence of P300, an event-related potential, is primarily associated with changes in natural neuron activity and elicited in response to infrequent stimuli, [...] Read more.
A new approach is introduced to address the subject dependency problem in P300-based brain-computer interfaces (BCI) by using transfer learning. The occurrence of P300, an event-related potential, is primarily associated with changes in natural neuron activity and elicited in response to infrequent stimuli, which can be monitored non-invasively through an electroencephalogram. However, implementing P300-based BCI in real-time requires many training samples and time-consuming calibration, making it challenging to use in practical applications. To tackle these challenges, the proposed approach harnesses the high-level feature extraction capability of a deep neural network, achieved through fine-tuning. To ensure similar distributions of feature extraction data, the approach of aligning data in Euclidean space is employed, which is then applied to a discriminatively restricted Boltzmann machine with a single layer for P300 detection. The performance of the proposed method on the BCI Competition III dataset II and the BCI competition II dataset II, the state-of-the-art dataset, was evaluated and compared with previous studies. The results showed that robust performance could be achieved using a small number of training samples, demonstrating the effectiveness of the transfer learning approach in P300-based BCI applications. Full article
(This article belongs to the Special Issue Human−Computer Interaction in the Era of Smart Cities and Spaces)
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34 pages, 1526 KiB  
Article
Determinants of Cyberattack Prevention in UAE Financial Organizations: Assessing the Mediating Role of Cybersecurity Leadership
by Nabil Hasan Al-Kumaim and Sultan Khalifa Alshamsi
Appl. Sci. 2023, 13(10), 5839; https://doi.org/10.3390/app13105839 - 09 May 2023
Viewed by 2663
Abstract
Cyberattack prevention factors have a significant impact on the perception of social and moral values in the business context. Despite leaders’ significant role in encouraging and enculturating cybersecurity practices in their organizations, there is a noticeable gap in the literature to highlight empirically [...] Read more.
Cyberattack prevention factors have a significant impact on the perception of social and moral values in the business context. Despite leaders’ significant role in encouraging and enculturating cybersecurity practices in their organizations, there is a noticeable gap in the literature to highlight empirically how leaders and top management in organizations foster organizational cybersecurity. Therefore, this study aims to explore the role of cybersecurity leadership in financial organizations in preventing cyberattacks and investigate other human and non-technical factors related to the individual in financial organizations. Based on Protection Motivation Theory (PMT), the research framework was developed with the tallying of new variables focusing on the role of an organization’s cybersecurity leadership, training frequency, and the role of government frequent alerting. This research employed a quantitative research method. The data were collected through a questionnaire from 310 financial executive officers from selected banks in UAE that use digital technology to enhance their daily banking operations. Using Structural Equation Modelling (SEM), the results indicated (1) a significant association between all investigated independent variables and cybersecurity leadership through hypothesis (H8–H14); (2) cybersecurity leadership mediates the relationship between investigated independent variables and cyberattack prevention, from hypothesis (H15, and H16–H22); (3) no significant association between investigated independent variables and cyberattack prevention from hypothesis (H1–H6), except hypothesis (H4 and H7), which show a significant association. The coefficient of cybersecurity leadership in this study is viewed as a prevention element against cyberattacks based on the findings. With greater cybersecurity leadership success, the implementation of cyberattack prevention increases. This study emphasizes the importance of cybersecurity leadership in a cyberspace environment that protects against cyberattacks and promotes cybersecurity awareness within financial organizations and society in UAE. Full article
(This article belongs to the Special Issue Human−Computer Interaction in the Era of Smart Cities and Spaces)
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