Advances in Smart Technologies - Selected Papers from 3rd EAI International Conference on Smart Technologies and Innovation Management

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: closed (1 May 2024) | Viewed by 2898

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Research & Development Department (Research Club), Hamta Group, Hamta Business Corporation, Vancouver, BC V6E 0A7, Canada
Interests: research methodology; leadership; business management; human resource management
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Department of Electrical, Computer, and Software Engineering Faculty of Engineering, University of Auckland, Auckland, New Zealand
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Special Issue Information

Dear Colleagues,

This Special Issue aims to showcase cutting-edge research and advancements in the field of smart technologies and innovation management, with a specific focus on artificial intelligence (AI), blockchain, cybersecurity, and innovation management. The International Conference on Smart Technologies and Innovation Management serves as the inspiration and foundation for this Special Issue, which seeks to capture the latest developments, findings, and insights shared by experts, researchers, and practitioners in this dynamic field.

Smart technologies have revolutionized various aspects of our lives, fundamentally changing the way we live, work, and interact with each other. With the growing adoption and integration of AI, blockchain, and cybersecurity technologies, the transformative potential of smart technologies is further enhanced.

This Special Issue invites researchers and scholars to contribute original research articles, review papers, and case studies that explore the diverse applications, challenges, and opportunities presented by AI, blockchain, and cybersecurity within the realm of smart technologies. The aim is to shed light on innovative approaches, methodologies, and best practices that contribute to the effective management and utilization of these technologies for sustainable development, improved decision-making, enhanced security, and overall societal impact.

Topics of interest for this Special Issue include, but are not limited to:

  • AI-enabled smart systems and applications;
  • Blockchain technology for secure transactions and decentralized solutions;
  • Cybersecurity challenges and solutions in the context of smart technologies;
  • Smart city infrastructure and governance;
  • Data analytics and machine learning in smart technology environments;
  • Ethical considerations in the deployment of smart technologies;
  • Innovation management strategies for smart technology adoption and implementation;
  • Socio-economic impacts and implications of smart technologies;
  • Integration of AI, blockchain, and cybersecurity for enhanced smart technology applications;
  • Case studies and real-world implementations of smart technologies;
  • Privacy and data protection in the context of AI, blockchain, and smart technologies;
  • Challenges and future directions in the field of smart technologies and innovation management.

We welcome submissions that present novel research findings, theoretical frameworks, innovative methodologies, and practical insights. The goal of this Special Issue is to foster interdisciplinary dialogue, promote knowledge exchange, and advance the understanding and adoption of AI, blockchain, and cybersecurity technologies within the realm of smart technologies.

Dr. Hamed Taherdoost
Dr. Mitra Madanchian
Dr. Seyed Reza Shahamiri
Dr. Mukesh Prasad
Guest Editors

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Published Papers (2 papers)

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Research

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20 pages, 1021 KiB  
Article
Empirical Investigation of Multilayered Framework for Predicting Academic Performance in Open and Distance Learning
by Muyideen Dele Adewale, Ambrose Azeta, Adebayo Abayomi-Alli and Amina Sambo-Magaji
Electronics 2024, 13(14), 2808; https://doi.org/10.3390/electronics13142808 - 17 Jul 2024
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Abstract
Integrating artificial intelligence (AI) in open and distance learning (ODL) necessitates comprehensive frameworks to evaluate its educational implications. Existing models lack a robust multilayered analysis of AI’s impact on educational outcomes in ODL. This study introduces a Multilayered Process Framework designed to predict [...] Read more.
Integrating artificial intelligence (AI) in open and distance learning (ODL) necessitates comprehensive frameworks to evaluate its educational implications. Existing models lack a robust multilayered analysis of AI’s impact on educational outcomes in ODL. This study introduces a Multilayered Process Framework designed to predict academic performance in ODL and enhance inclusivity, aligning with UNESCO’s 2030 educational goals. The current research employed structural equation modelling (SEM) to analyse the impact of AI adoption, focusing on the initial layers of the process framework. Preliminary validation of the SEM framework showed a good model fit, with a Chi-square/df ratio of 2.34, Root Mean Square Error of Approximation (RMSEA) of 0.045, and Comparative Fit Index (CFI) of 0.97, indicating the model’s effectiveness in capturing the complexities of AI impacts on student outcomes. This framework provides a structured, multilayered approach to understanding AI’s role in education, facilitating the development of equitable and accessible AI-driven educational technologies. It lays the foundational work for expanding research into predictive analytics with a support vector machine (SVM), aiming to universalise quality education and ensure global educational equity. This study highlights the practical implications for integrating AI in educational settings and suggests future research directions to enhance the adaptability and effectiveness of AI-driven educational interventions. Full article
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Review

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16 pages, 815 KiB  
Review
Prospective Directions in the Computer Systems Industry Foundation Classes (IFC) for Shaping Data Exchange in the Sustainability and Resilience of Cities
by Ebere Donatus Okonta, Vladimir Vukovic and Ezri Hayat
Electronics 2024, 13(12), 2297; https://doi.org/10.3390/electronics13122297 - 12 Jun 2024
Cited by 1 | Viewed by 1006
Abstract
Sustainability and resilience in addressing construction’s environmental, social, and economic challenges rely on interoperability. A model-centred approach using standardised information structures like industry foundation classes (IFC) is essential for data sharing in architecture, engineering, construction, and facility management. Achieving complete interoperability across domains [...] Read more.
Sustainability and resilience in addressing construction’s environmental, social, and economic challenges rely on interoperability. A model-centred approach using standardised information structures like industry foundation classes (IFC) is essential for data sharing in architecture, engineering, construction, and facility management. Achieving complete interoperability across domains requires further research. This review paper focuses on IFC schema, highlighting upcoming developments like IFC 5 and “IFC x”, with a core emphasis on modularisation to enhance domain interoperability, improved links between building information modelling (BIM) and geographic information systems (GIS), along with IoT integration into BIM, cloud-based collaboration, and support for other advanced technologies such as augmented reality (AR), virtual reality (VR), artificial intelligence (AI), and digital twins. Through a critical examination of the IFC and an outlook towards its future enhancements, the research has the potential to offer valuable insights into shaping the trajectory of future advancements within the AEC and facility management sectors. The study’s discoveries could aid in establishing standardised data exchange protocols in these industries, promoting uniformity across projects, facilitating smoother communication, and mitigating errors and inefficiencies. Anticipating enhancements in the IFC could catalyse innovation, fostering the adoption of emerging technologies and methodologies. Consequently, this could drive the creation of more sophisticated tools and procedures, ultimately enhancing project outcomes and operational effectiveness. Full article
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