AHCI RESEARCH GROUP
Publications
Papers published in international journals,
proceedings of conferences, workshops and books.
OUR RESEARCH
Scientific Publications
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You can expand the Abstract, Links and BibTex record for each paper.
2025
Arai, K.
Digital Twin Model from Freehanded Sketch to Facade Design, 2D-3D Conversion for Volume Design Journal Article
In: International Journal of Advanced Computer Science and Applications, vol. 16, no. 1, pp. 88–95, 2025, ISSN: 2158107X (ISSN).
Abstract | Links | BibTeX | Tags: 2D/3D conversion, AI, Architectural design, BIM, Digital Twins, Facade design, Facades, GauGAN, Generative AI, GeoTiff, GIS, IFC format, Metaverse, Metaverses, SketchUp, TriPo, Volume design, Volume Rendering
@article{arai_digital_2025,
title = {Digital Twin Model from Freehanded Sketch to Facade Design, 2D-3D Conversion for Volume Design},
author = {K. Arai},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85216872163&doi=10.14569%2fIJACSA.2025.0160109&partnerID=40&md5=fd4e69f9b20d86e3b5d07b4cdcb00b2d},
doi = {10.14569/IJACSA.2025.0160109},
issn = {2158107X (ISSN)},
year = {2025},
date = {2025-01-01},
journal = {International Journal of Advanced Computer Science and Applications},
volume = {16},
number = {1},
pages = {88–95},
abstract = {The article proposes a method for creating digital twins from freehand sketches for facade design, converting 2D designs to 3D volumes, and integrating these designs into real-world GIS systems. It outlines a process that involves generating 2D exterior images from sketches using generative AI (Gemini 1.5 Pro), converting these 2D images into 3D models with TriPo, and creating design drawings with SketchUp. Additionally, it describes a method for creating 3D exterior images using GauGAN, all for the purpose of construction exterior evaluation. The paper also discusses generating BIM data using generative AI, converting BIM data (in IFC file format) to GeoTiff, and displaying this information in GIS using QGIS software. Moreover, it suggests a method for generating digital twins with SketchUp to facilitate digital design information sharing and simulation within a virtual space. Lastly, it advocates for a cost-effective AI system designed for small and medium-sized construction companies, which often struggle to adopt BIM, to harness the advantages of digital twins. © (2025), (Science and Information Organization). All rights reserved.},
keywords = {2D/3D conversion, AI, Architectural design, BIM, Digital Twins, Facade design, Facades, GauGAN, Generative AI, GeoTiff, GIS, IFC format, Metaverse, Metaverses, SketchUp, TriPo, Volume design, Volume Rendering},
pubstate = {published},
tppubtype = {article}
}
The article proposes a method for creating digital twins from freehand sketches for facade design, converting 2D designs to 3D volumes, and integrating these designs into real-world GIS systems. It outlines a process that involves generating 2D exterior images from sketches using generative AI (Gemini 1.5 Pro), converting these 2D images into 3D models with TriPo, and creating design drawings with SketchUp. Additionally, it describes a method for creating 3D exterior images using GauGAN, all for the purpose of construction exterior evaluation. The paper also discusses generating BIM data using generative AI, converting BIM data (in IFC file format) to GeoTiff, and displaying this information in GIS using QGIS software. Moreover, it suggests a method for generating digital twins with SketchUp to facilitate digital design information sharing and simulation within a virtual space. Lastly, it advocates for a cost-effective AI system designed for small and medium-sized construction companies, which often struggle to adopt BIM, to harness the advantages of digital twins. © (2025), (Science and Information Organization). All rights reserved.
Nuemaihom, A.; Yakin, A. Al
Examining EFL Students' Perceptions and Experiences with AI-driven Metaverse Environments for Developing Communication Skills Journal Article
In: Forum for Linguistic Studies, vol. 7, no. 5, pp. 712–726, 2025, ISSN: 27050610 (ISSN).
Abstract | Links | BibTeX | Tags: AI, Communication Skills, EFL, Metaverse
@article{nuemaihom_examining_2025,
title = {Examining EFL Students' Perceptions and Experiences with AI-driven Metaverse Environments for Developing Communication Skills},
author = {A. Nuemaihom and A. Al Yakin},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105007603312&doi=10.30564%2ffls.v7i5.9453&partnerID=40&md5=2afdaef2a6dace54d8f2082ec8a1a7a2},
doi = {10.30564/fls.v7i5.9453},
issn = {27050610 (ISSN)},
year = {2025},
date = {2025-01-01},
journal = {Forum for Linguistic Studies},
volume = {7},
number = {5},
pages = {712–726},
abstract = {This study examines the development of oral communication skills in a second language (L2) context. This research employs an orally given text-based generative AI (GenAI) model as its methodology. The population in this study was 505 students at teaching and educational science faculties in universities. The demographics and sample for this study consisted of 25 undergraduate students who are majoring in Indonesian language education and 26 students who are from the Pancasila education and public health study program at Al Asyariah Mandar University, Indonesia in the 2022 academic year. They were selected via a purposive sampling method. The instruments utilized in this quantitative research are a questionnaire and observation. The research results indicated that the students' choice of interactions with virtual robots continued to improve their English communication skills, including vocabulary, intonation, gesture, and fluently dan volume. They also believe that AI can enhance their learning autonomy, critical thinking abilities, and confidence in practicing English effectively and quickly. This research contribution provides insight into the importance of using AI-robot technology so that participants achieve learning outcomes, making learning more enjoyable, the importance of soft skills for the cognitive process of language acquisition, and collaboratively foster communicative competencies in the 21st century. Copyright © 2025 by the author(s). Published by Bilingual Publishing Group.},
keywords = {AI, Communication Skills, EFL, Metaverse},
pubstate = {published},
tppubtype = {article}
}
This study examines the development of oral communication skills in a second language (L2) context. This research employs an orally given text-based generative AI (GenAI) model as its methodology. The population in this study was 505 students at teaching and educational science faculties in universities. The demographics and sample for this study consisted of 25 undergraduate students who are majoring in Indonesian language education and 26 students who are from the Pancasila education and public health study program at Al Asyariah Mandar University, Indonesia in the 2022 academic year. They were selected via a purposive sampling method. The instruments utilized in this quantitative research are a questionnaire and observation. The research results indicated that the students' choice of interactions with virtual robots continued to improve their English communication skills, including vocabulary, intonation, gesture, and fluently dan volume. They also believe that AI can enhance their learning autonomy, critical thinking abilities, and confidence in practicing English effectively and quickly. This research contribution provides insight into the importance of using AI-robot technology so that participants achieve learning outcomes, making learning more enjoyable, the importance of soft skills for the cognitive process of language acquisition, and collaboratively foster communicative competencies in the 21st century. Copyright © 2025 by the author(s). Published by Bilingual Publishing Group.
Banafa, A.
Artificial intelligence in action: Real-world applications and innovations Book
River Publishers, 2025, ISBN: 978-877004619-0 (ISBN); 978-877004620-6 (ISBN).
Abstract | Links | BibTeX | Tags: 5G, Affective Computing, AGI, AI, AI alignments, AI Ethics, AI hallucinations, AI hype, AI models, Alexa, ANI, ASI, Augmented Reality, Autoencoders, Autonomic computing, Autonomous Cars, Autoregressive models, Big Data, Big Data Analytics, Bitcoin, Blockchain, C3PO, Casual AI, Causal reasoning, ChatGPT, Cloud computing, Collective AI, Compression engines, Computer vision, Conditional Automation, Convolutional neural networks (CNNs), Cryptocurrency, Cybersecurity, Deceptive AI, Deep learning, Digital transformation, Driver Assistance, Driverless Cars, Drones, Elon Musk, Entanglement, Environment and sustainability, Ethereum, Explainable AI, Facebook, Facial Recognition, Feedforward. Neural Networks, Fog Computing, Full Automation, Future of AI, General AI, Generative Adversarial Networks (GANs), Generative AI, Google, Green AI, High Automation, Hybrid Blockchain, IEEE, Industrial Internet of Things (IIoT), Internet of things (IoT), Jarvis, Java, JavaScript, Long Short-Term Memory Networks, LTE, machine learning, Microsoft, MultiModal AI, Narrow AI, Natural disasters, Natural Language Generation (NLG), Natural Language Processing (NLP), NetFlix, Network Security, Neural Networks, Nuclear, Nuclear AI, NYTimes, Objective-driven AI, Open Source, Partial Automation, PayPal, Perfect AI, Private Blockchain, Private Cloud Computing, Programming languages, Python, Quantum Communications, Quantum Computing, Quantum Cryptography, Quantum internet, Quantum Machine Learning (QML), R2D2, Reactive machines. limited memory, Recurrent Neural Networks, Responsible AI, Robots, Sci-Fi movies, Self-Aware, Semiconductorâ??s, Sensate AI, Siri, Small Data, Smart Contracts. Hybrid Cloud Computing, Smart Devices, Sovereign AI, Super AI, Superposition, TensorFlow, Theory of Mind, Thick Data, Twitter, Variational Autoencoders (VAEs), Virtual Reality, Voice user interface (VUI), Wearable computing devices (WCD), Wearable Technology, Wi-Fi, XAI, Zero-Trust Model
@book{banafa_artificial_2025,
title = {Artificial intelligence in action: Real-world applications and innovations},
author = {A. Banafa},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105000403587&partnerID=40&md5=4b0d94be48194a942b22bef63f36d3bf},
isbn = {978-877004619-0 (ISBN); 978-877004620-6 (ISBN)},
year = {2025},
date = {2025-01-01},
publisher = {River Publishers},
series = {Artificial Intelligence in Action: Real-World Applications and Innovations},
abstract = {This comprehensive book dives deep into the current landscape of AI, exploring its fundamental principles, development challenges, potential risks, and the cutting-edge breakthroughs that are propelling it forward. Artificial intelligence (AI) is rapidly transforming industries and societies worldwide through groundbreaking innovations and real-world applications. Starting with the core concepts, the book examines the various types of AI systems, generative AI models, and the complexities of machine learning. It delves into the programming languages driving AI development, data pipelines, model creation and deployment processes, while shedding light on issues like AI hallucinations and the intricate path of machine unlearning. The book then showcases the remarkable real-world applications of AI across diverse domains. From preventing job displacement and promoting environmental sustainability, to enhancing disaster response, drone technology, and even nuclear energy innovation, it highlights how AI is tackling complex challenges and driving positive change. The book also explores the double-edged nature of AI, recognizing its tremendous potential while cautioning about the risks of misuse, unintended consequences, and the urgent need for responsible development practices. It examines the intersection of AI and fields like operating system design, warfare, and semiconductor technology, underscoring the wide-ranging implications of this transformative force. As the quest for artificial general intelligence (AGI) and superintelligent AI systems intensifies, the book delves into cutting-edge research, emerging trends, and the pursuit of multimodal, explainable, and causally aware AI systems. It explores the symbiotic relationship between AI and human creativity, the rise of user-friendly "casual AI," and the potential of AI to tackle open-ended tasks. This is an essential guide for understanding the profound impact of AI on our world today and its potential to shape our future. From the frontiers of innovation to the challenges of responsible development, this book offers a comprehensive and insightful exploration of the remarkable real-world applications and innovations driving the AI revolution. © 2025 River Publishers. All rights reserved.},
keywords = {5G, Affective Computing, AGI, AI, AI alignments, AI Ethics, AI hallucinations, AI hype, AI models, Alexa, ANI, ASI, Augmented Reality, Autoencoders, Autonomic computing, Autonomous Cars, Autoregressive models, Big Data, Big Data Analytics, Bitcoin, Blockchain, C3PO, Casual AI, Causal reasoning, ChatGPT, Cloud computing, Collective AI, Compression engines, Computer vision, Conditional Automation, Convolutional neural networks (CNNs), Cryptocurrency, Cybersecurity, Deceptive AI, Deep learning, Digital transformation, Driver Assistance, Driverless Cars, Drones, Elon Musk, Entanglement, Environment and sustainability, Ethereum, Explainable AI, Facebook, Facial Recognition, Feedforward. Neural Networks, Fog Computing, Full Automation, Future of AI, General AI, Generative Adversarial Networks (GANs), Generative AI, Google, Green AI, High Automation, Hybrid Blockchain, IEEE, Industrial Internet of Things (IIoT), Internet of things (IoT), Jarvis, Java, JavaScript, Long Short-Term Memory Networks, LTE, machine learning, Microsoft, MultiModal AI, Narrow AI, Natural disasters, Natural Language Generation (NLG), Natural Language Processing (NLP), NetFlix, Network Security, Neural Networks, Nuclear, Nuclear AI, NYTimes, Objective-driven AI, Open Source, Partial Automation, PayPal, Perfect AI, Private Blockchain, Private Cloud Computing, Programming languages, Python, Quantum Communications, Quantum Computing, Quantum Cryptography, Quantum internet, Quantum Machine Learning (QML), R2D2, Reactive machines. limited memory, Recurrent Neural Networks, Responsible AI, Robots, Sci-Fi movies, Self-Aware, Semiconductorâ??s, Sensate AI, Siri, Small Data, Smart Contracts. Hybrid Cloud Computing, Smart Devices, Sovereign AI, Super AI, Superposition, TensorFlow, Theory of Mind, Thick Data, Twitter, Variational Autoencoders (VAEs), Virtual Reality, Voice user interface (VUI), Wearable computing devices (WCD), Wearable Technology, Wi-Fi, XAI, Zero-Trust Model},
pubstate = {published},
tppubtype = {book}
}
This comprehensive book dives deep into the current landscape of AI, exploring its fundamental principles, development challenges, potential risks, and the cutting-edge breakthroughs that are propelling it forward. Artificial intelligence (AI) is rapidly transforming industries and societies worldwide through groundbreaking innovations and real-world applications. Starting with the core concepts, the book examines the various types of AI systems, generative AI models, and the complexities of machine learning. It delves into the programming languages driving AI development, data pipelines, model creation and deployment processes, while shedding light on issues like AI hallucinations and the intricate path of machine unlearning. The book then showcases the remarkable real-world applications of AI across diverse domains. From preventing job displacement and promoting environmental sustainability, to enhancing disaster response, drone technology, and even nuclear energy innovation, it highlights how AI is tackling complex challenges and driving positive change. The book also explores the double-edged nature of AI, recognizing its tremendous potential while cautioning about the risks of misuse, unintended consequences, and the urgent need for responsible development practices. It examines the intersection of AI and fields like operating system design, warfare, and semiconductor technology, underscoring the wide-ranging implications of this transformative force. As the quest for artificial general intelligence (AGI) and superintelligent AI systems intensifies, the book delves into cutting-edge research, emerging trends, and the pursuit of multimodal, explainable, and causally aware AI systems. It explores the symbiotic relationship between AI and human creativity, the rise of user-friendly "casual AI," and the potential of AI to tackle open-ended tasks. This is an essential guide for understanding the profound impact of AI on our world today and its potential to shape our future. From the frontiers of innovation to the challenges of responsible development, this book offers a comprehensive and insightful exploration of the remarkable real-world applications and innovations driving the AI revolution. © 2025 River Publishers. All rights reserved.
Tang, M.; Nikolaenko, M.; Alrefai, A.; Kumar, A.
Metaverse and Digital Twins in the Age of AI and Extended Reality Journal Article
In: Architecture, vol. 5, no. 2, 2025, ISSN: 26738945 (ISSN).
Abstract | Links | BibTeX | Tags: AI, digital twin, Extended reality, Metaverse
@article{tang_metaverse_2025,
title = {Metaverse and Digital Twins in the Age of AI and Extended Reality},
author = {M. Tang and M. Nikolaenko and A. Alrefai and A. Kumar},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105008903949&doi=10.3390%2farchitecture5020036&partnerID=40&md5=3b05b81a0cf25d3c441d4701a7749d66},
doi = {10.3390/architecture5020036},
issn = {26738945 (ISSN)},
year = {2025},
date = {2025-01-01},
journal = {Architecture},
volume = {5},
number = {2},
abstract = {This paper explores the evolving relationship between Digital Twins (DT) and the Metaverse, two foundational yet often conflated digital paradigms in digital architecture. While DTs function as mirrored models of real-world systems—integrating IoT, BIM, and real-time analytics to support decision-making—Metaverses are typically fictional, immersive, multi-user environments shaped by social, cultural, and speculative narratives. Through several research projects, the team investigate the divergence between DTs and Metaverses through the lens of their purpose, data structure, immersion, and interactivity, while highlighting areas of convergence driven by emerging technologies in Artificial Intelligence (AI) and Extended Reality (XR).This study aims to investigate the convergence of DTs and the Metaverse in digital architecture, examining how emerging technologies—such as AI, XR, and Large Language Models (LLMs)—are blurring their traditional boundaries. By analyzing their divergent purposes, data structures, and interactivity modes, as well as hybrid applications (e.g., data-integrated virtual environments and AI-driven collaboration), this study seeks to define the opportunities and challenges of this integration for architectural design, decision-making, and immersive user experiences. Our research spans multiple projects utilizing XR and AI to develop DT and the Metaverse. The team assess the capabilities of AI in DT environments, such as reality capture and smart building management. Concurrently, the team evaluates metaverse platforms for online collaboration and architectural education, focusing on features facilitating multi-user engagement. The paper presents evaluations of various virtual environment development pipelines, comparing traditional BIM+IoT workflows with novel approaches such as Gaussian Splatting and generative AI for content creation. The team further explores the integration of Large Language Models (LLMs) in both domains, such as virtual agents or LLM-powered Non-Player-Controlled Characters (NPC), enabling autonomous interaction and enhancing user engagement within spatial environments. Finally, the paper argues that DTs and Metaverse’s once-distinct boundaries are becoming increasingly porous. Hybrid digital spaces—such as virtual buildings with data-integrated twins and immersive, social metaverses—demonstrate this convergence. As digital environments mature, architects are uniquely positioned to shape these dual-purpose ecosystems, leveraging AI, XR, and spatial computing to fuse data-driven models with immersive and user-centered experiences. © 2025 by the authors.},
keywords = {AI, digital twin, Extended reality, Metaverse},
pubstate = {published},
tppubtype = {article}
}
This paper explores the evolving relationship between Digital Twins (DT) and the Metaverse, two foundational yet often conflated digital paradigms in digital architecture. While DTs function as mirrored models of real-world systems—integrating IoT, BIM, and real-time analytics to support decision-making—Metaverses are typically fictional, immersive, multi-user environments shaped by social, cultural, and speculative narratives. Through several research projects, the team investigate the divergence between DTs and Metaverses through the lens of their purpose, data structure, immersion, and interactivity, while highlighting areas of convergence driven by emerging technologies in Artificial Intelligence (AI) and Extended Reality (XR).This study aims to investigate the convergence of DTs and the Metaverse in digital architecture, examining how emerging technologies—such as AI, XR, and Large Language Models (LLMs)—are blurring their traditional boundaries. By analyzing their divergent purposes, data structures, and interactivity modes, as well as hybrid applications (e.g., data-integrated virtual environments and AI-driven collaboration), this study seeks to define the opportunities and challenges of this integration for architectural design, decision-making, and immersive user experiences. Our research spans multiple projects utilizing XR and AI to develop DT and the Metaverse. The team assess the capabilities of AI in DT environments, such as reality capture and smart building management. Concurrently, the team evaluates metaverse platforms for online collaboration and architectural education, focusing on features facilitating multi-user engagement. The paper presents evaluations of various virtual environment development pipelines, comparing traditional BIM+IoT workflows with novel approaches such as Gaussian Splatting and generative AI for content creation. The team further explores the integration of Large Language Models (LLMs) in both domains, such as virtual agents or LLM-powered Non-Player-Controlled Characters (NPC), enabling autonomous interaction and enhancing user engagement within spatial environments. Finally, the paper argues that DTs and Metaverse’s once-distinct boundaries are becoming increasingly porous. Hybrid digital spaces—such as virtual buildings with data-integrated twins and immersive, social metaverses—demonstrate this convergence. As digital environments mature, architects are uniquely positioned to shape these dual-purpose ecosystems, leveraging AI, XR, and spatial computing to fuse data-driven models with immersive and user-centered experiences. © 2025 by the authors.
2024
Asra, S. A.; Wickramarathne, J.
Artificial Intelligence (AI) in Augmented Reality (AR), Virtual Reality (VR) and Mixed Reality (MR) Experiences: Enhancing Immersion and Interaction for User Experiences Proceedings Article
In: B., Luo; S.K., Sahoo; Y.H., Lee; C.H.T., Lee; M., Ong; A., Alphones (Ed.): IEEE Reg 10 Annu Int Conf Proc TENCON, pp. 1700–1705, Institute of Electrical and Electronics Engineers Inc., 2024, ISBN: 21593442 (ISSN); 979-835035082-1 (ISBN).
Abstract | Links | BibTeX | Tags: AI, AR, Emersion experience, Immersive augmented realities, Mixed reality, MR, Primary sources, Real-world, Secondary sources, Training simulation, Users' experiences, Video game simulation, Video training, Virtual environments, VR
@inproceedings{asra_artificial_2024,
title = {Artificial Intelligence (AI) in Augmented Reality (AR), Virtual Reality (VR) and Mixed Reality (MR) Experiences: Enhancing Immersion and Interaction for User Experiences},
author = {S. A. Asra and J. Wickramarathne},
editor = {Luo B. and Sahoo S.K. and Lee Y.H. and Lee C.H.T. and Ong M. and Alphones A.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105000443498&doi=10.1109%2fTENCON61640.2024.10902724&partnerID=40&md5=2ff92b5e2529ae7fe797cd8026e8065d},
doi = {10.1109/TENCON61640.2024.10902724},
isbn = {21593442 (ISSN); 979-835035082-1 (ISBN)},
year = {2024},
date = {2024-01-01},
booktitle = {IEEE Reg 10 Annu Int Conf Proc TENCON},
pages = {1700–1705},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {The utilisation of Artificial Intelligence (AI) generated material is one of the most fascinating advancements in the rapidly growing fields of Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR). Two examples of how AI-generated material is revolutionising how we interact with AR, VR and MR are video games and training simulations. In this essay, we'll examine the intriguing potential of AI-generated content and how it's being used to the development of hybrid real-world/virtual experiences. Using this strategy, we acquired the information from primary and secondary sources. We surveyed AR, VR, and MR users to compile the data for the primary source. Then, utilising published papers as a secondary source, information was gathered. By elucidating the concept of context immersion, this research can lay the foundation for the advancement of information regarding immersive AR, VR, and MR contexts. We are able to offer recommendations for overcoming the weak parts and strengthening the good ones based on the questionnaire survey findings. © 2024 IEEE.},
keywords = {AI, AR, Emersion experience, Immersive augmented realities, Mixed reality, MR, Primary sources, Real-world, Secondary sources, Training simulation, Users' experiences, Video game simulation, Video training, Virtual environments, VR},
pubstate = {published},
tppubtype = {inproceedings}
}
The utilisation of Artificial Intelligence (AI) generated material is one of the most fascinating advancements in the rapidly growing fields of Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR). Two examples of how AI-generated material is revolutionising how we interact with AR, VR and MR are video games and training simulations. In this essay, we'll examine the intriguing potential of AI-generated content and how it's being used to the development of hybrid real-world/virtual experiences. Using this strategy, we acquired the information from primary and secondary sources. We surveyed AR, VR, and MR users to compile the data for the primary source. Then, utilising published papers as a secondary source, information was gathered. By elucidating the concept of context immersion, this research can lay the foundation for the advancement of information regarding immersive AR, VR, and MR contexts. We are able to offer recommendations for overcoming the weak parts and strengthening the good ones based on the questionnaire survey findings. © 2024 IEEE.
Wang, Y.; Zhang, Y.
Enhancing Cognitive Recall in Dementia Patients: Integrating Generative AI with Virtual Reality for Behavioral and Memory Rehabilitation Proceedings Article
In: ACM Int. Conf. Proc. Ser., pp. 86–91, Association for Computing Machinery, 2024, ISBN: 979-840071806-9 (ISBN).
Abstract | Links | BibTeX | Tags: AI, Cognitive rehabilitation, Cognitive stimulations, Dementia patients, Electronic health record, Firebase, Generalisation, Neurodegenerative diseases, Non visuals, Patient rehabilitation, Rehabilitation projects, Virtual environments, Virtual Reality, Virtual-reality environment, Visual memory, Visual-spatial, VR
@inproceedings{wang_enhancing_2024,
title = {Enhancing Cognitive Recall in Dementia Patients: Integrating Generative AI with Virtual Reality for Behavioral and Memory Rehabilitation},
author = {Y. Wang and Y. Zhang},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85205444838&doi=10.1145%2f3686540.3686552&partnerID=40&md5=1577754660fddd936254fc78586e6a17},
doi = {10.1145/3686540.3686552},
isbn = {979-840071806-9 (ISBN)},
year = {2024},
date = {2024-01-01},
booktitle = {ACM Int. Conf. Proc. Ser.},
pages = {86–91},
publisher = {Association for Computing Machinery},
abstract = {In this Project, we developed a cognitive rehabilitation program for dementia patients, leveraging generative AI and virtual reality (VR) to evoke personal memories [4]. Integrating Open AI, DreamStudio, and Unity, our system allows patients to input descriptions, generating visual memories in a VR environment [5]. In trials, 85% of AI-generated images matched patients' expectations, although some inaccuracies arose from AI generalizations. Further validation with dementia patients is needed to assess memory recovery impacts. This novel approach modernizes Cognitive Stimulation Therapy (CST), traditionally reliant on non-visual exercises, by incorporating AI and VR to enhance memory recall and visual-spatial skills. While the world is developing more and more into Artificial Intelligence (AI) and Virtual Reality (VR), our program successfully coordinates them to help stimulate dementia patients' brains and perform the memory recall and visual spatial aspects of CST. © 2024 Copyright held by the owner/author(s).},
keywords = {AI, Cognitive rehabilitation, Cognitive stimulations, Dementia patients, Electronic health record, Firebase, Generalisation, Neurodegenerative diseases, Non visuals, Patient rehabilitation, Rehabilitation projects, Virtual environments, Virtual Reality, Virtual-reality environment, Visual memory, Visual-spatial, VR},
pubstate = {published},
tppubtype = {inproceedings}
}
In this Project, we developed a cognitive rehabilitation program for dementia patients, leveraging generative AI and virtual reality (VR) to evoke personal memories [4]. Integrating Open AI, DreamStudio, and Unity, our system allows patients to input descriptions, generating visual memories in a VR environment [5]. In trials, 85% of AI-generated images matched patients' expectations, although some inaccuracies arose from AI generalizations. Further validation with dementia patients is needed to assess memory recovery impacts. This novel approach modernizes Cognitive Stimulation Therapy (CST), traditionally reliant on non-visual exercises, by incorporating AI and VR to enhance memory recall and visual-spatial skills. While the world is developing more and more into Artificial Intelligence (AI) and Virtual Reality (VR), our program successfully coordinates them to help stimulate dementia patients' brains and perform the memory recall and visual spatial aspects of CST. © 2024 Copyright held by the owner/author(s).
Rahmani, R.; Westin, T.; Nevelsteen, K.
Future Healthcare in Generative AI with Real Metaverse Proceedings Article
In: E.E., Shakshuki (Ed.): Procedia Comput. Sci., pp. 487–493, Elsevier B.V., 2024, ISBN: 18770509 (ISSN).
Abstract | Links | BibTeX | Tags: Adversarial machine learning, AI, Augmented Reality, Autism spectrum disorders, Contrastive Learning, Diseases, Edge Intelligence, Generative adversarial networks, Healthcare, Immersive learning, Independent living systems, Language Model, Large language model, LLM, Metaverses, Posttraumatic stress disorder, Real Metaverse, Social challenges, Virtual environments
@inproceedings{rahmani_future_2024,
title = {Future Healthcare in Generative AI with Real Metaverse},
author = {R. Rahmani and T. Westin and K. Nevelsteen},
editor = {Shakshuki E.E.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85214986921&doi=10.1016%2fj.procs.2024.11.137&partnerID=40&md5=3e25f2a1b023cd49f59a066a96bb2dd0},
doi = {10.1016/j.procs.2024.11.137},
isbn = {18770509 (ISSN)},
year = {2024},
date = {2024-01-01},
booktitle = {Procedia Comput. Sci.},
volume = {251},
pages = {487–493},
publisher = {Elsevier B.V.},
abstract = {The Metaverse offers a simulated environment that could transform healthcare by providing immersive learning experiences through Internet application and social form that integrates network of virtual reality environments. The Metaverse is expected to contribute to a new way of socializing, where users can enter a verse as avatars. The concept allows avatars to switch between verses seamlessly. Virtual Reality (VR) in healthcare has shown promise for social-skill training, especially for individuals with Autism Spectrum Disorder (ASD) and social challenge training of patients with Post-Traumatic Stress Disorder (PTSD) requiring adaptable support. The problem lies in the limited adaptability and functionality of existing Metaverse implementations for individuals with ASD and PTSD. While studies have explored various implementation ideas, such as VR platforms for training social skills, social challenge and context-aware Augmented Reality (AR) systems for daily activities, many lack adaptability of user input and output. A proposed solution involves a context-aware system using AI, Large Language Models (LLMs) and generative agents to support independent living for individuals with ASD and a tool to enhance emotional learning with PTSD. © 2024 The Authors.},
keywords = {Adversarial machine learning, AI, Augmented Reality, Autism spectrum disorders, Contrastive Learning, Diseases, Edge Intelligence, Generative adversarial networks, Healthcare, Immersive learning, Independent living systems, Language Model, Large language model, LLM, Metaverses, Posttraumatic stress disorder, Real Metaverse, Social challenges, Virtual environments},
pubstate = {published},
tppubtype = {inproceedings}
}
The Metaverse offers a simulated environment that could transform healthcare by providing immersive learning experiences through Internet application and social form that integrates network of virtual reality environments. The Metaverse is expected to contribute to a new way of socializing, where users can enter a verse as avatars. The concept allows avatars to switch between verses seamlessly. Virtual Reality (VR) in healthcare has shown promise for social-skill training, especially for individuals with Autism Spectrum Disorder (ASD) and social challenge training of patients with Post-Traumatic Stress Disorder (PTSD) requiring adaptable support. The problem lies in the limited adaptability and functionality of existing Metaverse implementations for individuals with ASD and PTSD. While studies have explored various implementation ideas, such as VR platforms for training social skills, social challenge and context-aware Augmented Reality (AR) systems for daily activities, many lack adaptability of user input and output. A proposed solution involves a context-aware system using AI, Large Language Models (LLMs) and generative agents to support independent living for individuals with ASD and a tool to enhance emotional learning with PTSD. © 2024 The Authors.
Si, J.; Yang, S.; Song, J.; Son, S.; Lee, S.; Kim, D.; Kim, S.
Generating and Integrating Diffusion Model-Based Panoramic Views for Virtual Interview Platform Proceedings Article
In: IEEE Int. Conf. Artif. Intell. Eng. Technol., IICAIET, pp. 343–348, Institute of Electrical and Electronics Engineers Inc., 2024, ISBN: 979-835038969-2 (ISBN).
Abstract | Links | BibTeX | Tags: AI, Deep learning, Diffusion, Diffusion Model, Diffusion technology, Digital elevation model, High quality, Manual process, Model-based OPC, New approaches, Panorama, Panoramic views, Virtual environments, Virtual Interview, Virtual Reality
@inproceedings{si_generating_2024,
title = {Generating and Integrating Diffusion Model-Based Panoramic Views for Virtual Interview Platform},
author = {J. Si and S. Yang and J. Song and S. Son and S. Lee and D. Kim and S. Kim},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85209663031&doi=10.1109%2fIICAIET62352.2024.10730450&partnerID=40&md5=a52689715ec912c54696948c34fc0263},
doi = {10.1109/IICAIET62352.2024.10730450},
isbn = {979-835038969-2 (ISBN)},
year = {2024},
date = {2024-01-01},
booktitle = {IEEE Int. Conf. Artif. Intell. Eng. Technol., IICAIET},
pages = {343–348},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {This paper presents a new approach to improve virtual interview platforms in education, which are gaining significant attention. This study aims to simplify the complex manual process of equipment setup to enhance the realism and reliability of virtual interviews. To this end, this study proposes a method for automatically constructing 3D virtual interview environments using diffusion technology in generative AI. In this research, we exploit a diffusion model capable of generating high-quality panoramic images. We generate images of interview rooms capable of delivering immersive interview experiences via refined text prompts. The resulting imagery is then reconstituted 3D VR content utilizing the Unity engine, facilitating enhanced interaction and engagement within virtual environments. This research compares and analyzes various methods presented in related research and proposes a new process for efficiently constructing 360-degree virtual environments. When wearing Oculus Quest 2 and experiencing the virtual environment created using the proposed method, a high sense of immersion was experienced, similar to the actual interview environment. © 2024 IEEE.},
keywords = {AI, Deep learning, Diffusion, Diffusion Model, Diffusion technology, Digital elevation model, High quality, Manual process, Model-based OPC, New approaches, Panorama, Panoramic views, Virtual environments, Virtual Interview, Virtual Reality},
pubstate = {published},
tppubtype = {inproceedings}
}
This paper presents a new approach to improve virtual interview platforms in education, which are gaining significant attention. This study aims to simplify the complex manual process of equipment setup to enhance the realism and reliability of virtual interviews. To this end, this study proposes a method for automatically constructing 3D virtual interview environments using diffusion technology in generative AI. In this research, we exploit a diffusion model capable of generating high-quality panoramic images. We generate images of interview rooms capable of delivering immersive interview experiences via refined text prompts. The resulting imagery is then reconstituted 3D VR content utilizing the Unity engine, facilitating enhanced interaction and engagement within virtual environments. This research compares and analyzes various methods presented in related research and proposes a new process for efficiently constructing 360-degree virtual environments. When wearing Oculus Quest 2 and experiencing the virtual environment created using the proposed method, a high sense of immersion was experienced, similar to the actual interview environment. © 2024 IEEE.
Klein, A.; Arnowitz, E.
AI in mixed reality - Copilot on HoloLens: Spatial computing with large language models Proceedings Article
In: S.N., Spencer (Ed.): Proc. - SIGGRAPH Real-Time Live!, Association for Computing Machinery, Inc, 2024, ISBN: 979-840070526-7 (ISBN).
Abstract | Links | BibTeX | Tags: 3D, AI, AR, Gesture, Gestures, HoloLens, Language Model, LLM, Mixed reality, Real- time, Real-time, Spatial computing, User experience design, User interfaces, Voice
@inproceedings{klein_ai_2024,
title = {AI in mixed reality - Copilot on HoloLens: Spatial computing with large language models},
author = {A. Klein and E. Arnowitz},
editor = {Spencer S.N.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200657459&doi=10.1145%2f3641520.3665305&partnerID=40&md5=07d385771b8813c1fafa0efb7ae7e9f2},
doi = {10.1145/3641520.3665305},
isbn = {979-840070526-7 (ISBN)},
year = {2024},
date = {2024-01-01},
booktitle = {Proc. - SIGGRAPH Real-Time Live!},
publisher = {Association for Computing Machinery, Inc},
abstract = {Mixed reality together with AI presents a human-first interface that promises to transform operations. Copilot can assist industrial workers in real-time with speech and holograms; generative AI is used to search technical documentation, service records, training content, and other sources. Copilot then summarizes to provide interactive guidance. © 2024 Owner/Author.},
keywords = {3D, AI, AR, Gesture, Gestures, HoloLens, Language Model, LLM, Mixed reality, Real- time, Real-time, Spatial computing, User experience design, User interfaces, Voice},
pubstate = {published},
tppubtype = {inproceedings}
}
Mixed reality together with AI presents a human-first interface that promises to transform operations. Copilot can assist industrial workers in real-time with speech and holograms; generative AI is used to search technical documentation, service records, training content, and other sources. Copilot then summarizes to provide interactive guidance. © 2024 Owner/Author.
2023
Su, Qiqi; Peretokin, Vadim; Basdekis, Ioannis; Kouris, Ioannis; Maggesi, Jonatan; Sicuranza, Mario; Acebes, Alberto; Bucur, Anca; Mukkala, Vinod Jaswanth Roy; Pozdniakov, Konstantin; Kloukinas, Christos; Koutsouris, Dimitrios D.; Iliadou, Elefteria; Leontsinis, Ioannis; Gallo, Luigi; Pietro, Giuseppe De; Spanoudakis, George
The SMART BEAR Project: An Overview of Its Infrastructure Proceedings Article
In: Maciaszek, Leszek A.; Mulvenna, Maurice D.; Ziefle, Martina (Ed.): Information and Communication Technologies for Ageing Well and E-Health, pp. 408–425, Springer Nature Switzerland, Cham, 2023, ISBN: 978-3-031-37496-8.
Abstract | Links | BibTeX | Tags: Ageing, AI, Balance Disorder, Cardiovascular Disease, Cloud, Evidence-based, GDPR, Healthcare, Hearing Loss, HL7 FHIR, Semantic interoperability
@inproceedings{suSMARTBEARProject2023,
title = {The SMART BEAR Project: An Overview of Its Infrastructure},
author = {Qiqi Su and Vadim Peretokin and Ioannis Basdekis and Ioannis Kouris and Jonatan Maggesi and Mario Sicuranza and Alberto Acebes and Anca Bucur and Vinod Jaswanth Roy Mukkala and Konstantin Pozdniakov and Christos Kloukinas and Dimitrios D. Koutsouris and Elefteria Iliadou and Ioannis Leontsinis and Luigi Gallo and Giuseppe De Pietro and George Spanoudakis},
editor = { Leszek A. Maciaszek and Maurice D. Mulvenna and Martina Ziefle},
url = {https://link.springer.com/chapter/10.1007/978-3-031-37496-8_21},
doi = {10.1007/978-3-031-37496-8_21},
isbn = {978-3-031-37496-8},
year = {2023},
date = {2023-07-14},
urldate = {2023-01-01},
booktitle = {Information and Communication Technologies for Ageing Well and E-Health},
pages = {408–425},
publisher = {Springer Nature Switzerland},
address = {Cham},
series = {Communications in Computer and Information Science},
abstract = {The paper describes a cloud-based platform that utilizes Artificial Intelligence (AI) and Explainable AI techniques to deliver evidence-based, personalized interventions to individuals over 65 suffering or at risk of hearing loss, cardiovascular disease, cognitive impairments, balance disorders, or mental health issues, while supporting efficient remote monitoring and clinician-driven guidance. As part of the SMART BEAR integrated project, this platform has been developed to support its large-scale clinical trials. The platform consists of a standards-based data harmonization and management layer, as well as a security component, a Big Data Analytics system, a Clinical Decision Support system, and a dashboard component to facilitate efficient data collection across pilot sites.},
keywords = {Ageing, AI, Balance Disorder, Cardiovascular Disease, Cloud, Evidence-based, GDPR, Healthcare, Hearing Loss, HL7 FHIR, Semantic interoperability},
pubstate = {published},
tppubtype = {inproceedings}
}
The paper describes a cloud-based platform that utilizes Artificial Intelligence (AI) and Explainable AI techniques to deliver evidence-based, personalized interventions to individuals over 65 suffering or at risk of hearing loss, cardiovascular disease, cognitive impairments, balance disorders, or mental health issues, while supporting efficient remote monitoring and clinician-driven guidance. As part of the SMART BEAR integrated project, this platform has been developed to support its large-scale clinical trials. The platform consists of a standards-based data harmonization and management layer, as well as a security component, a Big Data Analytics system, a Clinical Decision Support system, and a dashboard component to facilitate efficient data collection across pilot sites.
Su, Qiqi; Peretokin, Vadim; Basdekis, Ioannis; Kouris, Ioannis; Maggesi, Jonatan; Sicuranza, Mario; Acebes, Alberto; Bucur, Anca; Mukkala, Vinod Jaswanth Roy; Pozdniakov, Konstantin; Kloukinas, Christos; Koutsouris, Dimitrios D.; Iliadou, Elefteria; Leontsinis, Ioannis; Gallo, Luigi; Pietro, Giuseppe De; Spanoudakis, George
The SMART BEAR Project: An Overview of Its Infrastructure Proceedings Article
In: Maciaszek, Leszek A.; Mulvenna, Maurice D.; Ziefle, Martina (Ed.): Information and Communication Technologies for Ageing Well and e-Health, pp. 408–425, Springer Nature Switzerland, Cham, 2023, ISBN: 978-3-031-37496-8.
Abstract | Links | BibTeX | Tags: Ageing, AI, Balance Disorder, Cardiovascular Disease, Cloud, Evidence-based, GDPR, Healthcare, Hearing Loss, HL7 FHIR, Semantic interoperability
@inproceedings{su_smart_2023,
title = {The SMART BEAR Project: An Overview of Its Infrastructure},
author = {Qiqi Su and Vadim Peretokin and Ioannis Basdekis and Ioannis Kouris and Jonatan Maggesi and Mario Sicuranza and Alberto Acebes and Anca Bucur and Vinod Jaswanth Roy Mukkala and Konstantin Pozdniakov and Christos Kloukinas and Dimitrios D. Koutsouris and Elefteria Iliadou and Ioannis Leontsinis and Luigi Gallo and Giuseppe De Pietro and George Spanoudakis},
editor = {Leszek A. Maciaszek and Maurice D. Mulvenna and Martina Ziefle},
doi = {10.1007/978-3-031-37496-8_21},
isbn = {978-3-031-37496-8},
year = {2023},
date = {2023-01-01},
booktitle = {Information and Communication Technologies for Ageing Well and e-Health},
pages = {408–425},
publisher = {Springer Nature Switzerland},
address = {Cham},
series = {Communications in Computer and Information Science},
abstract = {The paper describes a cloud-based platform that utilizes Artificial Intelligence (AI) and Explainable AI techniques to deliver evidence-based, personalized interventions to individuals over 65 suffering or at risk of hearing loss, cardiovascular disease, cognitive impairments, balance disorders, or mental health issues, while supporting efficient remote monitoring and clinician-driven guidance. As part of the SMART BEAR integrated project, this platform has been developed to support its large-scale clinical trials. The platform consists of a standards-based data harmonization and management layer, as well as a security component, a Big Data Analytics system, a Clinical Decision Support system, and a dashboard component to facilitate efficient data collection across pilot sites.},
keywords = {Ageing, AI, Balance Disorder, Cardiovascular Disease, Cloud, Evidence-based, GDPR, Healthcare, Hearing Loss, HL7 FHIR, Semantic interoperability},
pubstate = {published},
tppubtype = {inproceedings}
}
The paper describes a cloud-based platform that utilizes Artificial Intelligence (AI) and Explainable AI techniques to deliver evidence-based, personalized interventions to individuals over 65 suffering or at risk of hearing loss, cardiovascular disease, cognitive impairments, balance disorders, or mental health issues, while supporting efficient remote monitoring and clinician-driven guidance. As part of the SMART BEAR integrated project, this platform has been developed to support its large-scale clinical trials. The platform consists of a standards-based data harmonization and management layer, as well as a security component, a Big Data Analytics system, a Clinical Decision Support system, and a dashboard component to facilitate efficient data collection across pilot sites.
Banafa, A.
Transformative AI: Responsible, Transparent, and Trustworthy AI Systems Book
River Publishers, 2023, ISBN: 978-877004018-1 (ISBN); 978-877004019-8 (ISBN).
Abstract | Links | BibTeX | Tags: 5G, Affective Computing, AI, AI Ethics, Alexa, Augment Reality, Autoencoders, Autonomous Cars, Autoregressive models, Big Data, Big Data Analytics, Bitcoin, Blockchain, C3PO, ChatGPT, Cloud computing, CNN, Computer vision, Conditional Automation, Convolutional Neural Networks, Cryptocurrency, Cybersecurity, Deep learning, Digital transformation, Driver Assistance, Driverless Cars, Entanglement, Ethereum, Explainable AI. Environment and sustainability, Facebook, Facial Recognition, Feedforward. Neural Networks, Fog Computing, Full Automation, General AI, Generative Adversarial Networks (GANs), Generative AI, Google, High Automation, Hybrid Blockchain, IEEE, IIoT, Industrial Internet of Things, Internet of Things, IoT, Jarvis, Long Short-Term Memory Networks, LTE, Machin Learning, Microsoft, Narrow AI, Natural Language Generation (NLG), Natural Language Processing (NLP), NetFlix, Network Security, Neural Networks, NYTimes, Open Source, Partial Automation, PayPal, Private Blockchain, Private Cloud Computing, Quantum Communications, Quantum Computing, Quantum Cryptography, Quantum Internet. Wearable Computing Devices (WCD). Autonomic Computing, Quantum Machine Learning (QML), R2D2, Reactive Machines . Limited Memory, Recurrent Neural Networks, Robots, Sci-Fi movies, Self-Aware, Siri, Small Data, Smart Contracts. Hybrid Cloud Computing, Smart Devices, Super AI, Superposition, Theory of Mind, Thick Data, Twitter, Variational Autoencoders (VAEs), Virtual Reality, Voice User Interface, VUI, Wearable Technology, Wi-Fi, Zero-Trust Model
@book{banafa_transformative_2023,
title = {Transformative AI: Responsible, Transparent, and Trustworthy AI Systems},
author = {A. Banafa},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85180544759&partnerID=40&md5=c1fcd00f4b40e16156d9877185f66554},
isbn = {978-877004018-1 (ISBN); 978-877004019-8 (ISBN)},
year = {2023},
date = {2023-01-01},
publisher = {River Publishers},
series = {Transformative AI: Responsible, Transparent, and Trustworthy AI Systems},
abstract = {Transformative AI provides a comprehensive overview of the latest trends, challenges, applications, and opportunities in the field of Artificial Intelligence. The book covers the state of the art in AI research, including machine learning, natural language processing, computer vision, and robotics, and explores how these technologies are transforming various industries and domains, such as healthcare, finance, education, and entertainment. The book also addresses the challenges that come with the widespread adoption of AI, including ethical concerns, bias, and the impact on jobs and society. It provides insights into how to mitigate these challenges and how to design AI systems that are responsible, transparent, and trustworthy. The book offers a forward-looking perspective on the future of AI, exploring the emerging trends and applications that are likely to shape the next decade of AI innovation. It also provides practical guidance for businesses and individuals on how to leverage the power of AI to create new products, services, and opportunities. Overall, the book is an essential read for anyone who wants to stay ahead of the curve in the rapidly evolving field of Artificial Intelligence and understand the impact that this transformative technology will have on our lives in the coming years. © 2024 River Publishers. All rights reserved.},
keywords = {5G, Affective Computing, AI, AI Ethics, Alexa, Augment Reality, Autoencoders, Autonomous Cars, Autoregressive models, Big Data, Big Data Analytics, Bitcoin, Blockchain, C3PO, ChatGPT, Cloud computing, CNN, Computer vision, Conditional Automation, Convolutional Neural Networks, Cryptocurrency, Cybersecurity, Deep learning, Digital transformation, Driver Assistance, Driverless Cars, Entanglement, Ethereum, Explainable AI. Environment and sustainability, Facebook, Facial Recognition, Feedforward. Neural Networks, Fog Computing, Full Automation, General AI, Generative Adversarial Networks (GANs), Generative AI, Google, High Automation, Hybrid Blockchain, IEEE, IIoT, Industrial Internet of Things, Internet of Things, IoT, Jarvis, Long Short-Term Memory Networks, LTE, Machin Learning, Microsoft, Narrow AI, Natural Language Generation (NLG), Natural Language Processing (NLP), NetFlix, Network Security, Neural Networks, NYTimes, Open Source, Partial Automation, PayPal, Private Blockchain, Private Cloud Computing, Quantum Communications, Quantum Computing, Quantum Cryptography, Quantum Internet. Wearable Computing Devices (WCD). Autonomic Computing, Quantum Machine Learning (QML), R2D2, Reactive Machines . Limited Memory, Recurrent Neural Networks, Robots, Sci-Fi movies, Self-Aware, Siri, Small Data, Smart Contracts. Hybrid Cloud Computing, Smart Devices, Super AI, Superposition, Theory of Mind, Thick Data, Twitter, Variational Autoencoders (VAEs), Virtual Reality, Voice User Interface, VUI, Wearable Technology, Wi-Fi, Zero-Trust Model},
pubstate = {published},
tppubtype = {book}
}
Transformative AI provides a comprehensive overview of the latest trends, challenges, applications, and opportunities in the field of Artificial Intelligence. The book covers the state of the art in AI research, including machine learning, natural language processing, computer vision, and robotics, and explores how these technologies are transforming various industries and domains, such as healthcare, finance, education, and entertainment. The book also addresses the challenges that come with the widespread adoption of AI, including ethical concerns, bias, and the impact on jobs and society. It provides insights into how to mitigate these challenges and how to design AI systems that are responsible, transparent, and trustworthy. The book offers a forward-looking perspective on the future of AI, exploring the emerging trends and applications that are likely to shape the next decade of AI innovation. It also provides practical guidance for businesses and individuals on how to leverage the power of AI to create new products, services, and opportunities. Overall, the book is an essential read for anyone who wants to stay ahead of the curve in the rapidly evolving field of Artificial Intelligence and understand the impact that this transformative technology will have on our lives in the coming years. © 2024 River Publishers. All rights reserved.