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 use the tag cloud to select only the papers dealing with specific research topics.
You can expand the Abstract, Links and BibTex record for each paper.
2025
Raj, P.
Generative AI for the enterprise metaverse system engineering Book Section
In: Engineering the Metaverse: Enabling technologies, platforms and use cases, pp. 97–118, Institution of Engineering and Technology, 2025, ISBN: 978-183953881-0 (ISBN); 978-183953880-3 (ISBN).
Abstract | Links | BibTeX | Tags: Computer vision, Cybersecurity, Digital avatars, Immersive and interactive experience, Internet of things (IoT)
@incollection{raj_generative_2025,
title = {Generative AI for the enterprise metaverse system engineering},
author = {P. Raj},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-86000473202&doi=10.1049%2fPBPC070E_ch6&partnerID=40&md5=274a94afa9c33ac10902194859e85e81},
doi = {10.1049/PBPC070E_ch6},
isbn = {978-183953881-0 (ISBN); 978-183953880-3 (ISBN)},
year = {2025},
date = {2025-01-01},
booktitle = {Engineering the Metaverse: Enabling technologies, platforms and use cases},
pages = {97–118},
publisher = {Institution of Engineering and Technology},
abstract = {With digitization and digitalization technologies flourishing, the digital era is dawning upon us influentially. Every tangible entity becomes digitized to participate in mainstream computing fluidly. When digital entities interact with one another purposefully, a massive amount of multi-structured data gets produced, collected, cleansed, and stocked for posterior data analytics to extract hidden insights, patterns, and other knowledge bases. Artificial intelligence (AI), the most popular digital transformation technology on the planet Earth, is succulently capable of making sense out of accumulating digital datasets. Knowledge discovery is disseminated to the concerned systems to make them aware of the power of knowledge-enabled systems. Notably, there are several illuminating and insightful improvisations (for example, multimodal generative AI) in the AI space. Blockchain, Web 3.0, the IoT, edge computing, cloud-native computing, immersive technologies such as virtual, augmented, mixed, and extended realities (VR, AR, MR and XR), multimodal LLMs for crafting 3D models for a variety of things including buildings, landscapes, etc., digital twins for complicated physical systems, processes and spaces, 5G communication, non-fungible tokens (NFTs), simulation tools, etc. are blending to establish 3D virtual environments to captivate users. Besides the consumer metaverse, enterprise metaverse systems emerge and evolve fast to bring delectable and decisive automation, acceleration, and augmentation to businesses. In this chapter, we have dug deep and dealt with the enterprise metaverse at length to educate and empower our esteemed readers. © The Institution of Engineering and Technology and its licensors 2024.},
keywords = {Computer vision, Cybersecurity, Digital avatars, Immersive and interactive experience, Internet of things (IoT)},
pubstate = {published},
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With digitization and digitalization technologies flourishing, the digital era is dawning upon us influentially. Every tangible entity becomes digitized to participate in mainstream computing fluidly. When digital entities interact with one another purposefully, a massive amount of multi-structured data gets produced, collected, cleansed, and stocked for posterior data analytics to extract hidden insights, patterns, and other knowledge bases. Artificial intelligence (AI), the most popular digital transformation technology on the planet Earth, is succulently capable of making sense out of accumulating digital datasets. Knowledge discovery is disseminated to the concerned systems to make them aware of the power of knowledge-enabled systems. Notably, there are several illuminating and insightful improvisations (for example, multimodal generative AI) in the AI space. Blockchain, Web 3.0, the IoT, edge computing, cloud-native computing, immersive technologies such as virtual, augmented, mixed, and extended realities (VR, AR, MR and XR), multimodal LLMs for crafting 3D models for a variety of things including buildings, landscapes, etc., digital twins for complicated physical systems, processes and spaces, 5G communication, non-fungible tokens (NFTs), simulation tools, etc. are blending to establish 3D virtual environments to captivate users. Besides the consumer metaverse, enterprise metaverse systems emerge and evolve fast to bring delectable and decisive automation, acceleration, and augmentation to businesses. In this chapter, we have dug deep and dealt with the enterprise metaverse at length to educate and empower our esteemed readers. © The Institution of Engineering and Technology and its licensors 2024.
Mendoza, A. P.; Quiroga, K. J. Barrios; Celis, S. D. Solano; M., C. G. Quintero
NAIA: A Multi-Technology Virtual Assistant for Boosting Academic Environments—A Case Study Journal Article
In: IEEE Access, vol. 13, pp. 141461–141483, 2025, ISSN: 21693536 (ISSN), (Publisher: Institute of Electrical and Electronics Engineers Inc.).
Abstract | Links | BibTeX | Tags: Academic environment, Artificial intelligence, Case-studies, Computational Linguistics, Computer vision, Digital avatar, Digital avatars, Efficiency, Human computer interaction, Human-AI Interaction, Interactive computer graphics, Language Model, Large language model, large language model (LLM), Learning systems, Natural language processing systems, Personal digital assistants, Personnel training, Population statistics, Speech communication, Speech processing, Speech to text, speech to text (STT), Text to speech, text to speech (TTS), user experience, User interfaces, Virtual assistant, Virtual assistants, Virtual Reality
@article{mendoza_naia_2025,
title = {NAIA: A Multi-Technology Virtual Assistant for Boosting Academic Environments—A Case Study},
author = {A. P. Mendoza and K. J. Barrios Quiroga and S. D. Solano Celis and C. G. Quintero M.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105013598763&doi=10.1109%2FACCESS.2025.3597565&partnerID=40&md5=7ad6b037cfedb943fc026642c4854284},
doi = {10.1109/ACCESS.2025.3597565},
issn = {21693536 (ISSN)},
year = {2025},
date = {2025-01-01},
journal = {IEEE Access},
volume = {13},
pages = {141461–141483},
abstract = {Virtual assistants have become essential tools for improving productivity and efficiency in various domains. This paper presents NAIA (Nimble Artificial Intelligence Assistant), an advanced multi-role and multi-task virtual assistant enhanced with artificial intelligence, designed to serve a university community case study. The system integrates AI technologies including Large Language Models (LLM), Computer Vision, and voice processing to create an immersive and efficient interaction through animated digital avatars. NAIA features five specialized roles: researcher, receptionist, personal skills trainer, personal assistant, and university guide, each equipped with specific capabilities to support different aspects of academic life. The system’s Computer Vision capabilities enable it to comment on users’ physical appearance and environment, enriching the interaction. Through natural language processing and voice interaction, NAIA aims to improve productivity and efficiency within the university environment while providing personalized assistance through a ubiquitous platform accessible across multiple devices. NAIA is evaluated through a user experience survey involving 30 participants with different demographic characteristics, this is the most accepted way by the community to evaluate this type of solution. Participants give their feedback after using one role of NAIA after using it for 30 minutes. The experiment showed that 90% of the participants considered NAIA-assisted tasks of higher quality and, on average, NAIA has a score of 4.27 out of 5 on user satisfaction. Participants particularly appreciated the assistant’s visual recognition, natural conversation flow, and user interaction capabilities. Results demonstrate NAIA’s capabilities and effectiveness across the five roles. © 2025 Elsevier B.V., All rights reserved.},
note = {Publisher: Institute of Electrical and Electronics Engineers Inc.},
keywords = {Academic environment, Artificial intelligence, Case-studies, Computational Linguistics, Computer vision, Digital avatar, Digital avatars, Efficiency, Human computer interaction, Human-AI Interaction, Interactive computer graphics, Language Model, Large language model, large language model (LLM), Learning systems, Natural language processing systems, Personal digital assistants, Personnel training, Population statistics, Speech communication, Speech processing, Speech to text, speech to text (STT), Text to speech, text to speech (TTS), user experience, User interfaces, Virtual assistant, Virtual assistants, Virtual Reality},
pubstate = {published},
tppubtype = {article}
}
Virtual assistants have become essential tools for improving productivity and efficiency in various domains. This paper presents NAIA (Nimble Artificial Intelligence Assistant), an advanced multi-role and multi-task virtual assistant enhanced with artificial intelligence, designed to serve a university community case study. The system integrates AI technologies including Large Language Models (LLM), Computer Vision, and voice processing to create an immersive and efficient interaction through animated digital avatars. NAIA features five specialized roles: researcher, receptionist, personal skills trainer, personal assistant, and university guide, each equipped with specific capabilities to support different aspects of academic life. The system’s Computer Vision capabilities enable it to comment on users’ physical appearance and environment, enriching the interaction. Through natural language processing and voice interaction, NAIA aims to improve productivity and efficiency within the university environment while providing personalized assistance through a ubiquitous platform accessible across multiple devices. NAIA is evaluated through a user experience survey involving 30 participants with different demographic characteristics, this is the most accepted way by the community to evaluate this type of solution. Participants give their feedback after using one role of NAIA after using it for 30 minutes. The experiment showed that 90% of the participants considered NAIA-assisted tasks of higher quality and, on average, NAIA has a score of 4.27 out of 5 on user satisfaction. Participants particularly appreciated the assistant’s visual recognition, natural conversation flow, and user interaction capabilities. Results demonstrate NAIA’s capabilities and effectiveness across the five roles. © 2025 Elsevier B.V., All rights reserved.
B, C. E. Pardo; R, O. I. Iglesias; A, M. D. León; M., C. G. Quintero
EverydAI: Virtual Assistant for Decision-Making in Daily Contexts, Powered by Artificial Intelligence Journal Article
In: Systems, vol. 13, no. 9, 2025, ISSN: 20798954 (ISSN), (Publisher: Multidisciplinary Digital Publishing Institute (MDPI)).
Abstract | Links | BibTeX | Tags: Artificial intelligence, Augmented Reality, Behavioral Research, Decision making, Decisions makings, Digital avatar, Digital avatars, Information overloads, Informed decision, Interactive computer graphics, Language Model, Large language model, large language models, Natural language processing systems, Natural languages, Object Detection, Object recognition, Objects detection, recommendation systems, Recommender systems, Three dimensional computer graphics, Virtual assistants, Virtual Reality, web scraping, Web scrapings
@article{pardo_b_everydai_2025,
title = {EverydAI: Virtual Assistant for Decision-Making in Daily Contexts, Powered by Artificial Intelligence},
author = {C. E. Pardo B and O. I. Iglesias R and M. D. León A and C. G. Quintero M.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105017115803&doi=10.3390%2Fsystems13090753&partnerID=40&md5=475327fffcdc43ee3466b4a65111866a},
doi = {10.3390/systems13090753},
issn = {20798954 (ISSN)},
year = {2025},
date = {2025-01-01},
journal = {Systems},
volume = {13},
number = {9},
abstract = {In an era of information overload, artificial intelligence plays a pivotal role in supporting everyday decision-making. This paper introduces EverydAI, a virtual AI-powered assistant designed to help users make informed decisions across various daily domains such as cooking, fashion, and fitness. By integrating advanced natural language processing, object detection, augmented reality, contextual understanding, digital 3D avatar models, web scraping, and image generation, EverydAI delivers personalized recommendations and insights tailored to individual needs. The proposed framework addresses challenges related to decision fatigue and information overload by combining real-time object detection and web scraping to enhance the relevance and reliability of its suggestions. EverydAI is evaluated through a two-phase survey, each one involving 30 participants with diverse demographic backgrounds. Results indicate that on average, 92.7% of users agreed or strongly agreed with statements reflecting the system’s usefulness, ease of use, and overall performance, indicating a high level of acceptance and perceived effectiveness. Additionally, EverydAI received an average user satisfaction score of 4.53 out of 5, underscoring its effectiveness in supporting users’ daily routines. © 2025 Elsevier B.V., All rights reserved.},
note = {Publisher: Multidisciplinary Digital Publishing Institute (MDPI)},
keywords = {Artificial intelligence, Augmented Reality, Behavioral Research, Decision making, Decisions makings, Digital avatar, Digital avatars, Information overloads, Informed decision, Interactive computer graphics, Language Model, Large language model, large language models, Natural language processing systems, Natural languages, Object Detection, Object recognition, Objects detection, recommendation systems, Recommender systems, Three dimensional computer graphics, Virtual assistants, Virtual Reality, web scraping, Web scrapings},
pubstate = {published},
tppubtype = {article}
}
In an era of information overload, artificial intelligence plays a pivotal role in supporting everyday decision-making. This paper introduces EverydAI, a virtual AI-powered assistant designed to help users make informed decisions across various daily domains such as cooking, fashion, and fitness. By integrating advanced natural language processing, object detection, augmented reality, contextual understanding, digital 3D avatar models, web scraping, and image generation, EverydAI delivers personalized recommendations and insights tailored to individual needs. The proposed framework addresses challenges related to decision fatigue and information overload by combining real-time object detection and web scraping to enhance the relevance and reliability of its suggestions. EverydAI is evaluated through a two-phase survey, each one involving 30 participants with diverse demographic backgrounds. Results indicate that on average, 92.7% of users agreed or strongly agreed with statements reflecting the system’s usefulness, ease of use, and overall performance, indicating a high level of acceptance and perceived effectiveness. Additionally, EverydAI received an average user satisfaction score of 4.53 out of 5, underscoring its effectiveness in supporting users’ daily routines. © 2025 Elsevier B.V., All rights reserved.