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.
2024
Cigliano, A.; Fallucchi, F.; Gerardi, M.
An Analysis of the State of Art of the Metaverse and Its Disruptive Impact on Services Proceedings Article
In: R., Fazzolari; A.A., Jaber; C., Randieri (Ed.): CEUR Workshop Proc., pp. 38–46, CEUR-WS, 2024, ISBN: 16130073 (ISSN).
Abstract | Links | BibTeX | Tags: AI: Artificial Intelligence, Artificial intelligence: artificial intelligence, Block-chain, Blockchain, DH: Digital Humanity, Digital humanities, Digital twin: digital twin, DT: Digital Twin, Economic and social effects, ER: Extended Reality, Extended reality: extended reality, GenI: Generative Artificial Intelligence, IoT, Language Model, LLM: Large Language Model, Metaverse, Metaverses, Natural language model, Nft, NLP: Natural Language Model, Quantum Computing, Virtual environments, VR: Virtual Reality
@inproceedings{cigliano_analysis_2024,
title = {An Analysis of the State of Art of the Metaverse and Its Disruptive Impact on Services},
author = {A. Cigliano and F. Fallucchi and M. Gerardi},
editor = {Fazzolari R. and Jaber A.A. and Randieri C.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85213681173&partnerID=40&md5=cf59e812c4d5bdc51c9daae3eb7c0406},
isbn = {16130073 (ISSN)},
year = {2024},
date = {2024-01-01},
booktitle = {CEUR Workshop Proc.},
volume = {3869},
pages = {38–46},
publisher = {CEUR-WS},
abstract = {The metaverse is a virtual environment where individuals may connect with one another, partake in a variety of activities, and access digital content. It coexists with the real world and it has the potential to significantly affect daily life as well as a variety of services and applications as it develops. To understand the importance of the impacts of the metaverse in today’s society, just think of the disruptive technologies that enable it: Artificial Intelligence (AI), Extended Reality (ER), IoT, Digital Twin (DT) and Blockchain/NFT all with assistance with the availability of large, rich and structured/unstructured dataset and advanced computational models. Metaverse is cadidated (and not only) to redefine everyday life, designing activities and services/products provisioning towards increasing efficiencies, money saving and quality performance, with a big impact in everyone and helping the design and testing of next generation of internet. However, there still remain not only technical and interoperability issues but above all ethical, human, social, and cultural concerns as to the metaverse’s influence upon its prospective scope in reconstructing the quality of urban life. This paper undertakes an upper-level scientific literature review of the area of the metaverse from a broader perspective. Further, it maps the some services and the relative requirements for declinate the enabling technologies of the metaverse, and explores their contributions. © 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).},
keywords = {AI: Artificial Intelligence, Artificial intelligence: artificial intelligence, Block-chain, Blockchain, DH: Digital Humanity, Digital humanities, Digital twin: digital twin, DT: Digital Twin, Economic and social effects, ER: Extended Reality, Extended reality: extended reality, GenI: Generative Artificial Intelligence, IoT, Language Model, LLM: Large Language Model, Metaverse, Metaverses, Natural language model, Nft, NLP: Natural Language Model, Quantum Computing, Virtual environments, VR: Virtual Reality},
pubstate = {published},
tppubtype = {inproceedings}
}
The metaverse is a virtual environment where individuals may connect with one another, partake in a variety of activities, and access digital content. It coexists with the real world and it has the potential to significantly affect daily life as well as a variety of services and applications as it develops. To understand the importance of the impacts of the metaverse in today’s society, just think of the disruptive technologies that enable it: Artificial Intelligence (AI), Extended Reality (ER), IoT, Digital Twin (DT) and Blockchain/NFT all with assistance with the availability of large, rich and structured/unstructured dataset and advanced computational models. Metaverse is cadidated (and not only) to redefine everyday life, designing activities and services/products provisioning towards increasing efficiencies, money saving and quality performance, with a big impact in everyone and helping the design and testing of next generation of internet. However, there still remain not only technical and interoperability issues but above all ethical, human, social, and cultural concerns as to the metaverse’s influence upon its prospective scope in reconstructing the quality of urban life. This paper undertakes an upper-level scientific literature review of the area of the metaverse from a broader perspective. Further, it maps the some services and the relative requirements for declinate the enabling technologies of the metaverse, and explores their contributions. © 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
Liang, Q.; Chen, Y.; Li, W.; Lai, M.; Ni, W.; Qiu, H.
In: L., Zhang; W., Yu; Q., Wang; Y., Laili; Y., Liu (Ed.): Commun. Comput. Info. Sci., pp. 12–24, Springer Science and Business Media Deutschland GmbH, 2024, ISBN: 18650929 (ISSN); 978-981973947-9 (ISBN).
Abstract | Links | BibTeX | Tags: Augmented Reality, Glass, Identity recognition, Internet of Things, Internet of things technologies, IoT, Language learning, Learning systems, LLM, Object Detection, Objects detection, Open Vocabulary Object Detection, Recognition systems, Semantics, Telephone sets, Translation (languages), Translation systems, Visual languages, Wearable computers, Wearable device, Wearable devices
@inproceedings{liang_iknowisee_2024,
title = {iKnowiSee: AR Glasses with Language Learning Translation System and Identity Recognition System Built Based on Large Pre-trained Models of Language and Vision and Internet of Things Technology},
author = {Q. Liang and Y. Chen and W. Li and M. Lai and W. Ni and H. Qiu},
editor = {Zhang L. and Yu W. and Wang Q. and Laili Y. and Liu Y.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200663840&doi=10.1007%2f978-981-97-3948-6_2&partnerID=40&md5=a0324ba6108674b1d39a338574269d60},
doi = {10.1007/978-981-97-3948-6_2},
isbn = {18650929 (ISSN); 978-981973947-9 (ISBN)},
year = {2024},
date = {2024-01-01},
booktitle = {Commun. Comput. Info. Sci.},
volume = {2139 CCIS},
pages = {12–24},
publisher = {Springer Science and Business Media Deutschland GmbH},
abstract = {AR glasses used in daily life have made good progress and have some practical value.However, the current design concept of AR glasses is basically to simply port the content of a cell phone and act as a secondary screen for the phone. In contrast, the AR glasses we designed are based on actual situations, focus on real-world interactions, and utilize IoT technology with the aim of enabling users to fully extract and utilize the digital information in their lives. We have created two innovative features, one is a language learning translation system for users to learn foreign languages, which integrates a large language model with an open vocabulary recognition model to fully extract the visual semantic information of the scene; and the other is a social conferencing system, which utilizes the IoT cloud, pipe, edge, and end development to reduce the cost of communication and improve the efficiency of exchanges in social situations. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.},
keywords = {Augmented Reality, Glass, Identity recognition, Internet of Things, Internet of things technologies, IoT, Language learning, Learning systems, LLM, Object Detection, Objects detection, Open Vocabulary Object Detection, Recognition systems, Semantics, Telephone sets, Translation (languages), Translation systems, Visual languages, Wearable computers, Wearable device, Wearable devices},
pubstate = {published},
tppubtype = {inproceedings}
}
AR glasses used in daily life have made good progress and have some practical value.However, the current design concept of AR glasses is basically to simply port the content of a cell phone and act as a secondary screen for the phone. In contrast, the AR glasses we designed are based on actual situations, focus on real-world interactions, and utilize IoT technology with the aim of enabling users to fully extract and utilize the digital information in their lives. We have created two innovative features, one is a language learning translation system for users to learn foreign languages, which integrates a large language model with an open vocabulary recognition model to fully extract the visual semantic information of the scene; and the other is a social conferencing system, which utilizes the IoT cloud, pipe, edge, and end development to reduce the cost of communication and improve the efficiency of exchanges in social situations. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
2023
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.
2022
Scianna, Andrea; Gaglio, Giuseppe Fulvio; Guardia, Marcello La
Structure Monitoring with BIM and IoT: The Case Study of a Bridge Beam Model Journal Article
In: ISPRS International Journal of Geo-Information, vol. 11, no. 3, 2022.
Abstract | Links | BibTeX | Tags: BIM, IoT
@article{sciannaStructureMonitoringBIM2022a,
title = {Structure Monitoring with BIM and IoT: The Case Study of a Bridge Beam Model},
author = { Andrea Scianna and Giuseppe Fulvio Gaglio and Marcello La Guardia},
doi = {10.3390/ijgi11030173},
year = {2022},
date = {2022-01-01},
journal = {ISPRS International Journal of Geo-Information},
volume = {11},
number = {3},
publisher = {MDPI},
abstract = {The diffusion of Building Information Modelling (BIM) as a reference methodology, applied to the world of construction, leads to important changes in the design and the management of big constructions and infrastructures. However, although the BIM approach is necessary for managing the entire life cycle of a construction, today, this methodology is still rarely adopted beyond the design phase. This represents a major flaw because the management of every phase of the life cycle of buildings needs accurate preliminary planning. Certainly, one of the most complex and important phases of the life cycle of a construction is the monitoring phase, which represents a fundamental aspect for the maintenance and the safe fruition of buildings or civil constructions. Considering this, the multidisciplinary approach of merging BIM methodology with real-time monitoring, using low-cost IoT (Internet of Things) sensors, seems to be an interesting topic to develop. In this paper, we will propose an example of a connection between an IoT system and a BIM model for monitoring the deflection of a bridge beam at the centerline using a schematic scale model reproduced in the laboratory and modelled in BIM. The developed system allows the real-time connection between the real model and its digital twin through the use of a relational database management system (RDBMS), to which the data detected by the sensor are transmitted, allowing the risk assessment of the real structure. This solution gives the possibility to remotely monitor, in real time, the behaviour of the structure visualised in the BIM model. textcopyright 2022 by the authors. Licensee MDPI, Basel, Switzerland.},
keywords = {BIM, IoT},
pubstate = {published},
tppubtype = {article}
}
The diffusion of Building Information Modelling (BIM) as a reference methodology, applied to the world of construction, leads to important changes in the design and the management of big constructions and infrastructures. However, although the BIM approach is necessary for managing the entire life cycle of a construction, today, this methodology is still rarely adopted beyond the design phase. This represents a major flaw because the management of every phase of the life cycle of buildings needs accurate preliminary planning. Certainly, one of the most complex and important phases of the life cycle of a construction is the monitoring phase, which represents a fundamental aspect for the maintenance and the safe fruition of buildings or civil constructions. Considering this, the multidisciplinary approach of merging BIM methodology with real-time monitoring, using low-cost IoT (Internet of Things) sensors, seems to be an interesting topic to develop. In this paper, we will propose an example of a connection between an IoT system and a BIM model for monitoring the deflection of a bridge beam at the centerline using a schematic scale model reproduced in the laboratory and modelled in BIM. The developed system allows the real-time connection between the real model and its digital twin through the use of a relational database management system (RDBMS), to which the data detected by the sensor are transmitted, allowing the risk assessment of the real structure. This solution gives the possibility to remotely monitor, in real time, the behaviour of the structure visualised in the BIM model. textcopyright 2022 by the authors. Licensee MDPI, Basel, Switzerland.
Scianna, Andrea; Gaglio, Giuseppe Fulvio; Guardia, Marcello La
Structure Monitoring with BIM and IoT: The Case Study of a Bridge Beam Model Journal Article
In: ISPRS International Journal of Geo-Information, vol. 11, no. 3, 2022, (Number: 3 Publisher: MDPI).
Abstract | Links | BibTeX | Tags: BIM, IoT
@article{scianna_structure_2022,
title = {Structure Monitoring with BIM and IoT: The Case Study of a Bridge Beam Model},
author = {Andrea Scianna and Giuseppe Fulvio Gaglio and Marcello La Guardia},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85126649022&doi=10.3390%2fijgi11030173&partnerID=40&md5=2c5373416cce1b71ed7063ea297a42d0},
doi = {10.3390/ijgi11030173},
year = {2022},
date = {2022-01-01},
journal = {ISPRS International Journal of Geo-Information},
volume = {11},
number = {3},
abstract = {The diffusion of Building Information Modelling (BIM) as a reference methodology, applied to the world of construction, leads to important changes in the design and the management of big constructions and infrastructures. However, although the BIM approach is necessary for managing the entire life cycle of a construction, today, this methodology is still rarely adopted beyond the design phase. This represents a major flaw because the management of every phase of the life cycle of buildings needs accurate preliminary planning. Certainly, one of the most complex and important phases of the life cycle of a construction is the monitoring phase, which represents a fundamental aspect for the maintenance and the safe fruition of buildings or civil constructions. Considering this, the multidisciplinary approach of merging BIM methodology with real-time monitoring, using low-cost IoT (Internet of Things) sensors, seems to be an interesting topic to develop. In this paper, we will propose an example of a connection between an IoT system and a BIM model for monitoring the deflection of a bridge beam at the centerline using a schematic scale model reproduced in the laboratory and modelled in BIM. The developed system allows the real-time connection between the real model and its digital twin through the use of a relational database management system (RDBMS), to which the data detected by the sensor are transmitted, allowing the risk assessment of the real structure. This solution gives the possibility to remotely monitor, in real time, the behaviour of the structure visualised in the BIM model. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.},
note = {Number: 3
Publisher: MDPI},
keywords = {BIM, IoT},
pubstate = {published},
tppubtype = {article}
}
The diffusion of Building Information Modelling (BIM) as a reference methodology, applied to the world of construction, leads to important changes in the design and the management of big constructions and infrastructures. However, although the BIM approach is necessary for managing the entire life cycle of a construction, today, this methodology is still rarely adopted beyond the design phase. This represents a major flaw because the management of every phase of the life cycle of buildings needs accurate preliminary planning. Certainly, one of the most complex and important phases of the life cycle of a construction is the monitoring phase, which represents a fundamental aspect for the maintenance and the safe fruition of buildings or civil constructions. Considering this, the multidisciplinary approach of merging BIM methodology with real-time monitoring, using low-cost IoT (Internet of Things) sensors, seems to be an interesting topic to develop. In this paper, we will propose an example of a connection between an IoT system and a BIM model for monitoring the deflection of a bridge beam at the centerline using a schematic scale model reproduced in the laboratory and modelled in BIM. The developed system allows the real-time connection between the real model and its digital twin through the use of a relational database management system (RDBMS), to which the data detected by the sensor are transmitted, allowing the risk assessment of the real structure. This solution gives the possibility to remotely monitor, in real time, the behaviour of the structure visualised in the BIM model. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
2019
Sabatucci, Luca; Cossentino, Massimo; Lopes, Salvatore
Service Composition with Partial Goal Satisfaction. Proceedings Article
In: AI&IoT@ AI* IA, pp. 55–67, 2019.
Abstract | BibTeX | Tags: Dynamic workflow, IoT, Partial goal satisfaction, Service Composition
@inproceedings{sabatucciServiceCompositionPartial2019,
title = {Service Composition with Partial Goal Satisfaction.},
author = { Luca Sabatucci and Massimo Cossentino and Salvatore Lopes},
year = {2019},
date = {2019-01-01},
booktitle = {AI&IoT@ AI* IA},
pages = {55--67},
abstract = {IoT applications are often ad-hoc compositions of services offered by connected devices that cooperate to satisfy user's goals. Sometimes, addressing full goal satisfaction is too stringent and replacing that with an easier to satisfy partial goal satisfaction is a good alternative to a complete failure. In this paper we propose a service composition approach that adopts a metrics for measuring the partial satisfaction of goal. The metrics adopts an electrical analogy extended for dealing with temporal goals.},
keywords = {Dynamic workflow, IoT, Partial goal satisfaction, Service Composition},
pubstate = {published},
tppubtype = {inproceedings}
}
IoT applications are often ad-hoc compositions of services offered by connected devices that cooperate to satisfy user's goals. Sometimes, addressing full goal satisfaction is too stringent and replacing that with an easier to satisfy partial goal satisfaction is a good alternative to a complete failure. In this paper we propose a service composition approach that adopts a metrics for measuring the partial satisfaction of goal. The metrics adopts an electrical analogy extended for dealing with temporal goals.
Sabatucci, Luca; Cossentino, Massimo; Lopes, Salvatore
Service Composition with Partial Goal Satisfaction. Proceedings Article
In: AI&IoT@ AI* IA, pp. 55–67, 2019.
Abstract | Links | BibTeX | Tags: Dynamic workflow, IoT, Partial goal satisfaction, Service Composition
@inproceedings{sabatucci_service_2019,
title = {Service Composition with Partial Goal Satisfaction.},
author = {Luca Sabatucci and Massimo Cossentino and Salvatore Lopes},
url = {https://ceur-ws.org/Vol-2502/paper4.pdf},
year = {2019},
date = {2019-01-01},
booktitle = {AI&IoT@ AI* IA},
pages = {55–67},
abstract = {IoT applications are often ad-hoc compositions of services offered by connected devices that cooperate to satisfy user's goals. Sometimes, addressing full goal satisfaction is too stringent and replacing that with an easier to satisfy partial goal satisfaction is a good alternative to a complete failure. In this paper we propose a service composition approach that adopts a metrics for measuring the partial satisfaction of goal. The metrics adopts an electrical analogy extended for dealing with temporal goals.},
keywords = {Dynamic workflow, IoT, Partial goal satisfaction, Service Composition},
pubstate = {published},
tppubtype = {inproceedings}
}
IoT applications are often ad-hoc compositions of services offered by connected devices that cooperate to satisfy user's goals. Sometimes, addressing full goal satisfaction is too stringent and replacing that with an easier to satisfy partial goal satisfaction is a good alternative to a complete failure. In this paper we propose a service composition approach that adopts a metrics for measuring the partial satisfaction of goal. The metrics adopts an electrical analogy extended for dealing with temporal goals.