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
Bernetti, I.; Borghini, T.; Capecchi, I.
Integrating Virtual Reality and Artificial Intelligence in Agricultural Planning: Insights from the V.AİḞ.AṘṀ. Application Proceedings Article
In: L.T., De Paolis; P., Arpaia; M., Sacco (Ed.): Lect. Notes Comput. Sci., pp. 342–350, Springer Science and Business Media Deutschland GmbH, 2024, ISBN: 03029743 (ISSN); 978-303171706-2 (ISBN).
Abstract | Links | BibTeX | Tags: Agricultural management, Agricultural planning, Agricultural resources, Artificial intelligence technologies, Collaborative Virtual Reality, Critical thinking, Educational approach, Management applications, Openai, Resource management
@inproceedings{bernetti_integrating_2024,
title = {Integrating Virtual Reality and Artificial Intelligence in Agricultural Planning: Insights from the V.AİḞ.AṘṀ. Application},
author = {I. Bernetti and T. Borghini and I. Capecchi},
editor = {De Paolis L.T. and Arpaia P. and Sacco M.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204516778&doi=10.1007%2f978-3-031-71707-9_28&partnerID=40&md5=a887379b08dc925667f255cfcacfb4b9},
doi = {10.1007/978-3-031-71707-9_28},
isbn = {03029743 (ISSN); 978-303171706-2 (ISBN)},
year = {2024},
date = {2024-01-01},
booktitle = {Lect. Notes Comput. Sci.},
volume = {15027 LNCS},
pages = {342–350},
publisher = {Springer Science and Business Media Deutschland GmbH},
abstract = {The V.A.I.F.A.R.M. (Virtual and Artificial Intelligence for Farming and Agricultural Resource Management) app explores the integration of collaborative virtual reality (VR) with generative artificial intelligence (AI), specifically utilizing ChatGPT, to enhance educational approaches within agricultural management and planning. This study aims to investigate the educational outcomes associated with the combined use of VR and AI technologies, with a particular focus on their impact on critical thinking, problem-solving abilities, and collaborative learning among university students engaged in agricultural studies. By employing VR, the project creates a simulated agricultural environment where students are tasked with various management and planning activities, offering a practical application of theoretical knowledge. The addition of ChatGPT facilitates interactive, AI-mediated dialogues, challenging students to tackle complex agricultural problems through informed decision-making processes. The research anticipates findings that suggest an improvement in student engagement and a better grasp of complicated agricultural concepts, attributed to the immersive and interactive nature of the learning experience. Furthermore, it examines the role of VR and AI in cultivating essential soft skills critical for the agricultural sector. The study contributes to the understanding of how collaborative VR and generative AI can be effectively combined to advance educational practices in agriculture, aiming for a balanced evaluation of their potential benefits without overstating the outcomes. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.},
keywords = {Agricultural management, Agricultural planning, Agricultural resources, Artificial intelligence technologies, Collaborative Virtual Reality, Critical thinking, Educational approach, Management applications, Openai, Resource management},
pubstate = {published},
tppubtype = {inproceedings}
}
The V.A.I.F.A.R.M. (Virtual and Artificial Intelligence for Farming and Agricultural Resource Management) app explores the integration of collaborative virtual reality (VR) with generative artificial intelligence (AI), specifically utilizing ChatGPT, to enhance educational approaches within agricultural management and planning. This study aims to investigate the educational outcomes associated with the combined use of VR and AI technologies, with a particular focus on their impact on critical thinking, problem-solving abilities, and collaborative learning among university students engaged in agricultural studies. By employing VR, the project creates a simulated agricultural environment where students are tasked with various management and planning activities, offering a practical application of theoretical knowledge. The addition of ChatGPT facilitates interactive, AI-mediated dialogues, challenging students to tackle complex agricultural problems through informed decision-making processes. The research anticipates findings that suggest an improvement in student engagement and a better grasp of complicated agricultural concepts, attributed to the immersive and interactive nature of the learning experience. Furthermore, it examines the role of VR and AI in cultivating essential soft skills critical for the agricultural sector. The study contributes to the understanding of how collaborative VR and generative AI can be effectively combined to advance educational practices in agriculture, aiming for a balanced evaluation of their potential benefits without overstating the outcomes. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Du, B.; Du, H.; Liu, H.; Niyato, D.; Xin, P.; Yu, J.; Qi, M.; Tang, Y.
YOLO-Based Semantic Communication with Generative AI-Aided Resource Allocation for Digital Twins Construction Journal Article
In: IEEE Internet of Things Journal, vol. 11, no. 5, pp. 7664–7678, 2024, ISSN: 23274662 (ISSN).
Abstract | Links | BibTeX | Tags: Cost reduction, Data transfer, Digital Twins, Edge detection, Image edge detection, Network layers, Object Detection, Object detectors, Objects detection, Physical world, Resource allocation, Resource management, Resources allocation, Semantic communication, Semantics, Semantics Information, Virtual Reality, Virtual worlds, Wireless communications
@article{du_yolo-based_2024,
title = {YOLO-Based Semantic Communication with Generative AI-Aided Resource Allocation for Digital Twins Construction},
author = {B. Du and H. Du and H. Liu and D. Niyato and P. Xin and J. Yu and M. Qi and Y. Tang},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173060990&doi=10.1109%2fJIOT.2023.3317629&partnerID=40&md5=60507e2f6ce2b1c345248867a9c527a1},
doi = {10.1109/JIOT.2023.3317629},
issn = {23274662 (ISSN)},
year = {2024},
date = {2024-01-01},
journal = {IEEE Internet of Things Journal},
volume = {11},
number = {5},
pages = {7664–7678},
abstract = {Digital Twins play a crucial role in bridging the physical and virtual worlds. Given the dynamic and evolving characteristics of the physical world, a huge volume of data transmission and exchange is necessary to attain synchronized updates in the virtual world. In this article, we propose a semantic communication framework based on you only look once (YOLO) to construct a virtual apple orchard with the aim of mitigating the costs associated with data transmission. Specifically, we first employ the YOLOv7-X object detector to extract semantic information from captured images of edge devices, thereby reducing the volume of transmitted data and saving transmission costs. Afterwards, we quantify the importance of each semantic information by the confidence generated through the object detector. Based on this, we propose two resource allocation schemes, i.e., the confidence-based scheme and the acrlong AI-generated scheme, aimed at enhancing the transmission quality of important semantic information. The proposed diffusion model generates an optimal allocation scheme that outperforms both the average allocation scheme and the confidence-based allocation scheme. Moreover, to obtain semantic information more effectively, we enhance the detection capability of the YOLOv7-X object detector by introducing new efficient layer aggregation network-horNet (ELAN-H) and SimAM attention modules, while reducing the model parameters and computational complexity, making it easier to run on edge devices with limited performance. The numerical results indicate that our proposed semantic communication framework and resource allocation schemes significantly reduce transmission costs while enhancing the transmission quality of important information in communication services. © 2014 IEEE.},
keywords = {Cost reduction, Data transfer, Digital Twins, Edge detection, Image edge detection, Network layers, Object Detection, Object detectors, Objects detection, Physical world, Resource allocation, Resource management, Resources allocation, Semantic communication, Semantics, Semantics Information, Virtual Reality, Virtual worlds, Wireless communications},
pubstate = {published},
tppubtype = {article}
}
Digital Twins play a crucial role in bridging the physical and virtual worlds. Given the dynamic and evolving characteristics of the physical world, a huge volume of data transmission and exchange is necessary to attain synchronized updates in the virtual world. In this article, we propose a semantic communication framework based on you only look once (YOLO) to construct a virtual apple orchard with the aim of mitigating the costs associated with data transmission. Specifically, we first employ the YOLOv7-X object detector to extract semantic information from captured images of edge devices, thereby reducing the volume of transmitted data and saving transmission costs. Afterwards, we quantify the importance of each semantic information by the confidence generated through the object detector. Based on this, we propose two resource allocation schemes, i.e., the confidence-based scheme and the acrlong AI-generated scheme, aimed at enhancing the transmission quality of important semantic information. The proposed diffusion model generates an optimal allocation scheme that outperforms both the average allocation scheme and the confidence-based allocation scheme. Moreover, to obtain semantic information more effectively, we enhance the detection capability of the YOLOv7-X object detector by introducing new efficient layer aggregation network-horNet (ELAN-H) and SimAM attention modules, while reducing the model parameters and computational complexity, making it easier to run on edge devices with limited performance. The numerical results indicate that our proposed semantic communication framework and resource allocation schemes significantly reduce transmission costs while enhancing the transmission quality of important information in communication services. © 2014 IEEE.
Lin, Y.; Gao, Z.; Du, H.; Niyato, D.; Kang, J.; Xiong, Z.; Zheng, Z.
Blockchain-Based Efficient and Trustworthy AIGC Services in Metaverse Journal Article
In: IEEE Transactions on Services Computing, vol. 17, no. 5, pp. 2067–2079, 2024, ISSN: 19391374 (ISSN).
Abstract | Links | BibTeX | Tags: AI-generated content, Block-chain, Blockchain, Computational modelling, Content services, Data Mining, Digital contents, Information Management, Metaverse, Metaverses, Resource management, Semantic communication, Semantics, Virtual Reality
@article{lin_blockchain-based_2024,
title = {Blockchain-Based Efficient and Trustworthy AIGC Services in Metaverse},
author = {Y. Lin and Z. Gao and H. Du and D. Niyato and J. Kang and Z. Xiong and Z. Zheng},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85189177655&doi=10.1109%2fTSC.2024.3382958&partnerID=40&md5=5e3e80fbc88a49293b892acd762af3e9},
doi = {10.1109/TSC.2024.3382958},
issn = {19391374 (ISSN)},
year = {2024},
date = {2024-01-01},
journal = {IEEE Transactions on Services Computing},
volume = {17},
number = {5},
pages = {2067–2079},
abstract = {AI-Generated Content (AIGC) services are essential in developing the Metaverse, providing various digital content to build shared virtual environments. The services can also offer personalized content with user assistance, making the Metaverse more human-centric. However, user-assisted content creation requires significant communication resources to exchange data and construct trust among unknown Metaverse participants, which challenges the traditional centralized communication paradigm. To address the above challenge, we integrate blockchain with semantic communication to establish decentralized trust among participants, reducing communication overhead and improving trustworthiness for AIGC services in Metaverse. To solve the out-of-distribution issue in data provided by users, we utilize the invariant risk minimization method to extract invariant semantic information across multiple virtual environments. To guarantee trustworthiness of digital contents, we also design a smart contract-based verification mechanism to prevent random outcomes of AIGC services. We utilize semantic information and quality of digital contents provided by the above mechanisms as metrics to develop a Stackelberg game-based content caching mechanism, which can maximize the profits of Metaverse participants. Simulation results show that the proposed semantic extraction and caching mechanism can improve accuracy by almost 15% and utility by 30% compared to other mechanisms. © 2008-2012 IEEE.},
keywords = {AI-generated content, Block-chain, Blockchain, Computational modelling, Content services, Data Mining, Digital contents, Information Management, Metaverse, Metaverses, Resource management, Semantic communication, Semantics, Virtual Reality},
pubstate = {published},
tppubtype = {article}
}
AI-Generated Content (AIGC) services are essential in developing the Metaverse, providing various digital content to build shared virtual environments. The services can also offer personalized content with user assistance, making the Metaverse more human-centric. However, user-assisted content creation requires significant communication resources to exchange data and construct trust among unknown Metaverse participants, which challenges the traditional centralized communication paradigm. To address the above challenge, we integrate blockchain with semantic communication to establish decentralized trust among participants, reducing communication overhead and improving trustworthiness for AIGC services in Metaverse. To solve the out-of-distribution issue in data provided by users, we utilize the invariant risk minimization method to extract invariant semantic information across multiple virtual environments. To guarantee trustworthiness of digital contents, we also design a smart contract-based verification mechanism to prevent random outcomes of AIGC services. We utilize semantic information and quality of digital contents provided by the above mechanisms as metrics to develop a Stackelberg game-based content caching mechanism, which can maximize the profits of Metaverse participants. Simulation results show that the proposed semantic extraction and caching mechanism can improve accuracy by almost 15% and utility by 30% compared to other mechanisms. © 2008-2012 IEEE.