On the Exploitation of 5G Multi-Access Edge Computing for Spatial Audio in Cultural Heritage Applications

Rinaldi, Claudia; Franchi, Fabio; Marotta, Andrea; Graziosi, Fabio; Centofanti, Carlo

doi:10.1109/access.2021.3128786

Cited by 16 publications

(10 citation statements)

References 35 publications

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“…Nevertheless, the paradigms of cloud computing [94] and edge computing [95] have the potential to address such requirement and, therefore, to become the main infrastructure of the MM. This is in particular relevant for 5G architectures [96,97].…”

Section: Computing Powermentioning

confidence: 99%

Musical Metaverse: vision, opportunities, and challenges

Turchet

2023

Pers Ubiquit Comput

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The so-called metaverse relates to a vision of a virtual, digital world which is parallel to the real, physical world, where each user owns and interact through his/her own avatar. Music is one of the possible activities that can be conducted in such a space. The “Musical Metaverse” (MM), the metaverse part which is dedicated to musical activities, is currently in its infancy, although is a concept that is constantly evolving and is progressing at a steady pace. However, to the best of the author’s knowledge, as of today an investigation about the opportunities and challenges posed by the MM has not been conducted yet. In this paper, we provide a vision for the MM and discuss what are the opportunities for musical stakeholders offered by current implementations of the MM, as well as we envision those that are likely to occur as the metaverse emerges. We also identify the technical, artistic, ethical, sustainability, and regulatory issues that need to be addressed so for the MM to be created and utilized in efficient, creative, and responsible ways. Given the importance and timeliness of the MM, we believe that a discussion on the related opportunities and concerns is useful to provide developers with guidelines for creating better virtual environments and musical interactions between stakeholders.

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Section: Computing Powermentioning

confidence: 99%

Musical Metaverse: vision, opportunities, and challenges

Turchet

2023

Pers Ubiquit Comput

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“…5) Networking: In Section II, we have seen that the realtime communication of audio-related information poses stringent requirements in terms of latency (delay from the transmission to the reception of packets), jitter (sudden variations of the latency) and reliability (probability of successful packet reception) [229]- [231]. Moreover, in some use cases the data rate is low, such as to detect crashes from accidents or simple acoustic signals, whereas in other use cases, the data rates are very high, such as when the acoustic signals carry complex information and need to be quantized at very high sampling rates.…”

Section: Relevant Work Common To Both Iomust and Ioautmentioning

confidence: 99%

“…The future composition of TSN and 5G protocols (when the source is a wireless device that needs to be connected to the Internet) will therefore allow to arguably meet most of the communication requirements of the Internet of Sounds. Recent research in this space has proposed dedicated architectures to interconnect distributed musicians over wireless links along with analysis of simulations under different conditions as well as real-world applications of such architectures [82], [231], [237], [238].…”

Section: Relevant Work Common To Both Iomust and Ioautmentioning

confidence: 99%

The Internet of Sounds: Convergent Trends, Insights, and Future Directions

Turchet

Lagrange

Rottondi

et al. 2023

IEEE Internet Things J.

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Current sound-based practices and systems developed in both academia and industry point to convergent research trends that bring together the field of Sound and Music Computing with that of the Internet of Things. This paper proposes a vision for the emerging field of the Internet of Sounds (IoS), which stems from such disciplines. The IoS relates to the network of Sound Things, i.e., devices capable of sensing, acquiring, processing, actuating, and exchanging data serving the purpose of communicating sound-related information. In the IoS paradigm, which merges under a unique umbrella the emerging fields of the Internet of Musical Things and the Internet of Audio Things, heterogeneous devices dedicated to musical and nonmusical tasks can interact and cooperate with one another and with other things connected to the Internet to facilitate soundbased services and applications that are globally available to the users. We survey the state of the art in this space, discuss the technological and non-technological challenges ahead of us and propose a comprehensive research agenda for the field.

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“…From the perspective of innovative management and improving management efficiency, relevant scholars decompose smart tourism into the construction of cloud platform, the construction of all-round perception system, and the construction of application platform as the top-level design of building smart tourism [ 14 ]. All kinds of information collected by tourist attractions are decomposed, refined, and constructed into management instructions for decision-making [ 15 , 16 ].…”

Section: Related Workmentioning

confidence: 99%

Implementation of Personalized Scenic Spot Recommendation Algorithm Based on Generalized Regression Neural Network for 5G Smart Tourism System

Lin

2022

Computational Intelligence and Neuroscience

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On the basis of the analysis of the evolution dynamics and the process of smart tourism service, this paper constructs the evolutionary game model of smart tourism service and reveals the evolution mechanism of smart tourism service based on the network platform. Based on the strategic main line of “advantages,” it proposes the design ideas and overall framework of the smart tourism service model based on the network platform, including the smart tourism information interactive service model, the element collaborative service model, and the value cocreation service model. The comparison of recommendation results shows that the recommendation error of the genetically improved generalized regression neural network algorithm is reduced, and the recommendation accuracy is better than that of the unimproved generalized regression neural network algorithm. In the recommendation scenario of click-through rate recommendation, the existing recommendation models are difficult to meet the functions of memory and generalization at the same time and cannot fully mine and combine low-level features, and the model parameters of the deep learning model are difficult to learn under the high-dimensional sparse data set of the recommendation system. To solve the problem of generalization, this paper proposes a deep CTR recommendation model based on the gradient boosting tree and factorization machine. It can fully mine low-level feature information and automatically realize low-level feature combination, which can better learn model parameters on high-dimensional sparse data sets, and the recommendation results are no longer overgeneralized. In this paper, simulation experiments are carried out on the data set, and the related recommendation models are compared. The experimental results show that the model proposed in this paper achieves better results in both the AUC (area under ROC curve) evaluation index and the cross-entropy evaluation index.

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On the Exploitation of 5G Multi-Access Edge Computing for Spatial Audio in Cultural Heritage Applications

Cited by 16 publications

References 35 publications

Musical Metaverse: vision, opportunities, and challenges

Musical Metaverse: vision, opportunities, and challenges

The Internet of Sounds: Convergent Trends, Insights, and Future Directions

Implementation of Personalized Scenic Spot Recommendation Algorithm Based on Generalized Regression Neural Network for 5G Smart Tourism System

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