Multi-Sensorial Human Perceptual Experience Model Identifier for Haptics Virtual Reality Services in Tactful Networking
The tactful networking paradigm is expected to play a crucial role in the next generation networks. Accordingly, adaptive human-aware environments, sensitive to the daily human behavior and individual traits have to be provided, in order to offer a fully immersive and customized experience to users....
Guardado en:
Autor principal: | |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
IEEE
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/c398521d6f134f2f8561a342d735b56d |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
id |
oai:doaj.org-article:c398521d6f134f2f8561a342d735b56d |
---|---|
record_format |
dspace |
spelling |
oai:doaj.org-article:c398521d6f134f2f8561a342d735b56d2021-11-18T00:10:16ZMulti-Sensorial Human Perceptual Experience Model Identifier for Haptics Virtual Reality Services in Tactful Networking2169-353610.1109/ACCESS.2021.3124607https://doaj.org/article/c398521d6f134f2f8561a342d735b56d2021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9597560/https://doaj.org/toc/2169-3536The tactful networking paradigm is expected to play a crucial role in the next generation networks. Accordingly, adaptive human-aware environments, sensitive to the daily human behavior and individual traits have to be provided, in order to offer a fully immersive and customized experience to users. On the basis of data collected by actual cognitive experiments, this paper proposes a learning framework to discover the multi-sensory human perceptual experience. The paper applies the mixture density network to identify the perception model considering different senses, and then the multi-sensory integration is performed, accordingly to the actual neuro-cognitive model. Furthermore, a supervised learning module has been used to cluster the users on the basis of the human perception identification strategy previously designed, assuming a multimodal structure for the cognitive brain activity. Finally, a practical contextualization is presented, in relation to the haptics virtual reality services. What emerges from the results is the effectiveness of the tactful approach, i.e., brain-aware, involving the proposed framework, which is validated in comparison to the more conventional brain-agnostic scheme. In fact, the system performance, expressed in terms of reliability in guaranteeing the service exploitation before a target deadline based on the integrated perception, reaches remarkable improvements applying the brain-aware strategy, which exploits the human perception knowledge.Benedetta PicanoIEEEarticleHuman-in-the-loopquality-of-experiencetactful networkingsupervised learningElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 147549-147558 (2021) |
institution |
DOAJ |
collection |
DOAJ |
language |
EN |
topic |
Human-in-the-loop quality-of-experience tactful networking supervised learning Electrical engineering. Electronics. Nuclear engineering TK1-9971 |
spellingShingle |
Human-in-the-loop quality-of-experience tactful networking supervised learning Electrical engineering. Electronics. Nuclear engineering TK1-9971 Benedetta Picano Multi-Sensorial Human Perceptual Experience Model Identifier for Haptics Virtual Reality Services in Tactful Networking |
description |
The tactful networking paradigm is expected to play a crucial role in the next generation networks. Accordingly, adaptive human-aware environments, sensitive to the daily human behavior and individual traits have to be provided, in order to offer a fully immersive and customized experience to users. On the basis of data collected by actual cognitive experiments, this paper proposes a learning framework to discover the multi-sensory human perceptual experience. The paper applies the mixture density network to identify the perception model considering different senses, and then the multi-sensory integration is performed, accordingly to the actual neuro-cognitive model. Furthermore, a supervised learning module has been used to cluster the users on the basis of the human perception identification strategy previously designed, assuming a multimodal structure for the cognitive brain activity. Finally, a practical contextualization is presented, in relation to the haptics virtual reality services. What emerges from the results is the effectiveness of the tactful approach, i.e., brain-aware, involving the proposed framework, which is validated in comparison to the more conventional brain-agnostic scheme. In fact, the system performance, expressed in terms of reliability in guaranteeing the service exploitation before a target deadline based on the integrated perception, reaches remarkable improvements applying the brain-aware strategy, which exploits the human perception knowledge. |
format |
article |
author |
Benedetta Picano |
author_facet |
Benedetta Picano |
author_sort |
Benedetta Picano |
title |
Multi-Sensorial Human Perceptual Experience Model Identifier for Haptics Virtual Reality Services in Tactful Networking |
title_short |
Multi-Sensorial Human Perceptual Experience Model Identifier for Haptics Virtual Reality Services in Tactful Networking |
title_full |
Multi-Sensorial Human Perceptual Experience Model Identifier for Haptics Virtual Reality Services in Tactful Networking |
title_fullStr |
Multi-Sensorial Human Perceptual Experience Model Identifier for Haptics Virtual Reality Services in Tactful Networking |
title_full_unstemmed |
Multi-Sensorial Human Perceptual Experience Model Identifier for Haptics Virtual Reality Services in Tactful Networking |
title_sort |
multi-sensorial human perceptual experience model identifier for haptics virtual reality services in tactful networking |
publisher |
IEEE |
publishDate |
2021 |
url |
https://doaj.org/article/c398521d6f134f2f8561a342d735b56d |
work_keys_str_mv |
AT benedettapicano multisensorialhumanperceptualexperiencemodelidentifierforhapticsvirtualrealityservicesintactfulnetworking |
_version_ |
1718425250432024576 |