Desempeño de los métodos de detección de señales con modulación QPSK en sistema GFDM para 5G
| dc.contributor.author | Verde, S. | |
| dc.contributor.author | Marcon, M. | |
| dc.contributor.author | Milani, S. | |
| dc.contributor.author | Tubaro, S. | |
| dc.date.accessioned | 2021-12-23T13:36:57Z | |
| dc.date.available | 2021-12-23T13:36:57Z | |
| dc.date.issued | 2020 | |
| dc.description.abstract | Internet of Things (IoT) applications play a relevant role in today's industry in sharing diagnostic data with off-site service teams, as well as in enabling reliable predictive maintenance systems. Several interventions scenarios, however, require the physical presence of a human operator: Augmented Reality (AR), together with a broad-band connection, represents a major opportunity to integrate diagnostic data with real-time in-situ acquisitions. Diagnostic information can be shared with remote specialists that are able to monitor and guide maintenance operations from a control room as if they were in place. Furthermore, integrating heterogeneous sensors with AR visualization displays could largely improve operators' safety in complex and dangerous industrial plants. In this paper, we present a complete setup for a remote assistive maintenance intervention based on 5G networking and tested at a Vodafone Base Transceiver Station (BTS) within the Vodafone 5G Program. Technicians' safety was improved by means of a lightweight AR Head-Mounted Display (HDM) equipped with a thermal camera and a depth sensor to foresee possible collisions with hot surfaces and dangerous objects, by leveraging the processing power of remote computing paired with the low latency of 5G connection. Field testing confirmed that the proposed approach can be a viable solution for egocentric environment understanding and enables an immersive integration of the obtained augmented data within the real scene. | en_ES |
| dc.identifier.citation | Verde, S., Marcon, M., Milani, S., & Tubaro, S. (2020). Advanced Assistive Maintenance Based on Augmented Reality and 5G Networking. En Sensors (Basel) (Vol. 20, Número 24). https://doi.org/10.3390/s20247157 | en_ES |
| dc.identifier.issn | 1424-8220 | |
| dc.identifier.uri | http://repositoriobibliotecas.uv.cl/handle/uvscl/3231 | |
| dc.language.iso | en_US | en_ES |
| dc.publisher | Sensors (Basel) | en_ES |
| dc.subject | 5G REAL-TIME NETWORKING | en_ES |
| dc.subject | ASSISTIVE MAINTENANCE | en_ES |
| dc.subject | AUGMENTED REALITY | en_ES |
| dc.subject | EDGE COMPUTER PROCESSING | en_ES |
| dc.title | Desempeño de los métodos de detección de señales con modulación QPSK en sistema GFDM para 5G | en_ES |
| dc.type | Articulo | en_ES |
| dc.ubicacion | https://doi.org/10.3390/s20247157 | en_ES |
| uv.catalogador | SGG | en_ES |
| uv.colection | Bibliografía 5G | en_ES |