Next Article in Journal
Tracking the Insider Attacker: A Blockchain Traceability System for Insider Threats
Previous Article in Journal
Towards an Ultra Sensitive Hybrid Mass Sensor Based on Mode Localization without Resonance Tracking
Open AccessArticle

A Heterogeneous Edge-Fog Environment Supporting Digital Twins for Remote Inspections

1
Department of Electrical Engineering, Federal University of Juiz de Fora, Juiz de Fora 36036-900, Brazil
2
Department of Computer Science, Federal University of Juiz de Fora, Juiz de Fora 36036-900, Brazil
3
Department of Electronics Engineering, Federal Center for Technological Education of Rio de Janeiro, Rio de Janeiro 20271-110, Brazil
4
Department of Electrical and Computer Engineering, Faculty of Engineering, Western University, London, ON N6G 1G8, Canada
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(18), 5296; https://doi.org/10.3390/s20185296
Received: 15 July 2020 / Revised: 7 September 2020 / Accepted: 8 September 2020 / Published: 16 September 2020
(This article belongs to the Section Internet of Things)
The increase in the development of digital twins brings several advantages to inspection and maintenance, but also new challenges. Digital models capable of representing real equipment for full remote inspection demand the synchronization, integration, and fusion of several sensors and methodologies such as stereo vision, monocular Simultaneous Localization and Mapping (SLAM), laser and RGB-D camera readings, texture analysis, filters, thermal, and multi-spectral images. This multidimensional information makes it possible to have a full understanding of given equipment, enabling remote diagnosis. To solve this problem, the present work uses an edge-fog-cloud architecture running over a publisher-subscriber communication framework to optimize the computational costs and throughput. In this approach, each process is embedded in an edge node responsible for prepossessing a given amount of data that optimizes the trade-off of processing capabilities and throughput delays. All information is integrated with different levels of fog nodes and a cloud server to maximize performance. To demonstrate this proposal, a real-time 3D reconstruction problem using moving cameras is shown. In this scenario, a stereo and RDB-D cameras run over edge nodes, filtering, and prepossessing the initial data. Furthermore, the point cloud and image registration, odometry, and filtering run over fog clusters. A cloud server is responsible for texturing and processing the final results. This approach enables us to optimize the time lag between data acquisition and operator visualization, and it is easily scalable if new sensors and algorithms must be added. The experimental results will demonstrate precision by comparing the results with ground-truth data, scalability by adding further readings and performance. View Full-Text
Keywords: fog-edge computing; distribuited 3D reconstruction; heterogeneous environment; digital twins; remote inspection fog-edge computing; distribuited 3D reconstruction; heterogeneous environment; digital twins; remote inspection
Show Figures

Figure 1

MDPI and ACS Style

Silva, L.A.Z.; Vidal, V.F.; Honório, L.M.; Dantas, M.A.R.; Pinto, M.F.; Capretz, M. A Heterogeneous Edge-Fog Environment Supporting Digital Twins for Remote Inspections. Sensors 2020, 20, 5296.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop