An IIoT Edge Environment as a Main Support to a 3D Reconstruction Virtualization Application
This paper describes an experimental research work, which was conducted to gather different types of cameras and computer node, as IIoT (Industrial IoT) devices, to produce support to a digital transformation with a 3D reconstruction virtualization for a real engineering application. The computational approach considered was a heterogeneous edge computing environment. In this environment, different cameras and computer node architectures, collaborate as heterogeneous IIoT processing elements, to provide a better, and as fast as possible, images to a virtualization project. The challenge and complexity related to software packages orchestration, from these IIoT devices, are also reported.
D. Shcherbinin, “Virtual reconstruction and 3d visualization of vostok space- craftequipment,” in Engineering Technologies and Computer Science (EnT), 2017International Workshop on, pp. 56-58, IEEE, 2017.
Dantas, M.A.R., Bogoni, P.E. and Filho, P.J.d.F. (2020) “An application study casetradeoff between throughput and latency on fog-cloud cooperation”, Int. J.Networking and Virtual Organisations, Vol. 23, No. 3, pp.247-260.
Decamps at al., A Heterogenous Edge Computing Platform Case Study Supporting aVirtual Scenario Application, submitted to ISCC 2020, 2020
DuoMC, https://duo3d.com/product/duo-me-lv1, accessed in February 2020.
Eduardo Camilo Inácio, Jorji Nonaka, Kenji Ono, Mario A. R. Dantas, FumiyoshiShoji: Characterizing I/O and Storage Activity on the K Computer for Post-Processing Purposes. ISCC 2018: 730-735.
Gopika Premsankar Mario Di Francesco Tarik Taleb, "Edge Computing for theInternet of Things: A Case Study", IEEE Internet of Things Journal , vol. 5, Issue: 2,pp 1275 — 1284, April 2018.
Grin, https://www ufjf.br/inerge/institucional/laboratorios/grin/, accessed in February2020.
H. Qing, “Research and application of virtual reality technology in mechanicalmaintenance,” in International Conference on Advanced Technology of Design andManufacture (ATDM 2010), p. 256 — 258, IET, 2010.
Hydropower, https://www hydropower.org/country-profiles/brazil, accessed in 2020.
Inerge, https://www ufjf.br/inerge/, accessed in February 2020.
Jan Erik Solem. Programming Computer Vision with Python. O'Reilly, O'Reilly Media,Inc.,1005 Gravenstein Highway North, Sebastopol, CA 95472, 2012.
Jetson, https://developer.nvidia.com/embedded/jetson-tx2, accessed in February 2020.
Jetson Hacks, JetsonHacks.com, accessed in February 2020.
Kaur, Kuljeet, et al. "Edge computing in the industrial internet of things environment:Software-defined-networks-based edge-cloud interplay." IEEE communicationsmagazine 56.2 (2018): 44-51.
L. Silva, V. Vidal, M. Silva, M. Santos, A. Carvalho, A. Cerqueira, L. Honório, H.Rezende, J. Ribeiro, A. Pancoti, et al., “Automatic recognition of electrical gridelements using convolutional neural networks,” in 2018 22nd InternationalConference on System Theory, Control and Computing (ICSTCC), pp. 822-826,TEEE, 2018.
NenC, http://www .ufjf.br/nenc/, accessed in Februry 2020.
Pointclouds, http://pointclouds.org, a: sed in February 2020.
RC Motta, KM de Oliveira, GH Travassos, “On challenges in engineering JoT softwaresystems "SBES '18: Proceedings of the XXXII Brazilian Symposium on SoftwareEngineering Pages 42-51, September 2018.
ROS, http://www ros.org/, accessed in February 2020.
Sabella, Dario, et al. "Developing software for multi-access edge computing." ETSI(2019).
Silva, Luiz Augusto Zillmann, Reconstruction with multiple cameras and distributedsystem under the fog paradigm, Msc Dissertation, Electrical EngineeringDepartment, UFJF, https://www.ufjf.br/ppee/20 19/02/21 /defesa-de-dissertacao-de-mestrado-luiz-augusto-zillmann-da-silva/, 2019.
Schonberger, J. L., Frahm J.-M., “Structure-from-motion revisited,” in Proceedings ofthe IEEE Conference on Computer Vision and Pattern Recognition, pp. 4104-4113,2016.
Stumberg, L. von, V. Usenko, J. Engel, J. Stickler, and D. Cremers, “From monocularslam to autonomous drone exploration,” in Mobile Robots (ECMR), 2017 EuropeanConference on, pp. 1-8, IEEE, 2017.
T. Masood and J. Egger. Augmented reality in support of industry 4.0 — implementation challenges and success factors. Robotics and Computer Integrated Manufacturing,58:181. 195, 2019.
tf, http:/Awiki.ros.org/tf, accessed in March 2020.
Thomas, Lucia Agnes Beena. "Edge Cloud: The Future Technology for Internet ofThings." Novel Practices and Trends in Grid and Cloud Computing. IGI Global,2019. 107-131.
Whelan T., M. Kaess, H. Johannsson, M. Fallon, J. J. Leonard, and J. McDonald, “Real-time large-scale dense rgb-d slam with volumetric fusion,” The International Journalof Robotics Research, vol. 34, no. 4-5, pp. 598-626, 2015.