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A framework to integrate multi-sensors data with building information modeling to support historic assets conservation and management

Grant number: 16/04991-0
Support type:Research Grants - eScience and Data Science Program - Regular Program Grants
Duration: March 01, 2017 - February 28, 2019
Field of knowledge:Interdisciplinary Subjects
Principal Investigator:Eloisa Dezen-Kempter
Grantee:Eloisa Dezen-Kempter
Home Institution: Faculdade de Tecnologia (FT). Universidade Estadual de Campinas (UNICAMP). Limeira , SP, Brazil
Assoc. researchers: Alex Soria Medina ; Marco Antonio Garcia de Carvalho
Associated scholarship(s):17/02787-9 - A framework to integrate multi-sensors data with building information modeling to support historic assets conservation and management, BP.MS


This Research Project is submitted by State University of Campinas (Limeira, SP, BR) in collaboration with Federal University of Parana (Curitiba, PR, BR) and University of Southern California (Los Angeles, CA, US) to develop and disseminate a new digital inventory model for historical assets. The research question being addressed: How can historical asset be benefited from Information and Communication Technologies (ICT) in order to leverage the process of their maintenance, conservation and restoration? The hypothesis that a new inventory model, based on ICT to create a comprehensive digital data repository (CDR) for historical assets, can provide a better basis for the process of data management related to the historical building, in order to improve its performance, functionality and quality, will be tested and its potential fully explored. The project has the potential to analyze existing tools for collecting spatial data on site; to develop tools and software to automate object recognition in images and point clouds generated by the capture process, as well as to process the fusion of images and point clouds. Finally, promote the automation for the creation of a 3D semantically enriched representation of the building based on Building Information Modeling (BIM) technology. The projects activities are to: (1) propose a novel framework using reverse engineering (through visual remote sensing technologies for accurate detection of geometrical features) for generating as-is 3D models; (2) improve the registration of scanned data sets; (3) propose an optimization algorithm to integrate hybrid surveying technologies; (4) automate object recognition to extract the features of interest using the captured data, in order to create the 3D BIM model. The project will advance understanding of ICT applied to historical assets conservation and restoration while promoting optimization of the reverse engineering process to create information rich 3D models of the as-is conditions of buildings, which are the CDR core. (AU)

Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
PAIVA, PEDRO V. V.; COGIMA, CAMILA K.; DEZEN-KEMPTER, ELOISA; CARVALHO, MARCO A. G. Historical building point cloud segmentation combining hierarchical watershed transform and curvature analysis. PATTERN RECOGNITION LETTERS, v. 135, p. 114-121, JUL 2020. Web of Science Citations: 0.

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