Machine Learning and Artificial Intelligence for Smart Visualization, Presentation, and Study of Architecture and Engineering in the Urban Environment

Author:

Giordano Andrea1ORCID,Huffman Kristin Love2,Bernardello Rachele Angela3,Perticarini Maurizio4,Basso Alessandro5ORCID

Affiliation:

1. University of Padova, Italy

2. Duke University, USA

3. University of Padua, Italy

4. Università degli Studi Luigi Vanvitelli, Italy

5. University of Camerino, Italy

Abstract

This research experiments the theme of cultural heritage (CH) in architectural/engineering fields, located in urban space. Primary sources and new tactics for digital reconstruction allow interactive contextualization-access to often inaccessible data creating pedagogical apps for spreading. Digital efforts are central, in recent years based on new technological opportunities that emerged from big data, Semantic Web technologies, and exponential growth of data accessible through digital libraries – EUROPEANA. Also, the use of data-based BIM allowed the gaining of high-level semantic concepts. Then, interdisciplinary collaborations between ICT and humanities disciplines are crucial for the advance of workflows that allow research on CH to exploit machine learning approaches. This chapter traces the visualizing cities progress, involving Duke and Padua University. This initiative embraces the analysis of urban systems to reveal with diverse methods how documentation/understanding of cultural sites complexities is part of a multimedia process that includes digital visualization of CH.

Publisher

IGI Global

Reference37 articles.

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4. Andrianaivo, L. N., D’Autilia, R. & Palma, V. (2019). Architecture recognition by means of convolutional neural networks. ISPRS Arch. XLII-2-W15, 77-84

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