AI-BIM Interdisciplinary Spill-Overs: Prospected Interplay of AI and BIM Development Paradigms

Ceccon, Lorenzo; Villa, Daniele

doi:10.1007/978-3-030-49278-6_12

Cited by 8 publications

(11 citation statements)

References 11 publications

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“…Methods including laser scanners and digital photogrammetry, BIM modeling, IoT sensors, all produce data that may be shareable through Cloud-based solutions. Although, still the industry seems to lack a coordinated effort to identify new streamlined workflow paradigms whereby the entire process, creating and managing the BIM model, would form a comprehensive tool [3]. In any case, data will be also at the center of the new technologies been incorporated, transforming also the AEC industry towards a complex ecosystem where DATA will be another valuable construction material with the less hard division between classical constructive processes and digital realm applications [3].…”

Section: ) Applications and Areas Of Developmentsmentioning

confidence: 99%

“…Although, still the industry seems to lack a coordinated effort to identify new streamlined workflow paradigms whereby the entire process, creating and managing the BIM model, would form a comprehensive tool [3]. In any case, data will be also at the center of the new technologies been incorporated, transforming also the AEC industry towards a complex ecosystem where DATA will be another valuable construction material with the less hard division between classical constructive processes and digital realm applications [3]. Around 42000 records were found related to AEC and AI industry [2], which makes desirable complementary methods to get more granular information on the contents of the articles.…”

Section: ) Applications and Areas Of Developmentsmentioning

confidence: 99%

“…The architecture, Engineering, and Construction (AEC) industry is speeding up in adopting the latest technological advances in the Artificial Intelligence (AI) and Internet of Things (IoT) ecosystems [1]- [3]. Applications of AI in the AEC industry (AEC-AI) have been developing from the early 70s in the last century, experimenting a substantial speed-up in the last 10 years [2].…”

Section: Introductionmentioning

confidence: 99%

“…Communication and Information Technologies (CIT) will boost and reshape the industry in almost every aspect: from Edge Computing to 5G and blockchain technologies processes and operations will be substantially transformed. The results will be a migration towards an ever more important role of data generation, analysis, and integration [3], [4]. AI optimization will reach the more complex areas in the AEC industry, and robotic automation promise to recapture interest in an increasingly more sophisticated workforce along with new skills and talents emerging in the technological sectors [5].…”

Section: Introductionmentioning

confidence: 99%

“…Several recent reviews and special issues conferences have addressed the state-of-the-art in Artificial Intelligence (AI) in the Architecture Engineering and Construction (AEC) Industry [1]- [3], [8]- [11]. Despite several efforts to advance in a systematic understanding of the mixture and interactions between the different processes been addressed by AIalgorithms and how they work in the AEC industry.…”

Section: Introductionmentioning

confidence: 99%

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Towards an AEC-AI Industry Optimization Algorithmic Knowledge Mapping: An Adaptive Methodology for Macroscopic Conceptual Analysis

Maureira¹,

Pinto

Yepes³

et al. 2021

IEEE Access

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The Architecture, Engineering, and Construction (AEC) Industry is one of the most important productive sectors, hence also produce a high impact on the economic balances, societal stability, and global challenges in climate change. Regarding its adoption of technologies, applications and processes is also recognized by its status-quo, its slow innovation pace, and the conservative approaches. However, a new technological era -Industry 4.0 fueled by AI-is driving productive sectors in a highly pressurized global technological competition and sociopolitical landscape. In this paper, we develop an adaptive approach to mining text content in the literature research corpus related to the AEC and AI (AEC-AI) industries, in particular on its relation to technological processes and applications. We present a first stage approach to an adaptive assessment of AI algorithms, to form an integrative AI platform in the AEC industry, the AEC-AI industry 4.0. At this stage, a macroscopic adaptive method is deployed to characterize "Optimization", a key term in AEC-AI industry, using a mixed methodology incorporating machine learning and classical evaluation process. Our results show that effective use of metadata, constrained search queries, and domain knowledge allows getting a macroscopic assessment of the target concept. This allows the extraction of a high-level mapping and conceptual structure characterization of the literature corpus. The results are comparable, at this level, to classical methodologies for the literature review. In addition, our method is designed for an adaptive assessment to incorporate further stages.

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Section: ) Applications and Areas Of Developmentsmentioning

confidence: 99%