Image-based construction of building energy models using computer vision

Dino, İpek Gürsel; Sari, Alp Eren; Iseri, Orcun Koral; Akin, Sahin; Kalfaoglu, M. Esat; Erdogan, Bilge; Kalkan, Sinan; Alatan, A. Aydın

doi:10.1016/j.autcon.2020.103231

Cited by 37 publications

(16 citation statements)

References 51 publications

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“…Some research [44] [45] achieved promising results related to building form and envelope design in the function of incident solar radiation and thermal performance. Furthermore, the benefits of the implementation of advanced computational approaches in this field are confirmed by the work of Dino et al [46] where they are used to develop an image-based 3D reconstruction pipeline for the semi-automated generation of 3D models and to build energy models. Other studies [47][48] [49] showed the feasibility of optimisation processes for design, prefabrication and assembly of building components and systems comprising the use of construction robots [50].…”

Section: Computational Design For Aec Processes Automationmentioning

confidence: 91%

On-demand generation of as-built infrastructure information models for mechanised Tunnelling from TBM data: A computational design approach

Getuli

Capone

Bruttini

et al. 2021

Automation in Construction

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When dealing with complex curved geometries and massive datasets linked to linear infrastructures, manual generation and maintenance of related multidisciplinary BIM models and documentation are yet to be fully automated. This research focused on the integration of BIM and computational design into an intuitive approach for the generation of as-built models of mechanised tunnelling projects, leveraging the use of the real-time data collected by TBM. A preliminary study of the parameters was conducted to describe the curved geometry of the tunnel, then their mutual alignment was followed by the identification of additional relevant information. To automate the tunnel's BIM-based modelling process, a system of four coupled algorithms was developed and tested with a sample TBM dataset. The results demonstrate how the adoption of computational design methods drastically enhances the modelling process for infrastructure projects, allowing for the on-demand generation of as-built BIM models, reducing time and errors.

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Section: Computational Design For Aec Processes Automationmentioning

confidence: 91%

On-demand generation of as-built infrastructure information models for mechanised Tunnelling from TBM data: A computational design approach

Getuli

Capone

Bruttini

et al. 2021

Automation in Construction

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show abstract

“…For example, great contributions have made by synthesizing UBEM tools and Geographic Information System (GIS) techniques to capture geometric information of buildings [22,24,26,27]. Drones [28], sensors [29], computer vision techniques [30], and other opensource datasets [31] are employed to obtain building properties. However, some building characteristics such as building shapes, thermal properties and interactions are challenging to simulate, which can significantly affect building shading, urban heat islands, and wind flow, then further directly or indirectly influence building energy consumption.…”

Section: Literture Reviewmentioning

confidence: 99%

Times series forecasting for urban building energy consumption based on graph convolutional network

Cheng

Wang

et al. 2022

Applied Energy

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“…There are several works that investigate the heat loss and similar relevant parameters in the context of building applications. Dino et al (2020) create 3D thermograms by overlaying thermal information on 3D models obtained using structure-from-motion approaches (which results in sparse point clouds). Typical parameters such as the conductive heat loss or the introduced heating energy are calculated for the considered indoor spaces.…”

Section: Related Workmentioning

confidence: 99%

Method and experimental investigation of surface heat dissipation measurement using 3D thermography

Schmoll

Schramm

Breitenstein

et al. 2022

J. Sens. Sens. Syst.

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Abstract. Three-dimensional thermography describes the fusion of geometry- and temperature-related sensor data. In the resulting 3D thermogram, thermal and spatial information of the measured object is available in one single model. Besides the simplified visualization of measurement results, the question arises how the additional data can be used to get further information. In this work, the Supplement information is used to calculate the surface heat dissipation caused by thermal radiation and natural convection. For this purpose, a 3D thermography system is presented, the calculation of the heat dissipation is described, and the first results for simply shaped measurement objects are presented.

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Image-based construction of building energy models using computer vision

Cited by 37 publications

References 51 publications

On-demand generation of as-built infrastructure information models for mechanised Tunnelling from TBM data: A computational design approach

On-demand generation of as-built infrastructure information models for mechanised Tunnelling from TBM data: A computational design approach

Times series forecasting for urban building energy consumption based on graph convolutional network

Method and experimental investigation of surface heat dissipation measurement using 3D thermography

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