Eco-sensitive site assessment: Integrating neural networks for environmentally conscious pre-project planning

The use of neural networks in the architectural design pre-phase is becoming increasingly prevalent among designers. This article presents a method of textual and graphical analysis of construction sites using neural networks. On the example of two projects, which won the architectural competition,...

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Main Authors: Zatsepina Aleksandra, Bardina Galina, Shindina Polina
Format: Article
Language:English
Published: EDP Sciences 2025-01-01
Series:E3S Web of Conferences
Online Access:https://www.e3s-conferences.org/articles/e3sconf/pdf/2025/14/e3sconf_icaw2024_05003.pdf
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author Zatsepina Aleksandra
Bardina Galina
Shindina Polina
author_facet Zatsepina Aleksandra
Bardina Galina
Shindina Polina
author_sort Zatsepina Aleksandra
collection DOAJ
description The use of neural networks in the architectural design pre-phase is becoming increasingly prevalent among designers. This article presents a method of textual and graphical analysis of construction sites using neural networks. On the example of two projects, which won the architectural competition, the following are considered: qualitative characteristics analysis of the territory using Autodesk Forma software, cultural context analysis using ChatGPT, image generation using MidJourney and 3D-models generation using the neural network Meshy.ai. In regard to ChatGPT, the "risks" method is presented as a means of achieving optimal results. The possibility of factual errors in ChatGPT text generations is indicated.
format Article
id doaj-art-97c18093ad6c45eba2a6c8d72fe41fa1
institution OA Journals
issn 2267-1242
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publishDate 2025-01-01
publisher EDP Sciences
record_format Article
series E3S Web of Conferences
spelling doaj-art-97c18093ad6c45eba2a6c8d72fe41fa12025-08-20T02:13:51ZengEDP SciencesE3S Web of Conferences2267-12422025-01-016140500310.1051/e3sconf/202561405003e3sconf_icaw2024_05003Eco-sensitive site assessment: Integrating neural networks for environmentally conscious pre-project planningZatsepina Aleksandra0Bardina Galina1Shindina Polina2Peter the Great St. Petersburg Polytechnic UniversityPeter the Great St. Petersburg Polytechnic UniversityPeter the Great St. Petersburg Polytechnic UniversityThe use of neural networks in the architectural design pre-phase is becoming increasingly prevalent among designers. This article presents a method of textual and graphical analysis of construction sites using neural networks. On the example of two projects, which won the architectural competition, the following are considered: qualitative characteristics analysis of the territory using Autodesk Forma software, cultural context analysis using ChatGPT, image generation using MidJourney and 3D-models generation using the neural network Meshy.ai. In regard to ChatGPT, the "risks" method is presented as a means of achieving optimal results. The possibility of factual errors in ChatGPT text generations is indicated.https://www.e3s-conferences.org/articles/e3sconf/pdf/2025/14/e3sconf_icaw2024_05003.pdf
spellingShingle Zatsepina Aleksandra
Bardina Galina
Shindina Polina
Eco-sensitive site assessment: Integrating neural networks for environmentally conscious pre-project planning
E3S Web of Conferences
title Eco-sensitive site assessment: Integrating neural networks for environmentally conscious pre-project planning
title_full Eco-sensitive site assessment: Integrating neural networks for environmentally conscious pre-project planning
title_fullStr Eco-sensitive site assessment: Integrating neural networks for environmentally conscious pre-project planning
title_full_unstemmed Eco-sensitive site assessment: Integrating neural networks for environmentally conscious pre-project planning
title_short Eco-sensitive site assessment: Integrating neural networks for environmentally conscious pre-project planning
title_sort eco sensitive site assessment integrating neural networks for environmentally conscious pre project planning
url https://www.e3s-conferences.org/articles/e3sconf/pdf/2025/14/e3sconf_icaw2024_05003.pdf
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AT bardinagalina ecosensitivesiteassessmentintegratingneuralnetworksforenvironmentallyconsciouspreprojectplanning
AT shindinapolina ecosensitivesiteassessmentintegratingneuralnetworksforenvironmentallyconsciouspreprojectplanning