PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

UrbanGraphica: Digital Twin for Estimation of Public Spaces Quality

Treść / Zawartość
Identyfikatory
Warianty tytułu
PL
UrbanGraphica: Cyfrowy bliźniak do szacowania jakości przestrzeni publicznych
Konferencja
9th World Multidisciplinary Congress on Civil Engineering, Architecture, and Urban Planning - WMCCAU 2024 : 2-6.09.2024
Języki publikacji
EN
Abstrakty
EN
The paper describes methods and process of creating a digital twin of the city on case study of Bratislava called UrbanGraphica. The process is divided into three stages. First stage includes collection of data and modelling of the digital model of the city. The second stage integrates a wide range of information layers from various sources into the model. These collected information layers include data on traffic, vegetation, noise, solar irradiation, shadows, key viewpoints and temperature. In the third stage, these diverse datasets are overlaid to enable a comprehensive scoring system aimed at quantitatively assessing the quality of public spaces. Subsequential validation of this quantitative assessment is based on the comparison with maps of public sentiment, which were obtained from city inhabitants through questionnaires available as open data. This comparative analysis may reveal correlations between the physical and social parameters of the city. Furthermore, these integrated datasets enable the development of advanced machine learning models capable of predicting the popularity of public spaces based on their measurable characteristics. These predictive models are possible to be used to evaluate and refine the design of future public spaces during the planning stages, thereby improving decision-making processes. Additionally, the created digital twin is also utilized for estimating the potential for solar and wind energy production and utilization, thus supporting sustainable development goals of the city. The created digital twin was already published as physical model and as online digital model. Collected data from various sources into one platform provides more comprehensive image of the city. Moreover, utilization of data analytics and machine learning leads to more responsive and sustainable urban environments, contributing to the wellbeing of the city inhabitants
PL
W artykule opisano metody i proces tworzenia cyfrowego bliźniaka miasta na przykładzie Bratysławy o nazwie UrbanGraphica. Proces jest podzielony na trzy etapy. Pierwszy etap obejmuje gromadzenie danych i modelowanie cyfrowego modelu miasta. Drugi etap integruje szeroki zakres warstw informacyjnych z różnych źródeł w modelu. Te zebrane informacje obejmują dane o ruchu drogowym, roślinności, hałasie, promieniowaniu słonecznym, cieniach, kluczowych punktach widokowych i temperaturze. W trzecim etapie, te różnorodne zbiory danych są nakładane na siebie, aby umożliwić kompleksowy system punktacji mający na celu ilościową ocenę jakości przestrzeni publicznych. Późniejsza walidacja tej oceny ilościowej opiera się na porównaniu z mapami nastrojów społecznych, które uzyskano od mieszkańców miasta. Ta analiza porównawcza może ujawnić korelacje między fizycznymi i społecznymi parametrami miasta. Ponadto te zintegrowane zbiory danych umożliwiają rozwój zaawansowanych modeli uczenia maszynowego zdolnych do przewidywania popularności przestrzeni publicznych na podstawie ich mierzalnych cech. Te modele predykcyjne mogą być wykorzystywane do oceny i udoskonalania projektów przyszłych przestrzeni publicznych na etapach planowania, usprawniając w ten sposób procesy decyzyjne. Dodatkowo, stworzony cyfrowy bliźniak jest również wykorzystywany do szacowania potencjału produkcji i wykorzystania energii słonecznej i wiatrowej, wspierając w ten sposób cele zrównoważonego rozwoju miasta.
Rocznik
Strony
art. no. 67
Opis fizyczny
Bibliogr. 28 poz., zdj.
Twórcy
  • Slovak University of Technology, Faculty of Architecture and Design, Námestie slobody 19, 812 45 Bratislava, Slovakia
  • Slovak University of Technology, Faculty of Architecture and Design, Námestie slobody 19, 812 45 Bratislava, Slovakia
  • Slovak University of Technology, Faculty of Architecture and Design, Námestie slobody 19, 812 45 Bratislava, Slovakia
Bibliografia
  • 1. United Nations, Department of Economic and Social Affairs, World Population Prospects 2022, Available online at: un.org/development/desa/pd/sites/www.un.org.development.desa.pd/files/wpp2022_summary_of_results.pdf (accessed 25th of July 2024)
  • 2. United Nations General Assembly, Transforming our World: The 2030 Agenda for Sustainable Development. Resolution Adopted by the General Assembly on 25 September 2015. Available online at: sdgs.un.org/2030agenda (accessed 25th of July 2024).
  • 3. World Health Organization, Sustainable development agenda. Available online at: https://www.who.int/healthtopics/sustainable-development#tab=tab_1 (accessed 25th of July 2024).
  • 4. World Health Organization, Urban Health Initiative. Available online at: who.int/initiatives/urban-health-initiative (accessed 25th of July 2024).
  • 5. European Commission, Communication from the Commission the European Green Deal, 2019. Available online at: eur-lex.europa.eu/legal-content/EN/TXT/?qid=1576150542719&uri=COM%3A2019%3A640%3AFIN (accessed 25th of July 2024).
  • 6. European Parliament, Resolution on the climate and environment emergency. 2019. Available online at: oeil.secure.europarl.europa.eu/oeil/popups/ficheprocedure.do?lang=en&reference=2019/2930(RSP) (accessed 25th of July 2024).
  • 7. European Commission, EU Adaptation Strategy. 2021 Available online at : climate.ec.europa.eu/euaction/adaptation-climate-change/eu-adaptation-strategy_en (accessed 25th of July 2024).
  • 8. Abbas S., Ali Tarlani B., Amir S. J., Mohammadsadegh N., Ahmad G. L., Mohsen A., “Application of artificial intelligence in digital twin models for stormwater infrastructure systems in smart cities.”, Advanced Engineering Informatics 61, 102485, (2024). ISSN 1474-0346, doi.org/10.1016/j.aei.2024.102485
  • 9. Francisco, A., Mohammadi, N. and Taylor, J. E., “Smart city digital twin-enabled energy management: toward realtime urban building energy benchmarking.”, J. Manag. Eng. 36, 2, (2019). doi.org/10.1061/(ASCE)ME.1943-5479.0000741
  • 10. Lee, G., Choi, B., Ahn, C. R. & Lee, S. “Wearable biosensor and hotspot analysis-based framework to detect stress hotspots for advancing elderly’s mobility.”, J. Manag. Eng. 36, 1-13, (2020).
  • 11. Lin, Y. and Cheung, W. “Developing WSN/BIM-based environmental monitoring management system for parking garages in smart cities.” J. Manag. Eng. 36, 3, (2020). doi.org/10.1061/(ASCE)ME.1943-5479.0000760
  • 12. Nováček, O., “Open planning: Qualification of urban space parameters from end user’s perspective.” ALFA 11, 3, (2020). Available online at: alfa.stuba.sk/wp-content/uploads/2020/11/03_2020_Novacek-1.pdf ISSN 2729-7640 (accessed 25th of July 2024).
  • 13. Francisco, A., Mohammadi, N. and Taylor, J. E., “Smart city digital twin-enabled energy management: toward realtime urban building energy benchmarking.” J. Manag. Eng. 36, 2, (2019) https://doi.org/10.1061/(ASCE)ME.1943-5479.0000741
  • 14. Lu, Q., Parlikad, A. K., Woodall, P., Ranasinghe, G. D., Heaton, J., “Developing a Dynamic Digital Twin at a Building Level: using Cambridge Campus as Case Study.” International Conference on Smart Infrastructure and Construction 2019 (ICSIC) 36, pp 67–75, (2019) doi.org/10.17863/CAM.38523
  • 15. Petrova-Antonova, D. and Ilieva, S., “Digital Twin Modeling of Smart Cities. Human Interaction, Emerging Technologies and Future Applications III”, in Human Interaction, Emerging Technologies and Future Applications III, Proceedings of the 3rd International Conference on Human Interaction and Emerging Technologies: Future Applications (IHIET 2020), edited by T. Ahram et al. (Springer Cham, 2020), pp 384–390
  • 16. ArcGIS, Use deep learning for feature extraction and classification. Available online at: doc.arcgis.com/en/imagery/workflows/resources/using-deep-learning-for-feature-extraction.htm (accessed 25th of July 2024).
  • 17. Pan, X., Mavrokapnidis, D., Ly, H.T. et al. “Assessing and forecasting collective urban heat exposure with smart city digital twins.”, Sci Rep 14, 9653, (2024). doi.org/10.1038/s41598-024-59228-8
  • 18. Eurosense, LiDAR measurements. Available online at: www.eurosense.com/products#Aerial-imagery (accessed 25th of July 2024).
  • 19. Geodesy, Cartography and Cadastre Authority of the Slovak Republic, Airborne Laser Scanning. Available online at: www.geoportal.sk/en/zbgis/als/ (accessed 25th of July 2024).
  • 20. Magistrát hlavného mesta SR Bratislavy, Pasport dopravného priestoru, sekcia spŕavy a údržby ciest. Available online at: arcgis.com/apps/webappviewer/index.html?id=8cc33b2da2af47388552ffc9b34eb5be&extent=1894172.0857%2C6120909.1104%2C1923218.1565%2C6136884.4493%2C102100 (accessed 25th of July 2024).
  • 21. United States Geological Survey, EarthExplorer. Available online at: earthexplorer.usgs.gov/ (accessed 25th of July 2024).
  • 22. Onačillová, K., Gallay, M., Paluba, D., Péliová, A., Tokarčík, O. and Laubertová, D. “Combining Landsat 8 and Sentinel-2 Data in Google Earth Engine to Derive Higher Resolution Land Surface Temperature Maps in Urban Environment.”, Remote Sens. 14, 4076. (2022). https://doi.org/10.3390/rs14164076
  • 23. Slovak hydrometeorological institute. Near real time data of selected station network. Available online at: www.shmu.sk/sk/?page=1&id=klimat_operativneudaje1&identif=11816&rok=2023&obdobie=1991-2020&sub=1 (accessed 25th of July 2024).
  • 24. Hofierka, J., Šúri, M., “The solar radiation model for Open source GIS. ” in Proceedings of the Open Source GISGRASS Users Conference., edited by M. Ciolli (University of Trento, Trento, 2002), Available online at: www.researchgate.net/publication/2539232_The_solar_radiation_model_for_Open_source_GIS_Implementation_and_applications (accessed 25th of July 2024).
  • 25. Hlavné mesto SR Bratislava and Euroakustik. Strategická hluková mapa. Available online at: cdnapi.bratislava.sk/strapi-homepage/upload/SHM_2021_2e5926a0c9.pdf (accessed 25th of July 2024).
  • 26. Implementačná jednotka Magistrátu hl. Mesta SR Bratislavy, Donauer, E. Open Data Bratislava: Pocitová mapa Bratislavy. Available online at: http://90.176.20.233/dataset/show/pocitova-mapa-bratislavy (accessed 25th of July 2024).
  • 27. Hajtmanek, R. UrbanGraphica available online at: urbangraphica.mixedrealityarchitecture.eu/ (accessed 25th of July 2024).
  • 28. Murray, Ch. “First life, then spaces, then buildings. The other way around never works.” Available online at: thedeveloper.live/podcasts/podcasts/first-life-then-spaces-then-buildings-the-other-way-around-never-works- (accessed 25th of July 2024).
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki i promocja sportu (2025).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-48a19b13-675e-4e4f-91db-8b52cc3aa629
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.