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Digital Twin Simulation Tools, Spatial Cognition Algorithms, and Multi-Sensor Fusion Technology in Sustainable Urban Governance Networks

Author

Listed:
  • Elvira Nica

    (Department of Administration and Public Management, The Bucharest University of Economic Studies, 010371 Bucharest, Romania)

  • Gheorghe H. Popescu

    (Department of Finance and Banking, Dimitrie Cantemir Christian University, 030134 Bucharest, Romania)

  • Milos Poliak

    (Faculty of Operation and Economics of Transport and Communications, University of Zilina, Univerzitna 1, 01026 Zilina, Slovakia)

  • Tomas Kliestik

    (Faculty of Operation and Economics of Transport and Communications, University of Zilina, Univerzitna 1, 01026 Zilina, Slovakia)

  • Oana-Matilda Sabie

    (Department of Administration and Public Management, The Bucharest University of Economic Studies, 010371 Bucharest, Romania)

Abstract

Relevant research has investigated how predictive modeling algorithms, deep-learning-based sensing technologies, and big urban data configure immersive hyperconnected virtual spaces in digital twin cities: digital twin modeling tools, monitoring and sensing technologies, and Internet-of-Things-based decision support systems articulate big-data-driven urban geopolitics. This systematic review aims to inspect the recently published literature on digital twin simulation tools, spatial cognition algorithms, and multi-sensor fusion technology in sustainable urban governance networks. We integrate research developing on how blockchain-based digital twins, smart infrastructure sensors, and real-time Internet of Things data assist urban computing technologies. The research problems are whether: data-driven smart sustainable urbanism requires visual recognition tools, monitoring and sensing technologies, and simulation-based digital twins; deep-learning-based sensing technologies, spatial cognition algorithms, and environment perception mechanisms configure digital twin cities; and digital twin simulation modeling, deep-learning-based sensing technologies, and urban data fusion optimize Internet-of-Things-based smart city environments. Our analyses particularly prove that virtual navigation tools, geospatial mapping technologies, and Internet of Things connected sensors enable smart urban governance. Digital twin simulation, data visualization tools, and ambient sound recognition software configure sustainable urban governance networks. Virtual simulation algorithms, deep learning neural network architectures, and cyber-physical cognitive systems articulate networked smart cities. Throughout January and March 2023, a quantitative literature review was carried out across the ProQuest, Scopus, and Web of Science databases, with search terms comprising “sustainable urban governance networks” + “digital twin simulation tools”, “spatial cognition algorithms”, and “multi-sensor fusion technology”. A Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) flow diagram was generated using a Shiny App. AXIS (Appraisal tool for Cross-Sectional Studies), Dedoose, MMAT (Mixed Methods Appraisal Tool), and the Systematic Review Data Repository (SRDR) were used to assess the quality of the identified scholarly sources. Dimensions and VOSviewer were employed for bibliometric mapping through spatial and data layout algorithms. The findings gathered from our analyses clarify that Internet-of-Things-based smart city environments integrate 3D virtual simulation technology, intelligent sensing devices, and digital twin modeling.

Suggested Citation

  • Elvira Nica & Gheorghe H. Popescu & Milos Poliak & Tomas Kliestik & Oana-Matilda Sabie, 2023. "Digital Twin Simulation Tools, Spatial Cognition Algorithms, and Multi-Sensor Fusion Technology in Sustainable Urban Governance Networks," Mathematics, MDPI, vol. 11(9), pages 1-25, April.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:9:p:1981-:d:1130072
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    References listed on IDEAS

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    1. Mihai Andronie & George Lãzãroiu & Roxana ?tefãnescu & Lumini?a Ionescu & Mãdãlina Coco?atu, 2021. "Neuromanagement decision-making and cognitive algorithmic processes in the technological adoption of mobile commerce apps," Oeconomia Copernicana, Institute of Economic Research, vol. 12(4), pages 1033-1062, December.
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    6. Mihai Andronie & George Lăzăroiu & Mariana Iatagan & Iulian Hurloiu & Irina Dijmărescu, 2021. "Sustainable Cyber-Physical Production Systems in Big Data-Driven Smart Urban Economy: A Systematic Literature Review," Sustainability, MDPI, vol. 13(2), pages 1-15, January.
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    8. Irene Meta & Feliu Serra-Burriel & José C. Carrasco-Jiménez & Fernando M. Cucchietti & Carla Diví-Cuesta & Carlos García Calatrava & David García & Eduardo Graells-Garrido & Germán Navarro & Qui, 2021. "The Camp Nou Stadium as a Testbed for City Physiology: A Modular Framework for Urban Digital Twins," Complexity, Hindawi, vol. 2021, pages 1-15, October.
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    1. Martin Bugaj & Pavol Durana & Roman Blazek & Jakub Horak, 2023. "Industry 4.0: Marvels in Profitability in the Transport Sector," Mathematics, MDPI, vol. 11(17), pages 1-23, August.
    2. Bong Gu Kang & Byeong Soo Kim, 2023. "A Study on Cognitive Error Validation for LED In-Ground Traffic Lights Using a Digital Twin and Virtual Environment," Mathematics, MDPI, vol. 11(17), pages 1-16, September.

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