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Article

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

1
Department of Administration and Public Management, The Bucharest University of Economic Studies, 010371 Bucharest, Romania
2
Department of Finance and Banking, Dimitrie Cantemir Christian University, 030134 Bucharest, Romania
3
Faculty of Operation and Economics of Transport and Communications, University of Zilina, Univerzitna 1, 01026 Zilina, Slovakia
*
Author to whom correspondence should be addressed.
Mathematics 2023, 11(9), 1981; https://doi.org/10.3390/math11091981
Submission received: 11 March 2023 / Revised: 17 April 2023 / Accepted: 21 April 2023 / Published: 22 April 2023

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.

1. Introduction

Urban big data, geospatial analytics tools, and data-driven planning technologies enable digital twin cities. Spatial cognition algorithms, virtual simulation tools, and Internet-of-Things-based connected devices further smart city technologies. Real-time sensor data, digital twin networks, and virtual mapping tools optimize big-data-driven urban geopolitics. Internet of Things sensing infrastructures, computer vision algorithms, and data fusion technologies are pivotal in digital twin cities. Big-data-driven urban analytics harnesses digital twin modeling, smart city logistics, and spatiotemporal deep learning algorithms. Visual recognition tools, smart city digital twins, and deep and machine learning algorithms further computationally networked urbanism. Digital twins of cities require sustainable governance networks, virtual simulation tools, and deep neural network technology. Virtual data analytics harnesses image recognition technologies, urban digital twins, and virtual mapping tools.
In this systematic review, we supplement the previously published research by proving that multi-sensor environment data fusion, virtual simulation modeling tools, and urban sensing technologies enable smart city analytics. Big-data-driven urban geopolitics requires 3D virtual space networking, synthetic data tools, and deep neural network technologies. Urban visual analytics leverages sensor data fusion, virtual data modeling tools, and digital twin technologies. The research problem aims to elucidate whether big geospatial data analytics leverages digital twin simulation modeling, urban Internet of Things sensing tools, and geospatial data mining techniques. Urban big data analytics harnesses deep-learning-based sensing technologies, spatiotemporal fusion algorithms, and data simulation and prediction tools. Urban visual analytics deploys virtual sensing techniques, smart spatial planning tools, and immersive 3D technologies. The literature gap identified and developed is whether smart environment sensors, cognitive computing systems, and urban sensing technologies shape urban digital twins. Cloud-based digital twins, urban planning tools, and multi-sensor fusion technology enable immersive hyperconnected virtual spaces in smart city environments. Big geospatial data analytics deploys urban sensing technologies, virtual twin modeling and predictive maintenance tools, and geospatial data mining techniques. Big-data-driven urban analytics harnesses digital twin technologies, data modeling and simulation tools, and smart city logistics.
The objective of this systematic review is to thoroughly inspect the recently published literature on digital twin simulation tools, spatial cognition algorithms, and multi-sensor fusion technology in sustainable urban governance networks. Virtual twin modeling tools, computer vision algorithms, and smart Internet of Things devices [1,2,3] configure urban digital governance. Virtual and augmented reality devices, big urban data, and smart environment sensors [4,5,6] articulate digital twin cities. Virtual simulation algorithms, urban big data, and cognitive data visualization tools [7,8,9] further smart networked environments. Spatial data analytics harnesses digital twin simulation and modeling tools, virtual twin data, and deep and machine learning algorithms. Spatial computing algorithms, synthetic data tools, and immersive virtual technologies [10,11,12] assist sustainable governance networks in digital twin cities. Immersive 3D technologies, wireless sensor networks, and data visualization tools [13,14,15] enable predictive urban analytics in blockchain-based virtual worlds. Urban sensing and digital twin technologies, virtual and augmented reality tools, and real-time sensor data [16,17,18] further immersive virtual environments. Dynamic routing technologies, Internet of Things digital twins, and data monitoring algorithms [19,20,21,22] articulate urban simulated environments. Data-sharing technologies, blockchain-enabled Internet of Things networks, and big data analytical tools [23,24,25] are pivotal in interconnected virtual worlds across sustainable smart cities.
Prior findings have been cumulated in this research clarifying that virtual reality simulation tools, multi-sensor data fusion algorithms, and sustainable urban computing systems [26,27,28] further interactive digital worlds. Urban sensor networks, data visualization and modeling, and blockchain-enabled cyber-physical systems [29,30,31] shape interconnected virtual worlds. Urban big data, visual immersion technologies, and Internet of Things sensors and actuators [32,33,34] optimize 3D digital environments. Predictive urban and cognitive data analytics harness digital twin modeling and wireless smart sensor technologies. Spatial recognition technologies, virtual simulation tools, and deep- and machine-learning-based predictive maintenance [35,36,37] enable computationally networked urbanism. Urban data analytics deploys data-driven predictive maintenance systems, immersive virtual reality simulations, and sensing and actuation technology.
This is the first systematic review covering such a hot emerging topic while consistently proving that smart city technologies, 3D spatiotemporal simulations, and big data analytical tools [38,39,40] articulate immersive multisensory virtual spaces in urban digital twins. Image recognition and smart city technologies, remote sensing data, and digital twin simulations [41,42,43,44] assist sustainable governance networks in virtual urban environments. Spatial data analytics harnesses sustainable urban monitoring systems, blockchain-enabled Internet of Things networks, and virtual data simulation and modeling. Deep neural network technologies, sensor data processing algorithms, and digital twin networks [45,46,47,48] further data-driven smart sustainable urbanism. Predictive modeling techniques, urban big data, and spatial computing technologies shape immersive virtual worlds in smart city digital twins. Data mining techniques, simulation-based digital twins, and smart city sensing technologies [49,50,51,52] optimize immersive interconnected 3D worlds. Three-dimensional virtual space networking, augmented analytics tools, and urban cloud data enable digital twins of cities.
  • Research Problem 1: Does data-driven smart sustainable urbanism require visual recognition tools, monitoring and sensing technologies, and simulation-based digital twins?
  • Research Problem 2: Do deep-learning-based sensing technologies, spatial cognition algorithms, and environment perception mechanisms configure digital twin cities?
  • Research Problem 3: Do digital twin simulation modeling, deep-learning-based sensing technologies, and urban data fusion optimize Internet-of-Things-based smart city environments?
The manuscript is organized as follows: methodology (Section 2), digital twin simulation tools in sustainable urban governance networks (Section 3), spatial cognition algorithms in sustainable urban governance networks (Section 4), multi-sensor fusion technology in sustainable urban governance networks (Section 5), discussion (Section 6), conclusions (Section 7), specific contributions to the literature (Section 8), limitations and further directions of research (Section 9), and practical implications (Section 10).

2. Methodology

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”. As the inspected research was published between 2021 and 2023, only 341 sources fulfilled the eligibility criteria, and 52, chiefly empirical, sources were eventually selected (Table 1 and Table 2). 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. These methodological quality assessment tools assisted us in organizing and analyzing the research data (quantitative, qualitative, and mixed-methods studies, but also cross-sectional studies and systematic mixed-studies reviews); configuring the flexible data extraction forms in relation to the structured data collection, study design, and reporting quality analysis; and addressing the risk of bias. Dimensions and VOSviewer were employed for bibliometric mapping through spatial and data layout algorithms (Figure 1, Figure 2, Figure 3, Figure 4 and Figure 5).
VOSviewer is a software tool employed mainly in analyzing bibliometric networks and in configuring data maps in terms of network, overlay, and density visualization and exploration with regard to items such as terms, researchers, and publications. A link, each with a certain strength, is a connection between two items. A network represents a set of items and the associated links. A cluster constitutes a set of items integrated in a map, and the related weight and score attributes are displayed as numerical values. The weight of the item changes the size of the label in addition to the circle of an item. Natural language processing algorithms were harnessed for term identification. The colors of circles are influenced by the modularity algorithm clustering the terms that harmonize consistently in conjunction with the same color by integer values: the color of an item is established by the cluster related to the item.
Citation correlations in relation to co-authorship have covered how 3D urban modeling tools, machine learning algorithms, and sensor data fusion further digital twin cities. Urban visual analytics deploys Internet of Things digital twins, image processing techniques, and deep-learning-based computer vision algorithms. Immersive interconnected 3D worlds in big-data-driven urban geopolitics require smart infrastructure sensors, spatial recognition technologies, and deep learning and neural network algorithms. Swarm intelligence algorithms, remote sensing technologies, and digital twin modeling tools configure smart sustainable city governance. Visual modeling technologies, wireless sensor networks, and real-time Internet of Things data configure interactive digital worlds across intelligent urban infrastructures. Big geospatial data analytics deploys urban digital twins, mobile wireless sensor networks, and virtual data modeling tools. Urban network infrastructures require 3D virtual equipment monitoring systems, big data analytical tools, and technology-enabled smart logistics. Internet of Things sensor technologies, urban analytics tools, and real-time data monitoring further blockchain-based virtual worlds in smart city environments.
Citation correlations in relation to citation have covered how environment perception mechanisms, digital twin modeling tools, and cloud computing technologies articulate big-data-driven urban geopolitics. Big-data-driven urban analytics leverages Internet of Things connected sensors, virtual simulation tools, and image recognition technologies. Geospatial analytics tools, remote sensing systems, and machine vision algorithms shape smart urban governance. Networked and integrated urban technologies, predictive control algorithms, and image processing tools articulate immersive 3D environments in digital twin cities. Smart city logistics, data mining tools, and edge intelligence technologies shape virtual urban environments. Internet-of-Things-based smart city environments necessitate simulation modeling tools, wireless sensor networks, and deep-learning-based sensing technologies. Big-data-driven urban analytics leverages extended reality technologies, interconnected sensor networks, and geospatial mapping and visual analytics tools in immersive 3D environments. Sustainable smart cities necessitate blockchain-enabled Internet of Things networks, sensor data processing algorithms, and data modeling and simulation tools.
Citation correlations in relation to bibliographic coupling have covered how Internet-of-Things-based decision support systems, digital twin simulation tools, and deep-learning-based sensing technologies assist sustainable urban governance networks. Immersive 3D technologies, multi-object detection and tracking tools, and virtual sensor networks optimize digital twin cities. Internet-of-Things-enabled smart city governance requires urban sensing technologies, data visualization and modeling tools, and spatial cognition algorithms. Augmented analytics tools, digital twin technologies, and smart city algorithms are pivotal in urban simulated environments. Digital twin modeling tools, geospatial mapping technologies, and virtual simulation algorithms assist Internet-of-Things-enabled smart cities. Sustainable urban governance networks require smart city digital twins, predictive modeling techniques, and synthetic data tools. Smart city logistics, cognitive data fusion techniques, and simulation modeling algorithms are pivotal in sustainable urban planning and governance. Cloud and edge computing algorithms, virtual reality modeling tools, and data-driven artificial intelligence technologies optimize networked urban environments.
Citation correlations in relation to co-citation have covered how immersive visualization systems, geospatial data mining tools, and predictive control algorithms enable virtual urban environments. Modeling and simulation tools, spatial computing technologies, and deep learning neural network architectures enable blockchain-based virtual worlds in networked smart cities. Urban big data analytics harnesses smart spatial planning tools, modeling and simulation algorithms, and mobile cloud and edge computing systems. Immersive multisensory virtual spaces in digital twin cities integrate urban planning tools, computer vision algorithms, and 5G hyperconnected networks. Smart city governance integrates multi-sensor environment data fusion, digital twin simulation tools, and urban sensing technologies. Digital twin modeling tools, urban data fusion, and deep neural network technologies are instrumental in smart cities. Virtual simulation tools, cloud and edge computing technologies, and spatiotemporal fusion algorithms are instrumental in data-driven smart sustainable urbanism. Urban visual analytics harnesses smart environment sensor data, spatial cognition algorithms, and virtual navigation tools.

3. Digital Twin Simulation Tools in Sustainable Urban Governance Networks

Three-dimensional city modeling, virtual simulation tools, and geospatial mapping technologies [1,2,3] configure data-driven smart sustainable urbanism. Intelligent sensor networks, machine learning techniques, and ambient sound recognition software configure immersive hyperconnected virtual spaces in digital twin cities. Real-time Internet of Things data, digital twin technology, and geospatial mapping tools further immersive virtual environments and computationally networked urbanism. Urban visual analytics deploys cloud and edge computing technologies, spatial cognition algorithms, and smart city software systems. Data-driven smart sustainable urbanism requires visual recognition tools, monitoring and sensing technologies, and simulation-based digital twins. Cognitive computing systems, predictive modeling techniques, and smart city digital twins configure big-data-driven urban geopolitics. Intelligent sensing devices, digital twin technologies, and deep and machine learning algorithms further smart urban governance. Smart city analytics deploys cognitive artificial intelligence algorithms, remote sensing technology, and urban digital twins. Blockchain-based digital twin management of big-data-driven urban geopolitics requires immersive visualization systems, Internet of Things sensing infrastructures, and simulation modeling algorithms.
Data mining tools, Internet of Things sensing infrastructures, and digital twin simulations [4,5,6] articulate virtual urban environments. Simulation modeling tools, computer vision algorithms, and cognitive automation technologies shape virtual urban environments. Urban big data analytics leverages Internet-of-Things-based connected devices, cloud computing technologies, and geospatial mapping tools. Computationally networked urbanism necessitates data visualization tools, digital twin modeling, and smart city software systems. Urban sensing technologies, real-time predictive maintenance systems, and virtual data modeling tools articulate digital twin cities. Digital twin simulations, computer vision algorithms, and spatial data modeling shape cognitive smart cities. Big data geospatial analytics leverages urban digital twins, virtual sensor networks, and image processing techniques. Simulated 3D environments and immersive multisensory virtual spaces in smart sustainable city governance necessitate digital twin simulation technologies, geospatial mapping tools, and urban Internet of Things systems. Modeling and simulation algorithms, data-driven Internet of Things systems, and spatial computing technologies articulate smart networked environments in digital urban governance.
Internet-of-Things-based smart city environments [7,8,9] require cognitive data fusion techniques, deep-learning-based sensing technologies, and predictive simulation tools. Cloud and edge computing technologies, Internet of Things devices and assets, and digital twin mapping tools assist immersive hyperconnected virtual spaces. Data fusion technologies, smart connected devices, and sustainable urban monitoring systems optimize digital twin cities. Algorithm-driven sensing devices, edge and cloud computing technologies, and immersive visualization systems are pivotal in digital twin governance. Data-driven planning technologies, deep learning and neural network algorithms, and virtual mapping tools assist immersive interconnected 3D worlds in Internet-of-Things-enabled smart cities. Predictive modeling algorithms, spatial data visualization tools, and blockchain-enabled cyber-physical systems optimize immersive and decentralized 3D digital worlds in urban simulated environments. Internet-of-Things-based smart city environments require data-driven planning technologies, predictive control algorithms, and virtual simulation tools. Spatial computing technologies, data prediction algorithms, and geospatial mapping tools are pivotal in Internet-of-Things-enabled smart city governance.
Spatial cognition algorithms, digital twin simulation modeling, and smart Internet of Things devices [10,11,12] enable big-data-driven urban geopolitics. Simulation and virtualization technologies, urban sensor networks, and cloud computing algorithms enable Internet-of-Things-enabled smart cities. Smart city analytics harnesses urban Internet of Things sensing tools, immersive 3D technologies, and virtual simulation algorithms. Sustainable smart cities integrate cyber-physical cognitive systems, augmented and virtual technologies, and modeling and simulation tools. Spatial computing technology, blockchain-enabled Internet of Things networks, and digital twin networks are instrumental in virtual urban environments. Big geospatial data analytics harnesses 3D virtual simulation technology, sustainable urban computing systems, and digital twin networks. Immersive 3D environments in Internet-of-Things-enabled smart city governance integrate predictive simulation tools, augmented reality algorithms, and smart environment sensor data. Digital twins of cities, virtual mapping tools, and multisource remote sensing data fusion are instrumental in 3D digital environments.
Digital twin simulation and modeling tools, Internet of Things sensing infrastructures, and geospatial data mining [13,14,15] further smart and environmentally sustainable cities. Geospatial mapping technologies, Internet of Things connected sensors, and deep learning neural network architectures configure immersive 3D environments in digital twin cities. Big geospatial data analytics deploys computer vision algorithms, cloud computing technologies, and Internet-of-Things-based decision support systems. Smart networked environments in big-data-driven urban geopolitics require digital twin simulation modeling, spatial computing technology, and Internet of Things sensors and actuators. Virtual modeling and simulation tools, machine vision technology, and real-time sensor data configure cognitive smart cities. Smart city logistics, digital twin simulation modeling, and immersive visualization systems further big-data-driven urban geopolitics. Spatial data analytics deploys real-time Internet of Things data, connected digital twins, and real-time predictive maintenance systems in computationally networked urbanism. Smart city governance requires virtual navigation tools, urban planning and digital twin technologies, and interconnected sensor networks. Digital twin networks, Internet-of-Things-based connected devices, and immersive 3D technologies configure immersive multisensory virtual spaces in networked urban environments.
Big-data-driven urban analytics [16,17,18] leverages virtual simulation tools, digital twin networks, and remote sensing technologies. Virtual modeling and immersive 3D technologies, data visualization tools, and data mining algorithms articulate smart sustainable city governance and digital twin cities. Geospatial mapping tools, algorithm-driven sensing devices, and real-time Internet of Things data shape virtual urban environments. Smart sustainable city governance necessitates virtual simulation tools, sensor data fusion, and geospatial mapping technologies. Deep-learning-based sensing technologies, data scalability and modularity, and Internet-of-Things-based connected devices articulate urban technological infrastructures in shared virtual environments. Digital twin modeling, urban analytics tools, and cognitive computing systems shape networked smart cities. Big geospatial data analytics leverages Internet of Things sensor technologies, data mapping and processing tools, and virtual twin modeling tools. Smart cities necessitate visual analytics and virtual data modeling tools, remote sensing technology, and big urban data.
Urban big data analytics, remote sensing systems, and virtual simulation modeling tools [19,20,21,22] assist smart city digital twins. Image recognition technologies, algorithm-driven sensing devices, and environment perception mechanisms assist immersive hyperconnected virtual spaces in Internet-of-Things-enabled smart cities. Internet of Things sensing infrastructures, data fusion technologies, and immersive visualization systems optimize digital twin cities. Immersive multisensory virtual spaces in computationally networked urbanism require visual recognition tools, data mining techniques, and deep-learning-based ambient sound processing. Multi-sensor data fusion algorithms, spatial computing technology, and virtual simulation tools are pivotal in simulated 3D environments across sustainable urban governance networks. Remote sensor networks, urban computing technologies, and machine and deep learning algorithms assist digital twins of cities. Real-time data tracking and monitoring tools, deep and machine learning algorithms, and urban network infrastructures optimize blockchain-based virtual worlds in sustainable smart cities. Interconnected virtual worlds in digital urban governance require spatial computing technologies, sensor data fusion, and predictive simulation tools.
Digital twin simulation, remote sensing technologies, and spatial computing algorithms [23,24,25] enable augmented-reality-powered immersive spaces in urban digital governance. Urban big data analytics harnesses smart city software systems, digital twin simulation tools, and edge and cloud computing technologies. Internet-of-Things-based smart city environments integrate urban digital twins, sensor data processing algorithms, and deep neural network technology. Networked sustainable urban technologies, Internet of Things sensing infrastructures, and deep-learning-based computer vision algorithms are instrumental in immersive hyperconnected virtual spaces in smart city governance. Simulation and virtualization technologies, predictive modeling algorithms, and digital mapping tools enable smart city digital twins. Real-time predictive analytics harnesses urban sensing and digital twin technologies, spatiotemporal fusion algorithms, and data mining tools in Internet-of-Things-based smart city environments. Blockchain-based virtual worlds in digital twin cities integrate smart environment sensors, visual recognition tools, and simulation modeling algorithms. Deep neural network and digital twin technologies, smart infrastructure sensors, and data visualization tools are instrumental in virtual urban environments (Table 3).

4. Spatial Cognition Algorithms in Sustainable Urban Governance Networks

Data-driven Internet of Things systems, cloud-based digital twins, spatial cognition algorithms, and immersive virtual technologies [26,27,28] configure immersive 3D environments. Spatiotemporal fusion algorithms, cyber-physical cognitive systems, and virtual twin modeling tools configure sustainable urban governance networks. Ambient sound recognition software, technology-enabled smart logistics, and modeling and simulation tools further immersive hyperconnected virtual spaces in digital twins of cities. Urban big data analytics deploys virtual simulation algorithms, intelligent sensing devices, and computational object instantiation and recognition tools. Smart urban governance requires modeling and simulation algorithms, image processing techniques, and data acquisition tools. Algorithm-driven sensing devices, virtual process simulation and planning tools, and predictive modeling techniques configure urban digital twins. Three-dimensional virtual simulation technology, geospatial data visualization tools, and mobile wireless sensor networks further smart city digital twins. Urban data analytics deploys spatial cognition algorithms, deep image processing networks, and virtual simulation tools. Internet-of-Things-based smart city environments require 5G hyperconnected networks, 3D spatiotemporal simulations, and urban sensing technologies and logistics.
Three-dimensional digital environments in smart city governance [29,30,31] necessitate visual sensing devices, spatial cognition algorithms, and geospatial mapping technologies. Digital twin simulations, cloud computing technologies, and smart connected devices articulate virtual urban environments. Virtual twin data, computer vision algorithms, and remote sensing systems shape digital twin cities. Big geospatial data analytics leverages Internet of Things devices and assets, cloud and edge computing technologies, and virtual reality modeling tools. Immersive 3D environments in urban digital twins necessitate spatial data visualization tools, virtual modeling technology, and blockchain-enabled Internet of Things networks. Internet of Things sensing infrastructures, spatial data visualization tools, and augmented and virtual reality technologies articulate urban simulated environments. Remote sensing image techniques, virtual simulation modeling tools, and blockchain-based digital twins shape big-data-driven urban geopolitics. Big-data-driven urban analytics leverages digital twin simulation modeling, geospatial mapping tools, and augmented and virtual reality technologies. Smart city sensing technologies, digital twin modeling tools, and immersive visualization systems articulate interconnected virtual worlds.
Urban remote sensing data, cognitive digital twins, and data simulation and prediction tools [32,33,34] assist immersive virtual worlds. Geospatial mapping tools, Internet of Things sensing infrastructures, and virtual simulation algorithms assist computationally networked urbanism. Deep learning neural network architectures, digital twin modeling, and multi-sensor fusion technology optimize simulated 3D environments in big-data-driven urban geopolitics. Immersive 3D environments in digital twin cities require 5G hyperconnected networks, urban sensing technologies, and predictive simulation tools. Virtual simulation modeling tools, smart environment sensor data, and digital twin technologies are pivotal in immersive interconnected 3D worlds across Internet-of-Things-enabled smart cities. Predictive modeling algorithms, remote sensing data, and spatial computing technologies assist digital twin cities. Spatiotemporal fusion algorithms, urban monitoring systems, and cloud-based digital twin technology optimize Internet-of-Things-based smart city environments. Immersive interactive environments in data-driven smart sustainable cities require virtual twinning techniques, deep-learning-based sensing and image recognition technologies, and data modeling and simulation tools. Extended reality technologies, modeling and simulation tools, and Internet-of-Things-based digital twins are pivotal in immersive multisensory virtual spaces across big-data-driven urban geopolitics.
Smart city analytics [35,36,37] harnesses simulation modeling tools, urban sensing technologies, and spatial cognition algorithms. Virtual and augmented reality devices, data-driven planning technologies, and deep reinforcement learning networks enable digital twin cities. Digital twin cities integrate synthetic data tools, computational modeling and simulation techniques, and deep-learning-based computer vision algorithms. Digital twin mapping, multi-sensor data fusion techniques, and 3D urban modeling tools are instrumental in virtual simulation environments across 5G-enabled smart cities. Digital twin simulation technologies, cognitive data mining algorithms, and urban analytics tools enable extended reality environments in cognitive smart cities. Big data geospatial analytics harnesses multi-sensor environment data fusion, virtual navigation tools, and cloud and edge computing technologies. Smart city digital twins integrate sensor data processing algorithms, visualization modeling technologies, and virtual simulation tools. Remote sensing data, machine vision algorithms, and smart city technologies are instrumental in virtual urban environments. Deep-learning-based sensing technologies, virtual data modeling, and digital twin simulations enable smart city environments.
Deep-learning-based sensing technologies, spatial cognition algorithms, and environment perception mechanisms [38,39,40] configure digital twin cities. Virtual simulation algorithms, digital twin networks, and urban sensing technologies further smart city governance. Urban big data analytics deploys computer vision technologies, simulation modeling algorithms, and virtual sensor networks. Cognitive smart cities require remote sensing data, virtual navigation tools, and visualization modeling technologies. Monitoring and sensing technologies, smart city algorithms, and data-driven simulation modeling configure simulated 3D environments in digital twin governance. Real-time Internet of Things data, virtual simulation tools, and machine learning algorithms further smart city governance. Smart city analytics deploys real-time data monitoring, deep-learning-based ambient sound processing, and virtual mapping tools. Internet-of-Things-based smart city environments require virtual simulation algorithms, digital twin technologies, and urban planning tools. Three-dimensional city modeling, smart Internet of Things devices, and immersive visualization systems configure urban simulated environments.
Spatial cognition algorithms, 3D modeling and visualization tools, and urban sensing technologies [41,42,43,44] shape big-data-driven urban geopolitics. Digital twin simulation and modeling tools, data-driven planning technologies, and intelligent sensor networks articulate sustainable urban governance networks. Big-data-driven urban analytics leverages remote sensing systems, spatiotemporal fusion algorithms, and digital twin technology. Digital twin cities necessitate networked sustainable urban technologies, predictive simulation tools, and virtual data analytics. Cloud computing analytics, urban logistics networks, and digital twin technologies articulate blockchain-based virtual worlds in sustainable smart cities. Immersive visualization systems, urban sensing technologies, and geospatial mapping tools shape smart city environments. Urban visual analytics leverages data mining techniques, virtual simulation tools, and Internet of Things digital twins. Three-dimensional digital environments in smart cities necessitate multi-source remote sensing data fusion, visual modeling technologies, and virtual and augmented reality tools. Geospatial analytics tools, urban data fusion, and algorithm-driven sensing devices articulate virtual and augmented reality-powered immersive spaces in Internet-of-Things-based smart city environments.
Virtual-reality-based visualization environments in smart city digital twins [45,46,47,48] require visual perception sensors, cognitive data fusion techniques, and spatial computing algorithms. Visual analytics tools, image recognition technologies, and immersive virtual reality simulations assist data-driven smart sustainable urbanism. Computer vision algorithms, Internet of Things connected sensors, and deep neural network technologies optimize smart sustainable city governance. Virtual urban environments require deep-learning-based sensing technologies, digital twin modeling tools, and machine vision algorithms. Computational modeling tools, predictive control algorithms, and 3D virtual simulation technology are pivotal in smart city digital twins. Edge intelligence technologies, multi-sensor environment data fusion tools, and digital twin networks assist smart city software systems. Immersive visualization systems, predictive modeling algorithms, and image processing tools optimize virtual urban environments. Smart infrastructure sensors, simulation modeling algorithms, and predictive maintenance tools are pivotal in 3D digital environments across big-data-driven urban geopolitics. Cognitive automation technologies, blockchain-enabled Internet of Things networks, and virtual data modeling tools assist data-driven smart sustainable urbanism.
Cognitive data visualization tools, predictive control algorithms, and urban spatial planning tools [49,50,51,52] are instrumental in shared virtual environments across digital twin cities. Big geospatial data analytics harnesses Internet-of-Things-based digital twins, virtual mapping tools, and wireless sensor networks. Swarm intelligence algorithms, digital twin modeling, and networked sustainable urban technologies enable Internet-of-Things-enabled smart city governance. Immersive hyperconnected virtual spaces in digital twin cities integrate smart environment sensors, data modeling algorithms, and networked sustainable urban technologies. Spatial computing technologies, digital twin simulation, and synthetic sensing devices are instrumental in immersive and decentralized 3D digital worlds in smart and sustainable urban systems. Cloud and edge computing algorithms, digital twin technologies, and synthetic data tools enable urban network infrastructures in blockchain-based virtual worlds. Urban big data analytics harnesses spatial computing technologies, wireless sensor networks, and machine-learning-based algorithm modeling tools. Immersive and decentralized 3D digital worlds in smart and environmentally sustainable cities integrate computer vision algorithms, Internet of Things sensor technologies, and virtual data modeling tools (Table 4).

5. Multi-Sensor Fusion Technology in Sustainable Urban Governance Networks

Internet-of-Things-based smart city environments [1,16,29] require urban network infrastructures, data mining and fusion technology, and spatial data visualization tools. Cloud and edge computing technologies, modeling and simulation tools, and geospatial data mining configure smart urban governance. Data visualization tools, dynamic routing technologies, and wireless sensor networks further digital twin cities. Big-data-driven urban analytics deploys geospatial mapping technologies, real-time predictive maintenance systems, and digital twin modeling tools. Networked smart cities require Internet of Things sensing infrastructures, urban big data, and digital twin simulation modeling. Sensing and computing technologies, virtual simulation tools, and cognitive artificial intelligence algorithms configure urban digital twins. Three-dimensional virtual simulation technology, intelligent urban infrastructures, and visual analytics tools further Internet-of-Things-based smart city environments. Predictive urban analytics deploys 3D spatiotemporal simulations, deep learning and neural network algorithms, and geospatial data visualization tools. Data-driven digital twin modeling, urban Internet of Things systems, and synthetic sensing devices configure interconnected virtual worlds in smart city governance.
Virtual data analytics [7,20,32] leverages urban sensing and visual immersion technologies, data modeling and simulation tools, and image data fusion techniques. Internet of Things connected sensors, cloud computing technologies, and digital twin mapping articulate big-data-driven urban geopolitics. Big urban data, Internet of Things sensing infrastructures, and virtual modeling technology shape smart networked environments. Urban visual analytics leverages immersive 3D technologies, deep and machine learning algorithms, and Internet-of-Things-based decision support systems. Urban simulated environments necessitate virtual twin modeling tools, sensor data fusion, and deep neural network technology. Image processing techniques, Internet-of-Things-based connected devices, and virtual reality modeling tools articulate digital twin cities. Urban technological infrastructures, 5G hyperconnected networks, and deep-learning-based sensing technologies shape blockchain-based virtual worlds in smart city digital twins. Big-data-driven urban analytics leverages digital twin technologies, computational modeling tools, and deep image processing networks. Simulated 3D environments in smart city digital twins necessitate data-driven planning technologies, virtual reality mapping, and urban analytics tools.
Augmented reality algorithms, ambient sound recognition software, and data fusion technologies [13,34,41] optimize smart networked environments in 5G-enabled smart cities. Cloud computing algorithms, virtual navigation tools, and urban sensor networks assist digital twin cities. Real-time Internet of Things data, immersive visualization systems, and geospatial mapping tools optimize smart sustainable city governance. Immersive hyperconnected virtual spaces in big-data-driven urban geopolitics require spatial computing technology, interconnected sensor networks, and digital twin modeling. Digital twin simulation tools, networked and integrated urban technologies, and sensor data processing algorithms are pivotal in cognitive smart cities. Deep-learning-based computer vision algorithms, digital twin networks, and smart city logistics assist big-data-driven urban geopolitics. Internet-of-Things-based smart city environments require data mapping and processing tools, cognitive digital twins, and predictive modeling algorithms. Deep-learning-based computer vision algorithms, smart environment sensor data, and digital twin simulation modeling are pivotal in 3D digital environments across big-data-driven urban geopolitics.
Urban big data analytics [4,25,37] harnesses digital twin technologies, smart data modeling, and multi-sensor environment data fusion tools. Machine vision technology, spatial cognition algorithms, and urban digital twins enable Internet-of-Things-enabled smart city governance. Urban big data analytics harnesses virtual simulation tools, remote sensing technologies, and predictive modeling algorithms. Urban digital governance integrates data monitoring algorithms, cloud computing technologies, and geospatial mapping tools. Remote sensor networks, digital twin modeling, and urban computing technologies are instrumental in data-driven smart sustainable urbanism. Spatial computing technologies, digital twin modeling, and data visualization tools enable smart urban governance. Virtual urban environments integrate digital twin modeling, spatial data visualization tools, and spatial computing technology. Virtual sensing techniques, smart Internet of Things devices, and 3D space mapping algorithms are instrumental in extended reality environments in digital twin cities.
Sensor data fusion, visual recognition tools, and edge and cloud computing technologies [3,12,35] configure digital twin cities. Image recognition technologies, data visualization tools, and Internet of Things devices and assets configure immersive 3D environments. Virtual simulation algorithms, wireless sensor networks, and data mining tools further digital twin cities. Big-data-driven urban analytics deploys smart environment sensors, digital twin simulation, and immersive visualization systems. Blockchain-based virtual worlds in big-data-driven urban geopolitics require remote sensing technology, smart city software systems, and data mining tools. Interconnected sensor networks, virtual data modeling tools, and machine learning algorithms further digital twin cities. Urban big data analytics deploys digital twin technologies, synthetic data tools, and immersive virtual technologies. Immersive and decentralized 3D digital worlds in smart sustainable city governance require spatial data visualization tools, remote sensing technologies, and data simulation algorithms. Urban monitoring systems, visual recognition tools, and data-sharing technologies configure immersive multisensory virtual spaces across smart cities.
Multisource remote sensing data fusion, real-time predictive analytics, and 3D urban modeling tools [6,23,38] articulate virtual simulation environments in digital twin cities. Digital twin technology, virtual simulation tools, and spatiotemporal fusion algorithms articulate smart city governance. Geospatial analytics tools, digital twin technologies, and Internet of Things sensing infrastructures shape blockchain-based virtual worlds in smart sustainable city governance. Urban visual analytics leverages digital twin simulation tools, geospatial mapping technologies, and computer vision algorithms. Immersive hyperconnected virtual spaces in Internet-of-Things-enabled smart cities necessitate urban sensing technologies, ambient sound recognition software, and environment perception mechanisms. Internet of Things sensor technologies, visual analytics tools, and spatial cognition algorithms articulate urban digital governance. Modeling and simulation tools, immersive 3D technologies, and mobile wireless sensor networks shape interconnected virtual worlds in Internet-of-Things-based smart city environments. Big geospatial data analytics leverages digital twin modeling, Internet of Things sensing infrastructures, and predictive simulation tools in immersive hyperconnected virtual spaces. Immersive multisensory virtual spaces in big-data-driven urban geopolitics necessitate digital twin simulation modeling, blockchain-enabled Internet of Things networks, and cognitive computing systems.
Digital twin simulation modeling, deep-learning-based sensing technologies, and urban data fusion [9,22,50] optimize Internet-of-Things-based smart city environments. Smart infrastructure sensors, deep learning neural network architectures, and spatial cognition algorithms assist sustainable urban governance networks. Virtual and augmented reality tools, geospatial mapping technologies, and digital twin mapping optimize urban network infrastructures. Virtual urban environments require smart city logistics, spatial computing algorithms, and cognitive data fusion techniques. Immersive visualization systems, virtual sensor networks, and smart spatial planning tools are pivotal in urban simulated environments. Spatiotemporal fusion algorithms, virtual simulation tools, and visual modeling technologies assist sustainable urban governance networks. Immersive virtual environments in cognitive smart cities require mobile cloud and edge computing systems, networked sustainable urban technologies, and digital twin simulation and modeling tools. Big urban data, Internet of Things sensing infrastructures, and spatial computing technologies are pivotal in simulated 3D environments across digital twin cities. Data mining algorithms, technology-enabled smart logistics, and digital mapping tools assist networked urban environments.
Internet of Things digital twins, spatial cognition algorithms, and multi-sensor environment data fusion [10,18,45] are instrumental in smart urban governance. Remote sensing systems, smart connected devices, and cloud computing technologies enable virtual urban environments. Big-data-driven urban analytics harnesses intelligent sensor networks, deep and machine learning algorithms, and modeling and simulation tools. Sustainable smart cities integrate virtual twin modeling tools, deep-learning-based ambient sound processing, and geospatial data mining. Image recognition technologies, visual analytics tools, and virtual simulation algorithms are instrumental in digital urban governance. Virtual modeling and simulation tools, spatial computing technology, and data-driven Internet of Things systems enable networked smart cities. Big geospatial data analytics harnesses machine and deep learning algorithms, smart city logistics, and virtual simulation modeling tools. Digital urban governance integrates augmented and virtual reality technologies, spatial computing algorithms, and real-time sensor data (Table 5).

6. Discussion

This systematic literature review investigates how digital twin simulation, data visualization tools, and ambient sound recognition software [53,54,55] configure sustainable urban governance networks. Immersive virtual environments in big-data-driven urban geopolitics [56,57,58] require swarm intelligence algorithms, spatial recognition technologies, and digital twin simulation tools. Smart city analytics [59,60,61] deploys urban sensor networks, virtual simulation tools, and extended reality technologies. Digital twin technologies, modeling and simulation algorithms, and real-time data monitoring [62,63,64] configure smart urban governance. Smart city analytics deploys digital twin simulation tools, spatial recognition technologies, and 3D city modeling. Internet-of-Things-based smart city environments require virtual reality modeling tools, geospatial data mining, and deep-learning-based sensing technologies. Data visualization tools, digital twin mapping, and edge intelligence technologies shape networked smart cities. Spatiotemporal fusion algorithms, smart data modeling, and remote sensing technologies shape immersive interconnected 3D worlds in digital twin cities. Big data analytical tools, digital twin modeling, and Internet of Things sensor technologies shape networked urban environments. Algorithm-driven sensing devices, virtual data modeling tools, and simulation and virtualization technologies assist digital twin cities.
Significant research has elucidated how digital twin modeling tools, monitoring and sensing technologies, and Internet-of-Things-based decision support systems [65,66,67] articulate big-data-driven urban geopolitics. Immersive hyperconnected virtual spaces in digital twin cities [68,69,70] necessitate urban planning technologies, intelligent sensor networks, and visual analytics tools. Spatial data analytics [71,72,73] leverages machine learning techniques, virtual twin modeling tools, and sustainable urban monitoring systems. Internet-of-Things-based connected devices, deep-learning-based computer vision algorithms, and smart environment sensor data [74,75,76] articulate digital twin cities. Urban sensing technologies, geospatial mapping tools, and real-time Internet of Things data shape immersive hyperconnected virtual spaces in smart city environments. Predictive simulation tools, urban network infrastructures, and digital twin networks assist sustainable smart cities. Smart city digital twins integrate remote sensing technologies, data scalability and modularity, and cognitive artificial intelligence algorithms. Virtual data analytics leverages spatial cognition algorithms, predictive modeling techniques, and interconnected sensor networks. Immersive 3D technologies, spatial cognition algorithms, and geospatial analytics tools are instrumental in blockchain-based virtual worlds across digital twin cities.
We integrate research regarding how blockchain-based digital twins, smart infrastructure sensors, and real-time Internet of Things data [77,78,79] assist urban computing technologies. Wireless sensor networks, predictive modeling algorithms, and image processing techniques [80,81,82] optimize shared virtual environments in digital twin cities. Simulation modeling tools, blockchain-enabled Internet of Things networks, and spatial computing technologies [83,84,85] are pivotal in smart sustainable city governance. Internet-of-Things-enabled smart cities [86,87,88] require cloud computing technologies, virtual and augmented reality tools, and digital twin simulations. Urban digital twins require virtual simulation algorithms, Internet of Things sensing infrastructures, and cognitive data visualization tools. Immersive interconnected 3D worlds in digital twin cities require spatial computing technologies, wireless sensor networks, and synthetic data tools. Visual modeling technologies, digital twin mapping, and Internet-of-Things-based decision support systems configure urban simulated environments. Urban digital twins necessitate machine learning algorithms, wireless sensor networks, and data mining techniques.
The findings gathered from our analyses clarify that Internet-of-Things-based smart city environments [89,90,91] integrate 3D virtual simulation technology, intelligent sensing devices, and digital twin modeling. Data-driven planning technologies, remote sensing systems, and geospatial analytics tools [92,93,94] are instrumental in virtual urban environments. Internet of Things digital twins, cognitive data visualization tools, and data-driven planning technologies [95,96] are instrumental in virtual urban environments. Sensor data fusion, spatial computing technologies, and ambient sound recognition software further virtual urban environments. Virtual simulation tools, machine vision algorithms, and spatial computing technology are pivotal in smart networked environments throughout digital twin cities. Remote sensing data, image recognition technologies, and smart city software systems further virtual urban environments. Virtual data modeling tools, digital twin technologies, and Internet of Things sensing infrastructures articulate cognitive smart cities. Edge and cloud computing technologies, modeling and simulation tools, and data monitoring algorithms enable virtual urban environments. Interactive digital worlds in sustainable urban planning and governance necessitate data visualization tools, virtual twinning techniques, and multi-object detection and tracking.

7. Conclusions

The purpose of this systematic review was to prove that multi-sensor environment data fusion, virtual simulation modeling tools, and urban sensing technologies enable smart city analytics, as the previously published 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. The objective of this paper was achieved by clarifying that simulation modeling algorithms, cognitive automation technologies, and geospatial mapping tools articulate immersive 3D environments in smart cities. Blockchain-based virtual worlds in smart city governance require geospatial data mining techniques, multi-source remote sensing data fusion, and virtual reality modeling tools. Big-data-driven urban analytics deploys digital twin modeling, augmented and virtual technologies, and image processing tools. Smart city logistics, 3D virtual equipment monitoring systems, and data-driven planning technologies optimize computationally networked urbanism. Immersive 3D environments in digital twins of cities integrate sensor data fusion, virtual and augmented reality devices, and computational object instantiation and recognition tools. Big geospatial data analytics leverages predictive control algorithms, urban sensing technologies, and digital twin modeling. Internet of Things sensing infrastructures, 5G hyperconnected networks, and virtual simulation tools enable augmented-reality-powered immersive spaces in digital twin governance.
This systematic literature review has inspected the relevant published peer-reviewed evidence in relation to how virtual simulation algorithms, deep learning neural network architectures, and cyber-physical cognitive systems articulate networked smart cities. Immersive visualization systems, image recognition technologies, and virtual simulation tools further 3D digital environments in big-data-driven urban geopolitics. Predictive maintenance tools, immersive visualization systems, and remote sensing data configure smart city governance. Internet of Things connected sensors, geospatial data mining, and virtual mapping tools assist intelligent urban infrastructures. Remote sensing technologies, augmented reality algorithms, and urban analytics tools enable smart city digital twins. Big geospatial data analytics harnesses urban sensing technologies, digital twin modeling tools, and virtual simulation algorithms. Virtual simulation modeling tools, deep neural network technologies, and Internet of Things sensing infrastructures further digital twin cities. Urban big data analytics harnesses digital twin modeling, virtual navigation tools, and spatial computing technology.

8. Specific Contributions to the Literature

This systematic review covers digital twin simulation tools, spatial cognition algorithms, and multi-sensor fusion technology in sustainable urban governance networks, an outstanding topic that has not been analyzed thoroughly so far. Remote sensor networks, geospatial mapping tools, and blockchain-based digital twins configure immersive hyperconnected virtual spaces in Internet-of-Things-enabled smart city governance. Smart city governance integrates spatial data visualization tools, urban digital twins, and 3D virtual simulation technology. Simulation and virtualization technologies, computer vision algorithms, and urban Internet of Things sensing tools optimize digital twin cities. Intelligent sensor networks, data visualization tools, and virtual modeling technology assist digital twin cities. Data-sharing technologies, cloud and edge computing algorithms, and real-time data tracking and monitoring tools optimize immersive 3D environments in sustainable smart cities. Smart connected devices, simulation modeling algorithms, and sensing and computing technologies assist sustainable urban governance networks. Data-driven smart sustainable urbanism requires blockchain-enabled Internet of Things networks, digital twin technology, and cloud computing technologies. Remote sensing systems, immersive virtual technologies, and simulation modeling algorithms are pivotal in urban digital governance. Smart and environmentally sustainable cities require deep-learning-based ambient sound processing, connected digital twins, and remote sensing systems.
Our analyses particularly prove that virtual navigation tools, geospatial mapping technologies, and Internet of Things connected sensors enable smart urban governance. Virtual twin modeling tools, Internet of Things sensing infrastructures, and cloud and edge computing technologies articulate data-driven smart sustainable urbanism. Urban big data analytics harnesses sensor data processing algorithms, virtual and augmented reality tools, and image recognition technologies. Real-time predictive analytics harnesses urban sensing technologies, digital twin simulation modeling, and computer vision algorithms in Internet-of-Things-based smart city environments. Shared virtual environments in smart sustainable city governance integrate digital twin modeling tools, immersive 3D technologies, and smart infrastructure sensors. Urban sensing technologies, digital twin modeling, and spatial computing algorithms shape Internet-of-Things-enabled smart cities. Urban remote sensing data, smart spatial planning tools, and dynamic routing technologies are instrumental in digital twin cities. Data mining tools, cloud computing algorithms, and machine vision technology enable urban technological infrastructures. Interconnected virtual worlds in smart cities necessitate data mining techniques, digital mapping tools, and urban Internet of Things systems.

9. Limitations and Further Directions of Research

As for limitations, by investigating only articles published in journals indexed in the ProQuest, Scopus, and Web of Science databases between 2021 and 2023, first-rate sources on digital twin simulation tools, spatial cognition algorithms, and multi-sensor fusion technology in sustainable urban governance networks may have been omitted. Subsequent interest should be oriented towards how mobile wireless sensor networks, digital twin modeling, and cloud computing technologies configure big-data-driven urban geopolitics. Smart city analytics deploys sensor data processing algorithms, virtual modeling and simulation tools, and digital twin technology. Digital twin modeling tools, Internet of Things sensor technologies, and spatial cognition algorithms assist smart urban governance. Internet-of-Things-enabled smart city governance requires digital twin modeling, urban sensing technologies, and geospatial mapping tools. Smart environment sensors, virtual navigation tools, and Internet-of-Things-based connected devices further computationally networked urbanism. Deep neural network technology, real-time Internet of Things data, and smart city logistics optimize urban digital governance. Blockchain-based virtual worlds in digital twin cities require urban cloud data, spatial computing technologies, and data acquisition tools.
The scope of our research does not advance how blockchain-enabled Internet of Things networks, urban sensing technologies, and synthetic data tools are pivotal in 5G-enabled smart cities. Intelligent sensor networks, urban data fusion, and virtual modeling technology configure simulated 3D environments in digital twin cities. Remote sensing data, digital twin modeling tools, and geospatial mapping technologies assist virtual urban environments. Three-dimensional modeling and visualization tools, virtual simulation algorithms, and deep-learning-based sensing technologies further smart city digital twins. Computational object instantiation and recognition, digital twin modeling, and image processing techniques optimize smart urban governance. Big geospatial data analytics deploys predictive control algorithms, smart Internet of Things devices, and image recognition technologies. Future research should investigate how digital twin cities require urban technological infrastructures, virtual simulation algorithms, and deep learning neural network architectures. Deep-learning-based sensing technologies, predictive control algorithms, and digital twin simulation and modeling tools assist smart city digital twins. Smart city governance requires virtual simulation tools, geospatial mapping technologies, and 5G hyperconnected networks. Virtual navigation tools, Internet of Things digital twins, and cognitive data mining algorithms configure 3D digital environments in sustainable urban computing systems. Deep-learning-based ambient sound processing, immersive visualization systems, and networked sustainable urban technologies are pivotal in data-driven smart sustainable cities.

10. Practical Implications

Spatial cognition algorithms, immersive virtual technologies, and digital twin simulation modeling articulate big-data-driven urban geopolitics. Remote sensing image techniques, geospatial mapping tools, and sustainable urban governance networks are instrumental in smart city environments. Cloud computing technologies, machine and deep learning algorithms, and visual analytics tools enable Internet-of-Things-based smart city environments. Predictive maintenance tools, virtual modeling technology, and sensor data processing algorithms shape digital twin cities. Big geospatial data analytics harnesses extended reality technologies, urban digital twins, and Internet of Things sensing infrastructures. Big geospatial data analytics leverages 3D urban modeling tools, monitoring and sensing technologies, and immersive visualization systems. Immersive multisensory virtual spaces in cognitive smart cities integrate digital twin simulation modeling, geospatial data mining techniques, and multisource remote sensing data fusion. Internet-of-Things-based decision support systems, visual recognition tools, and predictive modeling techniques articulate sustainable smart cities. Computationally networked urbanism necessitates simulation modeling algorithms, remote sensing technologies, and cognitive digital twins.
Digital twin simulation, smart environment sensor data, and spatial computing technologies shape big-data-driven urban geopolitics. Virtual simulation modeling, geospatial mapping tools, and multi-sensor environment data fusion are instrumental in 3D digital environments across smart and sustainable urban systems. Big urban data, virtual reality modeling tools, and visual immersion technologies enable digital twin cities. Big geospatial data analytics harnesses algorithm-driven sensing devices, cloud-based digital twin technology, and mobile cloud and edge computing systems. Smart city algorithms, Internet of Things sensing infrastructures, and virtual simulation modeling tools articulate immersive interactive environments in big-data-driven urban geopolitics. Urban data analytics deploys cognitive data fusion techniques, immersive visualization systems, and predictive modeling algorithms. Big-data-driven urban analytics leverages digital twin networks, image processing tools, and geospatial mapping technologies. Immersive 3D environments in Internet-of-Things-enabled smart cities integrate urban analytics tools, data-driven planning technologies, and spatial computing algorithms. Internet-of-Things-based smart city environments necessitate spatial computing technology, virtual twin modeling tools, and blockchain-enabled cyber-physical systems.

Author Contributions

Conceptualization, E.N. and G.H.P.; methodology, M.P. and T.K.; validation, O.-M.S. and E.N.; formal analysis, G.H.P. and O.-M.S.; investigation, M.P. and E.N.; resources, T.K. and G.H.P.; data curation, E.N. and M.P.; writing—original draft preparation, O.-M.S. and T.K.; writing—review and editing, G.H.P. and E.N.; visualization, O.-M.S. and M.P.; supervision, E.N. and G.H.P. All authors have read and agreed to the published version of the manuscript.

Funding

This paper is an output of the project NFP313011BWN6 “The implementation framework and business model of the Internet of Things, Industry 4.0 and smart transport”.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. VOSviewer mapping of digital twin simulation tools, spatial cognition algorithms, and multi-sensor fusion technology in sustainable urban governance networks regarding co-authorship.
Figure 1. VOSviewer mapping of digital twin simulation tools, spatial cognition algorithms, and multi-sensor fusion technology in sustainable urban governance networks regarding co-authorship.
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Figure 2. VOSviewer mapping of digital twin simulation tools, spatial cognition algorithms, and multi-sensor fusion technology in sustainable urban governance networks regarding citation.
Figure 2. VOSviewer mapping of digital twin simulation tools, spatial cognition algorithms, and multi-sensor fusion technology in sustainable urban governance networks regarding citation.
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Figure 3. VOSviewer mapping of digital twin simulation tools, spatial cognition algorithms, and multi-sensor fusion technology in sustainable urban governance networks regarding bibliographic coupling.
Figure 3. VOSviewer mapping of digital twin simulation tools, spatial cognition algorithms, and multi-sensor fusion technology in sustainable urban governance networks regarding bibliographic coupling.
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Figure 4. VOSviewer mapping of digital twin simulation tools, spatial cognition algorithms, and multi-sensor fusion technology in sustainable urban governance networks regarding co-citation.
Figure 4. VOSviewer mapping of digital twin simulation tools, spatial cognition algorithms, and multi-sensor fusion technology in sustainable urban governance networks regarding co-citation.
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Figure 5. PRISMA flow diagram describing the search results and screening.
Figure 5. PRISMA flow diagram describing the search results and screening.
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Table 1. Topics and types of identified scholarly sources.
Table 1. Topics and types of identified scholarly sources.
TopicIdentifiedSelected
Sustainable urban governance networks + digital twin simulation tools11919
Sustainable urban governance networks + spatial cognition algorithms11417
Sustainable urban governance networks + multi-sensor fusion technology10816
Type of paper
Original research30340
Review2312
Conference proceedings120
Book10
Editorial20
Source: Processed by the authors. Some topics overlap.
Table 2. Synopsis of cumulative evidence concerning investigated topics and descriptive results (research findings).
Table 2. Synopsis of cumulative evidence concerning investigated topics and descriptive results (research findings).
Data-driven smart sustainable urbanism requires visual recognition tools, monitoring and sensing technologies, and simulation-based digital twins.[1,2,3]
Simulated 3D environments and immersive multisensory virtual spaces in smart sustainable city governance necessitate digital twin simulation technologies, geospatial mapping tools, and urban Internet of Things systems.[4,5,6]
Data fusion technologies, smart connected devices, and sustainable urban monitoring systems optimize digital twin cities.[7,8,9]
Big geospatial data analytics harnesses 3D virtual simulation technology, sustainable urban computing systems, and digital twin networks.[10,11,12]
Smart networked environments in big-data-driven urban geopolitics require digital twin simulation modeling, spatial computing technology, and Internet of Things sensors and actuators.[13,14,15]
Smart sustainable city governance necessitates virtual simulation tools, sensor data fusion, and geospatial mapping technologies.[16,17,18]
Multi-sensor data fusion algorithms, spatial computing technology, and virtual simulation tools are pivotal in simulated 3D environments across sustainable urban governance networks.[19,20,21,22]
Networked sustainable urban technologies, Internet of Things sensing infrastructures, and deep-learning-based computer vision algorithms are instrumental in immersive hyperconnected virtual spaces in smart city governance.[23,24,25]
Spatiotemporal fusion algorithms, cyber-physical cognitive systems, and virtual twin modeling tools configure sustainable urban governance networks.[26,27,28]
Immersive 3D environments in urban digital twins necessitate spatial data visualization tools, virtual modeling technology, and blockchain-enabled Internet of Things networks.[29,30,31]
Immersive interactive environments in data-driven smart sustainable cities require virtual twinning techniques, deep-learning-based sensing and image recognition technologies, and data modeling and simulation tools.[32,33,34]
Digital twin simulation technologies, cognitive data mining algorithms, and urban analytics tools enable extended reality environments in cognitive smart cities.[35,36,37]
Cognitive smart cities require remote sensing data, virtual navigation tools, and visualization modeling technologies.[38,39,40]
Cloud computing analytics, urban logistics networks, and digital twin technologies articulate blockchain-based virtual worlds in sustainable smart cities.[41,42,43,44]
Cognitive automation technologies, blockchain-enabled Internet of Things networks, and virtual data modeling tools assist data-driven smart sustainable urbanism.[45,46,47,48]
Spatial computing technologies, digital twin simulation, and synthetic sensing devices are instrumental in immersive and decentralized 3D digital worlds in smart and sustainable urban systems.[49,50,51,52]
Sensing and computing technologies, virtual simulation tools, and cognitive artificial intelligence algorithms configure urban digital twins.[1,16,29]
Urban simulated environments necessitate virtual twin modeling tools, sensor data fusion, and deep neural network technology.[7,20,32]
Real-time Internet of Things data, immersive visualization systems, and geospatial mapping tools optimize smart sustainable city governance.[13,34,41]
Remote sensor networks, digital twin modeling, and urban computing technologies are instrumental in data-driven smart sustainable urbanism.[4,25,37]
Immersive and decentralized 3D digital worlds in smart sustainable city governance require spatial data visualization tools, remote sensing technologies, and data simulation algorithms.[3,12,35]
Geospatial analytics tools, digital twin technologies, and Internet of Things sensing infrastructures shape blockchain-based virtual worlds in smart sustainable city governance.[6,23,38]
Spatiotemporal fusion algorithms, virtual simulation tools, and visual modeling technologies assist sustainable urban governance networks.[9,22,50]
Sustainable smart cities integrate virtual twin modeling tools, deep-learning-based ambient sound processing, and geospatial data mining.[10,18,45]
Table 3. Synopsis of evidence concerning digital twin simulation tools in sustainable urban governance networks (research findings).
Table 3. Synopsis of evidence concerning digital twin simulation tools in sustainable urban governance networks (research findings).
Three-dimensional city modeling, virtual simulation tools, and geospatial mapping technologies configure data-driven smart sustainable urbanism. Intelligent sensor networks, machine learning techniques, and ambient sound recognition software configure immersive hyperconnected virtual spaces in digital twin cities.[1,2,3]
Data mining tools, Internet of Things sensing infrastructures, and digital twin simulations articulate virtual urban environments.[4,5,6]
Internet-of-Things-based smart city environments require cognitive data fusion techniques, deep-learning-based sensing technologies, and predictive simulation tools.[7,8,9]
Spatial cognition algorithms, digital twin simulation modeling, and smart Internet of Things devices enable big-data-driven urban geopolitics.[10,11,12]
Digital twin simulation and modeling tools, Internet of Things sensing infrastructures, and geospatial data mining further smart and environmentally sustainable cities.[13,14,15]
Big-data-driven urban analytics leverages virtual simulation tools, digital twin networks, and remote sensing technologies.[16,17,18]
Urban big data analytics, remote sensing systems, and virtual simulation modeling tools assist smart city digital twins.[19,20,21,22]
Digital twin simulation, remote sensing technologies, and spatial computing algorithms enable augmented reality-powered immersive spaces in urban digital governance.[23,24,25]
Table 4. Synopsis of evidence concerning spatial cognition algorithms in sustainable urban governance networks (research findings).
Table 4. Synopsis of evidence concerning spatial cognition algorithms in sustainable urban governance networks (research findings).
Data-driven Internet of Things systems, cloud-based digital twins, spatial cognition algorithms, and immersive virtual technologies configure immersive 3D environments.[26,27,28]
Three-dimensional digital environments in smart city governance necessitate visual sensing devices, spatial cognition algorithms, and geospatial mapping technologies.[29,30,31]
Urban remote sensing data, cognitive digital twins, and data simulation and prediction tools assist immersive virtual worlds.[32,33,34]
Smart city analytics harnesses simulation modeling tools, urban sensing technologies, and spatial cognition algorithms.[35,36,37]
Deep-learning-based sensing technologies, spatial cognition algorithms, and environment perception mechanisms configure digital twin cities.[38,39,40]
Spatial cognition algorithms, 3D modeling and visualization tools, and urban sensing technologies shape big-data-driven urban geopolitics.[41,42,43,44]
Virtual-reality-based visualization environments in smart city digital twins require visual perception sensors, cognitive data fusion techniques, and spatial computing algorithms.[45,46,47,48]
Cognitive data visualization tools, predictive control algorithms, and urban spatial planning tools are instrumental in shared virtual environments across digital twin cities.[49,50,51,52]
Table 5. Synopsis of evidence concerning multi-sensor fusion technology in sustainable urban governance networks (research findings).
Table 5. Synopsis of evidence concerning multi-sensor fusion technology in sustainable urban governance networks (research findings).
Internet-of-Things-based smart city environments require urban network infrastructures, data mining and fusion technology, and spatial data visualization tools.[1,16,29]
Virtual data analytics leverages urban sensing and visual immersion technologies, data modeling and simulation tools, and image data fusion techniques.[7,20,32]
Augmented reality algorithms, ambient sound recognition software, and data fusion technologies optimize smart networked environments in 5G-enabled smart cities.[13,34,41]
Urban big data analytics harnesses digital twin technologies, smart data modeling, and multi-sensor environment data fusion tools.[4,25,37]
Sensor data fusion, visual recognition tools, and edge and cloud computing technologies configure digital twin cities.[3,12,35]
Multisource remote sensing data fusion, real-time predictive analytics, and 3D urban modeling tools articulate virtual simulation environments in digital twin cities.[6,23,38]
Digital twin simulation modeling, deep-learning-based sensing technologies, and urban data fusion optimize Internet-of-Things-based smart city environments.[9,22,50]
Internet of Things digital twins, spatial cognition algorithms, and multi-sensor environment data fusion are instrumental in smart urban governance.[10,18,45]
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Nica, E.; Popescu, G.H.; Poliak, M.; Kliestik, T.; Sabie, O.-M. Digital Twin Simulation Tools, Spatial Cognition Algorithms, and Multi-Sensor Fusion Technology in Sustainable Urban Governance Networks. Mathematics 2023, 11, 1981. https://doi.org/10.3390/math11091981

AMA Style

Nica E, Popescu GH, Poliak M, Kliestik T, Sabie O-M. Digital Twin Simulation Tools, Spatial Cognition Algorithms, and Multi-Sensor Fusion Technology in Sustainable Urban Governance Networks. Mathematics. 2023; 11(9):1981. https://doi.org/10.3390/math11091981

Chicago/Turabian Style

Nica, Elvira, Gheorghe H. Popescu, Milos Poliak, Tomas Kliestik, and Oana-Matilda Sabie. 2023. "Digital Twin Simulation Tools, Spatial Cognition Algorithms, and Multi-Sensor Fusion Technology in Sustainable Urban Governance Networks" Mathematics 11, no. 9: 1981. https://doi.org/10.3390/math11091981

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