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

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