# Unleashing the Potential of 5G for Smart Cities: A Focus on Real-Time Digital Twin Integration
## 2 Current Trends for 5G in Smart Cities
### Existing Applications of 5G in Smart Cities
To simulate this network, a computational model was employed using a probabilistic graph-based approach, which mirrors how IoT devices might establish communication links in practice. The network was generated using a simulation where 20 sensor nodes were randomly placed within a defined area, with their positions defined within a two-dimensional area. Each node is assigned to a unique pair of X and Y coordinates to reflect the varied geographic deployment. The connectivity between these sensors was established using a fixed probability-based approach, meaning that each sensor had a 30% chance of being connected to any other sensor in this case. This is used to reflect the real-world uncertainty and dynamic nature of wireless links in urban environments, which can be affected by physical obstructions, interference, or transmission range limitations. The data were stored in an adjacency matrix, a mathematical structure used to define whether nodes are directly connected. The matrix was then used to construct an undirected graph representing the communication network. The visual output not only maps out the spatial layout of the sensor nodes but also provides an intuitive understanding of how urban IoT systems might self-organize and maintain real-time communication. IoT devices in a network are effortlessly combined to oversee and control urban systems in real time [20; 32; 33]. This network serves as the foundation for digital twins, allowing for the virtual duplication of the city's infrastructure and dynamics by delivering precise real-time data from physical sensors [32; 33; 34; 35]. The extensive implementation of 5G technology improves this ecosystem by providing ultra-low-latency and high-speed communication, facilitating rapid data transfer between the sensors and the analytical systems [33; 35]. Collectively, these technologies facilitate a more intelligent resource distribution, anticipatory maintenance, and enhanced urban living, emphasizing the collaboration among IoT, digital twins, and 5G in defining the future of smart cities [32; 33; 35]. Before the rollout of 5G, digital twins and real-time data models often encountered delays and data inconsistencies due to slower network speeds and their limited communication capacity. This affected the accuracy and timeliness of simulations, making it difficult to forecast urban dynamics effectively. 5G's rapid data transfer capabilities ensure the smooth integration of data from multiple IoT sensors into digital twin models, allowing for more accurate and timely predictions of urban behavior. The ultra-low latency of 5G ensures that these predictions can be acted upon almost immediately, enabling smarter decision-making and improving the standard of living in urban areas. Real-time environmental monitoring in smart city infrastructure is illustrated in Figure 3 by a connected network of IoT sensors powered by 5G [33; 37; 38; 39]. Each node represents a sensor collecting data concerning air quality, temperature, or traffic information [33; 37]. The edges indicate strong low-latency 5G links that facilitate uninterrupted communication [37; 38; 39]. Spatial differences in environmental conditions are accentuated by the heatmap overlay, facilitating dynamic data-driven insights [38; 39]. This representation corresponds with digital twin technology by presenting a virtual model of urban areas, enabling predictive simulations and effective city governance [9; 13; 38]. Through the incorporation of 5G, the system provides scalable, dependable, and high-velocity data transfer for the consistent functionality of smart city environments in real-time [33; 37; 38; 39]. Figure 2: 5G IoT device connectivity: urban sensor network expansion [32; 33; 36]. Figure 3 was generated through a MATLAB R2024b simulation designed to reflect the operational realities of a 5G-enabled wireless sensor network in an urban environment.