# Unleashing the Potential of 5G for Smart Cities: A Focus on Real-Time Digital Twin Integration
## 3 Emerging Challenges in Smart City Deployments  
Building upon the limitations outlined in the previous section, this section explores the broader emerging challenges that impact the successful deployment of smart city technologies. The introduction of smart city technologies, although providing revolutionary urban management solutions, encounters various challenges that need to be resolved for their successful and extensive implementation. A key concern is scalability, especially in heavily populated city areas where millions of devices are linked through IoT systems [10, 36, 51]. With the rise in connected devices, network infrastructure frequently faces challenges in sustaining reliability and low latency, resulting in bottlenecks that hinder real-time decision-making abilities [32, 33, 35, 36]. Songdo, South Korea, exemplifies a smart city that has effectively addressed the scalability challenges linked to IoT networks [58, 59]. The city has incorporated millions of interconnected devices that demand significant network resources to guarantee smooth communication and instant decision-making capabilities. The infrastructure of Songdo is built to manage data from multiple sources, including smart buildings, transport networks, and environmental sensors, utilizing a strong IoT framework [58, 59]. An essential approach for Songdo in addressing scalability challenges is the implementation of a collaborative communication strategy across business networks [58, 59]. Through the implementation of technologies such as distributed multi-user detection systems, Songdo has greatly improved its network dependability, minimizing congestion and bottlenecks that frequently arise in densely populated metropolitan regions. This guarantees that data transition smoothly, even amidst high-demand intervals. Songdo's method emphasizes dynamic load balancing, wherein network resources are smartly allocated according to real-time demand, enabling the city to sustain low latencies and high availability within its IoT networks [58, 59]. These approaches enhance Songdo's capacity to handle the extensive array of devices and applications in its smart city environment, showcasing how scalability can be successfully managed in highly populated urban settings. Thus, ensuring reliable connectivity in extensive IoT implementations demands significant infrastructure improvements and resource distribution [33, 35, 36]. The distribution of 5G infrastructure costs across key urban sectors in urban digital-twin smart cities is depicted in Figure 8. The Residential sector accounts for the largest share at 35%, followed by Commercial at 25% and Transport at 15%, reflecting the priority toward connectivity and digital services. Smaller shares are allocated to Healthcare (10%), Education (8%), and Public Services (7%), highlighting a balanced investment approach to enhance urban functionality and smart city objectives. The data used for this visualization are based on a reasonable allocation model of approximation rather than real-world empirical values to highlight key investment areas. If precise cost distributions are required, further validation using updated industry reports and financial studies would be necessary. Factors such as population density, demand for connectivity, and sector-specific digital transformation goals need to be considered for better accuracy [60, 61, 62]. Differences may occur due to regional variations in urban development approaches and changing rates of technology adoption. Figure 8 provides a conceptual representation of the cost distribution of 5G infrastructure across various urban sectors within the context of urban digital twins and smart cities [33, 60, 63, 64]. The purpose of this figure is to illustrate the relative importance of different sectors in 5G deployment rather than to present an exact financial breakdown. Smart city infrastructure, particularly those utilizing 5G networks, require significant energy to operate base stations, edge computing devices, and user-end equipment [36; 55].