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Engineering the Future: Skills for Tomorrow’s Workforce

Cities worldwide face mounting pressures from population growth, traffic congestion, infrastructure strain, and sustainability mandates. Smart-city technologies – combining data, sensors, and digital models are seen as key tools for addressing these challenges. Scholars observe that modern smart-city strategies focus on harnessing real-time data and connectivity to make “better decisions and improve quality of life”. In practice, this means creating integrated urban systems where traffic flows, energy use, public services, and environmental factors are monitored and optimized through ICT (information and communication technology). For example, advanced projects now use 3D data and Internet-of-Things (IoT) networks to model entire cities. According to the World Economic Forum, a digital twin city is “a virtual replica of a physical city that enables simulation, monitoring, and control of complex urban scenarios”. Such city- scale models allow planners to test interventions virtually (e.g. simulating flood response or traffic rerouting) before implementing them in the real world.

Smart cities rely on integrated data and virtual models for planning. Digital twins (see example illustration) fuse GIS, IoT sensor feeds and analytics into a live urban model. Cities using these tools can forecast outcomes of policies and optimize resources sustainably.

As one case shows, Singapore began scanning its entire island in 2012 to create “Virtual Singapore”, the first national-level digital twin. By 2023 this 3D model – maintained by government agencies – is used for flood risk analysis, infrastructure management, and even underground utility mapping. Such initiatives underscore how smart-city planning increasingly depends on data science and engineering expertise. However, implementing these complex technologies is not trivial: urban planners must overcome high setup costs, fragmented data standards, and the need for cross-disciplinary skills. Many cities still struggle to integrate legacy infrastructure into real-time systems.

Importantly, as one study of Tallinn (Estonia) notes, cities everywhere face the same core issues – from overpopulation and traffic to energy efficiency – and smart-city collaboration is a common response. This suggests a global convergence on tech-driven solutions. Yet universities in many regions have not fully caught up. To meet this opportunity, academic programs in engineering, urban planning, and computer science must incorporate smart-city models (e.g. the ISO 37120–based Smart City Maturity frameworks) and give students hands-on experience with digital twin tools. The proposed Center of Excellence will position itself as a crucial partner in this transformation, linking academia directly with municipalities and industry leaders to build the next generation of urban innovators.