Navigating the Path to Smart and Sustainable Cities: Insights from South Korea’s National Strategic Smart City Program

Abstract

This study evaluates the progress of Korea’s National Strategic Smart City Program (NSSCP), a flagship R&D initiative, in advancing sustainable and intelligent urban development on a global scale. Utilizing the United Nations’ United for Smart Sustainable Cities (U4SSC) framework, which integrates both sustainability and smartness in city development, this research examines the program’s alignment with global standards. The findings reveal that the NSSCP contributes to the attainment of the Sustainable Development Goals (SDGs) in areas such as health, energy, innovation, and sustainable communities. It also effectively addresses key dimensions of smart cities, including smart living, environmental stewardship, mobility, and economic vitality. Despite these achievements, this study identifies critical challenges, such as the absence of robust evaluation tools and an overemphasis on quantitative targets. This research is important in advancing the discourse on smart city development, offering insights into the efficacy of smart services and systems through the lens of the NSSCP’s cloud-based open data hub model.

1. Introduction

1.1. Research Background

The global transition toward smart cities is accelerating, with many countries actively developing national strategies. Notably, G20 nations have announced formal smart city initiatives [1]. Since 2017, South Korea has launched numerous smart city projects, building on earlier efforts under the “Ubiquitous City (U-City)” framework. Among these, the National Strategic Smart City Program (NSSCP) stands out as the largest and most recent initiative led by the central government. Implemented over five years (2018–2022), the NSSCP was coordinated by the Ministry of Land, Infrastructure, and Transport (MOLIT) and the Ministry of Science and ICT (MSIT), with a total investment of approximately USD 101 million. At its core, the NSSCP aimed to establish a centralized data hub as the foundation for smart city development and to pilot cutting-edge technologies in two major urban areas: Daegu Metropolitan City (Gyeongsang Province) and Siheung City (Gyeonggi Province).

Smart cities have emerged as potential solutions to the challenges of urban sustainability. However, it remains unclear whether smart city initiatives effectively lead to environmental, economic, and social sustainability outcomes. This uncertainty stems from the lack of holistic evaluations assessing the actual sustainability impacts of smart city projects [2]. Nevertheless, analyzing smart cities through the lens of sustainability is essential to ensure their long-term viability and to maintain a balance across environmental, social, and economic dimensions. In particular, this underscores the importance of integrating sustainability into smart city frameworks to address the complex challenges of urbanization effectively [3]. Trindade et al. [4] also emphasizes the need for forward-looking studies to examine the critical question of whether the smart city concept and its practices can truly contribute to urban sustainability.

Against this backdrop, the present study aims to assess whether the NSSCP, South Korea’s flagship smart city initiative, is progressing in a sustainable direction. Although 13 notable smart city projects have been implemented in South Korea [5], none have been evaluated from a sustainability-oriented perspective.

1.2. Related Studies and Research Purpose

There are relatively few studies that comprehensively analyze the NSSCP. Lee and Park [6] provide a general overview of the outcomes from smart city pilot projects and suggest directions for the expansion of data-driven smart cities in South Korea. Yang et al. [7], who conducted a more detailed analysis, compared the NSSCP with smart city initiatives in other countries, focusing on service domains. They found that, while leading global cities typically provide six core services—smart grids, renewable energy, parking management, 3D city models, and citizen engagement platforms—South Korea emphasizes the deployment of advanced communication technologies and data analytics (e.g., electricity demand forecasting and fine dust monitoring), along with the development of emerging technologies such as autonomous driving. The NSSCP has concentrated on delivering services in transportation, living, and built infrastructure, thereby reinforcing South Korea’s strengths in related core technologies.

However, the authors point out that South Korea’s traditionally top-down approach to smart city development, led primarily by the central government, has resulted in limited initiative and adaptability among service providers. Lim and Kim [8] also examined the NSSCP using the Stage-Gate model, a conceptual and operational framework to guide new product development from idea to launch. Their study suggests that large-scale transformation programs like the NSSCP could benefit from adopting more market-oriented Stage-Gate models to improve the investment efficiency, enhance the research quality, and support successful demonstrations and commercialization.

While these studies offer valuable insights, their analyses of the NSSCP remain largely at the micro level. As previously noted, a more comprehensive evaluation of whether smart city initiatives contribute meaningfully to sustainable urban development is essential in informing effective smart city policies and implementation strategies. Moreover, given the global proliferation of smart city projects, understanding their successes and limitations is critical in shaping future improvements [9]. As Li et al. [10] emphasize, systematic evaluation plays a vital role in guiding and fostering the development of smart cities. Nevertheless, the current evaluation efforts remain in their early stages, often focusing on isolated aspects and relying on indicators with limited scalability. These evaluations also tend to lack alignment with widely accepted and interoperable smart city frameworks [10].

Against this backdrop, this study aims to address the following research question: How effective is South Korea’s smart city promotion strategy in enhancing sustainability and smartness in urban areas? To answer this question, this study critically evaluates the outcomes of the NSSCP using the United for Smart Sustainable Cities (U4SSC) framework—a global initiative led by international organizations such as the International Telecommunication Union (ITU), the United Nations Economic Commission for Europe (UNECE), and UN-Habitat. Specifically, this study assesses the extent to which the NSSCP aligns with the Key Performance Indicators (KPIs) established by U4SSC. This evaluation involves analyzing the goals, content, and anticipated outcomes of the NSSCP’s 13 projects to determine their effectiveness in meeting U4SSC’s KPIs.

To achieve this, this study follows the research process illustrated in Figure 1.

2. Materials and Methods

2.1. Research Target: National Strategic Smart City Program in South Korea

Korea’s smart city development began in the early 2000s with the Ubiquitous City (U-City) project, focused on new towns like Hwaseong, Dongtan, and Songdo. Initiated by the public sector, the project was supported by the 2008 U-City Act, which aimed to streamline the construction and management of these cities. However, the concept of smart cities has since evolved, with the private sector now playing a pivotal role in ongoing innovation and technology integration. Smart city development has become a shared objective, essential for both new and existing urban areas [11].

Korea’s smart city policy has progressed through several stages. The first stage, up to 2013, involved the U-City project, which integrated ICT with urban development. This phase included the U-Eco City R&D project, funded at USD 84.49 million, to develop basic services, technology, and platforms. The second stage (2014–2017) focused on enhancing infrastructure utilization through projects like the Smart City Information R&D project, which aimed to develop intelligent urban infrastructure. During this period, the Smart City Integrated Platform (SCIP) was introduced, providing cloud-based services for emergency and disaster management across municipalities. The third stage, from 2018 onwards, expanded the scope to include new concepts like testbeds, living labs, and fourth industrial revolution technologies. The government’s “Korean New Deal” initiatives, including the 2020 Digital New Deal, emphasize data-driven urban management and innovation. This stage marks a shift toward a more inclusive and globally connected smart city ecosystem [11,12,13] (see Figure 2).

Korea defines a smart city as a platform leveraging fourth industrial revolution technologies to enhance quality of life, sustainability, and new industries. The government supports this through substantial investment and deregulation, with 78 local governments actively participating in smart city projects. The national smart city policy is guided by three visions: solving urban problems through advanced technology, developing inclusive cities, and fostering global collaboration. These are supported by four strategic goals and a five-year roadmap [12].

The National Strategic Smart City Program (NSSCP) was a major R&D initiative with a USD 101 million budget, running from 2018 to 2022. Funded by the government, local authorities, and the private sector, it involved 132 institutions and 1400 participants. The program aimed to develop data-driven smart cities that address urban challenges, improve quality of life, and promote sustainable economic growth. Key projects included developing a data hub model; implementing use cases in transportation, safety, and public administration; and conducting living lab demonstrations in the energy, environment, and welfare sectors. These efforts were expected to contribute significantly to Korea’s digital transformation under the New Deal (see

Table 1. Summary of the National Strategic Smart City Program.

Category	Project Title	Details	Keywords
1. Development of Smart City Model and Base Technology	Open Data Hub Architecture and Core Technology	Design of cloud-based open data hub architecture model to collect, process, and store data with standard data models and interfaces	Data Hub
	B. Massive Real-Time IoT Infrastructure and Network Technology	Development of intelligent IoT devices, infrastructure enhancement, network establishment, and control technology for massive IoT data (transportation, environment, energy, safety) processing in various communication environments	Massive IoT
	C. Digital Twin Smart City Service Virtualization Technology	Using virtual platform technology development for rendering and real-time synchronization of data-hub-collected data in digitalized virtual space	Digital Twin
	D. Smart City Project Management, Evaluation Model, and Cooperation Program	Developing a model to manage the smart city R&D project, as well as creating a system for the accumulation and spread of knowledge to implement the project successfully	R&D Management
2. Citizen-Centric Service Enhancement (Use Case Model)	Smart Mobility and Smart Parking Service Technology	Providing personalized smart mobility services that aim to mitigate traffic congestion on roadways and enhance user convenience in public and private transportation	Mobility
	B. Data-Sharing Safety Technology (Natural Disaster in Urban Areas and Emergency Rescue Technology)	Development of disaster real-time collection, real-time prediction/analysis/sharing system, and rescue services	Safety (Disaster and Emergency Management)
	C. Data Hub Center and City Administration Technology	Considering the status of Daegu Metropolitan City, the development and operation of the data hub center for use case services and citizen participation	Data Hub and Urban Administration
	D. Data-Based Smart City Use-Case Development for Solving Urban Problems with Citizen Participation	Specific service solutions development and real-life verification through citizen participation using design thinking methodology for global competitiveness	Citizen Participation
3. Technology Innovation and Business Intelligence (Living Lab Model)	Crowdsourcing Urban Air Quality Measurement and Forecasting Technology	2D/3D analysis information mapping and forecasting technology based on crowdsourcing, development of analysis technology for pollution sources, and information provision system	Sustainable Environment
	B. Integrated Energy Management System (Xems) for Home/Building/Factor/Public Facilities	Development and demonstration of integrated operation technology to improve the energy efficiency of the city	Total Energy Management System
	C. Total Care System for the Elderly Living Alone and Mobility Assurance System for the Disabled	Demonstration of living labs by developing and deploying a total care service platform for the elderly inside and outside the office	Social Health Care
	D. Open Data Hub Platform Based on the Living Lab Innovation Model	Build and demonstrate a data hub platform based on open data hub architecture	Data Hub
	E. Smart City Business Model Based on Needs in Local Society	Establishment of a smart city business model and support system for the industrial competitiveness of Siheung City	Business Creation and Citizen Participation

Source: Modified based on KAIA [14].

).

2.2. Theoretical Framework: United 4 Smart Sustainable Cities (U4SSC) Initiative

Smart cities have begun to play a central role in the sustainable development agenda of major economies, including the European Union [15]. The U4SSC initiative defines a smart sustainable city as “an innovative city that uses ICT and other means to improve quality of life, the efficiency of urban operations and services, and competitiveness, while ensuring that it meets the needs of present and future generations with respect to economic, social, environmental, and cultural aspects” [16]. This definition places ICT at the core of achieving urban sustainability—potentially, however, at the expense of the broader, multidimensional understanding of sustainability [17].

According to Schraven et al. [18], the concepts of the “sustainable city” and “smart city” form a conceptual duopoly, frequently appearing together and highlighting the complexity of their interrelation within sustainable urbanism. Theoretically, the vision of smart cities aligns with the goals of sustainable development [19]. Smart cities oriented toward sustainability offer a pathway to enhance both urban competitiveness and sustainability [20], while also supporting socioeconomic development and addressing environmental challenges [21].

Shao and Min [22] propose a four-pillar framework—environment, society, economy, and governance—to describe and integrate smart cities, further illustrating how these cities embody the principles of sustainability. Moreover, the concept of smart sustainable cities is inherently human-centered, involving the multidimensional integration of people and digital technologies and pointing to the likely trajectory of future urban development worldwide.

A credible and verifiable assessment framework that enables the tracking, analysis, and evaluation of the multidimensional performance of smart city development is a core component of integrated smart city management [23]. While numerous assessment tools for smart cities already exist, the need for more refined frameworks continues to grow as our understanding of smart cities evolves [17].

This raises a critical question: what metrics and standards should be used to evaluate smart and sustainable cities? International organizations such as the International Organization for Standardization (ISO), the International Telecommunication Union Telecommunication Standardization Sector (ITU-T), and the ISO/IEC Joint Technical Committee 1 (JTC 1) have made efforts to standardize the evaluation of smart city performance [24]. Among these, the ITU-T has taken a leading role by developing a standardized definition of smart sustainable cities and coordinating the development of related performance indicators.

The ITU’s U4SSC initiative offers one of the most balanced approaches to integrating sustainability and smartness in urban performance assessment [25]. Jointly led by the ITU and the UNECE, U4SSC has developed a comprehensive KPI manual that explicitly links smart city evaluation to the SDGs [26]. These KPIs serve as criteria for the assessment of the contribution of ICT to urban sustainability and smartness, while also providing a standardized framework for cities to conduct self-assessments.

To date, more than 100 cities worldwide have begun implementing the U4SSC KPIs. Designed to ensure consistency and comparability, these indicators help cities to collect standardized data, measure performance, and track progress toward the SDGs. In addition to enabling longitudinal performance evaluations, the KPI framework facilitates the exchange of best practices among cities. Furthermore, these evaluations serve as baselines in measuring urban progress toward achieving the SDGs [27].

The U4SSC KPI framework is built upon four key criteria: comprehensiveness, availability, simplicity, and timeliness. The indicators are designed to cover all essential aspects of a smart and sustainable city. They are quantitative in nature, with historical and current data either readily available or easily collectible. Each indicator is conceptually straightforward and intended to be easily understood by a broad range of urban stakeholders. The framework also emphasizes adaptability, ensuring that indicators can be generated in response to emerging challenges in smart and sustainable urban development.

The KPI framework includes a total of 91 indicators, divided into 54 core and 37 advanced indicators. The core indicators are mandatory for all participating cities and provide a fundamental overview of a city’s smartness and sustainability. In contrast, the advanced indicators offer a more nuanced assessment of cities that have implemented more sophisticated initiatives. Additionally, the indicators are categorized into three thematic groups: smart (20 indicators), structural (32 indicators), and sustainable (39 indicators) (see

Table 2. KPI structure.

Dimension	Sub-Dimension	Category
Economy	ICT	ICT Infrastructure Water and Sanitation Drainage Electricity Supply Transport Public Sector
	Productivity	Innovation Employment
	Infrastructure	Water and Sanitation Waste Electricity Supply Transport Buildings Urban Planning
Environment	Environment	Air Quality Water and Sanitation Waste Environmental Quality Public Space and Nature
	Energy	Energy
Society and Culture	Education, Health, and Culture	Education Health Culture
	Safety, Housing, and Social Inclusion	Housing Social Inclusion Safety Food Security

Source: Modified based on Smiciklas [27].

) [27].

The U4SSC initiative is conducting case studies in cities worldwide to evaluate the feasibility of its indicators and to support the development of a global smart sustainable city index [28]. Integrating the U4SSC framework into national project evaluations offers a standardized, internationally recognized approach that aligns local implementation with global sustainability benchmarks. This integration ensures that smart city development is not only strategic but also inclusive and globally relevant.

2.3. Application of the Theoretical Framework and Data Collection

To answer the research question, this study assesses the extent to which the NSSCP aligns with the 91 KPIs of U4SSC. It gauges the achievement of these KPIs by examining the goals, content, and likelihood of achieving planned outcomes within the NSSCP’s 13 projects.

For instance, within the category of “transport”, which falls under the “infrastructure” sub-dimension of the “economy” dimension, there exist eight KPIs: public transport network, public transport network convenience, bicycle network, transportation mode share, travel time index, shared bicycles, shared vehicles, and low-carbon emission passenger vehicles. This study conducts a detailed analysis of the definitions, descriptions, and methodologies of these eight KPIs to determine whether the goals, contents, and planned outcomes of Project 2A within the NSSCP align with them.

To conduct this evaluation, this study employed in-depth interviews as the primary data collection method. Through a snowball sampling method, a total of 17 key informants were selected to provide insights into the research questions. To respect the wishes of key informants who requested anonymity, their identities were kept confidential throughout the study. Semi-structured interviews were conducted to ensure the comprehensive collection of essential information, all of which took place in face-to-face settings. In the case of Category 1 projects, which are considered foundational within the NSSCP, two individuals were interviewed per project, while, in Categories 2 and 3, one person was interviewed per project. The interviewees represented officials from 11 organizations, including Category 1—Korea Electronics Technology Institute, Electronics and Telecommunications Research Institute, University of Seoul, Korea Institute of Civil Engineering and Building Technology; Category 2—Korea Transport Institute, Korea Land and Housing Corporation, SK Telecom Co., Ltd., University of Seoul; and Category 3—KT Corporation, Korea Electric Power Corporation, Korea Electronics Technology Institute, Korea Advanced Institute of Science and Technology, Advanced Institute of Convergence Technology, and others. The interview period spanned a total of six months, from May to October 2021.

The results of the analysis indicate that 8 out of the 13 projects within the NSSCP align with 13 of the 91 KPIs set by the U4SSC framework. Specifically, 7 out of 45 KPIs (16%) within the “economy” dimension, 4 out of 17 KPIs (24%) within the “environment” dimension, and 2 out of 29 KPIs (7%) within the “society and culture” dimension were achieved.

Table 3. The list of KPIs by sector and the corresponding projects in the NSSCP.

Dimension (No. of KPIs)	Sub-Dimension (Total No.)	Category	Relevant KPIs	Definition and Description	Project
Economy (45)	Productivity (2)	Innovation	R&D Expenditure Small and Medium-Sized Enterprises	Research and development expenditure as a percentage of city GDP Percentage of SMEs	All, 3E
	Infrastructure (6)	Transport	Public Transportation Network Public Transportation Convenience Transportation Mode Share	Length of public transport network per 100,000 inhabitants Percentage of the city population that has convenient access (within 0.5 km) to public transport The percentage of people using various forms of transportation to travel to work	2A
	ICT * (6)	Electricity Supply	Smart Electricity Meters Electricity Supply ICT Monitoring	Percentage implementation of smart electricity meters Percentage of electricity supply system monitored by ICT	3B
Environment (17)	Energy (1)	Energy	Electricity Consumption Residential Thermal Energy Consumption Public Building Energy Consumption	Electricity consumption per capita Residential thermal energy consumption per capita Annual energy consumption of public buildings
	Environment (5)	Air Quality	Air Pollution	Air quality index based on reported values for PM10, PM2.5, NO2, SO2, O3	3A, 2B, 3D
Society and Culture (29)	Education, Health, and Culture (3)	Health	Electronic Health Records	The percentage of city inhabitants with complete health records electronically accessible to all health providers	3C, 1A
	Safety, Housing, and Social Inclusion (4)	Safety	Emergency Service Response Time	Average response time for emergency services	2B
Inaccessible Field	Economy: ICT Infrastructure, Water and Sanitation, Drainage, Transport, Public Sector/Employment/Water and Sanitation, Waste, Electricity Supply, Buildings, Urban Planning Environment: Water and Sanitation, Waste, Environment Quality, Public Space, Nature Social and Culture: Education, Culture/Housing, Social Inclusion, Food Security

* The “electricity supply” category in the “economy” dimension is discussed with the “energy” category of the “environment” dimension because the project to be analyzed is the same. Source: Modified based on ITU and UNECE [26].

provides a list of the corresponding NSSCP projects that align with the U4SSC KPIs. This study conducts an in-depth analysis of the projects that meet these KPIs across eight categories.

3. Results

This study analyzed the sectors measurable within the NSSCP and aligned them with the KPIs of the U4SSC framework. The identified sectors include the economy (innovation and transportation), the environment (energy and air quality), and society and culture (health and safety).

3.1. Economy

3.1.1. Innovation

The NSSCP is a large-scale R&D project undertaken as part of a national strategic initiative in South Korea. The project has received a total R&D investment of USD 75.1 billion, combining contributions from the Korean government and the private sector. This investment represents 4.64% of South Korea’s GDP, positioning it as the second-largest country in the world, after Israel, with 4.94% of its GDP allocated to R&D [29].

Of this total investment, the Korean government’s R&D in the smart city field grew at an average annual rate of 16.8% from 2014 to 2016. This result is based on a search conducted by the Korea Institute of S&T Evaluation and Planning (KISTEP) that identified projects related to smart cities, smart energy, smart buildings, smart transportation, smart safety, and smart administration using the National Science and Technology Information Service (NTIS). In particular, there has been a significant increase since 2015, coinciding with the emergence of the fourth industrial revolution [30].

This R&D project had a budget of approximately USD 118 million, accounting for only 0.15% of the total R&D expenditure. In comparison, the European Union invests over USD 674 million annually in various R&D programs, including the European Innovation Partnership on Smart Cities and Communities (EIP-SCC) and Horizon 2020. In the United States, private companies lead in technology, while the federal government focuses on developing original technology. The Biden–Harris administration announced plans to invest USD 2 trillion in smart cities, while China has declared an investment of more than USD 421.76 billion in smart cities since 2013. Given these trends and the size of Korea’s economy, an annual investment of over USD 252.9 million in developing core technology for smart cities is necessary. Notably, the Korean government’s R&D efforts in digital twins, AI of Things (AIoT), cloud–edge computing technology, and urban informatics are still limited [31]. Against this backdrop, this project’s significance lies in its contribution to smart technology research and development in various fields, promoting the development of smart cities in Korea.

The 3D project developed smart city business and service models based on the local demands of a demonstration city (Siheung) and promoted new industries using smart city data. A smart city platform was created through the plan, with top-down and bottom-up projects, to provide local governments with various solutions to the problems that they wished to solve, with a strong focus on encouraging SME participation. In total, 14 out of 22 companies participating in the 3E project from 2019 to 2021 were SMEs.

One of the services developed through this initiative was a fine dust monitoring system based on light detection and ranging (LiDAR). This is the first in the world to use scanning LiDAR for ultrafine dust concentration measurements, with a resolution of 30 m and a radius of 5 km. This was developed through a collaboration between two state universities in Busan and Daejeon (Pukyong National University and Hanbat University) and Samwoo TCS Co., Ltd., an SME [32].

Moreover, the project aimed to create a smart daycare center model that addressed the heavy workload of childcare providers and ensured children’s safety through the use of smart technology. Three SMEs were involved in the development of this model. It provides AI and IoT-based customized education services that discover infant and toddlers’ talents and nurture creative talent suitable for the future society. Characteristic data are collected through intelligent CCTV, tracking technology, and facial recognition technology. Based on these technologies, the model creates a child-centered and play-centered customized childcare environment and prevents accidents. Additionally, it utilizes IoT-based smart devices, such as air purifiers that block fine dust and airborne bacteria and automatic thermal imaging cameras to prevent infection risks and predict health abnormalities. It also creates a comfortable indoor environment by smartly adjusting the heating, cooling, ventilation, and lighting. Finally, the model focuses on providing opportunities for children to grow and commune with nature, addressing the limitations of technology-oriented smart systems [33,34] (see Figure 3).

3.1.2. Transport

This R&D project placed a significant emphasis on smart transportation. The objective of the 2A project was to improve the convenience of public transportation and personal mobility through smart mobility and parking services and to tackle traffic congestion in the city center by promoting public transportation.

According to the in-depth interview with the Project Manager (PjM) of the 2A project, the smart mobility service provides personalized mobility services based on individual behavioral analysis. It collects and analyzes personal mobile information (such as taxi and private car usage) to identify various patterns of transport demand. It then connects various means of transport, including existing public transport (PT), demand-responsive transport (DRT), and personal mobility (PM), to offer comprehensive mobility services that cover the entire process from booking to use and payment, all tailored to meet the specific demands of the users (see Figure 4).

The smart parking service provides customized parking services that maximize the efficiency of parking facilities management using digitalized parking lot information. The project involved developing technologies to collect and integrate real-time parking data from public and private parking lots within the cities, offering technologies to provide and manage real-time parking data, designing the system to develop parking data standards and performance criteria, and analyzing the patterns of parking lot users. It provided customized parking services for users through the Mobility as a Service (MaaS) platform.

These technologies and systems of the 2A project directly improved the length of the public transport network, enabled convenient access to public transport, and increased the percentage of people using various forms of transportation to travel to work. In the long term, they have contributed to increasing the number of shared bicycles or vehicles and the lengths of bicycle paths and lanes and reducing the ratio of the travel time during peak periods to the travel time at free-flow periods.

The public transport network of the U4SSC initiative includes both high-capacity (such as heavy rail, metro, subway systems, and commuter rail systems) and light-capacity (such as light rail streetcars and trams, buses, and trolleybuses) modes of public transport. However, the total length of the public transport system does not necessarily provide accessibility information, and investments in public transport can be more expensive if the needs and demands are not taken into account. For example, the smart mobility service, which is an integrated service with public transportation, shared cars, and PM, can enhance the convenience of the public transport network. Additionally, the demand response service improves the mobility efficiency. These services increase citizens’ public transport network convenience and ensure convenient access.

The percentage of people who use various modes of transportation to travel to work is referred to as the transportation mode share. As congestion is typically the worst during peak hours, when people are driving to and from work, gathering data during these times is crucial in taking action to reduce congestion. The Daegu City empirical case of the 2A project indicated that business, tourism, school transportation, and vulnerable areas of traffic infrastructure were the travel types in the service area. In other words, the system uses various means of transportation for commuting and travel destinations, which are emphasized by the U4SSC initiative, ultimately reducing congestion.

3.2. Environment

3.2.1. Energy

The 3B project sought to enhance the city’s energy efficiency through the development of a community energy management system (CEMS) designed for residential homes, commercial buildings, factories, and public facilities. To achieve this, big data and machine-learning-based energy use analysis and demand forecasting technology have been developed. Energy sharing services and systems have also been developed by linking an integrated energy management system (x-EMS) that is optimized for various types of facility operating environments, such as buildings and factories. The x-EMS improves the energy consumption, facility performance, and operation methods and saves energy through the optimal operation of facilities. Depending on the characteristics of the facility, the x-EMS can be applied in various ways, such as a building EMS (BEMS), factory EMS (FEMS), data EMS (DEMS), retail EMS (REMS), smart farm EMS (SEMS), or water EMS (WEMS).

The FEMS and BEMS developed in the project contribute significantly toward reducing the per capita electricity consumption, residential thermal energy consumption, and energy usage of public buildings, aligning with the goals of U4SSC regarding the energy sector. The electricity supply category in the ICT sector is satisfied by presenting smart electricity meters as core indicators and electricity supply ICT monitoring as an advanced indicator. The former enables energy demand management through a smart meter that can measure the load of the power grid and consumers’ consumption habits more directly and in real time, while the latter enables the expectation of a stable energy supply by monitoring the power supply through the supervisory control and data acquisition (SCADA) system.

During the comprehensive interview with the PjM of the 3B project, it was revealed that an integrated metering infrastructure had also been developed to enable consumers to monitor their energy consumption comprehensively and efficiently. A platform for the monitoring of energy consumption was developed by detailing the specifications for smart meters that enable integrated meter readings. An integrated metering system based on a smart meter gateway (SMGw) was established to promote energy efficiency through the standardization of five types of energy (electricity, water, gas, heating, and hot water). Providing Smart Metering as a Service (SMaaS), which applies an advanced metering infrastructure (AMI) system based on SMGs to a large amount of metering data, contributes to the expansion of the remote metering of measured data and a reduction in the fixed cost for system construction and operation throughout the country.

To protect users’ personal information, the 3B project has developed a National Intelligence Service (NIS) authentication security system. Additionally, to enable an energy marketplace, the project has linked the integrated meter reading infrastructure to the behind-the-meter (BTM) system of the watt-hour meter (WHM), which supplies energy directly to homes and buildings. This creates an open service platform that shares usage information from various energy sources, including electricity, in real time.

However, in the context of smart sustainable cities, it is important to focus on improving the percentage of electricity supply systems that are monitored by ICT. This can be achieved by establishing SCADA systems to monitor and control the operational status of energy consumption facilities in buildings. Additionally, developing operating technology for optimal energy demand management in buildings will also contribute to improving the overall efficiency of energy consumption. These efforts will help to promote sustainable development and a more cost-effective energy supply system. Ultimately, establishing an integrated urban energy management system and periodically analyzing the effects of energy efficiency services promote energy efficiency.

3.2.2. Air Quality

The 3A project has developed a high-resolution fine particle information system for small-sized cities—specifically Siheung—utilizing ultrafine particle sensing technology and a prediction model based on crowdsourcing. While the Korea Environment Corporation’s “Air Korea” provides ultrafine particle information with a 3.5 km resolution every hour, Korea still ranks highly in terms of its fine dust concentrations among OECD countries [36]. Thus, citizens require prompt and detailed information on ultrafine particles to engage in safe outdoor activities. To address this issue, the KT Corporation, South Korea’s largest telecommunications company, has developed ultrafine particle sensors (fixed, portable, and deployable) and a prediction model, providing high-resolution ultrafine dust information at 1 km or less every 10 min to policymakers and citizens.

To generate ultrafine particle information, fixed sensors are deployed in a matrix at intervals of less than 1 km, movable sensors are installed in populated areas, and portable sensors are distributed to citizens in living labs. The air quality within citizens’ living spaces can be measured using these sensors. Consequently, it is possible to analyze the types of ultrafine dust pollution sources, identify high-risk areas, and improve citizens’ quality of life by providing web-based information. According to the thorough interview conducted with the PjM of the 3A project, this system is differentiated from existing ones in that it employs a crowdsourcing-based approach.

The 2B project developed the Massive IoT RF Gateway (GW) and Edge GW to comprehensively monitor, analyze, operate, and control fine dust. For instance, real-time indoor environmental information was measured and monitored for a daycare center in Siheung City. Ventilation equipment was automatically linked with real-time indoor/outdoor environmental information, and an intelligent control system was established. Additionally, the real-time measurement values of the classroom at the daycare center were visually expressed through indoor digital signage. A virtual network was introduced to prevent external malicious access to devices installed in daycare centers. Numerous fine dust sensors were placed in the surrounding areas of the daycare center and in areas where fine dust complaints had been made to measure the outdoor air quality. A massive IoT pilot network was established to collect outdoor air quality measurements.

Additionally, based on the results of an extensive interview with the PjM of 3D, it was revealed that they developed the world’s first fine particle monitoring system using scanning LiDAR in response to Siheung City’s demand, where industrial complexes are concentrated. This innovative system, as stated by Gwak [32], has the ability to scan ultrafine dust concentrations with a remarkable resolution of 30 m and a radius of 5 km (see Figure 5).

These technologies help to reduce air pollution, which is prioritized first among the environmental aspects of U4SSC. U4SSC classifies air pollution based on reported values for particulate matter (PM10 and PM2.5), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O3) using the air quality index (AQI). In other words, the 3A and 2B projects not only decrease fine dust concentration in the target area but also aid policy measures, such as mapping to identify hotspot areas requiring special attention and supporting people threatened by air quality deterioration. Ultimately, this is a step toward the environmentally sustainable smart city that U4SSC aims to achieve.

3.3. Society and Culture

3.3.1. Health

The detailed interview with the PjM of the 3C project revealed that a total care system had been established and was being operated to enhance the quality of life of vulnerable members of society, such as elderly individuals living alone. The service collects data using non-contact sensors installed in the home of the service users and uses smartphones and wearable devices to manage health conditions and predict dangerous situations among elderly people living alone. Specifically, it (a) provides health counseling and medication management through mobile apps and AI home robots for senior citizens living alone; (b) provides cognitive and emotional improvement programs for the elderly living alone after emergencies such as fires; (c) establishes a biometric data measurement system for chronic disease management in the public health center and branch office; and (d) provides a notification service to related parties by detecting emergencies among single elderly people, such as fires and falls.

In particular, the service manages patient information in cooperation with private companies, local communities, public health centers, and nursing hospitals by setting a local public medical institution as a care base. By providing a service to manage health and safety among the elderly living alone, this project aims to improve the accuracy in the prediction of health conditions, improve the mortality prevention rate, and reduce the lead time in tracking missing persons.

Furthermore, the project aims to enhance the quality of life of people with disabilities by offering a mobility assurance system. This system collects mobility data for the disabled by crowdsourcing; these data are collected and analyzed, and optimal routes and transportation (smart maps) are recommended through the system. To develop a route simulation for the disabled, AR technology was applied to simulate in-building routes, and image information-based mobility simulation technology was developed.

Technology that computerizes health information for vulnerable individuals and responds to emergencies is a means of achieving U4SSC’s health goal. The primary KPI in the health category is the percentage of city residents with electronic health records (e-health records). This system collects and stores patients’ health records digitally, making them accessible and shareable among all relevant health providers. e-health records contain the latest information on a patient, including visits to healthcare providers, immunizations, imaging results, and billing information, making them invaluable in emergencies, when a patient is unable to communicate.

In conclusion, the technology developed by the 3C project can computerize health records for a specific class, and it provides an emergency response system linked to the local community infrastructure. This system is focused on socially disadvantaged individuals, such as the elderly living alone and the disabled, and it can be a valuable tool in emergencies.

Another technology that computerizes and utilizes a patient’s health records is the “Korea Epidemiological Investigation Support System” (K-EISS), which is based on the data hub in the 1A project. This system rapidly obtains the movement routes of confirmed cases by analyzing real-time data such as location and payment information from telecom and credit card companies. It identifies the routes and hotspots of infection by conducting a spatial–temporal analysis of the movement of confirmed patients. Thanks to big data analysis, the system can automatically identify stay points by period and the source of infection in the region by finding a large-scale outbreak area. Previously, it took up to 24 h to conduct an epidemiological investigation of a confirmed COVID-19 case. The Act on the Prevention of Infectious Diseases required the Minister of Health and Welfare (MOHW) to request location information from the National Police Agency (NPA) about the confirmed person. The NPA would then request information from the individual telecommunication company via 18 local police agencies and precincts. However, the K-EISS can implement this process within 10 min through an online batch processing system that includes receiving, approval, and transmission (see Figure 6).

Such a system contributed to reducing the increase in the number of patients due to the global COVID-19 pandemic. In particular, automatic management through computerized records of the confirmed case made it possible to respond rapidly. While the U4SSC initiative raises concerns about sharing patient information, it may only be collected in exceptional or life-threatening situations through the system. Recently, the K-EISS has been bundled worldwide with a QR code-based electronic registry system and the Self-Quarantine Safety Protection Application, called the K-Quarantine Solution.

3.3.2. Safety

Out of the nine safety indicators of U4SSC, seven are mostly related to natural disasters, which include natural-disaster-related deaths, disaster-related economic losses, resilience plans, the population living in disaster-prone areas, emergency service response times, police services, and fire services. In project 2B, the goal is to reduce the average response time for emergency services by developing technology for the early alert of disasters and emergency rescue and response services through data sharing. The aim is to establish an early alert system to collect, analyze, and distribute information on risky situations and develop emergency rescue and response services to guarantee public safety and minimize the losses caused by disasters.

Data-driven disaster response systems are in operation, collecting and analyzing data on emergency situations through data platforms, as evidenced in an extensive interview with the PjM of the 2B project. Various data collected through sensors on disasters, such as slope collapses, floods, heatwaves, fires, and accidents, are displayed on the safety platform and data hub. Key analysis results, including disaster forecasts, are delivered to emergency aid and disaster control rooms and distributed to citizens through safety mobile applications. For example, the system provides “location-based real-time flood forecast and alert services” and “automatic rainwater pump and watergate operation services” by linking data from the Korea Meteorological Administration. It has smart services to provide heatwave information (map) and offer mitigation measures. It also classifies fire detection and fire accident hazard areas and services to support the mobilization of emergency rescue activities.

Emergency service response times are an indicator of the effectiveness of these services in responding to emergencies and safeguarding city inhabitants. Emergency services include police, firefighting, and ambulance services, including transport and urgent care. This indicator is often interpreted as the average time (in minutes) taken to respond to emergency calls from the initial call to arrival onsite. Although the project has not yet resulted in direct empirical results in terms of reducing the average time, the ultimate goal is to reduce the loss of lives and property caused by natural disasters such as slope collapses, flooding, and heatwaves by up to 20% and to reach the target of an 80% rate of arrival at the scene of the accident within the critical window.

Table 4. Summary of the key findings.

Dimension	Sub-Dimension	Category	Achievements
Economy	Productivity	Innovation	Expanded R&D activities in the previously underdeveloped smart city sector Increased SME participation in smart city technology and service development (14 of 22 participating companies are SMEs)
	Infrastructure	Transport	Enhanced mobility efficiency through integrated, user-tailored services (e.g., PT, DRT, PM connectivity) Improved usability and accessibility of the PT network Reduced congestion by promoting multimodal commuting
Environment	Energy	Energy	Lowered energy consumption and ensured stable supply via smart meters and ICT-based monitoring (e.g., CEMS, BEMS, FEMS)
	Environment	Air Quality	Delivered air quality data and supported proactive measures using fine dust sensors and prediction model
Society and Culture	Education, Health, and Culture	Health	Provided welfare and medical services for elderly residents and mobility support for persons with disabilities; digitized health records for vulnerable groups Developed the K-EISS to enable rapid COVID-19 response
	Safety, Housing, and Social Inclusion	Safety	Advanced disaster early warning and emergency response technologies through data integration and sharing

presents an overview of the key findings.

4. Discussion and Implications

This study investigated the NSSCP to determine the extent to which South Korea’s smart city promotion strategy contributes to sustainable and smart urban development. A comprehensive analysis of the results reveals the following findings. Firstly, the NSSCP has contributed to the achievement of SDGs 3, 7, 9, and 11, with a focus on people (innovation), mobility, energy, the environment, and living. This implies that the NSSCP covers almost all of the fundamental components of smart cities that are widely discussed globally. According to the U4SSC index classification system, 55 core indicators and 36 advanced indicators have been equally satisfied. This demonstrates that Korea’s smart city promotion strategy is moving in a sustainable and intelligent direction at an international level (refer to

Table 5. Sustainable and smart city metrics achieved through the NSSCP.

Dimension	Category	KPI	SDGs
Economy	Innovation	R&D Expenditure	9.5.1: Research and development expenditure as a percentage of GDP.
		Small and Medium-Sized Enterprises	9.3.1: Percentage of small-scale industries with total industry value added.
	Transport	Public Transport Network and Convenience	11.2: By 2030, provide access to safe, affordable, accessible, and sustainable transport systems for all, improving road safety, notably by expanding public transport, with special attention to the needs of those in vulnerable situations, women, children, persons with disabilities, and older persons.
		Transportation Mode Share
	Electricity Supply	Smart Electricity Meters	7.3: By 2030, double the global rate of improvement in energy efficiency.
		Electricity Supply ICT Monitoring
Environment	Energy	Electricity Consumption	7.3: By 2030, double the global rate of improvement in energy efficiency.
		Residential Thermal Energy Consumption
		Public Building Energy Consumption
	Air Quality	Air Pollution	11.6: By 2030, reduce the adverse per capita environmental impact of cities by paying special attention to air quality and municipal and other waste management. 11.6.2: Annual mean levels of fine particulate matter (e.g., PM2.5 and PM10) in cities (population-weighted)
Society and Culture	Health	Electronic Health Records	3.D: Strengthen the capacity of all countries—in particular, developing countries—for early warning, risk reduction, and the management of national and global health risks.
	Safety	Emergency Services Response Time

).

Secondly, the NSSCP employs a cloud-based open data hub architecture model to develop a data-driven smart city. For instance, the data hub model created by the NSSCP is utilized to offer all services in mobility (smart mobility and smart parking), energy (integrated energy management), and healthcare (total care for the elderly living alone). The development of the data hub architecture, as stated by the project manager of 1A, represents a significant step toward the advancement of smart cities.

Thirdly, this project lacks a tool to evaluate its outcomes and impacts and has primarily focused on achieving quantitative goals. It has paid less attention to the service quality, and there is no clear technology valuation index to assess the level of the system. It is crucial to establish a differentiation factor and produce unique results that distinguish it from other smart city development projects. Taking a long-term perspective, it is essential to prioritize quality improvement and the expansion of outcomes and outputs.

Globally, 11 of the G20 member countries have introduced national smart city strategies. Most of these strategies emphasize qualitative aspects—such as vision setting, stakeholder engagement, and governance frameworks—over quantitative criteria, including performance evaluation, key performance indicators (KPIs), and monitoring mechanisms [1]. In this respect, South Korea’s approach to smart city development diverges from that of many leading smart city nations. While developed countries often promote smart cities through public–private collaboration and data- or platform-centric solutions, developing countries tend to adopt public-sector-driven policies aimed at enhancing national competitiveness and addressing urban challenges. Although South Korea is an OECD member and thus categorized as a developed country, its smart city policy has largely followed a public-led model, more commonly associated with developing countries.

Regional variations in smart city approaches further illustrate these distinctions. In North America and Europe, smart city initiatives frequently leverage open data and living labs to foster citizen participation and enhance quality of life. In contrast, many Asian countries have prioritized the development of urban infrastructure to stimulate industrial ecosystems through emerging technologies—often aligned with the fourth industrial revolution. However, South Korea’s approach has been constrained by a limited focus on ecosystem revitalization as an integral element of smart city development.

Recognizing these shortcomings, Korea’s 4th Smart City Comprehensive Plan, released in 2024, identifies the need for greater private sector participation in smart city initiatives as a key strategic priority. As the highest-level statutory plan in the field—formulated every five years—it reflects a shift toward more market-driven approaches to complement existing public-led frameworks and address previous implementation challenges.

Nevertheless, the NSSCP exhibits certain limitations. Firstly, it functions as a state-led R&D initiative bolstered by substantial public funding. However, the successful commercialization of this research and development necessitates not only the participation of the central government but also active involvement from local governments. While smart technologies stemming from the NSSCP were implemented in Daegu Metropolitan City and Siheung City, significant challenges arose in data collection and the introduction of these technologies to pilot areas. This predicament arose because each instance required close cooperation between the respective cities and districts. It is crucial to recognize that, while the state can incentivize the development of novel and innovative technologies and spearhead related endeavors, the practical application and widespread adoption of these technologies often prove more effective when spearheaded by private companies and developers, with the cooperation of municipal governments.

One way to address these limitations is by considering the Lighthouse Project in Europe, an EU-funded smart city demonstration initiative implemented across various European cities. At the core of this project is a structured relationship between Lighthouse Cities—which serve as pioneers in deploying smart city technologies—and Fellow Cities, which adapt and replicate the proven solutions demonstrated by the former. Lighthouse Cities could pilot innovative technologies and solutions in real-world urban contexts, while Fellow Cities benefit from the lessons learned and successful practices established by their counterparts, facilitating more efficient and informed adoption. The diffusion process involves active collaboration among city governments, private companies, academic institutions, and research organizations, each contributing their expertise to advance the broader implementation of smart cities across Europe.

While the Lighthouse Project aligns with overarching EU policy objectives, it also emphasizes the development of locally tailored smart city strategies. These strategies respond to specific urban challenges and needs by applying targeted technologies and fostering robust citizen engagement. By responding directly to the needs and problems of urban communities, smart city technologies have the potential to mitigate critical issues such as social polarization and urban poverty [37]. Moreover, they can serve as instruments to reduce inter-regional disparities and foster balanced territorial development [38].

Importantly, the project extends beyond institutional participation. Citizens are actively involved through urban living labs, where they function not only as the end-users of smart city solutions but also as co-creators. They contribute by identifying local issues, providing feedback, and shaping the development and refinement of applied technologies [39].

Secondly, concerning the CEMS and the standardization of metering systems for the five energy sources (electricity, water, gas, heating, and hot water) developed by the NSSCP, it is imperative to delve into heterogeneous data integration. Energy data have the capacity to amalgamate diverse data types, including those from credit card companies, mobile operators, distributors, and manufacturers, thereby augmenting the data’s potential value. The seamless integration of heterogeneous data is essential in harnessing the full potential of smart technologies.

Furthermore, the data hub developed as part of the NSSCP’s efforts has exhibited highly favorable characteristics. For example, it was instrumental in the creation of the K-EISS, which played a critical role in effectively managing the COVID-19 outbreak and had a significant impact. Nonetheless, the imperative of safeguarding patients’ personal health information looms as a matter that requires future attention and resolution. Additionally, regarding early warning systems and emergency response services for natural disasters and catastrophic events, optimal data sharing will be realized when a clear consensus emerges regarding the integrated utilization of the system among relevant organizations, such as the Korea Meteorological Administration, the Ministry of Public Administration and Security, the National Police Agency, the National Fire Agency, and healthcare institutions.

While technology plays a critical role in the development of smart cities, not all smart city services are inherently technology-driven. The strategic integration of both technology-based and non-technology-based solutions can enhance urban performance and significantly improve residents’ quality of life [40]. Mondschein et al. [41] highlight that the primary challenges faced by policymakers—who are central stakeholders in the deployment of smart technologies—are often organizational rather than technological. This underscores the importance of stakeholder alignment as a key factor in the successful implementation of smart city initiatives. As noted by Kim et al. [42], “smartness” encompasses a broad spectrum of dimensions beyond technological innovation. Therefore, it is essential to recognize that smart cities are not solely defined by the presence of advanced technologies.

5. Conclusions

This research contributes to the field from three perspectives. Firstly, the analysis of the NSSCP project offers valuable insights into the current state of smart city development in South Korea. Despite the numerous smart city cases and practical experiences worldwide, the discussion surrounding smart cities in South Korea gained substantial momentum only after the NSSCP’s launch in 2018, as noted by Hwang and Shim [43]. This underscores the NSSCP’s pivotal role in shaping South Korea’s smart city development landscape. Moreover, the limited existing academic discourse on this project underscores the significance of this study in contributing to the smart city literature. Therefore, evaluating the project’s effectiveness using globally recognized evaluation criteria becomes highly meaningful as it expands the discourse on smart cities in South Korea and provides insights for future development pathways.

Secondly, this study could contribute to the development of sustainable smart cities as it highlights how the NSSCP represents a shift from a technology-centric smart city paradigm to a human-centric one, as observed by Lee [44]. The NSSCP is committed to analyzing human characteristics and their needs, rather than solely focusing on the development and deployment of smart city technologies or data platforms, utilizing methods such as use case and living lab approaches.

Lastly, the NSSCP marks the inaugural attempt to standardize data hubs on a nationwide scale. Most projects have primarily concentrated on local demonstrations, resulting in data fragmentation and hindering the efficiency of smart cities. The establishment of a standardized open data hub architecture creates a common foundation for transparent and shareable administrative services and fosters the digital economy. Ultimately, this data-driven and inclusive smart city model can be replicated in other urban settings, addressing diverse urban challenges. In this way, the NSSCP proposes forward-looking applications of smart city technologies.

Through the NSSCP, new policy strategies can be identified to help South Korean smart cities to generate greater economic and industrial opportunities. One limitation of this study is that, due to the short duration of the construction of the demonstration city, there are insufficient data to assess the performance of smart technologies and systems. Only when there are enough data to verify the accuracy of smart technologies will it be possible to clearly measure the degree of “digitalization” of a smart city. Measuring digitalization is a crucial undertaking as it allows for the evaluation of the potential benefits and risks associated with the adoption of smart technologies. Policymakers and industry leaders can leverage such assessments to identify areas for improvement in the adoption and implementation of smart technologies. Furthermore, this can facilitate the establishment of benchmarks to evaluate the efficacy of policies and initiatives aimed at promoting the development and adoption of smart technologies. In essence, the measurement of digitalization for smart technologies is imperative in offering valuable insights into their adoption, diffusion, and effectiveness. These insights can subsequently inform policymaking and industry decisions. This finding opens avenues for future research.

After conducting a comprehensive analysis of all aspects of the NSSCP, it becomes evident that the Korean government’s smart city project is progressing toward the goal of creating a sustainable and smart city. However, this research also reveals that many of the U4SSC indicators are not addressed within the project. This implies that the NSSCP does not inherently encompass all aspects of what the United Nations defines as sustainable and smart cities. Additionally, numerous technologies and services have already been developed in other projects, such as the nationwide implementation of a dynamic public transport information system. Hence, conducting a comparative analysis with other smart city projects in Korea would be valuable in determining whether Korea is advancing toward becoming a sustainable smart city in the future.