What Makes a City Smart? Code, Connectivity, and Collective Action

From Seoul to Stockholm, cities are deploying integrated technological systems to manage energy consumption, waste, traffic, security, and citizen services. But recent findings, drawn from a comprehensive bibliometric analysis of 1,559 scholarly articles, show that the story of smart cities is less about gadgets and more about strategic coordination between innovation, urban management, and civic purpose.

What Makes a City Smart?

According to a recent meta-research published in Heliyon, the defining characteristics of a smart city lie in how technology and data are used to align the systems of urban life—from transport and energy to education and healthcare. Using bibliographic tools like VOSViewer and SciMAT, researchers mapped thematic trends from 2014 to 2021, revealing seven main thematic axes: technology and innovation, environment, urbanism, energy, governance, mobility, and accessibility.

At the heart of nearly every paper lies one central force: the Internet of Things (IoT). IoT was referenced in more than 60% of the most-cited articles, showing that cities are prioritizing connected, sensor-driven systems to make real-time decisions.

The Invisible Architecture of Data

Think of smart cities as networked ecosystems. The most cited paper in the corpus by Zanella et al. places IoT as a core pillar for urban systems optimization. From LPWAN (low-power wide area networks) for citywide connectivity to real-time vehicular communications for smart mobility, the infrastructure of the smart city is built from protocols, not just pavement.

"Big data and edge computing aren't just buzzwords," says Dr. Sabine De Paris, one of the study's co-authors. "They're foundational to how cities can respond proactively rather than reactively."

Communication networks (44%), computing frameworks (19%), and big data (13%) are the most common enablers after IoT. These tools empower predictive analytics, energy modeling, and adaptive governance platforms that turn raw data into optimized service delivery.

The Business of Urban Intelligence

Smart cities are not purely governmental projects. The research shows a growing interdependence between academia, public agencies, and the private sector. In cities like Manchester and Seoul, real-time data hubs and urban innovation labs are enabling everything from on-demand public transit to virtual shopping at bus stops.

"A smart city isn't just a collection of smart technologies. It's a market opportunity, a platform for innovation, and increasingly, a policy challenge," says Dr. Alvaro Neuenfeldt Júnior, another lead researcher.

Private-sector engagement spans sectors: health wearables linked to municipal hospitals, dynamic energy tariffs managed by AI systems, or IoT-driven logistics platforms that power everything from garbage pickup to streetlight optimization.

Beyond Technology: Ethics, Equity, and Access

While technology is central, researchers warn against a techno-deterministic view. The findings stress the importance of governance, privacy, accessibility, and socio-economic inclusion. Smart city solutions must also be lean, integrated, and cost-efficient.

In the strategic diagram mapped using SciMAT, terms like "decision-making," "privacy," and "cost reduction" emerged as underexplored but increasingly relevant themes—pointing to open R&D questions about ethical AI, algorithmic governance, and inclusive urban planning.

Where Do We Go From Here?

Between 2014 and 2021, the number of keywords and published articles on smart cities grew sevenfold. This signals that the urban intelligence revolution is accelerating. But the real innovation isn't in sensors or platforms—it's in how we design inclusive, cross-sector collaborations that treat data as a civic asset, not just a technical input.

The next phase? Moving from experimental pilots to scalable, people-centered infrastructure. That means embedding intelligence into the physical, digital, and political fabric of our cities.

Artificial Intelligence: The Cognitive Layer of Smart Cities

While this study extensively maps the foundational role of IoT, big data, and communication networks in enabling smart cities, artificial intelligence emerges as the critical cognitive layer that transforms these infrastructures into intelligent systems. AI is not only a downstream beneficiary of data generated by urban sensors—it is increasingly the orchestrator. From predictive energy demand modeling and real-time traffic optimization to anomaly detection in public safety and adaptive learning systems in urban education, AI systems are enabling dynamic decision-making at scale. The bibliometric analysis shows a growing presence of terms like "deep learning," "decision-making," and "optimization"—highlighting the shift from static digital infrastructure to AI-driven adaptive urban environments. As smart cities evolve, AI will likely define their operational intelligence, mediating the interaction between systems, citizens, and services in real-time.