The Smart Cities research line studies the city as a socio-technical ecosystem that integrates data, IoT, artificial intelligence, information systems, governance, and citizen participation to improve quality of life and to promote sustainable, inclusive, and resilient urban development.
Helga Duarte Amaya
A smart city works more like a living organism than a mere collection of concrete and asphalt. It is made up of an almost invisible system of sensors, real-time data, and connectivity that lets it “sense” what happens on its streets and in its surroundings and respond appropriately before problems get out of control: smoother traffic, precise waste management, conscious energy use, or efficient responses to emergencies. It is not about accumulating technology, but about knowing how to use it optimally so that the city spends fewer resources, pollutes less, and gives quality time back to its citizens.
From a functional standpoint, a Smart City is a city that uses digital technologies, data, and innovation to improve its citizens' quality of life, optimize the management of urban services, and promote sustainable, inclusive, efficient, and resilient development. However, smart cities are living laboratories that evolve rapidly: the ITU speaks of people-centered cities, innovation, and co-creation; ISO emphasizes the integration of physical, digital, and human systems; and the OECD raises the need to experiment and adopt collaborative approaches.
Taking the above into account, we understand a Smart City as an intelligent, adaptive, and people-centered urban ecosystem that integrates data, emerging technologies, knowledge, and citizen participation to dynamically understand the territory, anticipate needs, discover opportunities, and co-create new ways of inhabiting, managing, and transforming the city, experimenting with solutions and continuously transforming the way urban services are designed and delivered, generating new forms of well-being, inclusion, sustainability, and public value. The goal is to move toward the paradigm of the city as a system that learns: one that detects patterns, learns from them, anticipates scenarios, and experiments.
Urban sensor networks, real-time monitoring, cyber-physical systems, and IoT–AI–Big Data integration as a foundation for the city to perceive its environment.
Intelligent public transport, traffic management, autonomous and connected vehicles, and sustainable mobility.
Data collection and integration, urban data platforms, predictive analytics, and data interoperability and quality.
AI for prediction and optimization, urban decision-support systems, generative AI for public services, and responsible, explainable, and trustworthy AI.
Digital government and open government, citizen participation, data-driven decision-making, and transparency and public policy.
Smart grids, smart buildings, intelligent public lighting, and smart management of urban infrastructure.
Personal data protection, security of critical infrastructure, surveillance and privacy, and algorithmic bias and AI ethics.
Digital inclusion and the digital divide, accessibility, health, education and safety, and citizen participation and co-creation.
Smart City indicators and KPIs, digital maturity models, assessment of social, economic, and environmental impact, and comparison between cities.