In transport, deep learning models are being used for traffic prediction and autonomous mobility networks. In environmental design, AI optimizes land use, monitors air quality, and manages energy distribution. Public health applications include spatial disease mapping and predictive analytics for emergency planning. Together, these uses mark a transition from isolated technical experiments to integrated urban intelligence systems.
Artificial intelligence (AI) is rapidly becoming a key tool in transforming the way planners model, design, and manage urban environments. A recent study, titled “Artificial Intelligence in Urban Planning: A Bibliometric Analysis and Hotspot Prediction”, provides the most comprehensive examination yet of how AI-driven technologies are transforming urban planning research worldwide.
Weiterlesen: AI-driven cities on the rise: Ethical and data integration challenges ahead
Today, smart city planning has become part of broader national development programmes. It is not only about sensors or buildings but about efficiency, data flow, and local ownership of innovation. The goal is to keep technology and income tied to local economies instead of depending on imported systems.
That financial discipline soon reached other industries tied to technology. Betting analysts began studying how digital infrastructure improved data accuracy for sports platforms, including 1xbet en ligne, which relied on stable network performance to update match information. The same systems that guide city transport or public safety now support entertainment and prediction platforms. In both cases, investment in infrastructure decides the quality of experience.
Weiterlesen: Building Smart Cities Through Domestic Tech Funding
The study finds that most smart city innovations rely on a layered structure, IoT sensors gather environmental and infrastructure data, AI models analyze and predict outcomes, and digital twins visualize scenarios for decision-making. The combination of these layers allows cities to forecast traffic patterns, monitor pollution, simulate disaster response, and plan infrastructure with precision that was once impossible.
The accelerating convergence of artificial intelligence, the Internet of Things (IoT), and urban digital twin (DT) technologies is reshaping how cities operate, plan, and respond to complex challenges. A study titled “IoT, AI, and Digital Twins in Smart Cities: A Systematic Review for a Thematic Mapping and Research Agenda” published in Smart Cities provides a structured look at this transformation, revealing where innovation is most effective and where serious gaps persist in smart urban development.
Weiterlesen: Future of smart cities with AI, IoT, and urban digital twins
Researchers propose a moral framework to guide AI decisions in smart cities, ensuring fairness, safety, and transparency.
Every streetlight, traffic camera, and trash can in tomorrow's cities could be part of one massive digital nervous system. Already, these devices record data on traffic, air quality, and even trash to make life more efficient. Yet, as cities get "smarter," the greatest challenge is not merely amassing data — it's figuring out how to get technology to make moral choices.
Weiterlesen: AI meets morality: Scientists are rethinking technology in ‘smart cities’
On a humid evening in Bengaluru, a stretch of road clears itself of traffic without a single policeman intervening. Sensors beneath the ground detect congestion forming a kilometre away and reroute vehicles before the jam materialises. In Surat, a water grid predicts leaks hours before a drop is lost. These are not glimpses of a distant future; they are signs of how Indian cities are beginning to evolve into thinking systems.
Before the end of this century, the most powerful and complex form of intelligence on Earth may not be biological or robotic. It will not walk or breathe. It will be something larger and more diffuse: our cities. What were once physical spaces for human activity are becoming living networks that sense, learn and act. Driven by data, algorithms, and sensors, cities are starting to function like giant neural systems. They will not simply respond to instructions — they will anticipate needs, adapt autonomously and influence decisions. They could prevent traffic jams before they occur, balance energy uses dynamically, detect disease outbreaks in advance and even help shape public policy in real time.