There are many successful use cases where smart cities are implementing mobility projects, using machine learning and AI to analyze data patterns and improve life for their residents. For example, in 2012, Pittsburgh’s city implemented Surtrac, an intelligent traffic signaling system, reducing travel times and emissions by optimizing vehicles’ movement through intersections. Analysis of the project found that the average travel times reduced by 25%, and cars spent up to 40% less time idling. This affected not only citizens’ quality of life but also the environment by reducing emissions.

This is just one example of how a smart city benefits its citizens. Still, smart cities are not just about how the city’s government officials can provide the infrastructure, services, and solutions to benefit its citizens. If that were the core point, it would simply be a digital city, not necessarily smart. A smart city’s very essence depends on its people to improve its services with gathered data, making it more efficient, more inclusive, and more secure.
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