Historic Italian city uses analytics to guide smarter urban planning

When people talk about smart cities, they often picture large metropolitan hubs powered by advanced technology. But a city doesn’t have to be big to be smart. Smaller communities can transform public services and quality of life when they embrace data-driven decision-making.

The Municipality of Pisa in Tuscany, Italy is a powerful example. Recognized in the ICity Rank 2024: Digitalization of Italian Cities report as one of 22 cities nearing full digitalization, Pisa manages challenges comparable to a much larger urban area, despite having just 90,000 residents. Today, the city is using SAS Viya to build a modern environmental monitoring and analysis system that connects public policy decisions with measurable impacts on the environment and public health.

Marco Redini, Director of the Environmental Department at the Municipality of Pisa, and Nunzia Linzalone, researcher in environmental and public health at the National Research Council of Italy, have been central to this transformation. “Our goal is to ensure transparency for citizens by providing updated and reliable environmental data,” Redini says.

Modernizing environmental governance

The Environmental Department is responsible for a wide range of activities – from waste management and noise pollution to industrial emissions and environmental assessments. But keeping pace with large volumes of rapidly changing data is beyond the capacity of manual processes. To meet the challenge, the Municipality of Pisa built a system based on automated, real-time data flows using SAS Viya.

Now, the department can analyze data continuously, quickly detect anomalies and gain a clearer picture of how city initiatives perform in practice. “SAS Viya allows us to verify the effects of political decisions on environmental conditions and citizens’ health, which is the ultimate objective of our work,” Redini says.

Why Pisa chose SAS Viya

Like most modern cities, Pisa generates large volumes of data, yet much of it has historically suffered from inconsistent quality. SAS Viya helps the municipality enforce structured, standardized data inputs.

“In this way, we improve the overall quality of the data, making it more reliable and reusable even by higher-level institutions, such as regional authorities or ministries,” Redini says. For a smaller municipality, this level of analytical rigor is essential. The benefits were immediate: processes became more organized, staff gained confidence and independence, and the city could make informed decisions with far greater precision.

Improved data quality has also strengthened collaborations with universities, health care agencies and national research bodies. Municipal datasets now fuel joint research and knowledge exchange, expanding the impact of Pisa’s work far beyond city borders.

Driving efficiency and public trust

The system now supports a wide range of services that directly influence residents’ lives. Reliable, transparent data enables the city to monitor trends, anticipate risks and identify vulnerable communities.

Operational processes have also become more efficient. Administrative workflows such as permits, inspections and authorizations are tracked visually using maps and dashboards, which highlight cases in progress, upcoming deadlines or completed tasks. This supports standardization and compliance with quality frameworks like ISO 9000.

Transparency has become a cornerstone of Pisa’s smart city approach. Citizens can easily access environmental information and understand what’s happening in their neighborhoods. They are no longer passive recipients of updates but active participants in their city’s progress.

This proved especially valuable when a committee of 800 residents raised concerns about aircraft noise. Using SAS, the municipality visualized real-time flight paths and demonstrated that takeoffs followed established rules – resolving a tense public debate with clear, objective data. Today, these flight path visualizations are openly accessible on the municipal portal.

Building a shared ecosystem

Pisa applies the same data-driven approach to sectors like waste cycle management, continuously monitoring production, collection and disposal to improve logistics and promptly address anomalies.

The city also shares its environmental data with health care agencies, universities and the National Research Council of Italy. Together, these organizations develop shared indicators and predictive models. This ongoing exchange has created a robust local knowledge network that strengthens decision-making and supports a practical model of open data.

As a result, analytics in Pisa is no longer just an administrative tool; it has reshaped the relationship among institutions, citizens and the territory, fostering transparency, collaboration and evidence-based governance.

Linking environment and health

One of Pisa’s most significant collaborations integrates environmental monitoring with public health analysis through geospatial modeling. Working with the National Research Council’s Institute of Clinical Physiology and local health care authorities, the city mapped standardized mortality rates at the neighborhood level and layered them with socioeconomic and demographic indicators validated by ISTAT. The analysis revealed spatial patterns that would not have been visible through sector-specific data alone, highlighting both high-risk clusters and unexpectedly resilient communities.¹

“This is what we call the ‘wow effect’ – the ability to correlate environmental and public health data through a geospatial lens,” Linzalone says. “By layering standardized mortality rates with socioeconomic and demographic indicators, we can pinpoint both critical and resilient areas of the city.”

To make the information accessible, the findings were presented with simple, color-coded maps and combined scores. Decision makers can now evaluate trade-offs and act on a shared analytical framework. “This transforms complex data into visual, evidence‑based tools that help policymakers move beyond perception and pressure and toward decisions grounded in science,” Linzalone explains.

The project has also earned international recognition for its innovative contribution to urban planning research.

Smart city as a mindset

Looking ahead, Pisa plans to use historical data and predictive models to forecast the policy impacts – beginning with waste management during major events like Giugno Pisano, a month-long festival celebrating Saint Ranieri. Better forecasting will help the city optimize logistics, reduce waste and prevent inefficiencies.

“We are also starting a collaboration with the Tuscany region and the Ministry of the Environment to extend this data pipeline at regional and national levels,” Redini says. “On the research front, our infrastructure already lays the foundation for participating in European projects on urban digital twins that allow cities to simulate scenarios and policies in a digital environment before applying them to the real world.”

The Pisa experience shows that a smart city is not defined by size, but by vision, methodology and a commitment to data-driven culture. Pisa has built a model of public governance that doesn’t just collect data but transforms it into practical tools for better decisions, stronger public participation and improved collective well-being.

¹Donzelli, G., De Nes, M., Vivani, P., Sera, F., & Linzalone, N. (2026). Visualizing neighbourhood health disparities: spatial epidemiology to map social vulnerability and mortality in an Italian city. Cities & Health, 1-19.