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Senseable City Lab Exploring 3D

4D smart city image senseable city lab

Known for integrating cutting-edge technology with architectural practices, Professor Carlo Ratti explains his visionary approach to urban design and shares with us his thoughts on the evolving role of architecture in shaping the world of tomorrow.

Interview by Elena Sbokou in Global Design News.

Global Design News: As an international architect, you have worked on projects all around the world. How do the challenges and opportunities of smart city initiatives differ between developed and developing countries?

Prof. Carlo Ratti: You mention “smart cities” here, but I have never been a fan of the term, which puts too much focus on the technology — and not enough on the ways we use it. That’s why, two decades ago, we called our lab at MIT the ‘Senseable’ City Lab—focusing on how to employ digital technologies to help our cities sense the needs of their inhabitants and respond intelligently.

Senseable technologies are not necessarily flashy or high-tech; instead, they are designed to address specific scenarios and needs. This adaptability is particularly effective in tackling the unique challenges of developing urban spaces. Of the 4 billion people living in cities worldwide, nearly 1 billion reside in informal settlements. These areas are often vast yet remain invisible to traditional mapping technologies—often depriving residents of urban rights (including property rights).

At the Senseable City Lab, we are working on a project called Favela 4D—utilizing 3D laser scanning technology to analyze the morphology of Rocinha, the largest favela in Rio de Janeiro. By making the informal visible, this project aims to enhance environmental conditions, including improved access to sunlight, air ventilation, and water—and also verifying structural vulnerabilities, which are one of the main causes of mortality.

GDN: How AI can affect and shape the future of urban development and master planning?

C.R: Let’s remember that there is no AI without data to train it. Using data, we can better understand urban environments, design them more effectively, and improve how we live in them.

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