Deep Learning City
Though it is unnecessary to frequently update terms to highlight a potential area of interest, it is still highly useful to explore different perspectives. In this short article, the authors consider that the “Smart City” should rather be termed a “Deep Learning City”.
A smart city is not about developing applications on the fly, but reflecting on its long-term evolution, at the service of the citizen, and driving this evolution with technology and data analysis. It is now more essential than ever to rethink the city as a citizen-centric model and achieve this vision with innovative solutions.
In other words, the smart city project revolves around a central idea: “data analysis and technology”. The bulk of smart city projects consists of adding sensors and collecting more and more data. Why? New AI and deep learning processes require a ton of data.
The authors therefore propose to move the terminology from “Smart” to “Deep Learning” in order to emphasize learning, whether through city governance or the algorithms that use this data.
In Tallinn, for example, the start-up Thinnect worked with the municipality to install a network of 800 sensors which will make it possible to assess the effect of a speed limit decrease on transport flow, noise pollution or air quality.
The more sensors we have, the more data we have, the more “data-based solutions will be correlated, the more public authorities will be able to make informed and rational decisions to support city dwellers in their daily lives”.
[In Singapore] the Safe Distance @ Parks and Space Out portals monitor crowds in parks and shopping centers in real time, providing essential data in times of crisis to adapt behavior.
A crucial point worth mentioning: the backlash against the smart city is typically based on two factors; companies try to control its implementation (see the Sidewalk Labs project in Toronto) and to keep control over the data.
The data itself is not a problem. Rather, it is choosing what is measured, by whom, when, under what permissions, and who will then access and own (or be responsible for) this data. Regardless of the term adopted for this new vision of the city, any reflection on smart cities and data is an opportunity to reflect on the how, why, and “by whom” of data management.
Photo: La Confluence, in Lyon, a district that serves as a Smart City model. (Source: Adobe Stock)