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Information is fed into data banks which is then swiftly analyzed, providing city planners with intel needed to make smart decisions

As we move further into the 21st century’s third decade, smart city innovations and implementations are happening all over the globe. We might not be at a smart city a la The Jetsons level yet, but plenty of advancements earlier pop culture imagined are starting to appear.

It’s easy to imagine Mr. Jetson using his smartwatch to find a parking space, he used it to make calls as watch TV in the show, after all. Today’s Apple Watches aren’t equipped to stream shows, but we can use them to send messages, and in some smart cities, citizens can already use an app to find the closest parking spot. It’s only a matter of time before native Watch apps perform the same function.

Smart city projects aim to create systems that make city life easier, cleaner, and more convenient. Leveraging the power of the Internet of Things (IoT) technologies and near-universal connectivity, vast webs of interconnected devices collect and collate information about nearly every aspect of city life. The information is fed into data banks which, thanks to machine learning, is then swiftly analyzed, providing city planners with the kind of intel needed to make smart decisions that better serve the community.

Below are some of the ways smart city projects are transforming our urban landscapes and changing the ways in which we live and interact with our cities.

Traffic management

In Adelaide, Australia, and several other cities worldwide, the implementation of Smart Parking’s SmartPark service means motorists can pull a Mr. Jetson and use an app on their smartphone to locate the closest available parking spot.

Sensors located at each site monitor real-time spot usage and feed this information back to the cloud, which in turn offers divers intel via the company’s app. Additionally, SmartPark can provide directions to drivers to help manage flow in and out of a parking area.

A few thousand miles away in Hangzhou, China, an AI created by online retail giant Alibaba has helped the city reduce traffic jams by an impressive 15 percent. Now, City Brain is set to make its mark on Kuala Lumpur.

Environmental matters

According to Chris Kennedy, a Professor of Civil Engineering at the University of Toronto, it is technically already possible for cities to reduce greenhouse gas emissions by 70 percent or even more. “This is the sort of reduction the international community is calling for, so we can avoid the potentially serious consequences of climate change,” Kennedy said.

In Munich, Germany, plans are underfoot to power the Bavarian capital solely by renewable energy as early as 2025. The city has already signed a contract to supply power to the S-Bahn, it’s city rail system, with energy from a North Sea wind park.


Vienna, Austria installed 200 or so pedestrian lights that recognize when an individual wants to cross. Commissioned by City of Vienna’s Municipal Department 33 and developed by a team at the TU Graz University’s Institute of Computer Graphics and Vision, it’s slated to replace the old button system and is adaptive to citizens’ needs. People with disabilities are given more time to cross as are larger groups.

The traffic lights’ cameras have a large visual field, and following global movement models, the team used these and pre-recorded data to develop learning algorithms. Images taken by the cameras are analyzed by on-site computers, not saved.

Elsewhere, such as in London, England, smart cameras are being used to make life more convenient for law enforcement agencies. Met Police have deployed smart cameras that utilize live facial recognition technology in the hopes of finding “suspects wanted for serious and violent crimes.” The cameras are in use for five to six hours at a time.

Faces in existing images owned by the Met Police are mapped against images the live cameras take, these are then compared by software and if a match is found, a notification is sent to the police. As some commentators have pointed out, live facial recognition is a boon for citizens; safety and security.

In New Zealand, police trialed the use of live facial recognition before gaining the go-ahead from the Privacy Commissioner. Additionally, the law enforcement agency partnered with the controversial firm, Clearview AI.

This incident serves as a sobering reminder of the privacy concerns that come hand in hand with mass data collection, which is an essential element in smart city innovations and development. To enact most of the technologies detailed above, municipalities must collect data on the minutiae of daily city life; how fast people walk on pavements, driving habits, GPS locations for vehicles, and much more. There are also concerns that privacy policies are worth little more than the Google docs they are written on.

Toronto’s Waterfront TO and Sidewalk Labs collaboration, for example, was recently mired in controversy when one of the project’s privacy experts quit, citing concerns. Ann Cavoukian said she imagined a smart city of privacy, not a “city of surveillance” after it became apparent that not all third-parties involved in the development were committed to depersonalizing the collected data.

The core of the issue is that in a fully-fledged smart city, there is no option to opt-out, no chance to turn down the devices mining one’s movements and actions for data. Citizens can take some steps to turn down the ‘Big Brother’ factor, such as using a VPN for privacy and to mask their personal devices’ true locations. But, avoiding the watchful eye of live facial recognition, for example, is rather more difficult.

In a recent article published by the Journal of Science Policy & Governance (JSPG) titled “Preventing Surveillance Cities: Developing a Set of Fundamental Privacy Provisions,” the authors note the “deployment of smart city technology could have a chilling effect on citizens’ constitutionally protected freedoms” unless the following key tenets are adhered to:

  • Differentiating personally identifiable data from de-identified data
  • Creating a warrant requirement for personal smart city data
  • Prohibiting the sharing of personally identifiable information collected by smart city sensors
  • Adopting data minimization requirements
  • Introducing private and public enforcement mechanisms

As we saw above, de-identification is already being flouted in some projects. It’s only a matter of time until data is sold to third parties and the third suggestion is turned on its head too. The rise of surveillance capitalism fits well in the smart city model, how far it will go is anyone’s guess.

Do you want a company knowing how fast you walk so it can bombard you with adverts for a new, targeted pair of shoes? It’s a question we should all ask ourselves before diving head-first into poorly regulated smart city developments.


Autor(en)/Author(s): Chris Jones

Quelle/Source: Electronic Products & Technology, 22.12.2020

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