The idea that technology is reshaping every aspect of life is not a revolutionary statement anymore – rather a common knowledge across society. Recently, we experienced numerous technological advancements in the scope of livelihood and city improvement. Among many inventions, we can enlist things like autonomous cars, boldly introduced to the mainstream market by Tesla, or light sensors which allow for efficient utilization of energy in the buildings.
By leveraging all these technological incentives, around 10 years ago, the concept of smart cities emerged on the horizon as an idea to make it easier for people to live in urban areas. As the foundation for developing such solutions, policymakers and tech enthusiasts picked the interconnection of the Internet of Things (IoT) – mostly sensors – and “urban” artificial intelligence algorithms. The reasoning behind those technologies comes from the IoT’s possibility to gather profound loads of data, whereas AI usage allows for its processing and development of further analysis, conclusions, and eventual recommendations.
Before we go further, it is worthwhile to unpack the term “urban AI” as it will be necessary to understand the lining of presented inventions. As an example of it, we can analyze lamp posts packed with sensors and cameras which allow for intelligent light adjustment based on current weather, luminosity, and traffic. Each day when you go down a highway, the AI algorithm learns about the city and captures different urban features such as rush hours, sundown, or weather forecasts. By processing this information and historical data, urban AI implemented within this solution allows for adjusting the lamp posts in the most optimal way and the most sustainable one. Not only does such action can prevent possible accidents on the road due to the correct lighting, but also provide the city with savings based on leveraging daily sunlight.
With the promise of improving functionalities, sustainability, and mobility, the concept of smart cities quickly became a buzzword under which many towns are now being developed. Analyzing the technological and regulatory framework, we can admit that there is still no chance of developing a completely self-maintaining city thanks to the introduced IoT, however, traveling around the world we can spot major improvements. As one of the best examples of a smart city, we can list Copenhagen which utilizes “wireless data from mobile devices, GPS in buses, and sensors in sewers and garbage cans to assess the state of the city in real-time and make improvements to decrease traffic, air pollution, and CO2 emissions.”
However, looking at those sensors and the loads of data they gather, we should also reflect on the possible dark side of smart cities. The regulatory framework is still not developed in many areas such as data protection and processing. This can cause ethical and legal dilemmas regarding who can access these databases and whether the government should have such profound access to the daily life of its citizens. The implementation of face recognition and sensors all over the city could actually provide information on your daily routine, who you meet up with, and where you go. As an interesting example of analysis of such data by the government, we can mention Social Credit System introduced in China. Is there a possibility that this practice will extend to Western countries with the bright idea of increasing cities’ sustainability by making them smart?
- Sensowork, A (really) Smart City Concept, 11.05.2021, https://www.sensoworks.com/a-really-smart-city-concept__9412
- Urban Artificial Intelligence: From Automationto Autonomy in the Smart City, Gregory P. Trencher, 30.06.2020, www.frontiersin.org/articles/10.3389/frsc.2020.00038/full#h3\
- BBC Ideas, How will artificial intelligence change the cities we live in?, 01.07.2021, https://www.youtube.com/watch?v=UXxyCBimRyM