The UN estimates that up to 55% of the world’s population currently live in urban areas and that this could rise up to 68% by 2050.
With many cities already struggling to address concerns over demand on infrastructure, rising costs and lower quality of life for inhabitants, AI may offer a solution in the form of Smart Cities.
Smart cities use the wealth of information and technologies available in many cities to improve quality of life, infrastructure and governance. A McKinsey study found that quality of life indicators such as crime reduction, lowered health burdens, shorter commutes and lower pollution could be improved by 10-30% in smart cities.
Smart cities would use the “big data” generated within them to provide predictive models of the city, which would be used to help residents and inform changes to the city.
Proposed smart cities would work on three levels with a technological base that collects data from smartphones and sensors. Computers process this data and then create solutions for specific problems. Information is then shared with the public to better inform their decisions.
Power: In Cities having a reliable power grid can often be taken for granted, but even a single outage can remind you how much of our lives are reliant on electricity. With ever increasing demand, smart grids would use sensors and accurate forecasting to improve the reliability, safety and performance of power grids.
Transport: Congestion, breakdowns and closures can make travelling in cities a nightmare. Smart cities propose to provide real-time information and suggestions to commuters, spreading the load across travel routes to allow individuals to make better choices and decrease congestion overall.
Safety: The network of cameras and sensors in a smart city can be used to lower crime rates and save lives. Traffic lights and sensors can be used to direct emergency services to accidents faster and provide information that helps inform further preventative measures. Likewise, crimes can be identified and used to inform investigations and police resource allocation.
When implementing a smart city there needs to be an abundance of data to process in order for AI to come up with helpful solutions, this presents issues as the information processed by a smart city could include personal information e.g., facial recognition profiles or geolocation of individuals. Even a small amount of this kind of data can be incredibly powerful.
There are of course rules and laws designed to address this, but even if the smart city is designed to follow incredibly strict data protection rules, the infrastructure needed provides an extensive surveillance structure that could be co-opted in the future.
The security implications of having a smart city where everything is controlled by one system are quite staggering, even with the best security available, is it worth the risk hackers could pose to a whole population?
Despite the risks of true smart cities, the benefits of some areas mean that we will likely see more elements of smart cities slowly be brought into our own. Correctly implemented these changes will benefit a huge amount of people bringing our cities into the information age.
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