4 Examples of How AI Can Make Cities Smarter

What makes a smart city “smart” can be hard to pin down. Proponents claim smart technology is clearly the future, citing the use of sensors, advanced data analytics and a cloud infrastructure as a way to improve services and increase efficiency while holding down costs. Skeptics might counter that “smart” is just a marketing buzzword tacked in front of products or services to make them seem better and more innovative, regardless of real value (like adding “blockchain” to a corporate name could drive up its stock price, at least temporarily, even if the company’s product is iced tea).

They’re both right. Most people have encountered or least heard about some “smart” devices of questionable intelligence or usefulness, like connected toothbrushes or water filters that won’t work without a smartphone app. Smart doesn’t always mean good. But any technological revolution will have its excesses and misfires, and there are signs of how smart technologies improve city services and how artificial intelligence accelerates the change.

While some proponents worry the United States is falling behind efforts such as those of Chinese company Alibaba, which has designed smart cities in China and recently launched the Malaysia City Brain in Kuala Lumpur, AI technologies are taking hold around the United States. Here are just a few examples of how AI, machine learning and analytics are being applied to create, or improve, services.

Driving in city traffic isn’t so much a matter of distance but of time. The office, restaurant, or theater you’re going to might not be far away in miles, but the time it takes to get there can be an open-ended question, with so much depending on congestion and how red lights contribute to it.

Adaptive signal control, applied in Los Angeles, San Antonio, Pittsburgh and some other cities, uses real-time data to change the timing on traffic lights to adjust to the flow of traffic. The Transportation Department says adaptive signal control can improve travel times by more than 10 percent — and in some areas with seriously outdated signals by 50 percent.

The idea of traffic signals timed to improve traffic flow isn’t new — 50 years ago, drivers going through West Philadelphia to Center City could hit nothing but green lights for about 30 blocks by maintaining a designated speed — but those older systems were static. Current systems that collect data from strategically-placed sensors and process it quickly can determine on the fly which lights should be red and which should be green.

And they could be improving. Surtrac, using technology patented by the Robotics Institute at Carnegie Mellon University, claims its technology can produce 25 percent reductions in travel time and 40 percent reductions in time spent waiting at intersections.

Better traffic flow not only makes driving more agreeable for motorists, but it has a tangible economic impact, according to the Transportation Department. The Texas Transportation Institute has estimated the cost of traffic congestion at $87.2 billion ($750 per traveler) in wasted fuel and lost productivity. Relieving congestion also can save states and cities money in the time and manpower cut on recording and responding to complaints.

Another benefit of better traffic flow and traffic sensors systems is better public transportation, whether in the form of taxis, Uber/Lyft-type services and buses.