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In the opening of this series of posts on situational intelligence and smarter cities, I outlined how cities can progress through solving different types of use cases to build their smart infrastructure of the future while also addressing current needs. Let’s look at how this might work for transportation in an evolving city.

As a first step, city officials can use situational intelligence to score and rank the most congested portions of city roadways and test possible solutions. Cities can also score and rank the risk posed by aging and overworked bridges, overpasses, and tunnels. Quantifiable evidence of the probability of asset failure, and the consequences should failure happen, provides strong evidence for seeking new funds to infrastructure improvement.

After addressing the most congested and riskiest transportation corridors, city planners can use situational intelligence to study and improve public transportation speed and capacity through major corridors. This helps to further reduce congestion and degradation of city streets.

Using situational intelligence to bring together traffic information, city planning, environmental data, economic development, and population growth data, city planners can design future neighborhoods and transportation corridors that provide increased convenience and safety with decreased noise and air pollution and traffic congestion.

In future blog posts, I’ll lay out similar use case progressions that can help evolve smarter cities today.

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