Smart cities have been depicted with autonomous cars driving down the street and intelligent robots performing everyday tasks. While these might be commonplace in the future, the true foundation of a smart city is sophisticated technology platforms that are powered by data science.
Today, city and county leaders need to look to data science to provide predictive, actionable insights that can indicate issues before they occur. They’ll need these insights to reimagine what’s possible with current bus fleets and transportation infrastructure as the United States population increases.
Some communities already understand the value of data. For example, earlier this year, the Rhode Island Public Transit Authority (RIPTA) began looking for a way to increase the reliability of its bus fleet and provide a better transit service to the region. It is turning to predictive data analytic software to monitor their fleet performance in real time, predict failures and diagnose causes and prescribe solutions.
Growing challenges for fleet operators
With the U.S. Department of Transportation estimating that another 70 million people will be added to the population by 2040, both cities (where nearly 85 percent of residents will live) and counties will have to serve more citizens and keep them moving safely and efficiently while doing so in an environmentally conscious way. Keeping fleets well maintained and operating at their highest level will be essential to achieve this — but it’s no easy task.
We don’t need to wait for the buses of the future to create these technology-driven outcomes. We can work with what we already have. The insights gleaned will prove valuable in the short term and force improved processes and technologies. This will lead to greater uptime, efficiency and money saved.
This technology also will empower workers to make better and faster decisions that stop imminent breakdowns by fixing the vehicles before they even leave the station, instead of when they’re stalled on the street full of riders.
For public transit agencies, this means better and real day-to-day outcomes like improved maintenance schedules and optimized parts inventory forecasting to reduce expenses. Preventing a broken down bus means preventing upset customers, loss of revenue for cities and a battered reputation. For riders, predictive data analytics software means being able to count on the bus to get them to their job and back home every day.
Improving quality of life
A May 2017 Government Information Quarterly Journal study notes that “smart cities contribute to social stability and economic prosperity.” It says that happens because smart cities encourage and enable “corporations to invest their resources and expertise in the cities and by providing more prosperity and contentment for their citizens.”
More importantly, the study found that citizens agree that when they use smart city services they have “an improved living environment and increase their overall quality of life.”
Having actionable intelligence flow freely within and between municipal entities gives life to a single, holistic understanding of how cities are functioning and performing – not just in the moment, but in the future.
The path to becoming a smart city is paved with data. Cities must look to harvest that data that was previously impossible to quickly analyze with cutting edge predictive analytic software that not only stop problems before they happen, but challenge us to build the future today.
Trey Clark is the Director of Strategic Initiatives at Uptake, a Chicago-based predictive analytics company. Clark leads Uptake’s Smart City and federal verticals. Learn more at www.uptake.com.