Editor’s Note: Minding the Smart Meters
In July 1935, newspaper owner Carl C. Magee installed 200 Park-O-Meters in the U.S. state of Oklahoma. The first parking meters in the world, they lined a busy commercial street in Oklahoma City and required $0.05 to park for 15 minutes to an hour, depending on the location.
Angry citizens immediately filed lawsuits in response, objecting to the meters’ aesthetics and alleging that the city was fleecing motorists, The New York Times reported.
However, the responses from the public were not entirely negative. “In favor of the meters,” the Times reported, “it is argued that shoppers and others visiting downtown buildings do not waste time when they think of the moving arrow checking off the passage of time. They get their business done as quickly as possible, hurry back to their cars and drive home, thus removing their automobiles from busy streets.”
The same basic balance is sought globally around parking today. In the United States, “250 million cars have an estimated 2 billion parking spots and spend 95 percent of their time parked,” writes Dayna Evans in Bloomberg Businessweek. Reforms to parking include suggestions that cities “price street parking according to market value, based on the desirability of the space, the time of day, and the number of open spots.”
Through artificial intelligence, smart cities are able to gather real-time traffic data to better understand the movement of cars and figure out solutions to congestion.
Parking has become a science: balancing the cost of parking and the accessibility of spaces to provide a happy medium where consumers gain access to businesses but don’t stay too long. But to find that equilibrium, cities require data.
Enter smart parking, which is projected to reach $19.29 billion by 2028, according to a recent report. This market, in turn, relies on data collection, analysis, and artificial intelligence (AI). According to Parking Today, “as cities strive to become smarter and more sustainable, artificial intelligence and its broad applications have been invaluable… Through artificial intelligence, smart cities are able to gather real-time traffic data to better understand the movement of cars and figure out solutions to congestion. This information can be used to recommend nearby parking spaces to cars in search of parking.”
The revolution that took parking from the meter to the smart city has happened in numerous industries, including security. In this month’s cover story, “The Next ESRM Revolution,” Val LeTellier discusses the various data sources that “monitor, track, and assess behavior in real time.” This “ubiquitous and persistent surveillance combined with advanced analytics has created a whole new enterprise risk equation.”
These new data sets have benefits, according to LeTellier, helping to meet the goals of enterprise security risk management (ESRM) by “providing the predictive analytics to make security smarter, efficient, and proactive.”
However, security professionals should be mindful of the pitfalls as well. “Data can be maliciously altered, advanced analytics can be inaccurate and even biased, and big data can create even bigger cybersecurity risks,” he writes.
But, like smart meters—and the Park-O-Meter before them—big data and AI are here to stay. Learning to manage these new risks is security’s next challenge.