Miami-Dade County is partnering with IBM to improve city policing, transportation and parks through predictive analytics.

J. Nicholas Hoover, Senior Editor, InformationWeek Government

February 28, 2013

4 Min Read

Big Data's Surprising Uses: From Lady Gaga To CIA

Big Data's Surprising Uses: From Lady Gaga To CIA


Big Data's Surprising Uses: From Lady Gaga To CIA (click image for larger view and for slideshow)

Miami is getting smarter. Miami-Dade County and IBM this week announced a partnership to leverage predictive analytics software to make better use of the city's data -- and to prevent problems even before they present themselves.

As part of the partnership, Miami-Dade will use IBM's Intelligent Operations Center dashboard, SPSS predictive analytics software, and Cognos business intelligence software to analyze data coming from the city's police databases, water meters and IP cameras, among other sources, in order to better address everything from leaky pipes to traffic problems and criminal activity before they get out of hand.

The push is expected to not only improve Miami-Dade's county operations and service to the county's citizens but also save money. Miami-Dade CIO Angel Petisco estimates that just one piece of the initiative, which ties into the county's parks to track leaks and broken pipes, could save the city $800,000 to $1 million.

[ Big data has value that's often not reflected in the books. Read What's Your Big Data Worth? ]

Many IT initiatives spring from specific problems, but, according to Petisco, this one arose as city managers "kept hearing about smarter cities, smarter communities, and started looking at the landscape of what was available, what they could be used for."

The first place that made sense, Petisco said in an interview, was the park system. "Parks were using way more water than you would think for keeping foliage green, and we suspected they had leaks," he said. A pilot system put in place helped determine in real time where leaks might be, and Miami-Dade then extended the system to the entire county park system.

Next, Miami-Dade moved on to crime data. Before IBM entered the picture, Miami-Dade already had a crime data warehouse, a product for geocoding, and crime maps. However, the police department knew it could get more from the data that it was collecting. Now IBM's Intelligent Operations Center software cobbles together data on evidence and crimes and allows police to make quicker conclusions by reducing the time to identify leads, investigate crimes and solve cases. Now, according to Petisco, the police "can't get enough of this stuff."

The next step in Miami-Dade is to use Intelligent Operations Center to help manage traffic in the county, which at 2.5 million residents spread across 35 municipalities, is the seventh most populous county in the United States. That means crowded roads.

The transportation initiative will begin with a pilot project to analyze traffic flow to help drive customers to local businesses in Miami-Dade's Brickell community. This will be done in part by determining, based on data, the most economically beneficial place to locate a new public transportation stop.

In the future, Petisco said, Miami-Dade plans to use camera feeds and other systems that register traffic volumes and combine that data with event data, such as sports or entertainment schedules, to determine when and how to adjust traffic signals and bus routes to best keep traffic flowing. According to Chris O'Connor, VP of Smarter Cities software at IBM, that data could also be combined with the police data to help law enforcement better manage events.

Miami is only one of a number of cities with which IBM has Smarter Cities initiatives. Although O'Connor says that Miami is unique in how far it is going with the data, IBM has worked with cities from New York to Zhenjiang, China, on Smarter Cities projects. It's not just IBM, either. This week, Seattle announced that it would use geotagged crime history and software designed at the University of California Los Angeles to determine where crime is likely to occur and when.

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About the Author(s)

J. Nicholas Hoover

Senior Editor, InformationWeek Government

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