RIVERSIDE, Calif., Nov. 4 (UPI) -- Researchers in California working with a local police force say they've developed a computer model than can anticipate crime hot spots.
University of California, Riverside, sociologist Robert Nash Parker has provided the model to the Police Department in the city of Indio to help deploy officers in areas where crimes such as burglary are likely to occur, the university reported Monday.
The result, the police said, was an 8 percent decline in thefts in the first nine months of 2013.
Parker began working with the Indio Police Department in 2010 to determine if a computer model could predict by census block group -- the smallest geographic unit the Census Bureau uses -- where burglaries were most likely to occur.
Using crime data and truancy records -- because truants account for a significant number of daytime burglaries -- Parker said he discovered patterns of crime over time and space.
"This is still cutting-edge and experimental," he said. "Big data gives you statistical power to make these kinds of predictions. It makes it possible for us to anticipate crime patterns, especially hot spots of crime, which allows law enforcement agencies to engage in targeted prevention activities that could disrupt the cause of crime before the crime happens."
Analyzing 10 years of data, Parker and Indio police found as truancy arrests shifted geographically in the city, burglaries appeared to follow one or two years later.
"We assumed there was a correlation between daytime burglaries and truancy," Indio Police Chief Richard P. Twiss said.
"We are deploying people differently and doing more community outreach," he said of the impact of the collaboration with Parker. "Instead of having to respond to past crimes our arrests went up and instances of theft were reduced. We want to produce real-time, weekly hot spot maps that will predict patterns and trends. That's the direction we're heading."