A new software system will help Atlantic City police predict high-crime and high-risk areas so they can intervene before crime happens, Atlantic County Prosecutor James McClain said Tuesday.
The Risk Terrain Modeling crime and forecasting tool, developed by Rutgers University, analyzes geographically related data from various sources to identify where crime is statistically most likely to occur, so law enforcement can better assign personnel where needed, said Joel Caplan, who developed the software with Leslie Kennedy.
RTM joins Rutgers, Atlantic City police and the Prosecutor’s Office in a proactive approach to fighting crime.
A six-city national study using RTM found that certain locations were 58 times more likely to have crime than other areas. About 5 percent of the study area accounted for nearly 30 percent of the crime. A police-intervention strategy based on RTM results yielded a 35 percent crime reduction in the target areas compared with a control area.
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The greatest reduction was seen in robberies, shootings and motor vehicle thefts.
“RTM is an innovative and practical approach to mitigating hotspots by addressing the underlying causes that attract criminal activity to these locations,” said Lt. James Sarkos, who heads Atlantic City’s Vice Unit and SWAT team.
Because the data is drawn geographically, rather than from individual and human demographics, it also respects citizens’ constitutional protections, McClain said.
“In other words, RTM focuses on the geographical characteristics that attract criminals to hotspots, rather than the people who happen to be inside a hotspot,” Police Chief Henry White said.
RTM is part of the Atlantic City Police Department’s Assessment, Corrections, Tasks, Intervention, Outcomes and Notifications plan, dubbed ACTION.
The prosecutor’s Intelligence Unit will assist in the implementation.
“The cost of the program will be paid from the criminal forfeiture fund,” McClain said. “Assets and cash seized from criminals will be used to more effectively and efficiently reduce crime.”