NSF Research Grant to Predict Crime, Social Harms

A new research grant from the National Science Foundation is assisting researchers at IUPUI with developing a system to predict crime.
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Grant funds assist IUPUI researchers in developing a system that can predict crime, allowing law enforcement to allocate resources where they are needed most. 

Researchers at the Indiana University-Purdue University Indianapolis (IUPUI) received a $791,513 grant from the Smart and Connected Communities program of the National Science Foundation to develop a system to predict crime and other social harms based on societal routines.

Crime Prediction Another Facet of Smart Cities

The three-year grant will allow IUPUI researchers to create algorithms and software capable of analyzing data and predict crime, giving city leaders and public safety officials reliable data to guide them in allocating resources.

George Mohler of the IUPUI School of Science said the system will give law enforcement a big-picture look at the needs of the community, a common theme with smart city solutions, according to the announcement.

“Police don’t only deal with crimes; they deal with many social harms,” Mohler said. “Our new NSF-funded project embraces the bigger picture of policing, and of smart cities in general. There are all sorts of patterns for which we can develop algorithms to detect, weigh their importance and come up with risk scores that can be used to allocate resources effectively.”

Algorithm Will Predict Crimes & Social Harms

While current policing techniques focus on specific areas known to be “hot beds” for crime, researchers hope the new algorithm will be able to tell them more about potential issues in the community, including social harms that threaten life, which will allow law enforcement and emergency services to staff and situate their resources accordingly.

Jeremy Carter, director of criminal justice in the School of Public and Environmental Affairs at IUPUI, said the goal of the system is to improve the quality of life for citizens.

“What we are predicting is the dynamic risk of social harm events. If we put quantified risk behind prevention, we can play the odds and hopefully position police, EMS and others in the right places at the times when social harms are most likely to occur,” said Carter, the criminologist who is a co-principal investigator on the NSF grant. “Crime, drug usage and motor vehicle crashes concentrate in time and place and are to some degree predictable because people have routine activities.”

Read the full grant proposal here:

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Rachel Engel

Rachel Engel

Author Rachel Engel is also Associate Editor of Military1.com. She is based in Kansas.