CHARLESTON, S.C., June 11, 2012 /PRNewswire/ -- The Charleston Police Department (CPD) in South Carolina is working with IBM (NYSE: IBM) to assist the city's more than 400 police officers to more accurately evaluate and forecast crime patterns. The department is using IBM predictive analytics software to better allocate its resources and identify criminal hot spots to prevent crime and increase public safety.
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Over the past five years, the City of Charleston has worked to continue to reduce crime in an ongoing commitment to create a safer environment for the city's residents and visitors through a variety of initiatives, including implementing a robust crime analysis system, increasing focused patrol strategies using weekly crime meetings to identify "hot spots", and the introduction of new technology to capture and disseminate information quickly to enhance officer situational awareness and productivity.
Today, working with IBM, the CPD is broadening its commitment to create a safer environment for the city's residents and visitors by applying predictive analytics software that analyzes past and present crime records in seconds and evaluates incident and arrest patterns throughout the city.
While the initial focus of the project is to reduce robberies, the CPD plans to broaden the scope to help the department be more effective in "hotspot" policing. By centralizing of all the information the CPD has at its disposal including analyzing past and present criminal data and patterns, the department will have a more holistic view of where crime is trending and allow the department to deploy officers to these areas to prevent crimes before they occur.
For example, burglaries often cluster in terms of time and location; the individuals committing these crimes tend to have predictable patterns, and incidents usually take place near their homes or familiar locations. In addition, property crimes are not displaceable crimes, which means the criminals won't simply move two miles to another location.
"Criminals continue to evolve and so must we in order to keep pace and reduce the criminal activity that impacts Charleston residents and visitors," Chief of Police, Gregory Mullen said. "Having worked with the IBM team to initiate the pilot project using the predictive analytics technology, we are already seeing the potential value from this approach. It will help us provide critical information to the officers in the field and will allow us to gain greater insight across operations to improve public safety."
Through predictive analytics, the CPD will be able to augment its officers' years of experience and knowledge and provide them with a more in-depth method of looking at crime trends by centralizing previously disparate information including patrols, types of criminal offenses that are trending, time of day, day of week and even weather conditions.
"Historically, police agencies focused on protecting the community by solving crimes quickly to serve as a deterrent to would-be criminals," Mark Cleverley, IBM global director of Public Safety solutions said. "Technology has proven to be a force multiplier that is helping solve crimes more quickly or to prevent them all together, and improve the way citizens are being served and resources are allocated."
Charleston joins the ranks of cities like New York, Rochester, Las Vegas, Memphis, Los Angeles, Vancouver, Northern Ireland and many others that are taking advantage of technology to establish Smarter Cities. This approach is helping to improve public safety and services for citizens.
The Charleston Police Department project is another example of the enormous promise new technologies hold to enable public officials to better manage their vast array of data and resources. IBM has more than 2,000 Smarter Cities engagements underway around the world, helping municipalities manage public services such as crime, emergency response, traffic and water systems more efficiently.
The Charleston Police Department is currently using IBM i2 Coplink technology and is piloting the IBM SPSS predictive analytics technology.
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