Predictive Policing

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Predictive Policing

Predictive Policing

Introduction

Technology's role cannot be avoided form the development of any organization as today's rapidly changing technological advancements have given leverage to companies as well as made things easier to individuals. Organizations in the present age function in a systematic manner and with advanced technology (Manzoor, 2012). Police departments are also one of them who need significant technologies in order to not only makes their operations better but to provide safety to public. COMPSTAT system has proven itself in the New York and all U.S. cities as a useful high-tech tool to predict about any potential crime and mobilize resources accordingly. This tool operated for 20 years now irreplaceable allows Police to decrease crime in every city, every neighborhood, and every street (Squires, 2011). The system was developed by mathematicians, anthropologists and criminologists that helped forestall certain crimes and have even led to many arrests. As an innovative example, the New York Police Department fights crime proactively through an approach based on the analysis of data.

Discussion

Application of Information Technology

The program is based on predictive analytics to make maps, identify and establish a relationship between neighborhoods and "hot spots" of criminal activity throughout the city, such as the outdoor pavilion where a concert takes place or any other specific urban area (McDonald, 2011). In this sense, predictive analytics plays a vital role in predicting criminal activities effectively and determine the most appropriate actions by allocating limited resources and deployment of police to protect citizens from looting, car-jacking or violent crimes. In this software, police department has loaded some daily statistics on crime and criminals. The software then searches it for patterns that occur repeatedly (Goode, 2011). The high degree of update makes predictions about the time and the scene of future criminal acts much more reliable than before. In fact, Predictive models can automate the ingestion, correlation and pattern detection involving massive amounts of data, and project forward, identifying the likelihood of criminal events when their enabling factors and triggers coincide again in the future. This tool is operational in several cities in the United States where he underwent tests and probation for check information. Verification of its effectiveness can easily be done by the statistical measure of development or brakes crime (Squires, 2011).

The implementation of this method has made incidents of theft down by 25%, as the cops arrive prior to the program areas are shown as more prone to attacks. For this reason and because of its success, its use has expanded to six other areas of New York and other U.S. cities. The application also allows the police to optimize their time and resources as they know in advance where and where patrol surveillance stay longer.

Implementation of COMPSTAT

Police and analysts have processed data three years past crimes in order to find acomputer algorithm that can accurately predict when and where it will be more likely to commit a crime offenders, and thus use time officers more efficiently. The software generates prediction boxes or hot spots of 500 square ...
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