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Smart Video-Surveillance System to Detect and Prevent Local Crimes in Urban Areas (SMARTPREVENT)
Start date: Mar 1, 2014, End date: Apr 30, 2016 PROJECT  FINISHED 

The increase in urban population lead to an increase in crime. This is aggravated by illegal immigration, criminal striping, degradation of zones. The increase of criminal activity is manifested in an increased frequency of small crimes like graffiti, theft, robbery, destruction of rubbish bins. This has had a big impact for local governments, citizens and businesses.Local government agencies are trying to solve these problems. As was shown in New York, a reduction in petty crimes increases the sense of public order which produces further reduction in crime in general. These organizations often treat the problem with classical solutions such as increase in police resources, reintegration of offenders, rehabilitation of degraded areas and modern solutions such as urban video surveillance. However, these new technologies are often underused and inadequate.The SmartPrevent project aims to enhance detection and prevention of crimes in local urban areas by exploiting the full potential of video-surveillance systems. We will develop and provide four important benefits: i) Systematic characterization of usual petty crimes in an area under automatic surveillance; ii) automatic detection of the most usual and frequent criminal activities; iii) a set of automated tools capable of alerting the appropriate responders; and iv) early prevention of crimes by prediction and early detection of crimes.Rather than providing new methodologies or tools, SmartPrevent will focus on: a) improving already-existing methodologies by means of a set of guidelines for the use of video-surveillance systems; and b) providing a set of tools capable to improve of the existing crime detection systems. Our solution will be validated by deploying a realistic prototype scenario, which will actively involve the detection and prevention for crimes in an urban areas and management of these detections by final users.

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