CMPD s Predictive Crime Analytics Implementation. Harold Medlock Deputy Chief Charlotte-Mecklenburg Police Department
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1 CMPD s Predictive Crime Analytics Implementation Harold Medlock Deputy Chief Charlotte-Mecklenburg Police Department
2 CMPD BI Dashboards & Predictive Crime Analytics Agency Background Information Estimated Population: 777,827 Land Area: 438 square miles 1725 Sworn Officers 500 Non-sworn personnel
3 Primary Project Goals Provide customized role-based delivery of crime data and predictive analytics to Officers and Command Staff Support resource deployment through the use of real-time information Achieve better visualization of crime patterns and trends
4 June RFP issued Project Timeline November Contract awarded to IBI for Law Enforcement Analytics (LEA) Solution January Project began May Operational Data Store (ODS) live September Operational Dashboards live October Predictive Dashboard live
5 Operational Data Store and Reporting Packages Operational Data Store (ODS) - Consolidates over a dozen major data sources to support real-time information delivery Command Level Reports - Fourteen report packages automated and electronically distributed to Captains & Commanders to support Monday morning briefings and weekly CompStat sessions Electronic Monitoring Reports - Crime scene correlation reports delivered daily to Detectives
6 Operational Data Store Oracle Oracle Data Collection Electronic Monitors Gang Data Crime Reports Probation Property Evidence Data Transform and Load Warrents CAD Events Phases of Moon Operational Data Store Arrest Data School Calendar Weather SQL Server Data Transform and Load Employee Data Special Event History Special Events Planned
7 Command Level Report
8 Electronic Monitoring Reports EM Hits by Beat for Response Area Commanders EM Hits by Crime Type for Detectives
9 Operational Dashboards Virtual Roll Call Dashboard - Allows Patrol Officers to share information through BLOGS and APB s Subjects of Interest Dashboard - Highlights priority offenders and warrants for Patrol Officers Current Crime Events Dashboard - Allows Officers to monitor calls for service and crime activity in real-time CompStat Dashboard - Allows Supervisors to monitor Beat Goals and visualize Officer Initiated Activities in relation to Part 1 crimes
10 Virtual Roll Call
11 Virtual Roll Call - APB Detail
12 Subjects of Interest
13 Current Crime Events
14 Calls for Service Activity
15 CompStat
16 Officer Initiated Activities
17 Predictive Dashboard Created predictive dashboard for the following major crime categories: Commercial Robbery Personal Robbery Aggravated Assault Residential Burglary Commercial Burglary Auto Theft Larceny from Auto
18 Predictive Dashboard (Continued) Built predictive models based on a series of inputs: Historical geographic crime patterns Recent criminal activity (within past hours) Day of week and time of day Weather conditions Recent call for service activity School holidays Special Events
19 Example Auto Theft Model Factors
20 Predictive Crime Analytics
21 Predictive Crime Analytics
22 Results Real-time Hotspot location information is now at the fingertips of frontline officers and commanders Synchronizes jurisdiction-level resource deployment Increased arrests Increased communication and collaboration between frontline officers and analysis team Increased accountability across the board Liberates analysts to do other activities that drive down crime Single version of the TRUTH Everyone is on the same page
23 Measure of Success When the system indicated a strong probability of burglaries within the Valleydale Corridor neighborhoods on weekdays between 11 am and 3 pm, I immediately assigned an officer to this area, with backup from the division s Burglary Suppression Unit and response area coordinators. Soon after, the officer received a call regarding a possible burglary at a vacant house in this targeted zone. The team moved in and quickly apprehended five subjects inside that residence. -- Sergeant Lisa Carriker, RA2, Freedom Division, CMPD
24 Next Steps Implement Additional Operational Dashboards to Better Allocate Officers based on Overtime/Offtime and Current Call Level Activity Implement Additional Predictive Models for Violent Crimes Implement Top 10 Alerts that give Patrol Officers Real-Time Insight into Potential Threats on Current CFS Explore Real-Time Integration with Pawn Data, License Plate Readers & Video Surveillance System Explore Citizen-Facing Applications for Better Transparency
25 Questions? Comments?
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