Missions

Strategically Plan Patrol Missions for Maximum Crime Deterrence

Crime forecasting and mission planning software enables more precise deployment of patrol resources

ShotSpotter Missions Overview

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Patrol Challenges

Patrol – it’s the backbone of every department. But command staff must assess whether patrol resources are consistently deployed in a data-driven way.

Does uncommitted patrol time take into account constantly changing environmental factors and trends that can impact the likelihood of where crime occurs and when?

Patrol Management Software

Patrol management software uses artificial intelligence-driven analysis to help strategically plan patrol missions
and tactics for maximum crime deterrence

Planning Patrol Time

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  • The system provides patrol officers with a forecast of the highest risk areas for crime that the agency is prioritizing. Boxes represent a precise area (250 meters by 250 meters) for patrol and are color coded by crime type
  • When officers arrive in the box, the mission officially begins and a configurable timer starts so that the area is not over or under patrolled
  • Authorized users such as crime analysts can add or suppress a mission based on new information
  • The mission can be viewed on an MDT, smartphone, desktop or printed out

Suggested Tactics

  • As the officer enters the mission area, they are presented with suggested tactics to use during the mission
  • The officer is able to self-report tactics used during the mission for reporting back to command staff
  • Tactics are configurable by agency and crime type

How Shotspotter Missions Works

ShotSpotter Missions creates crime risk forecasts that are more accurate
and precise by time and location than traditional hotspot methods

Initial Configuration

The agency selects which crime types to forecast and weights each based on police and community priorities. Mission duration and suggested tactics are configured. Local district maps with beat boundaries are created.Data feeds from CAD, RMS and crime analysis tools are integrated.

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Training the Model

The system is “trained” using machine learning based on the agency’s data along with temporal, geospatial data and event data. The model is then tested against recent crime data to calibrate forecast accuracy.

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Creating Missions

Once trained and tested, the model produces daily shift-by-shift recommended missions that sends officers to the most likely locations for crime.

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ShotSpotter Law Enforcement Solutions