Overview#
A patrol supervisor planning shift deployments for a Friday night knows from experience that certain neighbourhoods spike after midnight. What they may not know without analytical support is that this pattern is strongest in the third week of each month, correlates with a specific venue's event calendar, and has been shifting three blocks east over the past six months. Crime Analytics and Prediction surfaces that kind of insight so that deployment decisions are grounded in data, not just institutional memory.
The platform combines historical crime data, real-time intelligence, and predictive modelling to transform reactive policing into proactive prevention. It integrates with existing CAD and RMS systems, delivering real-time intelligence to command staff, patrol supervisors, and field officers across law enforcement agencies of all sizes.
Key Features#
Crime Pattern Analysis#
Identify geographic, temporal, and behavioural crime patterns through automated analysis of historical and real-time data. Detect crime clusters, series, and sprees with statistical significance testing to separate genuine patterns from random variation.
Predictive Modelling#
Forecast future crime locations and times based on historical patterns, environmental factors, and situational variables. Risk-based heat maps guide patrol deployment and resource allocation decisions with confidence intervals and data provenance clearly displayed.
Geographic Profiling#
Spatial analysis techniques estimate offender anchor points such as residence or workplace from crime series locations. Ranking suspects by geographic probability focuses investigative effort on the most likely individuals first.
Resource Optimisation#
Data-driven patrol deployment recommendations based on predicted crime risk, current resource positions, and response time requirements. Optimise shift scheduling, beat boundaries, and special operation targeting without manual spreadsheet modelling.
Repeat Offender Analysis#
Identify prolific offenders driving crime in specific areas through offender-crime linkage analysis. Targeted enforcement and early intervention strategies focus on high-impact individuals rather than broad area saturation.
Trend Reporting#
Long-term crime trend analysis for strategic planning, budget justification, and community reporting. Year-over-year comparisons, seasonal adjustment, and benchmark analysis against comparable jurisdictions give command teams defensible data for public accountability discussions.
Use Cases#
- Patrol Deployment: Data-driven recommendations for patrol positioning based on predicted crime risk, enabling proactive presence in high-risk areas during peak times.
- Crime Series Investigation: Automated detection of crime series with geographic profiling to narrow suspect search areas and prioritise investigative leads.
- Strategic Planning: Long-term trend analysis supporting staffing decisions, budget requests, and community policing strategy development.
- Community Transparency: Public-facing dashboards sharing crime trends, enforcement results, and resource allocation rationale for community trust-building.
Integration#
Connects with CAD and dispatch systems, records management platforms, and intelligence databases. Supports geospatial visualisation with GIS integration, automated report generation, and mobile access for field personnel. Multi-tenant architecture maintains organisation-level data isolation for multi-agency deployments.
Open Standards#
- GeoJSON (RFC 7946): All geographic zones, risk polygon boundaries, heat map areas, and offender anchor point estimates are represented and exchanged as GeoJSON Feature and Polygon objects.
- NIEM 6.0 / JXDM 7.2: Crime records, incident data, and investigative outputs are exported as National Information Exchange Model 6.0 JSON documents using the Justice (JXDM 7.2) and Emergency Management domain namespaces, enabling interoperability with other law enforcement and justice systems.
- OASIS Common Alerting Protocol (CAP) 1.2: Incidents and risk alerts are serialised to CAP 1.2 XML for downstream distribution to partner agencies and alerting systems.
- FBI National Incident-Based Reporting System (NIBRS): Incident and offence records are structured to conform with NIBRS Group A and Group B offence categories, enabling benchmark comparisons against national crime statistics and submission to federal reporting programmes.
- OGC Web Map Service (WMS 1.3.0): Patrol heat maps, risk layers, and geographic profiling outputs are published as OGC-compliant map service layers, allowing integration with any standards-conformant GIS client used by partner agencies.
- GraphQL (June 2018 specification): All analytical queries, predictive model results, and resource deployment recommendations are served through a typed GraphQL API, allowing clients to request only the data fields needed.
- ISO 8601: All temporal data, including forecast valid-from/valid-to windows, patrol shift timestamps, and trend report periods, is stored and transmitted in ISO 8601 UTC format to ensure unambiguous time-zone handling across multi-agency deployments.
- W3C WCAG 2.2: Command dashboards, public-facing crime trend pages, and community transparency views are built to Web Content Accessibility Guidelines 2.2 AA conformance level.
Last Reviewed: 2026-02-05 Last Updated: 2026-04-14