Community Safety Deployment Model: An AI solution for public safety deployment

The Problem

The post-pandemic recovery and rapid population growth toward two million people have created an unsustainable demand on resource deployment. This challenge is severely compounded by fragmented, siloed data across partner agencies, preventing proactive triage and integrated response efforts. Furthermore, because the pandemic rendered traditional, long-term historical forecasting models ineffective, existing systems lack the agile, real-time data insights required to achieve the core mission: deploying the right resource, at the right place, at the right time, with the right information.

The Solution

The Community Safety Deployment Model (CSDM) delivered on its core mission of deploying the right resource, place, time and information by replacing obsolete historical forecasting with an agile, "just-in-time" predictive model. It broke down institutional silos by unifying partner calls-for-service data into a single ecosystem, allowing operations to shift from reactive scheduling to proactive public safety triage. The tool was developed using open-source resources within the existing budget.

The Impact

The Community Safety Deployment Model (CSDM) transformed Edmonton’s safety operations by replacing reactive responses with a highly accurate, proactive deployment strategy. The model demonstrated exceptional predictive power, tracking incident locations and times nearly ten times better than random allocation.

Lessons Learned

The model is highly transferable to other municipalities because it uses open-source tools and anonymized, open-by-default data.

Launch year: 2020