Case Study: FDNY Understands Post-COVID Emergency Response Patterns with AirSage

FDNY analyzes 1,000 emergency events in 2 weeks with AirSage

The Fire Department of the City of New York (FDNY) faced a challenge understanding the root causes of slower emergency vehicle response times following the COVID-19 pandemic. Partnering with research center C2SMARTER, they sought to determine if changes in public travel patterns and congestion were contributing factors. To get a complete picture of activity at intersections, C2SMARTER selected vendor AirSage for its high-granularity trajectory data.

AirSage provided trajectory data aggregated at 30-second to 1-minute intervals, a significantly higher granularity than other available data. This allowed C2SMARTER to match thousands of events with FDNY records and analyze vehicle speeds at the exact moments emergency vehicles passed through intersections. While a statistically significant public slowdown was not confirmed, AirSage data successfully proved one key hypothesis: emergency response vehicles were traveling 8-17 miles per hour faster than civilian vehicles, providing crucial, data-driven insight into post-COVID emergency patterns.

FDNY