/https://pbcdn1.podbean.com/imglogo/image-logo/19927171/Podcast_Cover_Image8o4xk.png)
Smart Firefighting
Smart Firefighting
Episode 330: Building for the City of the Future: CAD Data, Digital Twins and Station Placement with Craig Hiltz – Darkhorse
SEP 11, 202619 MIN
/https://pbcdn1.podbean.com/imglogo/ep-logo/pbblog19927171/Craig_Hiltz_Episode_Cover_Image7jdt6.png)
Description
Every fire department already owns years of CAD and RMS data. Most of it sits untouched…
Hello Smart Firefighting Community!
Welcome to another episode of covering real world innovations via interviews with fire service and technology industry experts that empower YOU to develop your very own Smart Firefighting strategy.
Craig Hiltz of Darkhorse turns that data into a digital twin of the response system, so a chief can test a station, a roving engine or a staffing change on screen before spending a dollar on it.
Recorded at Interschutz, this conversation walks through what a digital twin is in plain language, why a dashboard only tells you what happened yesterday, and what departments in Meridian, Odessa and Toronto found when they asked the what-if questions. Craig also shares his own path from statistician and market researcher to the fire service.
Topics covered:
Why CAD and RMS data goes unused and what it can answer
Dashboards versus the why and the what if
Digital twins explained in plain language
Meridian, Boise and Eagle in one regional model
A roving engine instead of a new station
Accreditation data packages: SOC, CRA and the three axes risk model
Odessa: two minutes off dispatch equals ten new stations
Toronto: a ten percent budget cut and NFPA 1710 compliance
ALS to BLS, fleet decisions and firefighter call stress
Craig's path from statistics and market research to Dark Horse
So take a listen to hear what he has to share.
Head to www.smartfirefighting.com to discover how SFF accelerates innovation for emergency responders, to find out when our next event is, or review our curated resources.
Facebook | Instagram | Twitter | LinkedIn

