The American Housing Survey(AHS) provided some data on this in county level, and the American Community Survey(ACS) have more detailed results about many other questions in census block group level. They first targeted the areas of least likely to have smoke alarm installed. There was a similar project in New Orleans – Smoke Alarm Outreach Program. The ranking could came from multiple factors, like the possibility of don’t have smoke alarm installed, the risk of catching fire, the possible casualty and losses, maybe even taking the constraints of each Red Cross chapter into consideration. Given limited resources and the ambitious project goal, the American Red Cross want to have a priority list for regions backed with data and analysis. The choropleth map of Red Cross Smoke Alarm Home Visits per county in 10 months Project Goal

The Red Cross Smoke Alarm Home Visits is already a very successful campaign, but they were looking forward to the power of data and data science to further improve the project. I joined a project The Effectiveness of Smoke Alarm Installs and Home Fire for the American Red Cross.

In May, 2015 I went to a MeetUp organized by DataKind, where Volunteers came from all kinds of background joined together to help non-profit organizations with Data Science. Geocoded 18 millions address in NFIRS data with AWS server, Postgresql, PostGIS.Major contribution on model design, implemented NFIRS related predictors, and built interactive visualizations.Discovered the hidden information in NFIRS dataset, obtained and analyzed 10G NFIRS data.The project used public data to help Red Cross directing limited resources to homes that more vulnerable to fire risk and loss.This is a write-up for my volunteer Data Science project for the American Red Cross.

Download red cross fire alarm