Reflections from the DSSG 2015 Fire Team

(posted on behalf of the DSSG Fire team students)


After a year since the culmination of our DSSG 2015 summer program, we wanted to share a bit about how the work we did with DSSG last summer has developed since then.

We spent the summer of 2015 working with the Atlanta Fire Rescue Department (AFRD) to help them use disparate data sources from various city departments to identify new properties that required fire inspection, and we built a predictive model to help them prioritize fire inspections according to the fire risk of commercial properties.

You can see some of our blog posts from last summer on beginning the project, understanding and joining our data sources, riding along with fire inspectors to understand their existing processes, conducting preliminary analyses of the data, and building a predictive model of fire risk.

We created a framework, which we call Firebird, to describe this process of property discovery and risk prediction, as seen below.


As a more permanent home for this work, we have created a website for Firebird, which provides a high-level overview of the project, and includes a link to our code on Github.

At the end of last summer, we presented our work to an audience of local data scientists at the final summer presentation at General Assembly, garnering interest from several firefighters from neighboring counties that were in attendance. Following that presentation, Fire Chief Joel Baker, the head of AFRD, invited our team to speak at a meeting of the AFRD executive staff, including the battalion chiefs for each of the 7 battalions that comprise the city of Atlanta.

Following this, AFRD has already begun to implement our recommendations, from starting to inspect the properties at highest risk of fire at greater priority than other properties, to beginning conversations about allocation of inspection personnel and resources to reflect the distribution of commercial properties requiring inspection in the city.

In September 2015, we submitted and presented a short paper describing our work and its outcomes to the Bloomberg Data for Good Exchange, a conference on applications of data science for problems of social good, involving participants from academia, industry, government, and NGOs.

Then, wanting to further the impact of this work, we submitted a full paper to the 2016 Knowledge Discovery and Data Mining (KDD) conference, a top conference in the data mining field. It has recently been accepted, and we will be presenting the work there in August. A pre-print draft of the paper can be found here.

Finally, two representatives from our project, Dr. Bistra Dilkina and Dr. Matt Hinds-Aldrich, presented this work at the National Fire Protection Association (NFPA) Annual Conference this June. The NFPA magazine also recently published an article on Embracing Analytics, with a nice description of our work, explaining our process and its results to a wider audience of fire professionals.