Big Data in Fire Service
Big Data-it's a term that's everywhere. It's in newspaper headlines and in business journals. It's in boardrooms and classrooms. It's on cable news, network news and even in sports news. Five years ago, "Big Data" didn't even exist, but today it seems to be in the middle of everything-the center of a phenomenon that's sweeping across our social and economic landscape. Medicine, transportation, government services, and baseball, it seems like everyone is using Big Data to their advantage. Also, in the fire service, are no exception. These days, nearly all records are electronic, no matter what you're looking for. Financial records, tax information, geographic information, even football stats are all electronic, very accessible, and full of valuable information-if you know how to use them. In this post , we'll provide an overview of the Big Data landscape for the fire service. No one knows where and when a fire will happen, but we can guess. Often senior firefighters can guess with startling accuracy. They may call it just a "hunch," but in reality their guess is based on an assessment of their past experience applied to present conditions. They may know that when the weather turns cold, there always seems to be a job in that old row of tenement buildings around the corner. And, more often than you'd expect, they may be right.
With Big Data in our corner, we can. We may not all have decades of quality fire experience, but we can all have decades worth of quality fire data, which is enough to make a pretty good guess of our own. An amazingly good guess, in fact. Through rigorous analysis of a variety of data, it's possible to calculate the relative likelihood that a building will have a fire incident by looking to see what, if anything, is correlated with the incidence of fire. The result of all the analysis is that every building in an area can be assigned a level of fire risk. The more rigorous the analysis, the more specific the risk classification can be. A basic analysis can provide a division into broad categories, such as "high risk" or "low risk," or a more detailed analysis could yield a more specific, numerical "risk score," which could be used to create a more intricate ranking system. In the end, you have a list of the buildings with the highest risk of fire in a given area. The true power of these predictions-the ability to forecast workload and fire incidence-lies in what we can do with them. Information like this could easily prove vital to chronic issues in resource allocation for a department of any size. It could be used to inform staffing increases or redistribution to meet projected demand in certain areas or at certain times. Fire prevention resources could also be more effectively allocated by prioritizing inspections in higher risk buildings. Beyond resource allocation, fire forecast information could prove beneficial to field units as well. Situational awareness is a critical concern to responders in the field, and workload and fire forecasting can be a tremendous asset in that regard. By being aware of what to expect, and where to expect it, firefighters will be better prepared for whatever awaits them during the upcoming tour.