While LOVELAND and Pretty Robots see ample opportunity to deepen and refine the model, there are insights to be gleaned in its current form. For example, there may be no greater benefit to the people and property of Detroit when it comes to fire damage mitigation than to focus demolition efforts on properties that are at high risk and located directly adjacent to an occupied home.
While there is evidence of this approach in city demolition patterns, a focused policy to remove fuel for fires next to occupied homes could have stabilizing effects for many Detroit properties.
In advance of Angel’s Night in October 2015, LOVELAND published a blog post looking at high-risk areas of the city for arson in advance of the traditional uptick in fires around Halloween. Part of the analysis included the identification of occupied homes that are adjacent to vacant, publicly owned structures. At the time, LOVELAND identified approximately 11,700 occupied homes that have 8,800 vacant, publicly owned structures next to them.
The Site Control map below shows:
9,500 Hardest Hit Fund demolitions carried out over the last two years (light blue)
11,700 occupied homes (green) that are adjacent to 8,800 city-owned vacant structures (red)
Properties in black are those which suffered a suspicious fire in 2015 -- some of which occurred in vacant structures next door to occupied homes
With the fire risk model developed by Pretty Robots, city-owned vacant properties next door to occupied homes can be evaluated for which are, per the model, at highest risk for fire. This would amount to a demolition triage list of high-stakes properties where a fire can mean the loss of an occupied home. This is the kind of application of the fire risk model that LOVELAND and Pretty Robots envision.
Further citywide surveys could produce vastly higher resolution data for this model, which will allow the model to output more accurate and more insightful results. Further, the model exists now as a protocol — a series of steps and equations that produce fire risk assessments based on the data input. This can be turned into an application that is a component of the Motor City Mapping interface and that self-updates as new information comes into the system, allowing the fire department and others to see risk in real-time.