Invention Reference Number
Accurate identification of mobile home parks (MHPs) is essential for improving emergency response, infrastructure planning, and policymaking. This technology introduces a scalable data-driven framework that classifies MHPs across large geographic regions using unique morphological characteristics of the built environment. By distinguishing MHPs from other types of structures, this approach enables more proactive assessment of at-risk populations and better resource allocation before and after extreme events.
Description
This technology provides a machine learning–based framework for identifying mobile home parks at scale by analyzing distinctive patterns within the built environment. Traditional mapping efforts often overlook MHPs or identify them only after natural disasters, limiting effective response. This invention leverages a unique set of building morphology features—such as spatial distribution, density, and contextual relationships—to infer MHP locations across millions of structures. The method integrates these derived features into a computational model that classifies mobile home parks with high accuracy while remaining adaptable to diverse regional conditions. The resulting tool enhances situational awareness for emergency management and policy planning, offering a scalable and efficient way to capture a critical yet underrepresented segment of U.S. housing infrastructure.
Benefits
- Enables large-scale, high-accuracy identification of mobile home parks.
- Improves disaster preparedness and rapid response planning.
- Provides policymakers and planners with more comprehensive housing data.
Applications and Industries
- Emergency management and disaster response agencies
- Urban and regional planning organizations
- Utility and infrastructure resilience assessment
- Federal, state, and local housing policy programs
Contact
To learn more about this technology, email partnerships@ornl.gov or call 865-574-1051.
