🛩️ Flight to the Future: Predicting Drone Delivery Potential and Infrastructure Gaps for Critical Aid in Rural West Virginia
A NewForce Data Analytics Capstone Project by Walter Lovett
Flight to the Future is a data analytics capstone project that examines how drone technology can bridge critical infrastructure gaps in rural West Virginia. By analyzing food access, healthcare shortages, disaster vulnerability, and terrain barriers, this project builds a Drone Need Index (DNI) that identifies where drone-assisted delivery would have the greatest humanitarian impact.
The project focuses on rural Appalachian communities—particularly those isolated by geography, limited broadband, medical provider shortages, and high food insecurity. The result is a data-driven roadmap for where drones should fly first.
- Identify the West Virginia counties with the highest combined risk using food access, healthcare shortages, and disaster loss estimates.
- Build a Drone Need Index (DNI) to quantify and visualize priority areas.
- Use Power BI dashboards to communicate access gaps and infrastructure weaknesses.
- Create geospatial visualizations and a simulated drone route to demonstrate how drones bypass terrain barriers.
- Provide actionable insights for nonprofits, emergency responders, and rural health organizations.
- Python (Pandas, GeoPandas, Matplotlib)
- Power BI
- Power Query
- GIS & Geospatial Visualization
- USDA Food Access Data
- HRSA HPSA Healthcare Shortage Data
- FEMA Estimated Annual Loss (EAL)
- Google Earth Studio (drone route animation)
- GitHub for version control
A ranked table displaying:
- Food Desert Tracts
- Medical Need Index (MNI)
- Estimated Annual Loss (EAL)
- Composite Risk Score
Sorted from highest to lowest vulnerability.
A combined metric built from:
- Food Access
- Medical Need Index
- Disaster Exposure (EAL)
- Geographic isolation
This map highlights where drones can make the greatest impact first.
Color-coded:
- Red = High Risk
- Yellow = Medium Risk
- Green = Low Risk
- Blue = Non-food-desert counties
Provides an intuitive snapshot of statewide need.
A bar chart showing the Top 10 medical shortage sites (HPSA areas), including FCI McDowell and FCI Gilmer, demonstrating severe provider shortages in the highest-risk counties.
A 26-second simulated drone flight created in Google Earth Studio showing a delivery route from Charleston to Iaeger.
Demonstrates how drones can bypass terrain barriers and reduce emergency delivery times.
Rural Appalachian communities face:
- Limited broadband
- Physician shortages
- High food insecurity
- Disaster-prone terrain
- Long distances to care
Drones offer a scalable way to:
- Deliver medications
- Reach isolated homes
- Support food distribution
- Improve emergency response times
- Data Collection
- Transformation in Power Query
- Normalization of HPSA → Medical Need Index (MNI)
- Building the Drone Need Index (DNI)
- Power BI & Python visualizations
- Route simulation using Google Earth Studio
- McDowell, Kanawha, and Logan show the highest combined need.
- The Drone Need Index strongly aligns with food insecurity and healthcare shortages.
- Drones could significantly reduce emergency delivery times in high-risk areas.
- The project provides a humanitarian roadmap for drone-assisted logistics.
- 📊 data/ — Cleaned datasets
- 🐍 notebooks/ — Python notebooks
- 📈 powerbi/ — Power BI dashboards
- 🎥 media/ — Drone animations & images
- 📁 outputs/ — Final maps and visualizations
- Predictive modeling for road closures
- Integration with FAA & DHS drone regulations
- Real-world drone test flights
- Parcel-level geospatial modeling
- Integration with nonprofit delivery logistics (e.g., ABBA’S TENT)
Walter Lovett
NewForce Data Analytics Cohort
Focused on rural innovation, humanitarian technology, and drone-based logistics.